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Updated: Jan 24, 2026

Radiation Planning Assistant - A Streamlined, Fully Automated Radiotherapy Treatment Planning System
Published on: April 11, 2018
iCONE-SRS: Development of inverse treatment planning for cone-based stereotactic radiosurgery
Anthony Lausch1, Brian Nghiem1, Michelle Nielsen1
1Medical Physics Department, Carlo Fidani Peel Regional Cancer Centre, Trillium Health Partners, Mississauga, Canada.
Purpose:
At present, commercially available treatment planning systems (TPS) only offer manual planning functionality for cone-based stereotactic radiosurgery (SRS) leading to labor intensive treatment planning. Our objective was to reduce treatment planning time through development of a simple inverse TPS for cone-based SRS.
Methods:
The iCONE TPS was developed using MATLAB (R2015a, The MathWorks Inc.) and serves as an inverse planning adjunct to a commercially available TPS. Simulated annealing is used to determine optimal table angle, gantry start and stop angles, and cone sizes for a user-defined number of non-coplanar arcs relative to user-defined dose objectives. iCONE and clinically generated plans were compared through a retrospective planning study of 60 patients treated for 1-3 brain metastases (total of 100 lesions).
Results:
Planning target volume (PTV) coverage was enforced for all plans through normalization. PTV maximum dose was constrained to be within 120%-135% of the prescription dose. The median conformity index for iCONE plans was 1.35, 1.33, and 1.32 for 1, 2, and 3-target cases respectively corresponding to a median increase of 0.05 (range = -0.1 to 0.5, P < 0.05), 0.06 (range = -0.83 to 0.53, P < 0.05), and 0.03 (range = -1.21 to 0.74, P > 0.05) relative to the clinical plans. No clinically significant differences were found with respect to the dose to organs-at-risk. Median iCONE planning times were approximately a factor of five lower than consensus estimates for manual planning provided by local experienced SRS planners.
Conclusions:
A simple inverse TPS for cone-based SRS was developed. Plan quality was found to be similar to manually generated plans; however, degradation was observed in some cases highlighting the need for continued oversight and manual adjustment by experienced planners if implemented in the clinic. A factor of five reduction in treatment planning time was estimated.
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