Knowledge-Based Tradeoff Hyperplanes for Head and Neck Treatment Planning.

ABSTRACT:

Purpose

To develop a tradeoff hyperplane model to facilitate tradeoff decision-making before inverse planning.

Methods and materials

We propose a model-based approach to determine the tradeoff hyperplanes that allow physicians to navigate the clinically viable space of plans with best achievable dose-volume parameters before planning. For a given case, a case reference set (CRS) is selected using a novel anatomic similarity metric from a large reference plan pool. Then, a regression model is built on the CRS to estimate the expected dose-volume histograms (DVHs) for the current case. This model also predicts the DVHs for all CRS cases and captures the variation from the corresponding DVHs in the clinical plans. Finally, these DVH variations are analyzed using the principal c

SUBMITTER: Zhang J 

PROVIDER: S-EPMC7078019 | biostudies-literature | 2020 Apr

REPOSITORIES: biostudies-literature