Individualization of dose prescription based on normal-tissue dose–volume and radiosensitivity data

Abstract

Purpose: The aim of this paper is to illustrate the potential gain in tumor control probability (TCP) of prostate cancer patients by individualizing the prescription dose according to both normal-tissue (N-T) dose–volume and radiosensitivity data. Methods and Materials: Two exercises have been carried out. Firstly, patients’ dose prescriptions were individualised on the basis of N-T dose–volume histograms (DVHs) alone and secondly modeling potential differences in N-T sensitivity as well. In both cases, the change in tumor control that may be achieved by individualizing patients’ dose was estimated assuming that after the dose adjustments, every patient had ( 1) the same value of normal tissue complication probability (NTCP) (5%) and ( 2) NTCP equal to the average NTCP before individualization (i.e., without increasing the average NTCP). The Lyman-Kutcher-Burman NTCP model was used to predict the N-T response curves with two different sets of parameters. The first exercise, based only on individual NT DVHs (i.e., assuming all patient equally radiosensitive), was over a real population of 50 prostate cancer patients. The second exercise modeled a 10,000-prostate-cancer patient population with varying NT dose–volume distributions and radiosensitivity (through allowing TD 50 to vary). Results: A gain of more than 9% in TCP was predicted when doses were individualized based only on DVHs so that every patient had 5% NTCP after dose adjustments. By adding the estimate of radiosensitivity, the gain increased to more than 15%. When the individualisation was performed without increasing the mean NTCP, then the potential gain in TCP was almost 5% (for adjustment based on DVH distribution solely) increasing to 7% with the additional consideration of radiosensitivity. Conclusions: There is a potential gain (increase in local tumor control) from dose individualisation strategies based on both N-T dose–volume data and radiosensitivity (assuming that this is available). Dose prescription individualization based only on dose-volume data can be exploited provided that reliable N-T response models are available. There will be additional gains if some estimate of N-T radiosensitivity is available to allow further patient stratification, identification of patients with high radiosensitivity being particularly important.