Impact of database quality in knowledge-based treatment planning for prostate cancer

Publication date: Available online 13 March 2018
Source:Practical Radiation Oncology
Author(s): Phillip D.H. Wall, Robert L. Carver, Jonas D. Fontenot
PurposeInvestigate dose-volume prediction improvements in a common knowledge-based planning (KBP) method using a Pareto plan database compared to using a conventional, clinical plan database.MethodsTwo plan databases were created using retrospective, anonymized data of 124 VMAT prostate cancer patients. The clinical plan database (CPD) contained planning data from each patient's clinically-treated VMAT plan, which were manually optimized by various planners. The multi-criteria optimization database (MCOD) contained Pareto-optimal plan data from VMAT plans created using a standardized multi-criteria optimization protocol. Overlap volume histograms, incorporating fractional OAR volumes only within the treatment fields, were computed for each patient and used to match new patient anatomy to similar database patients. For each database patient, CPD and MCOD KBP predictions were generated for D10, D30, D50, D65, and D80 of the bladder and rectum in a leave-one-out manner. Prediction achievability was evaluated through a re-planning study on a subset of 31 randomly selected database patients using the best KBP predictions, regardless of plan database origin, as planning goals.ResultsMCOD predictions were significantly lower than CPD predictions for all five bladder dose-volumes and rectum D50 (p=0.004) and D65 (p<0.001), while CPD predictions for rectum D10 (p=0.005) and D30 (p<0.001) were significantly less than MCOD predictions. KBP predictions were statistically achievable in the re-plans for all predicted dose-volumes, excluding D10 of bladder (p=0.03) and rectum (p=0.04). Compared to clinical plans, re-plans showed significant average reductions in Dmean for bladder (7.8Gy; p<0.001) and rectum (9.4Gy; p<0.001), while maintaining statistically similar PTV, femoral head, and penile bulb dose.ConclusionKBP dose-volume predictions derived from Pareto plans were more optimal overall than those resulting from manually optimized clinical plans, which significantly improved KBP-assisted plan quality.



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