A model predictive control approach for discovering nonstationary fluence-maps in cancer radiotherapy fractionation

Ali Ajdari, Archis Ghate

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Scopus citations

Abstract

We consider an optimization problem in radiotherapy, where the goal is to maximize the biological effect on the tumor of radiation intensity profiles across multiple treatment sessions, while limiting their toxic effects on nearby healthy tissues. We utilize the standard linear-quadratic dose-response model, which yields a nonconvex quadratically constrained quadratic programming (QCQP) formulation. Since nonconvex QCQPs are in general computationally difficult, recent work on this problem has only considered stationary solutions. This restriction allows a convex reformulation, enabling efficient solution. All other generic convexification methods for nonconvex QCQPs also yield a stationary solution in our case. While stationary solutions could be sub-optimal, currently there is no efficient method for finding nonstationary solutions. We propose a model predictive control approach that can, in principle, efficiently discover nonstationary solutions. We demonstrate via numerical experiments on head-And-neck cancer that these nonstationary solutions could produce a larger biological effect on the tumor than stationary.

Original languageEnglish (US)
Title of host publication2016 Winter Simulation Conference
Subtitle of host publicationSimulating Complex Service Systems, WSC 2016
EditorsTheresa M. Roeder, Peter I. Frazier, Robert Szechtman, Enlu Zhou
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2065-2075
Number of pages11
ISBN (Electronic)9781509044863
DOIs
StatePublished - Jul 2 2016
Externally publishedYes
Event2016 Winter Simulation Conference, WSC 2016 - Arlington, United States
Duration: Dec 11 2016Dec 14 2016

Publication series

NameProceedings - Winter Simulation Conference
Volume0
ISSN (Print)0891-7736

Conference

Conference2016 Winter Simulation Conference, WSC 2016
Country/TerritoryUnited States
CityArlington
Period12/11/1612/14/16

Bibliographical note

Publisher Copyright:
© 2016 IEEE.

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