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Session: Quality Control in Treatment Planning and Delivery [Return to Session]

Plan Quality Assessment of the Leksell Gamma Knife Lightning Dose Optimizer

D Wieczorek1*, R Kotecha2, A Gutierrez3, M Hall4, M Tom5, S Davis6, M Mcdermott7, M Mehta8, R Tolakanahalli9, (1) Miami Cancer Institute, Miami, FL, (2) Miami Cancer Institute, ,,(3) Miami Cancer Institute, Baptist Health South Florida, Miami, FL, (4) Miami Cancer Institute, ,,(5) Miami Cancer Institute, Miami, ,(6) Miami Cancer Institute, Miami, FL, (7) Miami Neuroscience Institute, ,,(8) Miami Cancer Institute, Baptist Health South Florida, ,,(9) Miami Cancer Institute, Miami, FL


WE-D-TRACK 1-3 (Wednesday, 7/28/2021) 2:00 PM - 3:00 PM [Eastern Time (GMT-4)]

Purpose: To compare plan quality metrics of manual versus Elekta Lightning™-based inversely optimized radiosurgery plans for Gamma Knife.

Methods: Clinically treated plans for 100 consecutive patients (115 lesions; 67 metastatic and 48 benign) were replanned with the Lightning™ dose optimizer (based on a convex linear programming formulation). Plans were generated to match or exceed the following metrics in order of importance: Target Coverage, Paddick Conformity Index (PCI), delivery treatment time, and Gradient Index. Plan quality metrics in addition to delivery parameters such as spatial distribution of shots, collimator sizes and optimization times were investigated.

Results: Overall, 76% (87/115) of Lightning plans showed a statistically significant improvement in plan quality. As compared to manual plans, Lightning plans showed significant improvements of 2.0% in the median PCI (p < 0.01), 4.7% in median GI (p < 0.01) and an increase in median number of shots by 60.3% (p < 0.01). Target coverage and delivery treatment time differences were not statistically significant. Regarding plan specifics, Lightning plans showed a significant increase in use of 16mm (p < 0.01) and blocked shots (p < 0.01) while also showing a significant decrease in 8mm (p < 0.01) and 4mm (p < 0.01) shots when compared to manual plans. Use of multiple shots per coordinate was substantially more frequent in Lightning plans. The Lightning optimizer did fail to produce clinically acceptable results in 4/115 (3.5%) cases. Median optimization time for Lightning plans was 4.0 min (Range: 1.0 – 15.0 min).

Conclusion: Lightning offers a significant reduction in efforts for treatment planning while achieving comparable plan quality of an expert planner. Lightning plans employ non-intuitive increased use of blocked sectors and shot-in-shot technique to achieve high quality plans. A handful of Lightning plans severely failed in matching clinical plans and warrants further investigation.



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