PNaV: A tool for generating a high-dose-rate brachytherapy treatment plan by navigating the Pareto surface guided by the visualization of multidimensional trade-offs

Christopher L. Deufel, Marina A. Epelman, Kalyan S. Pasupathy, Mustafa Y. Sir, Victor W. Wu, Michael G. Herman

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

Purpose: A Pareto Navigation and Visualization (PNaV) tool is presented for interactively constructing a high-dose-rate (HDR) brachytherapy treatment plan by navigating and visualizing the multidimensional Pareto surface. PNaV aims to improve treatment planning time and quality and is generalizable to any number of dose–volume histogram (DVH) and convex dose metrics. Methods and Materials: Pareto surface visualization and navigation were demonstrated for prostate, breast, and cervix HDR brachytherapy sites. A library of treatment plans was created to span the Pareto surfaces over a 30% range of doses in each of five DVH metrics. The PNaV method, which uses a nonnegative least-squares model to interpolate the library plans, was compared against pure optimization for 11,250 navigated plans using data envelopment analysis. The visualization of the metric trade-offs was accomplished using numerically estimated partial derivatives to plot the local curvature of the Pareto surface. PNaV enables the user to control both the magnitude and direction of the trade-off during navigation. Results: Proof of principle of PNaV was demonstrated using a graphical user interface with visualization tools to enabled rapid plan selection and a quantitative review of metric trade-offs. PNaV produced deliverable plans with DVH metrics within < 0.4%, 0.6%, and 1.1% (95% confidence interval) of the Pareto surface using plan libraries with nominal plan spacing of 10%, 15%, and 30% in each metric dimension, respectively. The interpolation used for the navigation executed in 0.1 s. The fast interpolation allows for quick and efficient exploration of trade-off options by the physician, after an initial preprocessing step to generate the library. Conclusions: Generation, visualization, and navigation of the Pareto surface were validated for brachytherapy treatment planning. The PNaV method enables efficient and informed decision-making for radiotherapy.

Original languageEnglish (US)
Pages (from-to)518-531
Number of pages14
JournalBrachytherapy
Volume19
Issue number4
DOIs
StatePublished - Jul 1 2020

Keywords

  • Brachytherapy
  • HDR
  • MCO
  • Multicriteria optimization
  • Navigation
  • Pareto
  • Treatment planning

ASJC Scopus subject areas

  • Oncology
  • Radiology Nuclear Medicine and imaging

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