TY - JOUR
T1 - Minimizing metastatic risk in radiotherapy fractionation schedules
AU - Badri, Hamidreza
AU - Ramakrishnan, Jagdish
AU - Leder, Kevin
N1 - Publisher Copyright:
© 2015 Institute of Physics and Engineering in Medicine.
PY - 2015/10/28
Y1 - 2015/10/28
N2 - Metastasis is the process by which cells from a primary tumor disperse and form new tumors at distant anatomical locations. The treatment and prevention of metastatic cancer remains an extremely challenging problem. This work introduces a novel biologically motivated objective function to the radiation optimization community that takes into account metastatic risk instead of the status of the primary tumor. In this work, we consider the problem of developing fractionated irradiation schedules that minimize production of metastatic cancer cells while keeping normal tissue damage below an acceptable level. A dynamic programming framework is utilized to determine the optimal fractionation scheme. We evaluated our approach on a breast cancer case using the heart and the lung as organs-at-risk (OAR). For small tumor values, hypo-fractionated schedules were optimal, which is consistent with standard models. However, for relatively larger values, we found the type of schedule depended on various parameters such as the time when metastatic risk was evaluated, the values of the OARs, and the normal tissue sparing factors. Interestingly, in contrast to standard models, hypo-fractionated and semi-hypo-fractionated schedules (large initial doses with doses tapering off with time) were suggested even with large tumor α/β values. Numerical results indicate the potential for significant reduction in metastatic risk.
AB - Metastasis is the process by which cells from a primary tumor disperse and form new tumors at distant anatomical locations. The treatment and prevention of metastatic cancer remains an extremely challenging problem. This work introduces a novel biologically motivated objective function to the radiation optimization community that takes into account metastatic risk instead of the status of the primary tumor. In this work, we consider the problem of developing fractionated irradiation schedules that minimize production of metastatic cancer cells while keeping normal tissue damage below an acceptable level. A dynamic programming framework is utilized to determine the optimal fractionation scheme. We evaluated our approach on a breast cancer case using the heart and the lung as organs-at-risk (OAR). For small tumor values, hypo-fractionated schedules were optimal, which is consistent with standard models. However, for relatively larger values, we found the type of schedule depended on various parameters such as the time when metastatic risk was evaluated, the values of the OARs, and the normal tissue sparing factors. Interestingly, in contrast to standard models, hypo-fractionated and semi-hypo-fractionated schedules (large initial doses with doses tapering off with time) were suggested even with large tumor α/β values. Numerical results indicate the potential for significant reduction in metastatic risk.
KW - Radiotherapy
KW - metastasis
KW - optimal fractionation
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U2 - 10.1088/0031-9155/60/22/N405
DO - 10.1088/0031-9155/60/22/N405
M3 - Article
C2 - 26509743
AN - SCOPUS:84947069246
SN - 0031-9155
VL - 60
SP - N405-N417
JO - Physics in Medicine and Biology
JF - Physics in Medicine and Biology
IS - 22
ER -