Patient-specific collision zones for 4π trajectory optimized radiation therapy

Abstract

Purpose: The 4π methodology determines optimized noncoplanar subarcs for stereotactic radiation therapy that minimize dose to organs-at-risk. Every combination of treatment angle is examined, but some angles are not appropriate as a collision would occur between the gantry and the couch or the gantry and the patient. Those combinations of couch and gantry angles are referred to as collision zones. A major barrier to applying 4π to stereotactic body radiation therapy (SBRT) is the unknown shape of the collision zones, which are significant as patients take up a large volume within the 4π sphere. This study presents a system that determines patient-specific collision zones, without additional clinical steps, to enable safe and deliverable noncoplanar treatment trajectories for SBRT patients.

Methods: To augment patient's computed tomography (CT) scan, full body scans of patients in treatment position were acquired using an optical scanner. A library of a priori scans (N = 25) was created. Based on the patients' treatment position and their body dimensions, a library scan is selected and registered to the CT scan of the patient. Next, a model of the couch and immobilization equipment is added to the patient model. This results in a patient model that is then aligned with a model of the treatment LINAC in a "virtual treatment room," where both components can be rotated to test for collisions. To test the collision detection algorithm, an end-to-end test was performed using a cranial phantom. The registration algorithm was tested by comparing the registered patient collision zones to those generated by using the patient's matching scan.

Results: The collision detection algorithm was found to have a 97.80% accuracy, a 99.99% sensitivity, and a 99.99% negative predictive value (NPV). Analysis of the registration algorithm determined that a 6 cm buffer was required to achieve a 99.65% mean sensitivity, where a sensitivity of unity is considered to be a requirement for safe treatment delivery. With a 6 cm buffer, the mean accuracy was 86.70% and the mean NPV was 99.33%.

Conclusions: Our method of determining patient-specific collision zones can be accomplished with minimal user intervention based on an a priori library of body surface scans, thus enabling the safe application of 4π SBRT.

Keywords: collision detection; extracranial stereotactic/SBRT; noncoplanar VMAT; patient-specific.