Fully-automated, comprehensive knowledge-based planning for stereotactic radiosurgery – pre-clinical validation through blinded physician review

Publication date: Available online 19 April 2017
Source:Practical Radiation Oncology
Author(s): B.P. Ziemer, S. Shiraishi, J.A. Hattangadi-Gluth, P. Sanghvi, K.L. Moore
PurposeAs knowledge-based planning (KBP) attempts to augment and potentially supplant manual treatment planning, it is imperative to ensure any implementation maintains or improves overall plan quality in any disease site. The purpose of this study was to demonstrate the overall quality of KBP-driven automated stereotactic radiosurgery (SRS) treatment planning using blinded physician comparison and determine systematic factors predictive of physician plan preference to guide future KBP refinement.MethodsAutomated non-coplanar volume modulated arc therapy KBP routines were developed for 199 plans across three clinical SRS scenarios: isolated lesions (ISOLATED), lesions closely abutting (<3 cm) organs-at-risk (INVOLVED) and single-isocenter multiple metastases (MULTIMET). Overall plan quality and preference were assessed via blinded review of the plans by two SRS physicians. Quantitative quality metrics (QMs) were also compared to determine systematic differences in the treatment plans. Multiple parameters were investigated as predictors of KBP plan selection.ResultsFor the ISOLATED, INVOLVED and MULTIMET scenarios, the KBP plans were considered to be superior or equivalent to clinical plans 86.7%(91/105), 81.1%(43/53) and 78.1%(32/41) of the time, respectively. All investigated QMs were equivalent or indicated more sparing for all KBP plans. The only non-dosimetric predictor was PTV volume in the ISOLATED (p=0.02) and INVOLVED (p=0.05) groups. The dosimetric predictors for the ISOLATED group were gradient measure and heterogeneity index (both p<0.01). In the MULTIMET category, the only significant dosimetric predictor was inter-lesion dose (p=0.01).ConclusionsThe fully automated KBP SRS plans were equivalent or superior to previously treated plans in 83.4%(166/199) of cases. In clinical implementation, geometric features found to be predictive of KBP performance can be used to identify plans where KBP results might benefit from further refinement, while dosimetric predictive features could be used to further refine KBP optimization priorities.



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