Fifty-seventh annual meeting of the American association of physicists in medicine
TH-AB-BRB-07: A Feasibility Study for Personalized Fractionation Schedule for Lung Cancer
Investigate the feasibility of using spatio-temporal optimization, i.e., fractionation schedule optimization combined with IMRT to select the patient-specific fractionation schedule that best maximizes the tumor biologically equivalent dose (BED).
Methods and materials:
The optimal fractionation schedule for a patient depends on the tumor and organ at-risk (OAR) sensitivity to fraction size (i.e., α/β), the effective tumor doubling time, and the size and location of tumor target relative to one or more OAR. We used a novel spatio-temporal optimization method to identify the number of fractions N that maximizes the tumor BED using 3D BED distribution for sixteen lung phantom cases. The selection of the optimal fractionation schedule used equivalent 30-fraction OAR constraints for the heart (Dmean < 45 Gy), lungs (Dmean < 20 Gy), cord (Dmax < 45 Gy), esophagus (Dmax < 63 Gy), and unspecified tissues (D05 < 63 Gy). To asses plan quality, we considered the min, mean, max and D95 tumor BED and the equivalent uniform dose (EUD) for optimized plans to the corresponding BED values for a conventional IMRT plan (60 Gy in 30 fractions). A sensitivity analysis was performed to assess the effects on optimal fractionation schedule of the effective tumor doubling time (Td = 3–100 days) and lag-time for accelerated repopulation (Tk = 0 to 10 days)
For a tumor α/β = 10Gy, tumor max, min, mean, and D95 BED were about 20% larger than the BED for the conventional prescription. The EUD for the optimized fractionation schedule was up to 17% larger than conventional prescription. For fast proliferating tumor (Td < 10 days), there was no significant increase in tumor dose but the treatment course could be shortened, offering convenience for patients and efficient allocation of resources.