No abstract

To evaluate the potential benefit of HyperArc (HA) fractionated stereotactic radiotherapy (FSRT) for the benign brain lesion. Sixteen patients with a single deep-seated, centrally located benign brain lesion treated by CyberKnife (CK, G4 cone-based model) were enrolled. Treatment plans for HA with two different optimization algorithms (SRS NTO and ALDO) and coplanar RapidArc (RA) were generated for each patient to meet the corresponding treatment plan criteria. These four FSRT treatment plans were divided into two groups—the homogeneous delivery group (HA-SRS NTO and coplanar RA) and the inhomogeneous delivery group (HA-ALDO and cone-based CK)—to compare for dosimetric outcomes. For homogeneous delivery, the brain V5, V12, and V24 and the mean brainstem dose were significantly lower with the HA-SRS NTO plans than with the coplanar RA plans. The conformity index, high and intermediate dose spillage, and gradient radius were significantly better with the HA-SRS NTO plans than with the coplanar RA plans. For inhomogeneous delivery, the HA-ALDO exhibited superior PTV coverage levels to the cone-based CK plans. Almost all the doses delivered to organs at risk and dose distribution metrics were significantly better with the HA-ALDO plans than with the cone-based CK plans. Good dosimetric distribution makes HA an attractive FSRT technique for the treatment of benign brain lesions.

No abstract

Purpose: Collision detection of the patient with the proton gantry during treatment planning phase can reduce re‐planning effort and patient setup time. The collision detection in proton therapy should account for specific proton gantry design, treatment beam configuration, and patient geometry. Methods: The coordinates of the surface contour of the gantry head were captured from the proton CAD design and reconstructed relative to the isocenter. This reconstruction accounts for patient specific gantry rotation, snout position, collimator rotation and compensator dimensions based on patientˈs treatment plan. The patientˈs body contour and couch, captured from the CT structure DICOM file and CAD design, were also reconstructed relative to the isocenter while considering the couch angle from the treatment plan. The ray‐casting algorithm was applied to monitor collisions by determining if any of the patient and couch body points falls into the polygon formed by the proton gantry spatial contour. Results: A software program was developed for patient/couch‐gantry collision detection in proton therapy. We have successfully predicted collisions in real and artificially constructed treatment plan cases. The collision detection program is being clinically validated as an accurate and quick method to predict patient‐gantry collision in proton therapy. Conclusions: An accurate and quick patient‐specific collision detection program for proton therapy can be implemented and applied in treatment planning phase using proton CAD design and patient CT images.