UCLA

Anatomical motion during external beam radiotherapy can reduce the accuracy of radiation delivery and degrade treatment efficacy. Magnetic resonance image (MRI) guided radiotherapy systems provide unparalleled soft tissue contrast and the opportunity to monitor tumor motion in images acquired during treatment. Radiotherapy gating, turning the radiation beam on when the target is within the desired spatial window and off when the target moves outside this window, is performed to mitigate the effects of anatomical motion. A limitation of image-based respiratory gating is the requirement that the images must be acquired rapidly and continuously to avoid unacceptable gating latency. Consequently, images are typically acquired at a single slice position using a rapid imaging sequence. Pulse sequence selection and thereby image contrast is limited to those available using rapid imaging sequences. Only the portion of the target within the imaged slice can be tracked and target motion outside the currently imaged slice is not evaluated. Additionally, due to electronic, mechanical and computational constraints, MRI-guided radiotherapy systems cannot respond instantaneously to anatomical motion. System latencies can reduce the radiation dose delivered to the target and increase the radiation delivered to nearby normal tissues.

As a preliminary step, we evaluate characteristics of the MRI-guided radiotherapy machine at UCLA relevant to intra-fraction motion management. Specifically, we evaluate the geometric distortion and dosimetric accuracy of the ViewRay MRIdian MRI-guided radiotherapy system. We measure geometric distortion using a commercially available phantom and software developed in our laboratory. We measure the dosimetric accuracy of gated radiotherapy delivery using a motion phantom and radiochromic film.

The key contribution of our work is to develop motion model based methods to overcome limitations of the current technology arising from finite imaging speeds and beam triggering latencies. We propose the use of a motion model and external respiratory bellows surrogate to allow pulse sequences that require significant delays between image acquisitions to be used for radiotherapy gating. Additionally, we develop motion modeling methods to estimate tumor motion across multiple slice positions in real-time to inform radiotherapy gating decisions and provide three-dimensional target visualization. To overcome system latencies and improve the current clinical deformable registration-based target tracking algorithm we develop a novel motion prediction method. Our method exploits the rich image intensity information available during real-time MRI and can predict motion across the entire field of view in real-time. Finally, we propose an accompanying framework to evaluate motion prediction confidence to detect when predictions are likely to be inaccurate.