PURPOSE: Dynamic lung oxygen-enhanced MRI (OE-MRI) is challenging due to the presence of confounding signals and poor signal-to-noise ratio, particularly at 3 T. We have created a robust pipeline utilizing independent component analysis (ICA) to automatically extract the oxygen-induced signal change from confounding factors to improve the accuracy and sensitivity of lung OE-MRI. METHODS: Dynamic OE-MRI was performed on healthy participants using a dual-echo multi-slice spoiled gradient echo sequence at 3 T and cyclical gas delivery. ICA was applied to each echo within a thoracic mask. The ICA component relating to the oxygen-enhancement signal was automatically identified using correlation analysis. The oxygen-enhancement component was reconstructed, and the percentage signal enhancement (PSE) was calculated. The lung PSE of current smokers was compared with nonsmokers; scan-rescan repeatability, ICA pipeline repeatability, and reproducibility between two vendors were assessed. RESULTS: ICA successfully extracted a consistent oxygen-enhancement component for all participants. Lung tissue and oxygenated blood displayed the opposite oxygen-induced signal enhancements. A significant difference in PSE was observed between the lungs of current smokers and nonsmokers. The scan-rescan repeatability and the ICA pipeline repeatability were good. CONCLUSION: The developed pipeline demonstrated sensitivity to the signal enhancements of the lung tissue and oxygenated blood at 3 T. The difference in lung PSE between current smokers and nonsmokers indicates a likely sensitivity to lung function alterations that may be seen in mild pathology, supporting future use of our methods in patient studies..

PURPOSE: K trans $$ {K}^{\mathrm{trans}} $$ has often been proposed as a quantitative imaging biomarker for diagnosis, prognosis, and treatment response assessment for various tumors. None of the many software tools for K trans $$ {K}^{\mathrm{trans}} $$ quantification are standardized. The ISMRM Open Science Initiative for Perfusion Imaging-Dynamic Contrast-Enhanced (OSIPI-DCE) challenge was designed to benchmark methods to better help the efforts to standardize K trans $$ {K}^{\mathrm{trans}} $$ measurement. METHODS: A framework was created to evaluate K trans $$ {K}^{\mathrm{trans}} $$ values produced by DCE-MRI analysis pipelines to enable benchmarking. The perfusion MRI community was invited to apply their pipelines for K trans $$ {K}^{\mathrm{trans}} $$ quantification in glioblastoma from clinical and synthetic patients. Submissions were required to include the entrants' K trans $$ {K}^{\mathrm{trans}} $$ values, the applied software, and a standard operating procedure. These were evaluated using the proposed OSIP I gold $$ \mathrm{OSIP}{\mathrm{I}}_{\mathrm{gold}} $$ score defined with accuracy, repeatability, and reproducibility components. RESULTS: Across the 10 received submissions, the OSIP I gold $$ \mathrm{OSIP}{\mathrm{I}}_{\mathrm{gold}} $$ score ranged from 28% to 78% with a 59% median. The accuracy, repeatability, and reproducibility scores ranged from 0.54 to 0.92, 0.64 to 0.86, and 0.65 to 1.00, respectively (0-1 = lowest-highest). Manual arterial input function selection markedly affected the reproducibility and showed greater variability in K trans $$ {K}^{\mathrm{trans}} $$ analysis than automated methods. Furthermore, provision of a detailed standard operating procedure was critical for higher reproducibility. CONCLUSIONS: This study reports results from the OSIPI-DCE challenge and highlights the high inter-software variability within K trans $$ {K}^{\mathrm{trans}} $$ estimation, providing a framework for ongoing benchmarking against the scores presented. Through this challenge, the participating teams were ranked based on the performance of their software tools in the particular setting of this challenge. In a real-world clinical setting, many of these tools may perform differently with different benchmarking methodology..

Computer-extracted tumour characteristics have been incorporated into medical imaging computer-aided diagnosis (CAD) algorithms for decades. With the advent of radiomics, an extension of CAD involving high-throughput computer-extracted quantitative characterization of healthy or pathological structures and processes as captured by medical imaging, interest in such computer-extracted measurements has increased substantially. However, despite the thousands of radiomic studies, the number of settings in which radiomics has been successfully translated into a clinically useful tool or has obtained FDA clearance is comparatively small. This relative dearth might be attributable to factors such as the varying imaging and radiomic feature extraction protocols used from study to study, the numerous potential pitfalls in the analysis of radiomic data, and the lack of studies showing that acting upon a radiomic-based tool leads to a favourable benefit-risk balance for the patient. Several guidelines on specific aspects of radiomic data acquisition and analysis are already available, although a similar roadmap for the overall process of translating radiomics into tools that can be used in clinical care is needed. Herein, we provide 16 criteria for the effective execution of this process in the hopes that they will guide the development of more clinically useful radiomic tests in the future..

BACKGROUND AND PURPOSE: Tumour hypoxia is prognostic in head and neck cancer (HNC), associated with poor loco-regional control, poor survival and treatment resistance. The advent of hybrid MRI - radiotherapy linear accelerator or 'MR Linac' systems - could permit imaging for treatment adaptation based on hypoxic status. We sought to develop oxygen-enhanced MRI (OE-MRI) in HNC and translate the technique onto an MR Linac system. MATERIALS AND METHODS: MRI sequences were developed in phantoms and 15 healthy participants. Next, 14 HNC patients (with 21 primary or local nodal tumours) were evaluated. Baseline tissue longitudinal relaxation time (T1) was measured alongside the change in 1/T1 (termed ΔR1) between air and oxygen gas breathing phases. We compared results from 1.5 T diagnostic MR and MR Linac systems. RESULTS: Baseline T1 had excellent repeatability in phantoms, healthy participants and patients on both systems. Cohort nasal concha oxygen-induced ΔR1 significantly increased (p < 0.0001) in healthy participants demonstrating OE-MRI feasibility. ΔR1 repeatability coefficients (RC) were 0.023-0.040 s-1 across both MR systems. The tumour ΔR1 RC was 0.013 s-1 and the within-subject coefficient of variation (wCV) was 25% on the diagnostic MR. Tumour ΔR1 RC was 0.020 s-1 and wCV was 33% on the MR Linac. ΔR1 magnitude and time-course trends were similar on both systems. CONCLUSION: We demonstrate first-in-human translation of volumetric, dynamic OE-MRI onto an MR Linac system, yielding repeatable hypoxia biomarkers. Data were equivalent on the diagnostic MR and MR Linac systems. OE-MRI has potential to guide future clinical trials of biology guided adaptive radiotherapy..

PURPOSE: A single maintenance course of a PARP inhibitor (PARPi) improves progression-free survival (PFS) in germline BRCA1/2-mutant high-grade serous ovarian cancer (gBRCAm-HGSOC). The feasibility of a second maintenance course of PARPi was unknown. PATIENTS AND METHODS: Phase II trial with two entry points (EP1, EP2). Patients were recruited prior to rechallenge platinum. Patients with relapsed, gBRCAm-HGSOC were enrolled at EP1 if they were PARPi-naïve. Patients enrolled at EP2 had received their first course of olaparib prior to trial entry. EP1 patients were retreated with olaparib after RECIST complete/partial response (CR/PR) to platinum. EP2 patients were retreated with olaparib ± cediranib after RECIST CR/PR/stable disease to platinum and according to the platinum-free interval. Co-primary outcomes were the proportion of patients who received a second course of olaparib and the proportion who received olaparib retreatment for ≥6 months. Functional homologous recombination deficiency (HRD), somatic copy-number alteration (SCNA), and BRCAm reversions were investigated in tumor and liquid biopsies. RESULTS: Twenty-seven patients were treated (EP1 = 17, EP2 = 10), and 19 were evaluable. Twelve patients (63%) received a second course of olaparib and 4 received olaparib retreatment for ≥6 months. Common grade ≥2 adverse events during olaparib retreatment were anemia, nausea, and fatigue. No cases of MDS/AML occurred. Mean duration of olaparib treatment and retreatment differed (12.1 months vs. 4.4 months; P < 0.001). Functional HRD and SCNA did not predict PFS. A BRCA2 reversion mutation was detected in a post-olaparib liquid biopsy. CONCLUSIONS: A second course of olaparib can be safely administered to women with gBRCAm-HGSOC but is only modestly efficacious. See related commentary by Gonzalez-Ochoa and Oza, p. 2563..

PURPOSE OF REVIEW: Glioblastoma is the commonest primary brain cancer in adults whose outcomes are amongst the worst of any cancer. The current treatment pathway comprises surgery and postoperative chemoradiotherapy though unresectable diffusely infiltrative tumour cells remain untreated for several weeks post-diagnosis. Intratumoural heterogeneity combined with increased hypoxia in the postoperative tumour microenvironment potentially decreases the efficacy of adjuvant interventions and fails to prevent early postoperative regrowth, called rapid early progression (REP). In this review, we discuss the clinical implications and biological foundations of post-surgery REP. Subsequently, clinical interventions potentially targeting this phenomenon are reviewed systematically. RECENT FINDINGS: Early interventions include early systemic chemotherapy, neoadjuvant immunotherapy, local therapies delivered during surgery (including Gliadel wafers, nanoparticles and stem cell therapy) and several radiotherapy techniques. We critically appraise and compare these strategies in terms of their efficacy, toxicity, challenges and potential to prolong survival. Finally, we discuss the most promising strategies that could benefit future glioblastoma patients. There is biological rationale to suggest that early interventions could improve the outcome of glioblastoma patients and they should be investigated in future trials..

BACKGROUND: Vascular endothelial growth factor inhibitors (VEGFi) are compromised by a lack of validated biomarkers. Previously we showed that changes in the concentration of plasma Tie2 (pTie2) was a response biomarker for bevacizumab. Here, we investigated whether pTie2 can predict response and progression cross-tumour for generic VEGFi treatment. PATIENTS AND METHODS: Patients (n = 124) with advanced biliary tract cancer (ABC) received cisplatin/gemcitabine with cediranib or placebo (ABC-03 trial). Concentrations of pTie2 were measured longitudinally from before treatment until disease progression. Data from patients with ovarian cancer (n = 92, ICON7 trial) and patients with colorectal cancer (CRC) (n = 70, Travastin trial) were also included. RESULTS: Cediranib-treated ABC patients were deconvoluted into distinct groups where in one group pTie2 trajectories resembled those seen in placebo-treated patients and in another pTie2 significantly reduced (t-test P = 2.7 × 10-14). Using the 95% confidence interval for these two groups, we defined a vascular complete response (vCR) as a 24% reduction in pTie2 within 9 weeks; vascular no response (vNR) as a 7% increase in pTie2, and a vascular partial response (between these limits). vCR cediranib-treated patients had significantly improved progression-free survival (8.8 versus 7.5 months, restricted mean ratio 0.73, P = 0.012) and overall survival (18.8 versus 12.1 months, hazard ratio 0.49, P = 0.02). By integrating data across ovarian cancer, CRC and ABC, we show that (i) patients with vNR do not benefit from VEGFi and (ii) Tie2-defined vascular progression occurs sufficiently in advance of radiological progressive disease that changes in treatment could be offered to prevent clinical deterioration. CONCLUSION: pTie2 is the first cross-tumour, generic VEGFi, vascular response biomarker to guide optimum use of VEGFi in clinical practice..

BACKGROUND: Lesion/tissue segmentation on digital medical images enables biomarker extraction, image-guided therapy delivery, treatment response measurement, and training/validation for developing artificial intelligence algorithms and workflows. To ensure data reproducibility, criteria for standardised segmentation are critical but currently unavailable. METHODS: A modified Delphi process initiated by the European Imaging Biomarker Alliance (EIBALL) of the European Society of Radiology (ESR) and the European Organisation for Research and Treatment of Cancer (EORTC) Imaging Group was undertaken. Three multidisciplinary task forces addressed modality and image acquisition, segmentation methodology itself, and standards and logistics. Devised survey questions were fed via a facilitator to expert participants. The 58 respondents to Round 1 were invited to participate in Rounds 2-4. Subsequent rounds were informed by responses of previous rounds. RESULTS/CONCLUSIONS: Items with ≥ 75% consensus are considered a recommendation. These include system performance certification, thresholds for image signal-to-noise, contrast-to-noise and tumour-to-background ratios, spatial resolution, and artefact levels. Direct, iterative, and machine or deep learning reconstruction methods, use of a mixture of CE marked and verified research tools were agreed and use of specified reference standards and validation processes considered essential. Operator training and refreshment were considered mandatory for clinical trials and clinical research. Items with a 60-74% agreement require reporting (site-specific accreditation for clinical research, minimal pixel number within lesion segmented, use of post-reconstruction algorithms, operator training refreshment for clinical practice). Items with ≤ 60% agreement are outside current recommendations for segmentation (frequency of system performance tests, use of only CE-marked tools, board certification of operators, frequency of operator refresher training). Recommendations by anatomical area are also specified..

PURPOSE: This overview of the current landscape of quantitative magnetic resonance imaging biomarkers (qMR IBs) aims to support the standardisation of academic IBs to assist their translation to clinical practice. METHODS: We used three complementary approaches to investigate qMR IB use and quality management practices within the UK: 1) a literature search of qMR and quality management terms during 2011-2015 and 2016-2020; 2) a database search for clinical research studies using qMR IBs during 2016-2020; and 3) a survey to ascertain the current availability and quality management practices for clinical MRI scanners and associated equipment at research institutions across the UK. RESULTS: The analysis showed increased use of all qMR methods between the periods 2011-2015 and 2016-2020 and diffusion-tensor MRI and volumetry to be popular methods. However, the "translation ratio" of journal articles to clinical research studies was higher for qMR methods that have evidence of clinical translation via a commercial route, such as fat fraction and T2 mapping. The number of journal articles citing quality management terms doubled between the periods 2011-2015 and 2016-2020; although, its proportion relative to all journal articles only increased by 3.0%. The survey suggested that quality assurance (QA) and quality control (QC) of data acquisition procedures are under-reported in the literature and that QA/QC of acquired data/data analysis are under-developed and lack consistency between institutions. CONCLUSIONS: We summarise current attempts to standardise and translate qMR IBs, and conclude by outlining the ideal quality management practices and providing a gap analysis between current practice and a metrological standard..

OBJECTIVES: Radiomics is a promising avenue in non-invasive characterisation of diffuse glioma. Clinical translation is hampered by lack of reproducibility across centres and difficulty in standardising image intensity in MRI datasets. The study aim was to perform a systematic review of different methods of MRI intensity standardisation prior to radiomic feature extraction. METHODS: MEDLINE, EMBASE, and SCOPUS were searched for articles meeting the following eligibility criteria: MRI radiomic studies where one method of intensity normalisation was compared with another or no normalisation, and original research concerning patients diagnosed with diffuse gliomas. Using PRISMA criteria, data were extracted from short-listed studies including number of patients, MRI sequences, validation status, radiomics software, method of segmentation, and intensity standardisation. QUADAS-2 was used for quality appraisal. RESULTS: After duplicate removal, 741 results were returned from database and reference searches and, from these, 12 papers were eligible. Due to a lack of common pre-processing and different analyses, a narrative synthesis was sought. Three different intensity standardisation techniques have been studied: histogram matching (5/12), limiting or rescaling signal intensity (8/12), and deep learning (1/12)-only two papers compared different methods. From these studies, histogram matching produced the more reliable features compared to other methods of altering MRI signal intensity. CONCLUSION: Multiple methods of intensity standardisation have been described in the literature without clear consensus. Further research that directly compares different methods of intensity standardisation on glioma MRI datasets is required. KEY POINTS: • Intensity standardisation is a key pre-processing step in the development of robust radiomic signatures to evaluate diffuse glioma. • A minority of studies compared the impact of two or more methods. • Further research is required to directly compare multiple methods of MRI intensity standardisation on glioma datasets..

PURPOSE: Retrospective studies have identified a link between the average set-up error of lung cancer patients treated with image-guided radiotherapy (IGRT) and survival. The IGRT protocol was subsequently changed to reduce the action threshold. In this study, we use a Bayesian approach to evaluate the clinical impact of this change to practice using routine 'real-world' patient data. METHODS AND MATERIALS: Two cohorts of NSCLC patients treated with IGRT were compared: pre-protocol change (N = 780, 5 mm action threshold) and post-protocol change (N = 411, 2 mm action threshold). Survival models were fitted to each cohort and changes in the hazard ratios (HR) associated with residual set-up errors was assessed. The influence of using an uninformative and a skeptical prior in the model was investigated. RESULTS: Following the reduction of the action threshold, the HR for residual set-up error towards the heart was reduced by up to 10%. Median patient survival increased for patients with set-up errors towards the heart, and remained similar for patients with set-up errors away from the heart. Depending on the prior used, a residual hazard ratio may remain. CONCLUSIONS: Our analysis found a reduced hazard of death and increased survival for patients with residual set-up errors towards versus away from the heart post-protocol change. This study demonstrates the value of a Bayesian approach in the assessment of technical changes in radiotherapy practice and supports the consideration of adopting this approach in further prospective evaluations of changes to clinical practice..

Imaging biomarkers are used in therapy development to identify and quantify therapeutic response. In oncology, use of MRI, PET and other imaging methods can be complicated by spatially complex and heterogeneous tumor micro-environments, non-Gaussian data and small sample sizes. Linear Poisson Modelling (LPM) enables analysis of complex data that is quantitative and can operate in small data domains. We performed experiments in 5 mouse models to evaluate the ability of LPM to identify responding tumor habitats across a range of radiation and targeted drug therapies. We tested if LPM could identify differential biological response rates. We calculated the theoretical sample size constraints for applying LPM to new data. We then performed a co-clinical trial using small data to test if LPM could detect multiple therapeutics with both improved power and reduced animal numbers compared to conventional t-test approaches. Our data showed that LPM greatly increased the amount of information extracted from diffusion-weighted imaging, compared to cohort t-tests. LPM distinguished biological response rates between Calu6 tumors treated with 3 different therapies and between Calu6 tumors and 4 other xenograft models treated with radiotherapy. A simulated co-clinical trial using real data detected high precision per-tumor treatment effects in as few as 3 mice per cohort, with p-values as low as 1 in 10,000. These findings provide a route to simultaneously improve the information derived from preclinical imaging while reducing and refining the use of animals in cancer research..

BACKGROUND: Size-based assessments are inaccurate indicators of tumor response in soft-tissue sarcoma (STS), motivating the requirement for new response imaging biomarkers for this rare and heterogeneous disease. In this study, we assess the test-retest repeatability of radiomic features from MR diffusion-weighted imaging (DWI) and derived maps of apparent diffusion coefficient (ADC) in retroperitoneal STS and compare baseline repeatability with changes in radiomic features following radiotherapy (RT). MATERIALS AND METHODS: Thirty patients with retroperitoneal STS received an MR examination prior to treatment, of whom 23/30 were investigated in our repeatability analysis having received repeat baseline examinations and 14/30 patients were investigated in our post-treatment analysis having received an MR examination after completing pre-operative RT. One hundred and seven radiomic features were extracted from the full manually delineated tumor region using PyRadiomics. Test-retest repeatability was assessed using an intraclass correlation coefficient (baseline ICC), and post-radiotherapy variance analysis (post-RT-IMS) was used to compare the change in radiomic feature value to baseline repeatability. RESULTS: For the ADC maps and DWI images, 101 and 102 features demonstrated good baseline repeatability (baseline ICC > 0.85), respectively. Forty-three and 2 features demonstrated both good baseline repeatability and a high post-RT-IMS (>0.85), respectively. Pearson correlation between the baseline ICC and post-RT-IMS was weak (0.432 and 0.133, respectively). CONCLUSIONS: The ADC-based radiomic analysis shows better test-retest repeatability compared with features derived from DWI images in STS, and some of these features are sensitive to post-treatment change. However, good repeatability at baseline does not imply sensitivity to post-treatment change..

.

Glioblastoma is a high-grade aggressive neoplasm characterised by significant intra-tumoral spatial heterogeneity. Personalising therapy for this tumour requires non-invasive tools to visualise its heterogeneity to monitor treatment response on a regional level. To date, efforts to characterise glioblastoma's imaging features and heterogeneity have focussed on individual imaging biomarkers, or high-throughput radiomic approaches that consider a vast number of imaging variables across the tumour as a whole. Habitat imaging is a novel approach to cancer imaging that identifies tumour regions or 'habitats' based on shared imaging characteristics, usually defined using multiple imaging biomarkers. Habitat imaging reflects the evolution of imaging biomarkers and offers spatially preserved assessment of tumour physiological processes such perfusion and cellularity. This allows for regional assessment of treatment response to facilitate personalised therapy. In this review, we explore different methodologies to derive imaging habitats in glioblastoma, strategies to overcome its technical challenges, contrast experiences to other cancers, and describe potential clinical applications..

PURPOSE: Tumor hypoxia fuels an aggressive tumor phenotype and confers resistance to anticancer treatments. We conducted a clinical trial to determine whether the antimalarial drug atovaquone, a known mitochondrial inhibitor, reduces hypoxia in non-small cell lung cancer (NSCLC). PATIENTS AND METHODS: Patients with NSCLC scheduled for surgery were recruited sequentially into two cohorts: cohort 1 received oral atovaquone at the standard clinical dose of 750 mg twice daily, while cohort 2 did not. Primary imaging endpoint was change in tumor hypoxic volume (HV) measured by hypoxia PET-CT. Intercohort comparison of hypoxia gene expression signatures using RNA sequencing from resected tumors was performed. RESULTS: Thirty patients were evaluable for hypoxia PET-CT analysis, 15 per cohort. Median treatment duration was 12 days. Eleven (73.3%) atovaquone-treated patients had meaningful HV reduction, with median change -28% [95% confidence interval (CI), -58.2 to -4.4]. In contrast, median change in untreated patients was +15.5% (95% CI, -6.5 to 35.5). Linear regression estimated the expected mean HV was 55% (95% CI, 24%-74%) lower in cohort 1 compared with cohort 2 (P = 0.004), adjusting for cohort, tumor volume, and baseline HV. A key pharmacodynamics endpoint was reduction in hypoxia-regulated genes, which were significantly downregulated in atovaquone-treated tumors. Data from multiple additional measures of tumor hypoxia and perfusion are presented. No atovaquone-related adverse events were reported. CONCLUSIONS: This is the first clinical evidence that targeting tumor mitochondrial metabolism can reduce hypoxia and produce relevant antitumor effects at the mRNA level. Repurposing atovaquone for this purpose may improve treatment outcomes for NSCLC..

BACKGROUND: Patients with metastatic colorectal cancer are treated with cytotoxic chemotherapy supplemented by molecularly targeted therapies. There is a critical need to define biomarkers that can optimise the use of these therapies to maximise efficacy and avoid unnecessary toxicity. However, it is important to first define the changes in potential biomarkers following cytotoxic chemotherapy alone. This study reports the impact of standard cytotoxic chemotherapy across a range of circulating and imaging biomarkers. METHODS: A single-centre, prospective, biomarker-driven study. Eligible patients included those diagnosed with colorectal cancer with liver metastases that were planned to receive first line oxaliplatin plus 5-fluorouracil or capecitabine. Patients underwent paired blood sampling and magnetic resonance imaging (MRI), and biomarkers were associated with progression-free survival (PFS) and overall survival (OS). RESULTS: Twenty patients were recruited to the study. Data showed that chemotherapy significantly reduced the number of circulating tumour cells as well as the circulating concentrations of Ang1, Ang2, VEGF-A, VEGF-C and VEGF-D from pre-treatment to cycle 2 day 2. The changes in circulating concentrations were not associated with PFS or OS. On average, the MRI perfusion/permeability parameter, Ktrans, increased in response to cytotoxic chemotherapy from pre-treatment to cycle 2 day 2 and this increase was associated with worse OS (HR 1.099, 95%CI 1.01-1.20, p = 0.025). CONCLUSIONS: In patients diagnosed with colorectal cancer with liver metastases, treatment with standard chemotherapy changes cell- and protein-based biomarkers, although these changes are not associated with survival outcomes. In contrast, the imaging biomarker, Ktrans, offers promise to direct molecularly targeted therapies such as anti-angiogenic agents..

Existing quantitative imaging biomarkers (QIBs) are associated with known biological tissue characteristics and follow a well-understood path of technical, biological and clinical validation before incorporation into clinical trials. In radiomics, novel data-driven processes extract numerous visually imperceptible statistical features from the imaging data with no a priori assumptions on their correlation with biological processes. The selection of relevant features (radiomic signature) and incorporation into clinical trials therefore requires additional considerations to ensure meaningful imaging endpoints. Also, the number of radiomic features tested means that power calculations would result in sample sizes impossible to achieve within clinical trials. This article examines how the process of standardising and validating data-driven imaging biomarkers differs from those based on biological associations. Radiomic signatures are best developed initially on datasets that represent diversity of acquisition protocols as well as diversity of disease and of normal findings, rather than within clinical trials with standardised and optimised protocols as this would risk the selection of radiomic features being linked to the imaging process rather than the pathology. Normalisation through discretisation and feature harmonisation are essential pre-processing steps. Biological correlation may be performed after the technical and clinical validity of a radiomic signature is established, but is not mandatory. Feature selection may be part of discovery within a radiomics-specific trial or represent exploratory endpoints within an established trial; a previously validated radiomic signature may even be used as a primary/secondary endpoint, particularly if associations are demonstrated with specific biological processes and pathways being targeted within clinical trials. KEY POINTS: • Data-driven processes like radiomics risk false discoveries due to high-dimensionality of the dataset compared to sample size, making adequate diversity of the data, cross-validation and external validation essential to mitigate the risks of spurious associations and overfitting. • Use of radiomic signatures within clinical trials requires multistep standardisation of image acquisition, image analysis and data mining processes. • Biological correlation may be established after clinical validation but is not mandatory..

PURPOSE: We introduce a novel, generalized tracer kinetic model selection framework to quantify microvascular characteristics of liver and tumor tissue in gadoxetate-enhanced dynamic contrast-enhanced MRI (DCE-MRI). METHODS: Our framework includes a hierarchy of nested models, from which physiological parameters are derived in 2 regimes, corresponding to the active transport and free diffusion of gadoxetate. We use simulations to show the sensitivity of model selection and parameter estimation to temporal resolution, time-series duration, and noise. We apply the framework in 8 healthy volunteers (time-series duration up to 24 minutes) and 10 patients with hepatocellular carcinoma (6 minutes). RESULTS: The active transport regime is preferred in 98.6% of voxels in volunteers, 82.1% of patients' non-tumorous liver, and 32.2% of tumor voxels. Interpatient variations correspond to known co-morbidities. Simulations suggest both datasets have sufficient temporal resolution and signal-to-noise ratio, while patient data would be improved by using a time-series duration of at least 12 minutes. CONCLUSIONS: In patient data, gadoxetate exhibits different kinetics: (a) between liver and tumor regions and (b) within regions due to liver disease and/or tumor heterogeneity. Our generalized framework selects a physiological interpretation at each voxel, without preselecting a model for each region or duplicating time-consuming optimizations for models with identical functional forms..

Radiomics refers to the extraction of mineable data from medical imaging and has been applied within oncology to improve diagnosis, prognostication, and clinical decision support, with the goal of delivering precision medicine. The authors provide a practical approach for successfully implementing a radiomic workflow from planning and conceptualization through manuscript writing. Applications in oncology typically are either classification tasks that involve computing the probability of a sample belonging to a category, such as benign versus malignant, or prediction of clinical events with a time-to-event analysis, such as overall survival. The radiomic workflow is multidisciplinary, involving radiologists and data and imaging scientists, and follows a stepwise process involving tumor segmentation, image preprocessing, feature extraction, model development, and validation. Images are curated and processed before segmentation, which can be performed on tumors, tumor subregions, or peritumoral zones. Extracted features typically describe the distribution of signal intensities and spatial relationship of pixels within a region of interest. To improve model performance and reduce overfitting, redundant and nonreproducible features are removed. Validation is essential to estimate model performance in new data and can be performed iteratively on samples of the dataset (cross-validation) or on a separate hold-out dataset by using internal or external data. A variety of noncommercial and commercial radiomic software applications can be used. Guidelines and artificial intelligence checklists are useful when planning and writing up radiomic studies. Although interest in the field continues to grow, radiologists should be familiar with potential pitfalls to ensure that meaningful conclusions can be drawn. Online supplemental material is available for this article. Published under a CC BY 4.0 license..

Imaging biomarkers require technical, biological, and clinical validation to be translated into robust tools in research or clinical settings. This study contributes to the technical validation of radiomic features from magnetic resonance imaging (MRI) by evaluating the repeatability of features from four MR sequences: pre-contrast T1- and T2-weighted images, pre-contrast quantitative T1 maps (qT1), and contrast-enhanced T1-weighted images. Fifty-one patients with colorectal cancer liver metastases were scanned twice, up to 7 days apart. Repeatability was quantified using the intraclass correlation coefficient (ICC) and repeatability coefficient (RC), and the impact of non-Gaussian feature distributions and image normalisation was evaluated. Most radiomic features had non-Gaussian distributions, but Box-Cox transformations enabled ICCs and RCs to be calculated appropriately for an average of 97% of features across sequences. ICCs ranged from 0.30 to 0.99, with volume and other shape features tending to be most repeatable; volume ICC > 0.98 for all sequences. 19% of features from non-normalised images exhibited significantly different ICCs in pair-wise sequence comparisons. Normalisation tended to increase ICCs for pre-contrast T1- and T2-weighted images, and decrease ICCs for qT1 maps. RCs tended to vary more between sequences than ICCs, showing that evaluations of feature performance depend on the chosen metric. This work suggests that feature-specific repeatability, from specific combinations of MR sequence and pre-processing steps, should be evaluated to select robust radiomic features as biomarkers in specific studies. In addition, as different repeatability metrics can provide different insights into a specific feature, consideration of the appropriate metric should be taken in a study-specific context..

The National Cancer Imaging Translational Accelerator (NCITA) is creating a UK national coordinated infrastructure for accelerated translation of imaging biomarkers for clinical use. Through the development of standardised protocols, data integration tools and ongoing training programmes, NCITA provides a unique scalable infrastructure for imaging biomarker qualification using multicentre clinical studies..

The annual global incidence of cervical cancer is approximately 604 000 cases/342 000 deaths, making it the fourth most common cancer in women. Cervical cancer is a major healthcare problem in low and middle income countries where 85% of new cases and deaths occur. Secondary prevention measures have reduced incidence and mortality in developed countries over the past 30 years, but cervical cancer remains a major cause of cancer deaths in women. For women who present with Fédération Internationale de Gynécologie et d'Obstétrique (FIGO 2018) stages IB3 or upwards, chemoradiation is the established treatment. Despite high rates of local control, overall survival is less than 50%, largely due to distant relapse. Reducing the health burden of cervical cancer requires greater individualization of treatment, identifying those at risk of relapse and progression for modified or intensified treatment. Hypoxia is a well known feature of solid tumors and an established therapeutic target. Low tumorous oxygenation increases the risk of local invasion, metastasis and treatment failure. While meta-analyses show benefit, many individual trials targeting hypoxia failed in part due to not selecting patients most likely to benefit. This review summarizes the available hypoxia-targeted strategies and identifies further research and new treatment paradigms needed to improve patient outcomes. The applications and limitations of hypoxia biomarkers for treatment selection and response monitoring are discussed. Finally, areas of greatest unmet clinical need are identified to measure and target hypoxia and therefore improve cervical cancer outcomes..

Perianal Crohn's Disease (pCD) is a common manifestation of Crohn's Disease. Absence of reliable disease measures makes disease monitoring unreliable. Qualitative MRI has been increasingly used for diagnosing and monitoring pCD and has shown potential for assessing response to treatment. Quantitative MRI sequences, such as diffusion-weighted imaging (DWI), dynamic contrast enhancement (DCE) and magnetisation transfer (MT), along with T2 relaxometry, offer opportunities to improve diagnostic capability. Quantitative MRI sequences (DWI, DCE, MT and T2) were used in a cohort of 25 pCD patients before and 12 weeks after biological therapy at two different field strengths (1.5 and 3 T). Disease activity was measured with the Perianal Crohn's Disease Activity index (PDAI) and serum C-reactive protein (CRP). Diseased tissue areas on MRI were defined by a radiologist. A baseline model to predict outcome at 12 weeks was developed. No differences were seen in the quantitative MR measured in the diseased tissue regions from baseline to 12 weeks; however, PDAI and CRP decreased. Baseline PDAI, CRP, T2 relaxometry and surgical history were found to have a moderate ability to predict response after 12 weeks of biological treatment. Validation in larger cohorts with MRI and clinical measures are needed in order to further develop the model..

MOTIVATION: Probabilistic latent semantic analysis (pLSA) is commonly applied to describe mass spectra (MS) images. However, the method does not provide certain outputs necessary for the quantitative scientific interpretation of data. In particular, it lacks assessment of statistical uncertainty and the ability to perform hypothesis testing. We show how linear Poisson modelling advances pLSA, giving covariances on model parameters and supporting χ2 testing for the presence/absence of MS signal components. As an example, this is useful for the identification of pathology in MALDI biological samples. We also show potential wider applicability, beyond MS, using magnetic resonance imaging (MRI) data from colorectal xenograft models. RESULTS: Simulations and MALDI spectra of a stroke-damaged rat brain show MS signals from pathological tissue can be quantified. MRI diffusion data of control and radiotherapy-treated tumours further show high sensitivity hypothesis testing for treatment effects. Successful χ2 and degrees-of-freedom are computed, allowing null-hypothesis thresholding at high levels of confidence. AVAILABILITY AND IMPLEMENTATION: Open-source image analysis software available from TINA Vision, www.tina-vision.net. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online..

Radiomics has become a popular image analysis method in the last few years. Its key hypothesis is that medical images harbor biological, prognostic and predictive information that is not revealed upon visual inspection. In contrast to previous work with a priori defined imaging biomarkers, radiomics instead calculates image features at scale and uses statistical methods to identify those most strongly associated to outcome. This builds on years of research into computer aided diagnosis and pattern recognition. While the potential of radiomics to aid personalized medicine is widely recognized, several technical limitations exist which hinder biomarker translation. Aspects of the radiomic workflow lack repeatability or reproducibility under particular circumstances, which is a key requirement for the translation of imaging biomarkers into clinical practice. One of the most commonly studied uses of radiomics is for personalized medicine applications in Non-Small Cell Lung Cancer (NSCLC). In this review, we summarize reported methodological limitations in CT based radiomic analyses together with suggested solutions. We then evaluate the current NSCLC radiomics literature to assess the risk associated with accepting the published conclusions with respect to these limitations. We review different complementary scoring systems and initiatives that can be used to critically appraise data from radiomics studies. Wider awareness should improve the quality of ongoing and future radiomics studies and advance their potential as clinically relevant biomarkers for personalized medicine in patients with NSCLC..

PURPOSE: MRI biomarkers of tumor response to treatment are typically obtained from parameters derived from a model applied to pre-treatment and post-treatment data. However, as tumors are spatially and temporally heterogeneous, different models may be necessary in different tumor regions, and model suitability may change over time. This work evaluates how the suitability of two diffusion-weighted (DW) MRI models varies spatially within tumors at the voxel level and in response to radiotherapy, potentially allowing inference of qualitatively different tumor microenvironments. METHODS: DW-MRI data were acquired in CT26 subcutaneous allografts before and after radiotherapy. Restricted and time-independent diffusion models were compared, with regions well-described by the former hypothesized to reflect cellular tissue, and those well-described by the latter expected to reflect necrosis or oedema. Technical and biological validation of the percentage of tissue described by the restricted diffusion microstructural model (termed %MM) was performed through simulations and histological comparison. RESULTS: Spatial and radiotherapy-related variation in model suitability was observed. %MM decreased from a mean of 64% at baseline to 44% 6 days post-radiotherapy in the treated group. %MM correlated negatively with the percentage of necrosis from histology, but overestimated it due to noise. Within MM regions, microstructural parameters were sensitive to radiotherapy-induced changes. CONCLUSIONS: There is spatial and radiotherapy-related variation in different models' suitability for describing diffusion in tumor tissue, suggesting the presence of different and changing tumor sub-regions. The biological and technical validation of the proposed %MM cancer imaging biomarker suggests it correlates with, but overestimates, the percentage of necrosis..

OBJECTIVE: To investigate the effects of Image Biomarker Standardisation Initiative (IBSI) compliance, harmonisation of calculation settings and platform version on the statistical reliability of radiomic features and their corresponding ability to predict clinical outcome. METHODS: The statistical reliability of radiomic features was assessed retrospectively in three clinical datasets (patient numbers: 108 head and neck cancer, 37 small-cell lung cancer, 47 non-small-cell lung cancer). Features were calculated using four platforms (PyRadiomics, LIFEx, CERR and IBEX). PyRadiomics, LIFEx and CERR are IBSI-compliant, whereas IBEX is not. The effects of IBSI compliance, user-defined calculation settings and platform version were assessed by calculating intraclass correlation coefficients and confidence intervals. The influence of platform choice on the relationship between radiomic biomarkers and survival was evaluated using univariable cox regression in the largest dataset. RESULTS: The reliability of radiomic features calculated by the different software platforms was only excellent (ICC > 0.9) for 4/17 radiomic features when comparing all four platforms. Reliability improved to ICC > 0.9 for 15/17 radiomic features when analysis was restricted to the three IBSI-compliant platforms. Failure to harmonise calculation settings resulted in poor reliability, even across the IBSI-compliant platforms. Software platform version also had a marked effect on feature reliability in CERR and LIFEx. Features identified as having significant relationship to survival varied between platforms, as did the direction of hazard ratios. CONCLUSION: IBSI compliance, user-defined calculation settings and choice of platform version all influence the statistical reliability and corresponding performance of prognostic models in radiomics. KEY POINTS: • Reliability of radiomic features varies between feature calculation platforms and with choice of software version. • Image Biomarker Standardisation Initiative (IBSI) compliance improves reliability of radiomic features across platforms, but only when calculation settings are harmonised. • IBSI compliance, user-defined calculation settings and choice of platform version collectively affect the prognostic value of features..

PURPOSE: Hypoxia is associated with poor prognosis and is predictive of poor response to cancer treatments, including radiotherapy. Developing noninvasive biomarkers that both detect hypoxia prior to treatment and track change in tumor hypoxia following treatment is required urgently. EXPERIMENTAL DESIGN: We evaluated the ability of oxygen-enhanced MRI (OE-MRI) to map and quantify therapy-induced changes in tumor hypoxia by measuring oxygen-refractory signals in perfused tissue (perfused Oxy-R). Clinical first-in-human study in patients with non-small cell lung cancer (NSCLC) was performed alongside preclinical experiments in two xenograft tumors (Calu6 NSCLC model and U87 glioma model). RESULTS: MRI perfused Oxy-R tumor fraction measurement of hypoxia was validated with ex vivo tissue pathology in both xenograft models. Calu6 and U87 experiments showed that MRI perfused Oxy-R tumor volume was reduced relative to control following single fraction 10-Gy radiation and fractionated chemoradiotherapy (P < 0.001) due to both improved perfusion and reduced oxygen consumption rate. Next, evaluation of 23 patients with NSCLC showed that OE-MRI was clinically feasible and that tumor perfused Oxy-R volume is repeatable [interclass correlation coefficient: 0.961 (95% CI, 0.858-0.990); coefficient of variation: 25.880%]. Group-wise perfused Oxy-R volume was reduced at 14 days following start of radiotherapy (P = 0.015). OE-MRI detected between-subject variation in hypoxia modification in both xenograft and patient tumors. CONCLUSIONS: These findings support applying OE-MRI biomarkers to monitor hypoxia modification, to stratify patients in clinical trials of hypoxia-modifying therapies, to identify patients with hypoxic tumors that may fail treatment with immunotherapy, and to guide adaptive radiotherapy by mapping regional hypoxia..

Hypoxia is known to be a poor prognostic indicator for nearly all solid tumours and also is predictive of treatment failure for radiotherapy, chemotherapy, surgery and targeted therapies. Imaging has potential to identify, spatially map and quantify tumour hypoxia prior to therapy, as well as track changes in hypoxia on treatment. At present no hypoxia imaging methods are available for routine clinical use. Research has largely focused on positron emission tomography (PET)-based techniques, but there is gathering evidence that MRI techniques may provide a practical and more readily translational alternative. In this review we focus on the potential for imaging hypoxia by measuring changes in longitudinal relaxation [R1; termed oxygen-enhanced MRI or tumour oxygenation level dependent (TOLD) MRI] and effective transverse relaxation [R2*; termed blood oxygenation level dependent (BOLD) MRI], induced by inhalation of either 100% oxygen or the radiosensitising hyperoxic gas carbogen. We explain the scientific principles behind oxygen-enhanced MRI and BOLD and discuss significant studies and their limitations. All imaging biomarkers require rigorous validation in order to translate into clinical use and the steps required to further develop oxygen-enhanced MRI and BOLD MRI into decision-making tools are discussed..

Clinical workflows for the non-invasive detection and characterization of disease states could benefit from optical-imaging biomarkers. In this Perspective, we discuss opportunities and challenges towards the clinical implementation of optical-imaging biomarkers for the early detection of cancer by analysing two case studies: the assessment of skin lesions in primary care, and the surveillance of patients with Barrett's oesophagus in specialist care. We stress the importance of technical and biological validations and clinical-utility assessments, and the need to address implementation bottlenecks. In addition, we define a translational roadmap for the widespread clinical implementation of optical-imaging technologies..

BACKGROUND: Many translational MR biomarkers derive from measurements of the water proton longitudinal relaxation rate R1, but evidence for between-site reproducibility of R1 in small-animal MRI is lacking. OBJECTIVE: To assess R1 repeatability and multi-site reproducibility in phantoms for preclinical MRI. METHODS: R1 was measured by saturation recovery in 2% agarose phantoms with five nickel chloride concentrations in 12 magnets at 5 field strengths in 11 centres on two different occasions within 1-13 days. R1 was analysed in three different regions of interest, giving 360 measurements in total. Root-mean-square repeatability and reproducibility coefficients of variation (CoV) were calculated. Propagation of reproducibility errors into 21 translational MR measurements and biomarkers was estimated. Relaxivities were calculated. Dynamic signal stability was also measured. RESULTS: CoV for day-to-day repeatability (N = 180 regions of interest) was 2.34% and for between-centre reproducibility (N = 9 centres) was 1.43%. Mostly, these do not propagate to biologically significant between-centre error, although a few R1-based MR biomarkers were found to be quite sensitive even to such small errors in R1, notably in myocardial fibrosis, in white matter, and in oxygen-enhanced MRI. The relaxivity of aqueous Ni2+ in 2% agarose varied between 0.66 s-1 mM-1 at 3 T and 0.94 s-1 mM-1 at 11.7T. INTERPRETATION: While several factors affect the reproducibility of R1-based MR biomarkers measured preclinically, between-centre propagation of errors arising from intrinsic equipment irreproducibility should in most cases be small. However, in a few specific cases exceptional efforts might be required to ensure R1-reproducibility..

BACKGROUND: The DREAMtherapy (Dual REctal Angiogenesis MEK inhibition radiotherapy) trial is a novel intertwined design whereby two tyrosine kinase inhibitors (cediranib and selumetinib) were independently evaluated with rectal chemoradiotherapy (CRT) in an efficient manner to limit the extended follow-up period often required for radiotherapy studies. PATIENTS AND METHODS: Cediranib or selumetinib was commenced 10 days before and then continued with RT (45 Gy/25#/5 wks) and capecitabine (825 mg/m2 twice a day (BID)). When three patients in the cediranib 15-mg once daily (OD) cohort were in the surveillance period, recruitment to the selumetinib cohort commenced. This alternating schedule was followed throughout. Three cediranib (15, 20 and 30 mg OD) and two selumetinib cohorts (50 and 75 mg BID) were planned. Circulating and imaging biomarkers of inflammation/angiogenesis were evaluated. RESULTS: In case of cediranib, dose-limiting diarrhoea, fatigue and skin reactions were seen in the 30-mg OD cohort, and therefore, 20 mg OD was defined as the maximum tolerated dose. Forty-one percent patients achieved a clinical or pathological complete response (7/17), and 53% (9/17) had an excellent clinical or pathological response (ECPR). Significantly lower level of pre-treatment plasma tumour necrosis factor alpha (TNFα) was found in patients who had an ECPR. In case of selumetinib, the 50-mg BID cohort was poorly tolerated (fatigue and diarrhoea); a reduced dose cohort of 75-mg OD was opened which was also poorly tolerated, and further recruitment was abandoned. Of the 12 patients treated, two attained an ECPR (17%). CONCLUSIONS: This novel intertwined trial design is an effective way to independently investigate multiple agents with radiotherapy. The combination of cediranib with CRT was well tolerated with encouraging efficacy. TNFα emerged as a potential predictive biomarker of response and warrants further evaluation..

Observer-driven pattern recognition is the standard for interpretation of medical images. To achieve global parity in interpretation, semi-quantitative scoring systems have been developed based on observer assessments; these are widely used in scoring coronary artery disease, the arthritides and neurological conditions and for indicating the likelihood of malignancy. However, in an era of machine learning and artificial intelligence, it is increasingly desirable that we extract quantitative biomarkers from medical images that inform on disease detection, characterisation, monitoring and assessment of response to treatment. Quantitation has the potential to provide objective decision-support tools in the management pathway of patients. Despite this, the quantitative potential of imaging remains under-exploited because of variability of the measurement, lack of harmonised systems for data acquisition and analysis, and crucially, a paucity of evidence on how such quantitation potentially affects clinical decision-making and patient outcome. This article reviews the current evidence for the use of semi-quantitative and quantitative biomarkers in clinical settings at various stages of the disease pathway including diagnosis, staging and prognosis, as well as predicting and detecting treatment response. It critically appraises current practice and sets out recommendations for using imaging objectively to drive patient management decisions..

MOTIVATION: Imaging demonstrates that preclinical and human tumors are heterogeneous, i.e. a single tumor can exhibit multiple regions that behave differently during both development and also in response to treatment. The large variations observed in control group, tumors can obscure detection of significant therapeutic effects due to the ambiguity in attributing causes of change. This can hinder development of effective therapies due to limitations in experimental design rather than due to therapeutic failure. An improved method to model biological variation and heterogeneity in imaging signals is described. Specifically, linear Poisson modeling (LPM) evaluates changes in apparent diffusion co-efficient between baseline and 72 h after radiotherapy, in two xenograft models of colorectal cancer. The statistical significance of measured changes is compared to those attainable using a conventional t-test analysis on basic apparent diffusion co-efficient distribution parameters. RESULTS: When LPMs were applied to treated tumors, the LPMs detected highly significant changes. The analyses were significant for all tumors, equating to a gain in power of 4-fold (i.e. equivalent to having a sample size 16 times larger), compared with the conventional approach. In contrast, highly significant changes are only detected at a cohort level using t-tests, restricting their potential use within personalized medicine and increasing the number of animals required during testing. Furthermore, LPM enabled the relative volumes of responding and non-responding tissue to be estimated for each xenograft model. Leave-one-out analysis of the treated xenografts provided quality control and identified potential outliers, raising confidence in LPM data at clinically relevant sample sizes. AVAILABILITY AND IMPLEMENTATION: TINA Vision open source software is available from www.tina-vision.net. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online..

Oxygen deprivation (hypoxia) in non-small cell lung cancer (NSCLC) is an important factor in treatment resistance and poor survival. Hypoxia is an attractive therapeutic target, particularly in the context of radiotherapy, which is delivered to more than half of NSCLC patients. However, NSCLC hypoxia-targeted therapy trials have not yet translated into patient benefit. Recently, early termination of promising evofosfamide and tarloxotinib bromide studies due to futility highlighted the need for a paradigm shift in our approach to avoid disappointments in future trials. Radiotherapy dose painting strategies based on hypoxia imaging require careful refinement prior to clinical investigation. This review will summarize the role of hypoxia, highlight the potential of hypoxia as a therapeutic target, and outline past and ongoing hypoxia-targeted therapy trials in NSCLC. Evidence supporting radiotherapy dose painting based on hypoxia imaging will be critically appraised. Carefully selected hypoxia biomarkers suitable for integration within future NSCLC hypoxia-targeted therapy trials will be examined. Research gaps will be identified to guide future investigation. Although this review will focus on NSCLC hypoxia, more general discussions (eg, obstacles of hypoxia biomarker research and developing a framework for future hypoxia trials) are applicable to other tumor sites..

OBJECTIVE: Application of whole body diffusion-weighted MRI (WB-DWI) for oncology are rapidly increasing within both research and routine clinical domains. However, WB-DWI as a quantitative imaging biomarker (QIB) has significantly slower adoption. To date, challenges relating to accuracy and reproducibility, essential criteria for a good QIB, have limited widespread clinical translation. In recognition, a UK workgroup was established in 2016 to provide technical consensus guidelines (to maximise accuracy and reproducibility of WB-MRI QIBs) and accelerate the clinical translation of quantitative WB-DWI applications for oncology. METHODS: A panel of experts convened from cancer centres around the UK with subspecialty expertise in quantitative imaging and/or the use of WB-MRI with DWI. A formal consensus method was used to obtain consensus agreement regarding best practice. Questions were asked about the appropriateness or otherwise on scanner hardware and software, sequence optimisation, acquisition protocols, reporting, and ongoing quality control programs to monitor precision and accuracy and agreement on quality control. RESULTS: The consensus panel was able to reach consensus on 73% (255/351) items and based on consensus areas made recommendations to maximise accuracy and reproducibly of quantitative WB-DWI studies performed at 1.5T. The panel were unable to reach consensus on the majority of items related to quantitative WB-DWI performed at 3T. CONCLUSION: This UK Quantitative WB-DWI Technical Workgroup consensus provides guidance on maximising accuracy and reproducibly of quantitative WB-DWI for oncology. The consensus guidance can be used by researchers and clinicians to harmonise WB-DWI protocols which will accelerate clinical translation of WB-DWI-derived QIBs..

BACKGROUND: Solid tumours exhibit enhanced vessel permeability and fenestrated endothelium to varying degree, but it is unknown how this varies in patients between and within tumour types. Dynamic contrast-enhanced (DCE) MRI provides a measure of perfusion and permeability, the transfer constant Ktrans, which could be employed for such comparisons in patients. AIM: To test the hypothesis that different tumour types exhibit systematically different Ktrans. MATERIALS AND METHODS: DCE-MRI data were retrieved from 342 solid tumours in 230 patients. These data were from 18 previous studies, each of which had had a different analysis protocol. All data were reanalysed using a standardised workflow using an extended Tofts model. A model of the posterior density of median Ktrans was built assuming a log-normal distribution and fitting a simple Bayesian hierarchical model. RESULTS: 12 histological tumour types were included. In glioma, median Ktrans was 0.016min-1 and for non-glioma tumours, median Ktrans ranged from 0.10 (cervical) to 0.21min-1 (prostate metastatic to bone). The geometric mean (95% CI) across all the non-glioma tumours was 0.15 (0.05, 0.45)min-1. There was insufficient separation between the posterior densities to be able to predict the Ktrans value of a tumour given the tumour type, except that the median Ktrans for gliomas was below 0.05min-1 with 80% probability, and median Ktrans measurements for the remaining tumour types were between 0.05 and 0.4min-1 with 80% probability. CONCLUSION: With the exception of glioma, our hypothesis that different tumour types exhibit different Ktrans was not supported. Studies in which tumour permeability is believed to affect outcome should not simply seek tumour types thought to exhibit high permeability. Instead, Ktrans is an idiopathic parameter, and, where permeability is important, Ktrans should be measured in each tumour to personalise that treatment..

The current standard of care for the management of inoperable stage 3 non-small cell lung cancer (NSCLC) is concurrent chemoradiotherapy (cCRT) using radiotherapy dose-fractionation and chemotherapy regimens that were established 3 decades ago. In an attempt to improve the chances of long-term control from cCRT, dose-escalation of the radiotherapy dose was assessed in the RTOG 0617 randomised control study comparing the standard 60 Gy in 30 fractions with a high-dose arm receiving 74 Gy in 37 fractions. Following the publication of this trial the thoracic oncology community were surprised to learn that there was worse survival in the dose-escalated arm and that for now the standard of care must remain with the lower dose. In this article we review the RTOG 0617 paper with subsequent analyses and studies to explore why the use of dose-escalated cCRT in stage 3 NSCLC has not shown the benefits that were expected. The overarching theme of this opinion piece is how heterogeneity between stage 3 NSCLC cases in terms of patient, tumour, and clinical factors may obscure the potential benefits of dose-escalation by causing imbalances in the arms of studies such as RTOG 0617. We also examine recent advances in the staging, management, and technological delivery of radiotherapy in NSCLC and how these may be employed to optimise cCRT trials in the future and ensure that any potential benefits of dose-escalation can be detected..

PURPOSE: Previous work has shown that combining dynamic contrast-enhanced (DCE)-MRI and oxygen-enhanced (OE)-MRI binary enhancement maps can identify tumor hypoxia. The current work proposes a novel, data-driven method for mapping tissue oxygenation and perfusion heterogeneity, based on clustering DCE/OE-MRI data. METHODS: DCE-MRI and OE-MRI were performed on nine U87 (glioblastoma) and seven Calu6 (non-small cell lung cancer) murine xenograft tumors. Area under the curve and principal component analysis features were calculated and clustered separately using Gaussian mixture modelling. Evaluation metrics were calculated to determine the optimum feature set and cluster number. Outputs were quantitatively compared with a previous non data-driven approach. RESULTS: The optimum method located six robustly identifiable clusters in the data, yielding tumor region maps with spatially contiguous regions in a rim-core structure, suggesting a biological basis. Mean within-cluster enhancement curves showed physiologically distinct, intuitive kinetics of enhancement. Regions of DCE/OE-MRI enhancement mismatch were located, and voxel categorization agreed well with the previous non data-driven approach (Cohen's kappa = 0.61, proportional agreement = 0.75). CONCLUSION: The proposed method locates similar regions to the previous published method of binarization of DCE/OE-MRI enhancement, but renders a finer segmentation of intra-tumoral oxygenation and perfusion. This could aid in understanding the tumor microenvironment and its heterogeneity. Magn Reson Med 79:2236-2245, 2018. © 2017 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited..

Oncological use of anti-angiogenic VEGF inhibitors has been limited by the lack of informative biomarkers. Previously we reported circulating Tie2 as a vascular response biomarker for bevacizumab-treated ovarian cancer patients. Using advanced MRI and circulating biomarkers we have extended these findings in metastatic colorectal cancer (n = 70). Bevacizumab (10 mg/kg) was administered to elicit a biomarker response, followed by FOLFOX6-bevacizumab until disease progression. Bevacizumab induced a correlation between Tie2 and the tumor vascular imaging biomarker, Ktrans (R:-0.21 to 0.47) implying that Tie2 originated from the tumor vasculature. Tie2 trajectories were independently associated with pre-treatment tumor vascular characteristics, tumor response, progression free survival (HR for progression = 3.01, p = 0.00014; median PFS 248 vs. 348 days p = 0.0008) and the modeling of progressive disease (p < 0.0001), suggesting that Tie2 should be monitored clinically to optimize VEGF inhibitor use. A vascular response is defined as a 30% reduction in Tie2; vascular progression as a 40% increase in Tie2 above the nadir. Tie2 is the first, validated, tumor vascular response biomarker for VEGFi..

Purpose To cross-validate T1-weighted oxygen-enhanced (OE) MRI measurements of tumor hypoxia with intrinsic susceptibility MRI measurements and to demonstrate the feasibility of translation of the technique for patients. Materials and Methods Preclinical studies in nine 786-0-R renal cell carcinoma (RCC) xenografts and prospective clinical studies in eight patients with RCC were performed. Longitudinal relaxation rate changes (∆R1) after 100% oxygen inhalation were quantified, reflecting the paramagnetic effect on tissue protons because of the presence of molecular oxygen. Native transverse relaxation rate (R2*) and oxygen-induced R2* change (∆R2*) were measured, reflecting presence of deoxygenated hemoglobin molecules. Median and voxel-wise values of ∆R1 were compared with values of R2* and ∆R2*. Tumor regions with dynamic contrast agent-enhanced MRI perfusion, refractory to signal change at OE MRI (referred to as perfused Oxy-R), were distinguished from perfused oxygen-enhancing (perfused Oxy-E) and nonperfused regions. R2* and ∆R2* values in each tumor subregion were compared by using one-way analysis of variance. Results Tumor-wise and voxel-wise ∆R1 and ∆R2* comparisons did not show correlative relationships. In xenografts, parcellation analysis revealed that perfused Oxy-R regions had faster native R2* (102.4 sec-1 vs 81.7 sec-1) and greater negative ∆R2* (-22.9 sec-1 vs -5.4 sec-1), compared with perfused Oxy-E and nonperfused subregions (all P < .001), respectively. Similar findings were present in human tumors (P < .001). Further, perfused Oxy-R helped identify tumor hypoxia, measured at pathologic analysis, in both xenografts (P = .002) and human tumors (P = .003). Conclusion Intrinsic susceptibility biomarkers provide cross validation of the OE MRI biomarker perfused Oxy-R. Consistent relationship to pathologic analyses was found in xenografts and human tumors, demonstrating biomarker translation. Published under a CC BY 4.0 license. Online supplemental material is available for this article..

Magnetic resonance imaging (MRI) is a highly versatile imaging modality that can be used to measure features of the tumour microenvironment including cell death, proliferation, metabolism, angiogenesis, and hypoxia. Mapping and quantifying these pathophysiological features has the potential to alter the use of adaptive radiotherapy planning. Although these methods are available for use on diagnostic machines, several challenges exist for implementing these functional MRI methods on the MRI-linear accelerators (linacs). This review considers these challenges and potential solutions..

Imaging biomarkers (IBs) are integral to the routine management of patients with cancer. IBs used daily in oncology include clinical TNM stage, objective response and left ventricular ejection fraction. Other CT, MRI, PET and ultrasonography biomarkers are used extensively in cancer research and drug development. New IBs need to be established either as useful tools for testing research hypotheses in clinical trials and research studies, or as clinical decision-making tools for use in healthcare, by crossing 'translational gaps' through validation and qualification. Important differences exist between IBs and biospecimen-derived biomarkers and, therefore, the development of IBs requires a tailored 'roadmap'. Recognizing this need, Cancer Research UK (CRUK) and the European Organisation for Research and Treatment of Cancer (EORTC) assembled experts to review, debate and summarize the challenges of IB validation and qualification. This consensus group has produced 14 key recommendations for accelerating the clinical translation of IBs, which highlight the role of parallel (rather than sequential) tracks of technical (assay) validation, biological/clinical validation and assessment of cost-effectiveness; the need for IB standardization and accreditation systems; the need to continually revisit IB precision; an alternative framework for biological/clinical validation of IBs; and the essential requirements for multicentre studies to qualify IBs for clinical use..

There is interest in identifying and quantifying tumor heterogeneity at the genomic, tissue pathology and clinical imaging scales, as this may help better understand tumor biology and may yield useful biomarkers for guiding therapy-based decision making. This review focuses on the role and value of using x-ray, CT, MRI and PET based imaging methods that identify, measure and map tumor heterogeneity. In particular we highlight the potential value of these techniques and the key challenges required to validate and qualify these biomarkers for clinical use..

Radiomics has the potential to improve the management of cancer patients, but further research is required before it can be adopted into routine clinical practice..

Poor oxygenation of solid tumours has been linked with resistance to chemo- and radio-therapy and poor patient outcomes, hence non-invasive imaging of oxygen supply and demand in tumours could improve disease staging and therapeutic monitoring. Optoacoustic tomography (OT) is an emerging clinical imaging modality that provides static images of endogenous haemoglobin concentration and oxygenation. Here, we demonstrate oxygen enhanced (OE)-OT, exploiting an oxygen gas challenge to visualise the spatiotemporal heterogeneity of tumour vascular function. We show that tracking oxygenation dynamics using OE-OT reveals significant differences between two prostate cancer models in nude mice with markedly different vascular function (PC3 & LNCaP), which appear identical in static OT. LNCaP tumours showed a spatially heterogeneous response within and between tumours, with a substantial but slow response to the gas challenge, aligned with ex vivo analysis, which revealed a generally perfused and viable tumour with marked areas of haemorrhage. PC3 tumours had a lower fraction of responding pixels compared to LNCaP with a high disparity between rim and core response. While the PC3 core showed little or no dynamic response, the rim showed a rapid change, consistent with our ex vivo findings of hypoxic and necrotic core tissue surrounded by a rim of mature and perfused vasculature. OE-OT metrics are shown to be highly repeatable and correlate directly on a per-tumour basis to tumour vessel function assessed ex vivo. OE-OT provides a non-invasive approach to reveal the complex dynamics of tumour vessel perfusion, permeability and vasoactivity in real time. Our findings indicate that OE-OT holds potential for application in prostate cancer patients, to improve delineation of aggressive and indolent disease as well as in patient stratification for chemo- and radio-therapy..

Dynamic contrast-enhanced (DCE) MR imaging is used increasingly often to evaluate tumor angiogenesis and the efficacy of antiangiogenic drugs. In clinical practice DCE-MR imaging applications are largely centered on lesion detection, characterization, and localization. In research, DCE-MR imaging helps inform decision making in early-phase clinical trials by showing efficacy and by selecting dose and schedule. However, the role of these techniques in patient selection is uncertain. Future research is required to optimize existing DCE-MR imaging methods and to fully validate these biomarkers for wider use in patient care and in drug development..

PURPOSE: To evaluate blood oxygenation level-dependent (BOLD) contrast changes in healthy breast parenchyma and breast carcinoma during administration of vasoactive gas stimuli. MATERIALS AND METHODS: Magnetic resonance imaging (MRI) was performed at 3T in 19 healthy premenopausal female volunteers using a single-shot fast spin echo sequence to acquire dynamic T2 -weighted images. 2% (n = 9) and 5% (n = 10) carbogen gas mixtures were interleaved with either medical air or oxygen in 2-minute blocks, for four complete cycles. A 12-minute medical air breathing period was used to determine background physiological modulation. Pixel-wise correlation analysis was applied to evaluate response to the stimuli in breast parenchyma and these results were compared to the all-air control. The relative BOLD effect size was compared between two groups of volunteers scanned in different phases of the menstrual cycle. The optimal stimulus design was evaluated in five breast cancer patients. RESULTS: Of the four stimulus combinations tested, oxygen vs. 5% carbogen produced a response that was significantly stronger (P < 0.05) than air-only breathing in volunteers. Subjects imaged during the follicular phase of their cycle when estrogen levels typically peak exhibited a significantly smaller BOLD response (P = 0.01). Results in malignant tissue were variable, with three out of five lesions exhibiting a diminished response to the gas stimulus. CONCLUSION: Oxygen vs. 5% carbogen is the most robust stimulus for inducing BOLD contrast, consistent with the opposing vasomotor effects of these two gases. Measurements may be confounded by background physiological fluctuations and menstrual cycle changes. J. Magn. Reson. Imaging 2016;44:335-345..

In countries with the best cancer outcomes, approximately 60% of patients receive radiotherapy as part of their treatment, which is one of the most cost-effective cancer treatments. Notably, around 40% of cancer cures include the use of radiotherapy, either as a single modality or combined with other treatments. Radiotherapy can provide enormous benefit to patients with cancer. In the past decade, significant technical advances, such as image-guided radiotherapy, intensity-modulated radiotherapy, stereotactic radiotherapy, and proton therapy enable higher doses of radiotherapy to be delivered to the tumour with significantly lower doses to normal surrounding tissues. However, apart from the combination of traditional cytotoxic chemotherapy with radiotherapy, little progress has been made in identifying and defining optimal targeted therapy and radiotherapy combinations to improve the efficacy of cancer treatment. The National Cancer Research Institute Clinical and Translational Radiotherapy Research Working Group (CTRad) formed a Joint Working Group with representatives from academia, industry, patient groups and regulatory bodies to address this lack of progress and to publish recommendations for future clinical research. Herein, we highlight the Working Group's consensus recommendations to increase the number of novel drugs being successfully registered in combination with radiotherapy to improve clinical outcomes for patients with cancer..

There is a clinical need for noninvasive biomarkers of tumor hypoxia for prognostic and predictive studies, radiotherapy planning, and therapy monitoring. Oxygen-enhanced MRI (OE-MRI) is an emerging imaging technique for quantifying the spatial distribution and extent of tumor oxygen delivery in vivo. In OE-MRI, the longitudinal relaxation rate of protons (ΔR1) changes in proportion to the concentration of molecular oxygen dissolved in plasma or interstitial tissue fluid. Therefore, well-oxygenated tissues show positive ΔR1. We hypothesized that the fraction of tumor tissue refractory to oxygen challenge (lack of positive ΔR1, termed "Oxy-R fraction") would be a robust biomarker of hypoxia in models with varying vascular and hypoxic features. Here, we demonstrate that OE-MRI signals are accurate, precise, and sensitive to changes in tumor pO2 in highly vascular 786-0 renal cancer xenografts. Furthermore, we show that Oxy-R fraction can quantify the hypoxic fraction in multiple models with differing hypoxic and vascular phenotypes, when used in combination with measurements of tumor perfusion. Finally, Oxy-R fraction can detect dynamic changes in hypoxia induced by the vasomodulator agent hydralazine. In contrast, more conventional biomarkers of hypoxia (derived from blood oxygenation-level dependent MRI and dynamic contrast-enhanced MRI) did not relate to tumor hypoxia consistently. Our results show that the Oxy-R fraction accurately quantifies tumor hypoxia noninvasively and is immediately translatable to the clinic..

PURPOSE: Most dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) data are evaluated for individual patients with cohorts analyzed to detect significant changes from baseline values, repeating the process at each posttreatment timepoint. Our study aimed to develop a statistically valid model for the complete time course of DCE-MRI data in a patient cohort. MATERIALS AND METHODS: Data from 10 patients with colorectal cancer liver metastases were analyzed, including two baseline scans and four post-bevacizumab scans. Apparent changes in tumor median K(trans) were adjusted for changes in observed enhancing tumor fraction (EnF) by multiplying K(trans) by EnF (KEnF). A mixed-effects model (MEM) was defined to describe the KEnF time course for all patients simultaneously by assuming a three-parameter indirect response model with model parameters lognormally distributed across patients. RESULTS: The typical cohort time course showed a KEnF reduction to 59% of baseline at 24 hours, returning to 65% of baseline values by day 12. Interpatient variability of model parameters ranged from 11% to 307%. CONCLUSION: The MEM approach has potential for comparing responses at a group level in clinical trials with different doses, schedules, or combination regimens. Furthermore, the KEnF biomarker successfully resolved confounds in interpreting K(trans) arising from therapy induced changes in the volume of enhancing tumor..

PURPOSE: To evaluate between-site agreement of apparent diffusion coefficient (ADC) measurements in preclinical magnetic resonance imaging (MRI) systems. MATERIALS AND METHODS: A miniaturized thermally stable ice-water phantom was devised. ADC (mean and interquartile range) was measured over several days, on 4.7T, 7T, and 9.4T Bruker, Agilent, and Magnex small-animal MRI systems using a common protocol across seven sites. Day-to-day repeatability was expressed as percent variation of mean ADC between acquisitions. Cross-site reproducibility was expressed as 1.96 × standard deviation of percent deviation of ADC values. RESULTS: ADC measurements were equivalent across all seven sites with a cross-site ADC reproducibility of 6.3%. Mean day-to-day repeatability of ADC measurements was 2.3%, and no site was identified as presenting different measurements than others (analysis of variance [ANOVA] P = 0.02, post-hoc test n.s.). Between-slice ADC variability was negligible and similar between sites (P = 0.15). Mean within-region-of-interest ADC variability was 5.5%, with one site presenting a significantly greater variation than the others (P = 0.0013). CONCLUSION: Absolute ADC values in preclinical studies are comparable between sites and equipment, provided standardized protocols are employed..

Tumors exhibit genomic and phenotypic heterogeneity, which has prognostic significance and may influence response to therapy. Imaging can quantify the spatial variation in architecture and function of individual tumors through quantifying basic biophysical parameters such as CT density or MRI signal relaxation rate; through measurements of blood flow, hypoxia, metabolism, cell death, and other phenotypic features; and through mapping the spatial distribution of biochemical pathways and cell signaling networks using PET, MRI, and other emerging molecular imaging techniques. These methods can establish whether one tumor is more or less heterogeneous than another and can identify subregions with differing biology. In this article, we review the image analysis methods currently used to quantify spatial heterogeneity within tumors. We discuss how analysis of intratumor heterogeneity can provide benefit over more simple biomarkers such as tumor size and average function. We consider how imaging methods can be integrated with genomic and pathology data, instead of being developed in isolation. Finally, we identify the challenges that must be overcome before measurements of intratumoral heterogeneity can be used routinely to guide patient care..

PURPOSE: To develop significance testing methodology applicable to spatially heterogeneous parametric maps of biophysical and physiological measurements arising from imaging studies. THEORY: Heterogeneity can confound statistical analyses. Indexed distribution analysis (IDA) transforms a reference distribution, establishing correspondences across parameter maps to which significance tests are applied. METHODS: Well-controlled simulated and clinical K(trans) data from a dynamic contrast-enhanced magnetic resonance imaging study of bevacizumab were analyzed using conventional significance tests of parameter averages, histogram analysis, and IDA. Repeated pretreatment scans provided negative control; a post treatment scan provided positive control. RESULTS: Histogram analysis was insensitive to simulated and known effects. Simulation: conventional analysis identified treatment effect (P ≈ 5 × 10(-4)) and direction, but underestimated magnitude (relative error 67-81%); IDA identified treatment effect (P = 0.001), magnitude, direction, and spatial extent (100% accuracy). Bevacizumab: conventional analysis was sensitive to treatment effect (P = 0.01; 95% confidence interval on K(trans) decrease: 23-37%); IDA was sensitive to treatment effect (P < 0.05; K(trans) decrease approximately 25%), inferred its spatial extent to be 94-96%, and inferred that K(trans) decrease is independent of baseline value, an inference that conventional and histogram analyses cannot make. CONCLUSIONS: In the presence of heterogeneity, IDA can accurately infer the magnitude, direction, and spatial extent of between samples of parametric maps, which can be visualized spatially with respect to the original parameter maps..

PURPOSE: There is a clinical need for noninvasive, nonionizing imaging biomarkers of tumor hypoxia and oxygenation. We evaluated the relationship of T1 -weighted oxygen-enhanced magnetic resonance imaging (OE-MRI) measurements to histopathology measurements of tumor hypoxia in a murine glioma xenograft and demonstrated technique translation in human glioblastoma multiforme. METHODS: Preclinical evaluation was performed in a subcutaneous murine human glioma xenograft (U87MG). Animals underwent OE-MRI followed by dynamic contrast-enhanced MRI (DCE-MRI) and histological measurement including reduced pimonidazole adducts and CD31 staining. Area under the curve (AUC) was measured for the R1 curve for OE-MRI and the gadolinium concentration curve for DCE-MRI. Clinical evaluation in five patients used analogous imaging protocols and analyses. RESULTS: Changes in AUC of OE-MRI (AUCOE ) signal were regionally heterogeneous across all U87MG tumors. Tumor regions with negative AUCOE typically had low DCE-MRI perfusion, had positive correlation with hypoxic area (P = 0.029), and had negative correlation with vessel density (P = 0.004). DCE-MRI measurements did not relate to either hypoxia or vessel density in U87MG tumors. Clinical data confirmed comparable signal changes in patients with glioblastoma. CONCLUSION: These data support further investigation of T1 -weighted OE-MRI to identify regional tumor hypoxia. The quantification of AUCOE has translational potential as a clinical biomarker of hypoxia..

Hypoxia was identified as a microenvironmental component of solid tumours over 60 years ago and was immediately recognised as a potential barrier to therapy through the reliance of radiotherapy on oxygen to elicit maximal cytotoxicity. Over the last two decades both clinical and experimental studies have markedly enhanced our understanding of how hypoxia influences cellular behaviour and therapy response. Furthermore, they have confirmed early assumptions that low oxygenation status in tumours is an exploitable target in cancer therapy. Generally such approaches will be more beneficial to patients with hypoxic tumours, necessitating the use of biomarkers that reflect oxygenation status. Tissue biomarkers have shown utility in many studies. Further significant advances have been made in the non-invasive measurement of tumour hypoxia with positron emission tomography, magnetic resonance imaging and other imaging modalities. Here, we describe the complexities of defining and measuring tumour hypoxia and highlight the therapeutic approaches to combat it..

INTRODUCTION: Breast cancer remains a significant scientific, clinical and societal challenge. This gap analysis has reviewed and critically assessed enduring issues and new challenges emerging from recent research, and proposes strategies for translating solutions into practice. METHODS: More than 100 internationally recognised specialist breast cancer scientists, clinicians and healthcare professionals collaborated to address nine thematic areas: genetics, epigenetics and epidemiology; molecular pathology and cell biology; hormonal influences and endocrine therapy; imaging, detection and screening; current/novel therapies and biomarkers; drug resistance; metastasis, angiogenesis, circulating tumour cells, cancer 'stem' cells; risk and prevention; living with and managing breast cancer and its treatment. The groups developed summary papers through an iterative process which, following further appraisal from experts and patients, were melded into this summary account. RESULTS: The 10 major gaps identified were: (1) understanding the functions and contextual interactions of genetic and epigenetic changes in normal breast development and during malignant transformation; (2) how to implement sustainable lifestyle changes (diet, exercise and weight) and chemopreventive strategies; (3) the need for tailored screening approaches including clinically actionable tests; (4) enhancing knowledge of molecular drivers behind breast cancer subtypes, progression and metastasis; (5) understanding the molecular mechanisms of tumour heterogeneity, dormancy, de novo or acquired resistance and how to target key nodes in these dynamic processes; (6) developing validated markers for chemosensitivity and radiosensitivity; (7) understanding the optimal duration, sequencing and rational combinations of treatment for improved personalised therapy; (8) validating multimodality imaging biomarkers for minimally invasive diagnosis and monitoring of responses in primary and metastatic disease; (9) developing interventions and support to improve the survivorship experience; (10) a continuing need for clinical material for translational research derived from normal breast, blood, primary, relapsed, metastatic and drug-resistant cancers with expert bioinformatics support to maximise its utility. The proposed infrastructural enablers include enhanced resources to support clinically relevant in vitro and in vivo tumour models; improved access to appropriate, fully annotated clinical samples; extended biomarker discovery, validation and standardisation; and facilitated cross-discipline working. CONCLUSIONS: With resources to conduct further high-quality targeted research focusing on the gaps identified, increased knowledge translating into improved clinical care should be achievable within five years..

Most tumours, even those of the same histological type and grade, demonstrate considerable biological heterogeneity. Variations in genomic subtype, growth factor expression and local microenvironmental factors can result in regional variations within individual tumours. For example, localised variations in tumour cell proliferation, cell death, metabolic activity and vascular structure will be accompanied by variations in oxygenation status, pH and drug delivery that may directly affect therapeutic response. Documenting and quantifying regional heterogeneity within the tumour requires histological or imaging techniques. There is increasing evidence that quantitative imaging biomarkers can be used in vivo to provide important, reproducible and repeatable estimates of tumoural heterogeneity. In this article we review the imaging methods available to provide appropriate biomarkers of tumour structure and function. We also discuss the significant technical issues involved in the quantitative estimation of heterogeneity and the range of descriptive metrics that can be derived. Finally, we have reviewed the existing clinical evidence that heterogeneity metrics provide additional useful information in drug discovery and development and in clinical practice..

About 100 early-phase clinical trials and investigator-led studies of targeted antivascular therapies--both anti-angiogenic and vascular-targeting agents--have reported data derived from T1-weighted dynamic contrast-enhanced (DCE)-MRI. However, the role of DCE-MRI for decision making during the drug-development process remains controversial. Despite well-documented guidelines on image acquisition and analysis, several key questions concerning the role of this technique in early-phase trial design remain unanswered. This Review describes studies of single-agent antivascular therapies, in which DCE-MRI parameters are incorporated as pharmacodynamic biomarkers. We discuss whether these parameters, such as volume transfer constant (K(trans)), are reproducible and reliable biomarkers of both drug efficacy and proof of concept, and whether they assist in dose selection and drug scheduling for subsequent phase II trials. Emerging evidence indicates that multiparametric analysis of DCE-MRI data offers greater insight into the mechanism of drug action than studies measuring a single parameter, such as K(trans). We also provide an overview of current data and appraise the future directions of this technique in oncology trials. Finally, major hurdles in imaging biomarker development, validation and qualification that hinder a wide application of DCE-MRI techniques in clinical trials are addressed..

The management of solid tumors has been transformed by the advent of VEGF pathway inhibitors. Early clinical evaluation of these drugs has used pharmacodynamic biomarkers derived from advanced imaging such as dynamic MRI, computed tomography (CT), and ultrasound to establish proof of principle. We have reviewed published studies that used these imaging techniques to determine whether the same biomarkers relate to survival in renal, hepatocellular, and brain tumors in patients treated with VEGF inhibitors. Data show that in renal cancer, pretreatment measurements of K(trans) and early pharmacodynamic reduction in tumor enhancement and density have prognostic significance in patients treated with VEGF inhibitors. A weaker, but significant, relationship is seen with subtle early size change (10% in one dimension) and survival. Data from high-grade glioma suggest that pretreatment fractional blood volume and K(trans) were prognostic of overall survival. However, lack of control data with other therapies prevents assessment of the predictive nature of these biomarkers, and such studies are urgently required..

BACKGROUND: Cediranib (RECENTIN™) is an oral, highly potent VEGF inhibitor. This study evaluated the effect of food on the pharmacokinetics of cediranib and compared the administration of continual cediranib via two dosing strategies using this as a platform to investigate pharmacodynamic imaging biomarkers. METHODS: Sixty patients were randomised to receive two single doses of cediranib in either fed/fasted or fasted/fed state (Part A). In continual dosage phase (Part B), patients were randomised to a fixed-dose or dose-escalation arm. Exploratory pharmacodynamic assessments were performed using DCE-MRI and CT enhancing fraction (EnF). RESULTS: In part A, plasma AUC and C (max) of cediranib were lower in the presence of food by a mean of 24 and 33%, respectively (94% CI: AUC, 12-34% and C (max), 20-43%), indicating food reduces cediranib plasma exposure. In part B, cediranib 30 mg/day appeared to be the most sustainable for chronic dosing. Continuous cediranib therapy was associated with sustained antivascular effects up to 16 weeks, with significant reductions in DCE-MRI parameters and CT EnF. CONCLUSIONS: It is recommended that cediranib be administered at least 1 h before or 2 h after food. Evidence of antitumour activity was observed, with significant sustained effects upon imaging vascular parameters..

Conventional contrast-enhanced CT and MRI are now in routine clinical use for the diagnosis, treatment and monitoring of diseases in the brain. The presence of contrast enhancement is a proxy for the pathological changes that occur in the normally highly regulated brain vasculature and blood-brain barrier. With recognition of the limitations of these techniques, and a greater appreciation for the nuanced mechanisms of microvascular change in a variety of pathological processes, novel techniques are under investigation for their utility in further interrogating the microvasculature of the brain. This is particularly important in tumours, where the reliance on angiogenesis (new vessel formation) is crucial for tumour growth, and the resulting microvascular configuration and derangement has profound implications for diagnosis, treatment and monitoring. In addition, novel therapeutic approaches that seek to directly modify the microvasculature require more sensitive and specific biological markers of baseline tumour behaviour and response. The currently used imaging biomarkers of angiogenesis and brain tumour microvascular environment are reviewed..

Over the last few decades there has been considerable research into quantifying the cerebral microvasculature with imaging, for use in studies of the human brain and various pathologies including cerebral tumours. This review highlights key issues in dynamic contrast-enhanced CT, dynamic contrast-enhanced MRI and arterial spin labelling, the various applications of which are considered elsewhere in this special issue of the British Journal of Radiology..

PURPOSE: Treatment efficacy and toxicity are difficult to predict in lymphoma patients. In this study, the utility of circulating biomarkers in predicting and/or monitoring treatment efficacy/toxicity were investigated. PATIENTS AND METHODS: Circulating biomarkers of cell death (nucleosomal DNA (nDNA) and cytokeratin 18 (CK18)), and circulating FLT3 ligand, a potential biomarker of myelosuppression, were assessed before and serially after standard chemotherapy in 49 patients with Hodgkin and non-Hodgkin lymphoma. Cytokeratin 18 is not expressed in lymphoma cells so is a potential biomarker of epithelial toxicity in this setting. Tumour response was assessed before and after completion of chemotherapy by 2D and 3D computed tomography radiological response. RESULTS: Baseline nDNA level was significantly higher in all lymphoma subtypes compared with 61 healthy controls and was prognostic for progression-free survival in diffuse large B-cell lymphoma (DLBCL). Decreases in nDNA levels were observed in the first week after chemotherapy; in FL, early falls in nDNA predicted for long remission following therapy. In DLBCL, elevations in nDNA occurred in cases with progressive disease. Circulating CK18 increased within 48 h of chemotherapy and was significantly higher in patients experiencing epithelial toxicity graded >3 by Common Terminology for Classification of Adverse Events criteria. FLT3 ligand was elevated within 3-8 days of chemotherapy initiation and predicted those patients who subsequently developed neutropenic sepsis. CONCLUSION: These data suggest circulating biomarkers contribute useful information regarding tumour response and toxicity in patients receiving standard chemotherapy and have potential utility in the development of individualised treatment approaches in lymphoma. These biomarkers are now being tested within multicentre phase III trials to progress their qualification..

BACKGROUND: There is limited evidence that imaging biomarkers can predict subsequent response to therapy. Such prognostic and/or predictive biomarkers would facilitate development of personalised medicine. We hypothesised that pre-treatment measurement of the heterogeneity of tumour vascular enhancement could predict clinical outcome following combination anti-angiogenic and cytotoxic chemotherapy in colorectal cancer (CRC) liver metastases. METHODS: Ten patients with 26 CRC liver metastases had two dynamic contrast-enhanced MRI (DCE-MRI) examinations before starting first-line bevacizumab and FOLFOX-6. Pre-treatment biomarkers of tumour microvasculature were computed and a regression analysis was performed against the post-treatment change in tumour volume after five cycles of therapy. The ability of the resulting linear model to predict tumour shrinkage was evaluated using leave-one-out validation. Robustness to inter-visit variation was investigated using data from a second baseline scan. RESULTS: In all, 86% of the variance in post-treatment tumour shrinkage was explained by the median extravascular extracellular volume (v(e)), tumour enhancing fraction (E(F)), and microvascular uniformity (assessed with the fractal measure box dimension, d(0)) (R(2)=0.86, P<0.00005). Other variables, including baseline volume were not statistically significant. Median prediction error was 12%. Equivalent results were obtained from the second scan. CONCLUSION: Traditional image analyses may over-simplify tumour biology. Measuring microvascular heterogeneity may yield important prognostic and/or predictive biomarkers..

Angiogenesis is a key process in the growth and metastasis of cancer, and genitourinary tumors are no exception. The evolution of angiogenesis as an important target for novel anticancer therapeutics has brought with it new challenges for in vivo imaging. Most imaging techniques quantify physiological parameters, such as blood volume and capillary endothelial permeability. Although CT, PET and ultrasonography have shown promise, MRI is the most common method used to evaluate angiogenesis in clinical trials of genitourinary tumors. Pilot studies of MRI, CT and ultrasonography in patients with renal cancer have produced promising results; reductions in vascular permeability and blood flow have been correlated with progression-free survival. The vascular characteristics of prostate cancer have been evaluated by MRI, and this has been suggested as a means of assessing tumor response to hormone deprivation therapy. Current evidence highlights the potential of angiogenesis imaging in the diagnosis, staging and possibly response monitoring of bladder cancer. In the future, assessment of the angiogenic process at the structural, functional and molecular levels, before, during and after antiangiogenic therapy will undoubtedly be integrated into wider clinical practice..

BACKGROUND AND PURPOSE: EnF is a newly described measure of proportional tumor enhancement derived from DCE-MR imaging. The aim of this study was to assess the relationship between EnF and the more established DCE-MR imaging parameters: K(trans), v(e), and v(p). MATERIALS AND METHODS: Forty-two patients with 43 gliomas (16 grade II, 3 grade III, and 24 grade IV) were studied. Imaging included pre- and postcontrast T1-weighted sequences through the lesion and T1-weighted DCE-MR imaging. Parametric maps of EnF, K(trans), v(e), and v(p) were generated. Voxels were classified as enhancing if the IAUC was positive (EnF(IAUC)(60>0)). A threshold of IAUC > 2.5 mmol.s was used to generate EnF(IAUC)(60>2.5). Both measures of EnF were compared with the DCE-MR imaging parameters (K(trans), v(e), and v(p)). RESULTS: In grade II gliomas, EnF(IAUC60>0) and EnF(IAUC60>2.5) correlated with v(p) (R(2) = 0.6245, P < .0005; and R(2) = 0.4727, P = .003) but not with K(trans) or v(e). In grade IV tumors, both EnF(IAUC60>0) and EnF(IAUC60>2.5) correlated with K(trans) (R(2) = 0.3501, P = .001; and R(2) = 0.4699, P < .0005) and v(p) (R(2) = 0.1564, P = .01; and R(2) = 0.2429, P = .007), but not with v(e). Multiple regression analysis showed K(trans) as the only independent correlate of both EnF(IAUC60>0) and EnF(IAUC60>2.5) for grade IV tumors. CONCLUSIONS: This study suggests that in grade II tumors, EnF reflects v(p) and varies due to changes in vascular density. In grade IV gliomas, EnF is affected by K(trans) with secondary associated changes in v(p)..

BACKGROUND: There is a need for simple imaging parameters capable of predicting therapeutic outcome. METHODS: This retrospective study analysed 50 patients with locally advanced carcinoma of the cervix who underwent dynamic contrast-enhanced MRI before receiving potentially curative radiotherapy. The proportion of enhancing pixels (E(F)) in the whole-tumour volume post-contrast agent injection was calculated and assessed in relation to disease-free survival (DFS). RESULTS: Tumours with high E(F) had a significantly poorer probability of DFS than those with low E(F) (P=0.011). INTERPRETATION: E(F) is a simple imaging biomarker that should be studied further in a multi-centre setting..

BACKGROUND: Patients with recurrent ovarian cancer often achieve partial response following chemotherapy, resulting in persistent small volume disease. After completion of treatment, the dilemma of when to initiate subsequent chemotherapy arises. Identification of biomarkers that could be used to predict when subsequent treatment is needed would be of significant benefit. DESIGN: Twenty-three patients with advanced ovarian cancer and residual asymptomatic disease following chemotherapy underwent dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) at study entry, 4, 8, 12, 18 and 26 weeks or disease progression. A subgroup of patients provided plasma samples within which a panel of angiogenic biomarkers was quantified. RESULTS: By 4 weeks, significant differences in whole tumour volume, enhancing fraction and Ca125 were observed between patients whose disease progressed by 26 weeks and those who remained stable. Significant correlations between plasma soluble vascular endothelial growth factor receptor-1 (sVEGFR-1) and sVEGFR-2 concentrations, and blood volume and tumour endothelial permeability surface area product measured by DCE-MRI were observed. CONCLUSIONS: Imaging markers have a potential role in early prediction of disease progression in patients with residual ovarian cancer and may supplement current measures of progression. The correlation of DCE-MRI and serological biomarkers suggests that tumour angiogenesis affects these markers through common biological means and warrants further investigation..

Clinical trials of anti-angiogenic and vascular-disrupting agents often use biomarkers derived from DCE-MRI, typically reporting whole-tumor summary statistics and so overlooking spatial parameter variations caused by tissue heterogeneity. We present a data-driven segmentation method comprising tracer-kinetic model-driven registration for motion correction, conversion from MR signal intensity to contrast agent concentration for cross-visit normalization, iterative principal components analysis for imputation of missing data and dimensionality reduction, and statistical outlier detection using the minimum covariance determinant to obtain a robust Mahalanobis distance. After applying these techniques we cluster in the principal components space using k-means. We present results from a clinical trial of a VEGF inhibitor, using time-series data selected because of problems due to motion and outlier time series. We obtained spatially-contiguous clusters that map to regions with distinct microvascular characteristics. This methodology has the potential to uncover localized effects in trials using DCE-MRI-based biomarkers..

PURPOSE: Little is known concerning the onset, duration, and magnitude of direct therapeutic effects of anti-vascular endothelial growth factor (VEGF) therapies. Such knowledge would help guide the rational development of targeted therapeutics from bench to bedside and optimize use of imaging technologies that quantify tumor function in early-phase clinical trials. EXPERIMENTAL DESIGN: Preclinical studies were done using ex vivo microcomputed tomography and in vivo ultrasound imaging to characterize tumor vasculature in a human HM-7 colorectal xenograft model treated with the anti-VEGF antibody G6-31. Clinical evaluation was by quantitative magnetic resonance imaging in 10 patients with metastatic colorectal cancer treated with bevacizumab. RESULTS: Microcomputed tomography experiments showed reduction in perfused vessels within 24 to 48 h of G6-31 drug administration (P

Magnetic resonance imaging has shown promise for evaluating tissue oxygenation. In this study differences in the tissue longitudinal relaxation rate (R(1)) and effective transverse relaxation rate (R(*)(2)), induced by inhalation of pure oxygen and carbogen, were evaluated in 10 healthy subjects. Significant reductions in R(1) were demonstrated following both oxygen and carbogen inhalation in the spleen (both P < 0.001), liver (P = 0.002 air vs. oxygen; P = 0.001 air vs. carbogen), skeletal muscle (both P < 0.001), and renal cortex (P = 0.005 air vs. oxygen; P = 0.008 air vs. carbogen). No significant change in R(*)(2) occurred following pure oxygen in any organ. However, a significant increase in R(*)(2) was observed in the spleen (P < 0.001), liver (P = 0.001), skeletal muscle (P = 0.026), and renal cortex (P = 0.001) following carbogen inhalation, an opposite effect to that observed in many studies of tumor pathophysiology. Changes in R(1) and R(*)(2) were independent of the gas administration order in the spleen and skeletal muscle. These findings suggest that the R(1) and R(*)(2) responses to hyperoxic gases are independent biomarkers of oxygen physiology..

The aim of this research was to determine whether the proportion of a tumour that enhances (enhancing fraction, EnF) and changes in EnF with enhancement threshold differ between low and high grade glioma. Forty-four patients (45 gliomas comprising 16 grade II, 5 grade III and 24 grade IV) were studied. Imaging included pre- and post-contrast-enhanced T(1)-weighted sequences and T(1)-weighted DCE-MRI. Thresholded enhancement maps were generated for each tumour by using a range of values of the initial area under the contrast concentration curve (IAUC). A plot of EnF versus threshold value was generated. We examined the relationship between tumour grade and enhancement metrics including: EnF (threshold IAUC > 0 mMol s), EnF (threshold IAUC > 2.5 mMol s), initial slope of the EnF/threshold curve (partial differentialEnF), IAUC, and two previously described signal-intensity-based metrics. EnF, defined as the proportion of tumour showing any enhancement (threshold IAUC > 0 mMol s), showed no difference between low and high grade glioma. All other measures demonstrated significant differences between grade II and IV, and low (grade II) and high grade (grades III/ IV) gliomas (p < 0.01). Two measures, partial differentialEnF and Pronin's measure of enhancement, showed differences between grade III and IV (p < 0.05). No measure separated grade II from III. Metrics which describe the enhancing fraction and its variation with enhancement threshold partial differentialEnF show considerably different behaviour in low and high grade tumours. These observations suggest that these metrics may provide important biological information concerning tumour biology and therapeutic responses and encourage further research to characterise and validate these novel biomarkers..

Dynamic contrast-enhanced MRI is becoming a standard tool for imaging-based trials of anti-vascular/angiogenic agents in cancer. So far, however, biomarkers derived from DCE-MRI parameter maps have largely neglected the fact that the maps have spatial structure and instead focussed on distributional summary statistics. Such statistics-e.g., biomarkers based on median values-neglect the spatial arrangement of parameters, which may carry important diagnostic and prognostic information. This article describes two types of heterogeneity biomarker that are sensitive to both parameter values and their spatial arrangement. Methods based on Rényi fractal dimensions and geometrical properties are developed, both of which attempt to describe the complexity of DCE-MRI parameter maps. Experiments using simulated data show that the proposed biomarkers are sensitive to changes that distribution-based summary statistics cannot detect and demonstrate that heterogeneity biomarkers could be applied in the drug trial setting. An experiment using 23 DCE-MRI parameter maps of gliomas-a class of tumour that is graded on the basis of heterogeneity-shows that the proposed heterogeneity biomarkers are able to differentiate between low- and high-grade tumours..

PURPOSE: There is considerable interest in developing non-invasive methods of mapping tumor hypoxia. Changes in tissue oxygen concentration produce proportional changes in the magnetic resonance imaging (MRI) longitudinal relaxation rate (R(1)). This technique has been used previously to evaluate oxygen delivery to healthy tissues and is distinct from blood oxygenation level-dependent (BOLD) imaging. Here we report application of this method to detect alteration in tumor oxygenation status. METHODS AND MATERIALS: Ten patients with advanced cancer of the abdomen and pelvis underwent serial measurement of tumor R(1) while breathing medical air (21% oxygen) followed by 100% oxygen (oxygen-enhanced MRI). Gadolinium-based dynamic contrast-enhanced MRI was then performed to compare the spatial distribution of perfusion with that of oxygen-induced DeltaR(1). RESULTS: DeltaR(1) showed significant increases of 0.021 to 0.058 s(-1) in eight patients with either locally recurrent tumor from cervical and hepatocellular carcinomas or metastases from ovarian and colorectal carcinomas. In general, there was congruency between perfusion and oxygen concentration. However, regional mismatch was observed in some tumor cores. Here, moderate gadolinium uptake (consistent with moderate perfusion) was associated with low area under the DeltaR(1) curve (consistent with minimal increase in oxygen concentration). CONCLUSIONS: These results provide evidence that oxygen-enhanced longitudinal relaxation can monitor changes in tumor oxygen concentration. The technique shows promise in identifying hypoxic regions within tumors and may enable spatial mapping of change in tumor oxygen concentration..

The objective was to measure the effect of 100% oxygen inhalation on T1 relaxation times in skeletal muscle. Healthy volunteers were scanned using three different MRI protocols while breathing medical air and 100% oxygen. Measurements of T1 were made from regions of interest (ROIs) within various skeletal muscle groups. Dynamic data of subjects breathing a sequence of air-oxygen-air allowed the calculation of characteristic wash-in and -out times for dissolved oxygen in muscle. Contrary to previous findings, a statistically significant decrease in T1 in skeletal muscle was observed due to oxygen inhalation. We report approximate baseline characteristic values for the response of skeletal muscle to oxygen inhalation. This measurement may provide new biomarkers for evaluation of oxygen delivery and consumption in normal and diseased skeletal muscle..

PURPOSE: To prospectively use dynamic contrast material-enhanced magnetic resonance (MR) imaging and a tracer kinetic model to compare parotid gland microvascular characteristics in patients who have Sjögren syndrome (SS) with those in healthy volunteers. MATERIALS AND METHODS: The local research ethics committee approved the study, and written informed consent was obtained from all participants. Twenty-one patients (19 women, two men; age range, 31-73 years) with a diagnosis of SS and 11 healthy volunteers (10 women, one man; age range, 41-68 years) underwent three-dimensional T1-weighted dynamic contrast-enhanced MR imaging of the parotid gland at 1.5 T. A voxel-wise tracer kinetic model and a model-free analysis were applied to the dynamic MR data. Parameter medians and standard deviations were computed to summarize gland microvascular characteristics and gland heterogeneity, respectively. Differences were investigated by using multivariate analysis of variance, t, or U tests. Further investigation was performed by using linear discriminant and receiver operating characteristic analyses. RESULTS: Compared with the healthy volunteers, the patients with SS had highly significant elevations (P << .001) in the model-free parameter initial area under the curve and in tracer kinetic model parameters, including transcapillary contrast agent transfer constant (P < .001) and extracellular extravascular volume (P < .001). Gland heterogeneity was significantly greater (P < .001) in the patients with SS. Parameter medians and standard deviations enabled excellent differentiation (areas under receiver operating characteristic curve, 0.96 and 1.00, respectively) between the patients with SS and the healthy volunteers. CONCLUSION: Dynamic contrast-enhanced MR imaging has the potential to be used in clinical settings to quantify microvascular function in SS and to differentiate between patients with and those without SS..

Targeted therapeutics have challenged how imaging techniques assess tumour response to treatment because many new agents are thought to cause cytostasis rather than cytotoxicity. Advanced tracer development, image acquisition, and image analysis have been used to produce quantitative biomarkers of pathophysiology, with particular focus on measurement of tumour vascular characteristics. Here, we critically appraise strategies available to generate imaging biomarkers for use in development of targeted therapeutics. We consider important practical and technical features of data acquisition and analysis because these factors determine the precise physiological meaning of every biomarker. We discuss the merits of volume-based and other size-based metrics for assessment of targeted therapeutics, and we examine the strengths and weaknesses of CT, MRI, and PET biomarkers derived from conventional clinical data. We review imaging biomarkers of tumour microvasculature and discuss imaging strategies that probe other physiological processes including cell proliferation, apoptosis, and tumour invasion. We conclude on the need to develop comprehensive compound-specific imaging biomarkers that are appropriate for every class of targeted therapeutics, and to investigate the complementary information given in multimodality imaging studies of targeted therapeutics..

Molecular oxygen has been previously shown to shorten longitudinal relaxation time (T1) in the spleen and renal cortex, but not in the liver or fat. In this study, the magnitude and temporal evolution of this effect were investigated. Medical air, oxygen, and carbogen (95% oxygen/5% CO2) were administered sequentially in 16 healthy volunteers. T1 maps were acquired using spoiled gradient echo sequences (TR=3.5 ms, TE=0.9 ms, alpha=2 degrees/8 degrees/17 degrees) with six acquisitions on air, 12 on oxygen, 12 on carbogen, and six to 12 back on air. Mean T1 values and change in relaxation rate were compared between each phase of gas inhalation in the liver, spleen, skeletal muscle, renal cortex, and fat by one-way analysis of variance. Oxygen-induced T1-shortening occurred in the liver in fasted subjects (P<0.001) but not in non-fasted subjects (P=0.244). T1-shortening in spleen and renal cortex (both P<0.001) were greater than previously reported. Carbogen induced conflicting responses in different organs, suggesting a complex relationship with organ vasculature. Shortening of tissue T1 by oxygen is more pronounced and more complex than previously recognized. The effect may be useful as a biomarker of arterial flow and oxygen delivery to vascular beds..

Dynamic contrast-enhanced MRI (DCE-MRI) time series data are subject to unavoidable physiological motion during acquisition (e.g., due to breathing) and this motion causes significant errors when fitting tracer kinetic models to the data, particularly with voxel-by-voxel fitting approaches. Motion correction is problematic, as contrast enhancement introduces new features into postcontrast images and conventional registration similarity measures cannot fully account for the increased image information content. A methodology is presented for tracer kinetic model-driven registration that addresses these problems by explicitly including a model of contrast enhancement in the registration process. The iterative registration procedure is focused on a tumor volume of interest (VOI), employing a three-dimensional (3D) translational transformation that follows only tumor motion. The implementation accurately removes motion corruption in a DCE-MRI software phantom and it is able to reduce model fitting errors and improve localization in 3D parameter maps in patient data sets that were selected for significant motion problems. Sufficient improvement was observed in the modeling results to salvage clinical trial DCE-MRI data sets that would otherwise have to be rejected due to motion corruption..

PURPOSE: To define a simple radiologic biomarker of prognosis in patients with advanced epithelial ovarian carcinoma on first-line chemotherapy. EXPERIMENTAL DESIGN: Twenty-seven patients receiving platinum-based chemotherapy with >2 cm residual disease [International Federation of Gynecology and Obstetrics (FIGO) stages IIIC or IV] after surgery were identified. The proportion of enhancing tumor tissue--the enhancing fraction--was calculated on pre-chemotherapy computed tomography scans at four Hounsfield unit (HU) thresholds and assessed for correlation with CA125 response, Response Evaluation Criteria in Solid Tumors (RECIST) radiologic response, and time to progression. Discriminative power was assessed by leave-one-out discriminant analysis. RESULTS: Pre-chemotherapy residual tumor volume did not correlate with clinical outcome. Pre-chemotherapy enhancing fraction at all thresholds significantly correlated with CA125 response (P < 0.001, rho = 0.553 for 50 HU; P < 0.001, rho = 0.565 for 60 HU; P < 0.001, rho = 0.553 for 70 HU; P = 0.001, rho = 0.516 for 80 HU). Significant correlations were also shown for radiologic response at all thresholds. Enhancing fraction predicted CA125 response with 81.9% to 86.4% specificity and Response Evaluation Criteria in Solid Tumors response with 74.9% to 76.8% specificity at 95% sensitivity (dependent on threshold). Enhancing fraction correlated with time to progression at the 60 HU (P = 0.045, rho = 0.336) and 70 HU (P = 0.042; rho = 0.340) thresholds. CONCLUSION: Pre-chemotherapy enhancing fraction is a simple quantitative radiologic measure. Further evaluation in larger trials is required to confirm the potential of enhancing fraction as a predictive factor, particularly for patients who may benefit from the addition of antiangiogenic therapy..

This article reviews the application of dynamic contrast-enhanced magnetic resonance imaging in both clinical studies and early-phase trials of angiogenesis inhibitors. Emphasis is placed on how variation in image acquisition and analysis affects the meaning and use of derived variables. We then review the potential for future developments, with particular reference to the application of dynamic contrast-enhanced magnetic resonance imaging to evaluate the heterogeneity of tumor tissues..

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is now frequently used in early clinical trial assessment of antiangiogenic and vascular disrupting compounds. Evidence of drug efficacy and dose-dependent response has been demonstrated with some angiogenesis inhibitors. This review highlights the critical issues that influence T(1)-weighted DCE-MRI data acquisition and analysis, identifies important areas for future development and reviews the clinical trial findings to date..

RATIONALE AND OBJECTIVES: The quantitative analysis of dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) data is subject to model fitting errors caused by motion during the time-series data acquisition. However, the time-varying features that occur as a result of contrast enhancement can confound motion correction techniques based on conventional registration similarity measures. We have therefore developed a heuristic, locally controlled tracer kinetic model-driven registration procedure, in which the model accounts for contrast enhancement, and applied it to the registration of abdominal DCE-MRI data at high temporal resolution. MATERIALS AND METHODS: Using severely motion-corrupted data sets that had been excluded from analysis in a clinical trial of an antiangiogenic agent, we compared the results obtained when using different models to drive the tracer kinetic model-driven registration with those obtained when using a conventional registration against the time series mean image volume. RESULTS: Using tracer kinetic model-driven registration, it was possible to improve model fitting by reducing the sum of squared errors but the improvement was only realized when using a model that adequately described the features of the time series data. The registration against the time series mean significantly distorted the time series data, as did tracer kinetic model-driven registration using a simpler model of contrast enhancement. CONCLUSION: When an appropriate model is used, tracer kinetic model-driven registration influences motion-corrupted model fit parameter estimates and provides significant improvements in localization in three-dimensional parameter maps. This has positive implications for the use of quantitative DCE-MRI for example in clinical trials of antiangiogenic or antivascular agents..

Head and neck cancers usually spread first to the regional lymph nodes but rarely may metastasize to distant sites. Metastasis to distant lymph node groups is a rare event. Furthermore, delayed multiple metastases without local recurrence is relatively uncommon. A case of retroperitoneal metastasis from a squamous cell carcinoma of the tonsil, secreting beta human chorionic gonadotrophin (beta-hCG), is reported. A 58-year-old man had undergone a tonsillectomy and chemo-radiotherapy for squamous cell carcinoma of the left tonsil and 13 months later presented with non-specific abdominal pain. The serum beta-hCG levels were high and an abdominal ultrasound scan revealed hydronephrosis on the left side. A computed tomography scan demonstrated para-aortic retroperitoneal lymphadenopathy. The patient underwent an open lymph node biopsy. The initial pathological analysis was interpreted as extra-gonadal germ cell tumour and the patient received chemotherapy. A subsequent review was consistent with a metastatic squamous cell carcinoma of the tonsil, as immunohistochemical studies showed positive staining for epithelial membrane antigen and cytokeratins 5/6 but a negative reaction to placental alkaline phosphatase. Following this, the chemotherapy regimen was changed; however, a restaging scan demonstrated progression, and the patient died from aspiration pneumonia secondary to alcohol intoxication. To our knowledge, this is the first reported case of retroperitoneal metastasis from a squamous cell carcinoma of the tonsil, secreting beta-hCG and causing hydronephrosis. This case highlights the necessity of using clinical, histological, immunohistological and ultrastructural examination to establish precise diagnosis and to avoid inappropriate treatment..

.

.

Renal-cell carcinoma (RCC) during pregnancy is rare. Laparoscopic nephrectomy has been used effectively and safely in nonpregnant patients with RCC. We report a case of a 34-year-old pregnant woman with RCC, which we believe to be the first such case to be managed by laparoscopic nephrectomy..

.

.

.

.

.