Development and validation of an indigenous, radiobiological model-based tumor control probability and normal tissue complication probability estimation software for routine plan evaluation in clinics

Abstract

Purpose: Development and validation of a simple and convenient computational program in MATLAB environment for estimating the tumor control probability (TCP) and the normal tissue complication probability (NTCP), as a decision support system for routine plan evaluation. Materials and Methods: We developed an in-house software using MATLAB 2016b (Mathworks) for estimating TCP and NTCP named as RBMODELV1. The program contains Niemierko free equivalent uniform dose (EUD) program code provided in authors research article. For rest of radiobiological (RB) models in the software separate coding is performed. The program accepts cumulative dose–volume histogram file in (.txt) format containing two columns dose and volume. A set of two RB parameters were prepared, default and user-dependent in excel sheet named as RBDATA. We cross-validated results of RBMODELV1 software with BioSuite software for Poisson's TCP model and Lyman-Kutcher-Burman (LKB) model. A set of total 20 patient's data of head and neck site took under study and respective TCP and NTCP calculated by all the RB models and compared. Results: This is the first study in which we tried to establish correlation between the mean doses (EUD) received by parallel structure (parotid gland and oral cavity) and predicted percentage of NTCP values. It is found that mean dose in the range of 35–40 Gy for parotid gland can result in more than 50% NTCP predicted by all four RB models. Similarly oral cavity receiving mean dose in the range of 53–58 Gy can results in more than 35% NTCP predicted by all the four models. There is <3% variation observed between TCP calculated by BioSuite and RBMODELV1 software and <4% variation observed between predicted NTCP for parotid gland and oral cavity OAR from LKB model by both the software. Conclusion: We created simple software RBMODELV1 which can be used as a research tool as well as decision support system.