title: Using individual patient anatomy to predict protocol compliance for prostate intensity-modulated radiotherapy.
abstract: If a prostate intensity-modulated radiation therapy (IMRT) or volumetric-modulated arc therapy (VMAT) plan has protocol violations, it is often a challenge knowing whether this is due to unfavorable anatomy or suboptimal planning. This study aimed to create a model to predict protocol violations based on patient anatomical variables and their potential relationship to target and organ at risk (OAR) end points in the setting of definitive, dose-escalated IMRT/VMAT prostate planning. Radiotherapy plans from 200 consecutive patients treated with definitive radiation for prostate cancer using IMRT or VMAT were analyzed. The first 100 patient plans (hypothesis-generating cohort) were examined to identify anatomical variables that predict for dosimetric outcome, in particular OAR end points. Variables that scored significance were further assessed for their ability to predict protocol violations using a Classification and Regression Tree (CART) analysis. These results were then validated in a second group of 100 patients (validation cohort). In the initial analysis of the hypothesis-generating cohort, percentage of rectum overlap in the planning target volume (PTV) (%OR) and percentage of bladder overlap in the PTV (%OB) were highlighted as significant predictors of rectal and bladder dosimetry. Lymph node treatment was also significant for bladder outcomes. For the validation cohort, CART analysis showed that %OR of < 6%, 6% to 9% and > 9% predicted a 13%, 63%, and 100% rate of rectal protocol violations respectively. For the bladder, %OB of < 9% vs > 9% is associated with 13% vs 88% rate of bladder constraint violations when lymph nodes were not treated. If nodal irradiation was delivered, plans with a %OB of < 9% had a 59% risk of violations. Percentage of rectum and bladder within the PTV can be used to identify individual plan potential to achieve dose-volume histogram (DVH) constraints. A model based on these factors could be used to reduce planning time, improve work flow, and strengthen plan quality and consistency.
authors.affiliation: Radiation Oncology, Royal North Shore Hospital, Northern Sydney Cancer Centre, New South Wales, Australia.
authors.forename: Hannah
authors.initials: H
authors.lastname: Caine
authors.affiliation: Radiation Oncology, Royal North Shore Hospital, Northern Sydney Cancer Centre, New South Wales, Australia.
authors.forename: Deborah
authors.initials: D
authors.lastname: Whalley
authors.affiliation: Radiation Oncology, Royal North Shore Hospital, Northern Sydney Cancer Centre, New South Wales, Australia; Northern Clinical School, University of Sydney, Camperdown, New South Wales, Australia.
authors.forename: Andrew
authors.initials: A
authors.lastname: Kneebone
authors.affiliation: McCloud Consulting Group, New South Wales, Australia.
authors.forename: Philip
authors.initials: P
authors.lastname: McCloud
authors.affiliation: Radiation Oncology, Royal North Shore Hospital, Northern Sydney Cancer Centre, New South Wales, Australia; Northern Clinical School, University of Sydney, Camperdown, New South Wales, Australia. Electronic address: Thomas.Eade@health.nsw.gov.au.
authors.forename: Thomas
authors.initials: T
authors.lastname: Eade
mesh_terms: D019983:Guideline Adherence / Q000706:statistics & numerical data*; D006801:Humans; D008297:Male; D008962:Models, Theoretical; D011471:Prostatic Neoplasms / Q000532:radiotherapy*; D050397:Radiotherapy, Intensity-Modulated / Q000592:standards*; D057188:Workflow
keywords: IMRT; Knowledge based; Multivariate analysis; Plan quality; Prostate cancer; Radiotherapy planning