Related Experiment Video
Updated: Jul 7, 2026

Proton Therapy Delivery and Its Clinical Application in Select Solid Tumor Malignancies
Published on: February 6, 2019
Experience-driven dose-volume histogram maps of NTCP risk as an aid for radiation treatment plan selection and
Connor Kupchak1, Jerry Battista, Jake Van Dyk
1Department of Physics and Engineering, London Regional Cancer Program, London N6A 4G5, Canada. ckupchak@phas.ucalgary.ca
Abstract:
Commonly, the quality of treatment plans is judged by a dose-volume histogram (DVH) in regards to satisfying a series of dose-volume constraints. This paper presents a novel technique for mapping normal tissue complication probabilities (NTCP) onto regions of dose-volume space with statistical considerations of risk. Mapping is done for DVHs specific to one treatment technique for one disease site. In this study, the method is illustrated for simplified intensity modulated arc therapy of the prostate, and the resulting NTCP values apply to complications in the rectum. The method consists of implementing a Monte Carlo algorithm that creates a large set of DVH curves by simulating random walks through dose-volume space. The walks are guided by a base set of clinical DVHs. Grid points in the dose-volume space have an associated NTCP spectrum for curves passing above right of the grid point of interest. After a DVH is simulated and the NTCP estimate calculated using the Lyman model, dose-volume points located to the bottom left of the curve are scored with this NTCP value and contributed to the spectrum of each point. A NTCP tolerance value is then selected and the risk of violating this tolerance is identified by a gray-scale map in regions of dose-volume space. The generated maps distinguish technique-specific, high-risk regions, a feature which is advantageous over fixed single-point dose-volume constraints commonly used. The maps also provide a visualization tool to help select safe and robust treatment plans and open the possibility for improving the efficiency of biologically based plan optimization by focusing on the more critical sections of DVH curves.
More Related Videos
08:25Radiation Planning Assistant - A Streamlined, Fully Automated Radiotherapy Treatment Planning System
Published on: April 11, 2018
07:57Positron Emission Tomography-based Dose Painting Radiation Therapy in a Glioblastoma Rat Model using the Small Animal Radiation Research Platform
Published on: March 24, 2022