Motion management for MRI-guided abdominal radiotherapy

Abstract

The recent introduction of hybrid MRI-linac (MRL) systems will drive a paradigm shift in radiotherapy. For the first time in history we have the ability to visualize both the tumor and surrounding healthy tissue before and during treatment in real time. The first high-field MRL, which was developed within the department of radiotherapy at the UMC Utrecht, in cooperation with Philips and Elekta, successfully treated the first patients in May 2017 at the UMC Utrecht. MR-guided radiotherapy has the potential to boost successful treatment outcomes by decreasing uncertainties in tumor detection, location, and shape through unprecedented soft-tissue contrast. For abdominal tumors this could induce more conformal dose distributions using precies pre-treatment imaging, real-time image feedback, and accurate dose calculations in a large field-of-view. To maximize this potential, accurate MR image guidance in all stages of treatment is essential. A general challenge for these tumors is physiological-induced motion, such as respiration. This thesis described various acquisitions, reconstruction and post-processing methods for managing this motion in pre-treatment, pre-beam, beam-on and post-beam phase of an MR-guided abdominal radiotherapy treatment. First, a method is described for pre-treatment and pre-beam 4D-MRI motion characterization, based on a volumetric radial stack-of-stars (SOS) acquisition. It is shown that this sampling, in combination with an internal surrogate, is a robust method to generate phase-resolved 4D-MRIs. Second, the radial SOS sampling is used as a motion compensation method in the presence of bulk motion for robust free-breathing abdominal imaging. Using the free-induction decay signal, bulk motion is automatically detected and excluded in real time. It is shown that this increases image quality, reduces artifacts and results in an overall increase in acquisition robustness. Third, a motion model is introduced to generate volumetric MRI with high spatio-temporal resolution, so-called volumetric cine-MRI. Using the aforementioned 4D-MRI acquisition, a motion model is generated by parameterizing the underlying motion. Subsequently, 3D volumes are generated by filling in the missing volumetric information of fast 2D beam-on cine-MR images using the model. Fourth, these volumetric cine-MRIs are used to calculate the accumulated dose of abdominal treatments. It is shown that precise imaging with sufficient temporal resolution is required for accurate dose tracking in abdominal tumors and both fast and slow variations in breathing should be taken into account. Last, a mathematical framework is outlined to optimize acceleration parameters of simultaneous multi-slice acquisitions that can accelerate pre-treatment and pre-beam imaging, or increase volumetric coverage of beam-on imaging. By optimizing these acceleration parameters, higher acceleration can be accomplished, while maintaining similar signal-to-noise ratios. The presented methods can directly add valuable information for all stages of an MR-guided abdominal radiotherapy treatment. Ultimately, these methods can aid real-time image guidance and online plan adaptation to improve treatment outcomes