Abstract Objectives The objective of this study is to evaluate the user‐defined optimization settings in the Fast Inverse Planning (FIP) optimizer in Leksell GammaPlan® and determine the parameters that result… Click to show full abstract
Abstract Objectives The objective of this study is to evaluate the user‐defined optimization settings in the Fast Inverse Planning (FIP) optimizer in Leksell GammaPlan® and determine the parameters that result in the best stereotactic radiosurgery (SRS) plan quality for brain metastases, benign tumors, and arteriovenous malformations (AVMs). Methods Thirty patients with metastases and 30 with benign lesions—vestibular schwannoma, AVMs, pituitary adenoma, and meningioma‐treated with SRS were evaluated. Each target was planned by varying the low dose (LD) and beam‐on‐time (BOT) penalties in increments of 0.1, from 0 to 1. The following plan quality metrics were recorded for each plan: Paddick conformity index (PCI), gradient index (GI), BOT, and maximum organ‐at‐risk (OAR) doses. A novel objective score matrix was calculated for each target using a linearly weighted combination of the aforementioned metrics. A histogram of optimal solutions containing the five best scores was extracted. Results A total of 7260 plans were analyzed with 121 plans per patient for the range of LD/BOT penalties. The ranges of PCI, GI, and BOT across all metastatic lesions were 0.58–0.97, 2.1–3.8, and 8.8–238 min, respectively, and were 0.13–0.97, 2.1–3.8, and 8.8–238 min, respectively, for benign lesions. The objective score matrix showed unique optimal solutions for metastatic lesions and benign lesions. Additionally, the plan metrics of the optimal solutions were significantly improved compared to the clinical plans for metastatic lesions with equivalent metrics for all other cases. Conclusion In this study, FIP optimizer was evaluated to determine the optimal solution space to maximize PCI and minimize GI, BOT and OAR doses simultaneously for single metastatic/benign/non‐neoplastic targets. The optimal solution chart was determined using a novel objective score which provides novice and expert planners a roadmap to generate the most optimal plans efficiently using FIP.
               
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