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Title: Approximating convex Pareto surfaces in multiobjective radiotherapy planning

Abstract

Radiotherapy planning involves inherent tradeoffs: the primary mission, to treat the tumor with a high, uniform dose, is in conflict with normal tissue sparing. We seek to understand these tradeoffs on a case-to-case basis, by computing for each patient a database of Pareto optimal plans. A treatment plan is Pareto optimal if there does not exist another plan which is better in every measurable dimension. The set of all such plans is called the Pareto optimal surface. This article presents an algorithm for computing well distributed points on the (convex) Pareto optimal surface of a multiobjective programming problem. The algorithm is applied to intensity-modulated radiation therapy inverse planning problems, and results of a prostate case and a skull base case are presented, in three and four dimensions, investigating tradeoffs between tumor coverage and critical organ sparing.

Authors:
; ; ;  [1]
  1. Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts 02114 (United States)
Publication Date:
OSTI Identifier:
20853459
Resource Type:
Journal Article
Journal Name:
Medical Physics
Additional Journal Information:
Journal Volume: 33; Journal Issue: 9; Other Information: DOI: 10.1118/1.2335486; (c) 2006 American Association of Physicists in Medicine; Country of input: International Atomic Energy Agency (IAEA); Journal ID: ISSN 0094-2405
Country of Publication:
United States
Language:
English
Subject:
62 RADIOLOGY AND NUCLEAR MEDICINE; ALGORITHMS; CARCINOMAS; DOSIMETRY; OPTIMIZATION; PATIENTS; PLANNING; PROSTATE; RADIATION DOSES; RADIOTHERAPY; SKULL

Citation Formats

Craft, David L, Halabi, Tarek F, Shih, Helen A, and Bortfeld, Thomas R. Approximating convex Pareto surfaces in multiobjective radiotherapy planning. United States: N. p., 2006. Web. doi:10.1118/1.2335486.
Craft, David L, Halabi, Tarek F, Shih, Helen A, & Bortfeld, Thomas R. Approximating convex Pareto surfaces in multiobjective radiotherapy planning. United States. https://doi.org/10.1118/1.2335486
Craft, David L, Halabi, Tarek F, Shih, Helen A, and Bortfeld, Thomas R. 2006. "Approximating convex Pareto surfaces in multiobjective radiotherapy planning". United States. https://doi.org/10.1118/1.2335486.
@article{osti_20853459,
title = {Approximating convex Pareto surfaces in multiobjective radiotherapy planning},
author = {Craft, David L and Halabi, Tarek F and Shih, Helen A and Bortfeld, Thomas R},
abstractNote = {Radiotherapy planning involves inherent tradeoffs: the primary mission, to treat the tumor with a high, uniform dose, is in conflict with normal tissue sparing. We seek to understand these tradeoffs on a case-to-case basis, by computing for each patient a database of Pareto optimal plans. A treatment plan is Pareto optimal if there does not exist another plan which is better in every measurable dimension. The set of all such plans is called the Pareto optimal surface. This article presents an algorithm for computing well distributed points on the (convex) Pareto optimal surface of a multiobjective programming problem. The algorithm is applied to intensity-modulated radiation therapy inverse planning problems, and results of a prostate case and a skull base case are presented, in three and four dimensions, investigating tradeoffs between tumor coverage and critical organ sparing.},
doi = {10.1118/1.2335486},
url = {https://www.osti.gov/biblio/20853459}, journal = {Medical Physics},
issn = {0094-2405},
number = 9,
volume = 33,
place = {United States},
year = {Fri Sep 15 00:00:00 EDT 2006},
month = {Fri Sep 15 00:00:00 EDT 2006}
}