Optimizing Radiation Therapy for Brain Metastasis Patients: A Comparative Study of Knowledge-Based Treatment Planning with HyperArc

Abstract

The purpose of this study is to examine the benefits of using a knowledge-based treatment planning (KBP) model in treating brain metastasis patients with HyperArc (HA) automated non-coplanar stereotactic radiosurgery (SRS). Treatment plans of the 113 patients with either single or multiple brain metastases treated with HA were enrolled in the study. The eighty-two treatment plans with 190 metastatic brain lesions were used to construct the training model using the DVH estimation algorithm. The model was then validated on the remaining 31 patients' treatment plans with 56 metastatic brain lesions. Two corresponding HA plans were manually generated for these 31 patients using the two optimization algorithms (SRS NTO and ALDO). The SRS NTO plan generates a rapid dose falloff and prevents dose bridging of adjacent disparate targets, while the ALDO plan can cover the target with the prescribed dose but may create a high inhomogeneous dose within the target. The dosimetric outcomes were compared between the KBP, SRS NTO, and ALDO plans. The KBP, SRS NTO, and ALDO plan consistently showed CTV and PTV coverage levels of over 99%. The KBP plans resulted in similar doses to the organs at risk compared to the SRS NTO plans, but significantly reduced doses to the brainstem and optic apparatus (lens, eyes, optic nerves, and optic chiasma) by 17% to 67% compared to the ALDO plans (P = 0.003 for brainstem and P < 0.001 for optic apparatus). The mean brain dose was not significantly different between the three plans (P = 0.694 for KBP vs. SRS NTO and P = 0.381 for KBP vs. ALDO). However, the ALDO plans showed a statistically better brain V12 Gy than the KBP plans (P = 0.009), with a difference of less than 2 c.c. that was deemed not clinically significant. The ALDO plans also had a significantly better intermediate dose spillage, gradient radius, and conformity index than the KBP plans. The KBP plans showed a significantly faster gradient index and intermediate dose spillage compared to the SRS NTO plans. This study demonstrates the ability of the KBP model (RapidPlan) to generate accurate DVH predictions for use with HA in generating SRS plans that achieve optimal sparing of organs at risk while maintaining dose falloff. The KBP plans showed balanced dosimetric results compared to the SRS NTO and ALDO optimization algorithms.