Tumor and Organs at Risk Motion: An Opportunity for Better DMLC IMRT Delivery Systems

Abstract:

Intensity modulated radiation therapy (IMRT) requires tight coordination between computational systems and the physical devices that deliver the prescribed treatment plan, making it a perfect example of cyber-physical system. The current approach to addressing tumor motion in radiation therapy is to treat it as a problem and not as a therapeutic opportunity. Existing treatment planning methods attempt to create dose distributions that are at best dosimetrically equivalent to the static case. However, it is possible that during tumor and healthy organs motion the tumor is better exposed for treatment, allowing for the prescribed dose treatment of the tumor (target) while reducing the exposure of healthy organs to radiation.This work aims to demonstrate a treatment planning and delivery paradigm that takes advantage of the differential motion of tumors and healthy organs to deliver the prescribed tumor dose while reducing the critical (healthy) structure dose relative to the static case. The project includes development of algorithmic solutions for fast (possibly real time) adjustments for dynamic multileaf collimation (DMLC) that can be integrated within existing devices, such as the Varian delivery platforms, and can be used for training of students and practitioners. The research utilizes geometric optimization algorithms and applies them in radiation therapy studies. The investigation branches into a few major directions that include optimization of gantry movement, a moving regions approach, GPU acceleration, and the simulation of multiple treatment plans.The target tumor and surrounding regions of interest (ROIs) are often non-static due to motion introduced by the involuntary actions of the patient such as breathing and heartbeat. To compensate for this the target and ROIs are modeled as a set of moving polygons in the beam's eye view. By creating a kinetic data structure to keep track of the area of overlap between the polygon representing the target tumor and the surrounding polygons representing other ROIs, it is possible to pinpoint the time at which the target is more exposed than in the planning stage and healthy tissues can be better avoided. Such times can be used to formulate improved treatment plans or to make real time changes to a delivery procedure. Kinetic Data Structures (KDS) can be used to keep track of the area of overlap. These are event driven data structures that need to be updated only at discrete points of time. The project implemented a KDS to model two dimensional motion of polygons and to track the overall exposure of the target tumor. Two dimensional motion is relevant in practice since in the beam's eye view the target and organs at risks are seen as two dimensional objects in a projection plane. The project involved the development of an IMRT plan simulator, extended with GPU capabilities. The simulator allows for DICOM images to be read and it can load a CT volume of the patient. Multiple views of a treatment plan can also be visualized. Multiple treatment plans can be visualized and compared side by side by the physicians to evaluate the performance of each and select the best.