Stochastic frontier analysis as knowledge-based model to improve sparing of organs-at-risk for VMAT-treated prostate cancer.

Stochastic frontier analysis as knowledge-based model to improve sparing of organs-at-risk for VMAT-treated prostate cancer. Phys Med Biol. 2019 Feb 28;: Authors: Kroshko A, Morin O, Archambault L Abstract Stochastic frontier analysis is used as a novel knowledge-based technique in order to develop a predictive model of dosimetric features from signicant geometric parameters describing a patient morphology. 406 patients treated with VMAT for prostate cancer were analyzed retrospectively. Cases were divided into three prescription-based groups. Seven geometric parameters are extracted to characterize the relationship between the organs-at-risk (bladder and rectum) with the planning volume (PTV). In total, 37 dosimetric parameters are tested for these two OARs. Stochastic frontier analysis allows the determination of the minimum achievable dose to the OAR based on the geometric parameters. Stochastic frontier are determined with a maximum likelihood estimation technique. The stochastic frontier analysis model was tested using validation cohort (30 patients with prescribed dose between 60 and 70 Gy) where 77% (23 out of 30) of the predicted DVHs present a 5% or less dose deterioration for the bladder and rectum with the planned DVH. Stochastic frontier analysis can be used in EBRT planning as a predictive model based on anatomical features of previously treated plans. PMID: 30818294 [PubMed - as supplied by publisher]
Source: Physics in Medicine and Biology - Category: Physics Authors: Tags: Phys Med Biol Source Type: research