Organ Motion Tracking for Motion Compensated Therapy
E Harris, JC Bamber, PM Evans JRN Symonds-Tayler, in collaboration with M Lediju, G Trahey, Biomedical Engineering Dept., Duke University, NC, USA; WA N'Djin, D Melodelima, JY Chapelon, Inserm unité 556, Université de Lyon, France
Source of funding: CRUK, Royal Marsden NHS Trust, Inserm, Whitaker Foundation
The ability of intensity-modulated radiotherapy (IMRT) to deliver high dose to tumour and low dose to nearby tissue could in principle be improved by using 4D (3D+time) ultrasound to monitor and compensate for tissue motion and deformation during treatment. The most commonly available 4D ultrasound probe works by mechanically rocking a curvilinear array, which restricts large volume acquisition rates to about 2 Hz.
We previously showed in volunteers that, despite these low volume rates, 3D cross-correlation speckle tracking methods can automatically track hepatic blood vessel features in vivo to within 1.7mm of manually tracked displacements. Loss of speckle correlation, however, prevents such performance when anatomical features are not within the tracked field.
New work with phantoms has demonstrated that a large part of the reason for the speckle decorrelation is due to interaction between the speed and direction of the probe sweep and that of the organ motion. Recent work has therefore concentrated on determining the volume rates adequate for automatic speckle-based tracking of respiratory and cardiovascular liver motion in vivo. This has been carried out in collaboration with B Lediju of Duke University, using 48 vol/s radio frequency image data obtained with a Siemens SC2000 scanner and a 2D matrix array probe. Findings indicate that 8 vol/s is required to track liver motion with better than 2 mm agreement with tracking at very high volume rate.
As illustrated in Figure 8, 3D displacement data are available from such analysis, providing future potential for characterising tissue deformation during treatment. Organ motion also makes abdominal tumours difficult to treat accurately with focused ultrasound. Ongoing work, in collaboration with D Melodelima, Université de Lyon, aims to apply 3D speckle tracking methods to characterise the effects of liver motion on various types of HIFU treatments. Fig.8. Examples of triplane slices through 3D data from human liver in vivo, showing ultrasound B-mode (a) and three components of (cardiovascular-induced) displacement in a 21 ms period (during breat-hold): (b) axial, (c) lateral and (d) elevation. The spatial position scales are in samples, and the displacement (colour) scale is in mm.