TY - JOUR
T1 - A stochastic control formalism for dynamic biologically conformal radiation therapy
AU - Kim, Minsun
AU - Ghate, Archis
AU - Phillips, Mark H.
PY - 2012/6/16
Y1 - 2012/6/16
N2 - State-of-the-art methods for optimizing cancer treatment over several weeks of external beam radiotherapy take a static-deterministic view of the treatment planning process, mainly focusing on spatial distribution of dose. Recent progress in quantitative functional imaging as well as mathematical models of tumor response to radiotherapy is increasingly enabling treatment planners to monitor/predict a patient's biological response over weeks of treatment. In this paper we introduce dynamic biologically conformal radiation therapy (DBCRT), a mathematical framework intended to exploit these emerging technological and biological modeling advances to design patient-specific radiation treatment strategies that dynamically adapt to the spatiotemporal evolution of a patient's biological response over several treatment sessions in order to achieve the best possible health outcome. More specifically, we propose a discrete-time stochastic control formalism where we use the patient's biological condition to model the system state and the beam intensities as controls. Three approximate control schemes are then applied and compared for efficiency. Numerical simulations on test cases show that DBCRT results in a 64-98% improvement in treatment efficacy as compared to the more conventional static-deterministic approach.
AB - State-of-the-art methods for optimizing cancer treatment over several weeks of external beam radiotherapy take a static-deterministic view of the treatment planning process, mainly focusing on spatial distribution of dose. Recent progress in quantitative functional imaging as well as mathematical models of tumor response to radiotherapy is increasingly enabling treatment planners to monitor/predict a patient's biological response over weeks of treatment. In this paper we introduce dynamic biologically conformal radiation therapy (DBCRT), a mathematical framework intended to exploit these emerging technological and biological modeling advances to design patient-specific radiation treatment strategies that dynamically adapt to the spatiotemporal evolution of a patient's biological response over several treatment sessions in order to achieve the best possible health outcome. More specifically, we propose a discrete-time stochastic control formalism where we use the patient's biological condition to model the system state and the beam intensities as controls. Three approximate control schemes are then applied and compared for efficiency. Numerical simulations on test cases show that DBCRT results in a 64-98% improvement in treatment efficacy as compared to the more conventional static-deterministic approach.
KW - Adaptive radiotherapy
KW - Control
KW - Dynamic programming
KW - Intensity modulated radiation therapy
KW - OR in health services
UR - http://www.scopus.com/inward/record.url?scp=84857915067&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84857915067&partnerID=8YFLogxK
U2 - 10.1016/j.ejor.2011.10.039
DO - 10.1016/j.ejor.2011.10.039
M3 - Article
AN - SCOPUS:84857915067
SN - 0377-2217
VL - 219
SP - 541
EP - 556
JO - European Journal of Operational Research
JF - European Journal of Operational Research
IS - 3
ER -