Document Type: Conference Proceedings
Department of Medical Physics, School of Medicine, Iran University of Medical Sciences, Tehran, Iran
Department of Radiotherapy and Oncology, Shiraz University of Medical Sciences, Shiraz, Iran Ionizing and Non-Ionizing Radiation Protection Research Center, Shiraz University of Medical Sciences, Shiraz, Iran
Radiotherapy (RT) plan evaluation using dose response models has become a feasible approach in routine clinical practice. Although there are several tools for this task, they suffer from limitations including number of different dose response models and parameters. In the present study, we aimed to develop a free program for RT plan evaluation based on a variety dose response models and parameters.
Materials and Methods:
The program was developed in MATLAB. It includes four dose response models for normal tissue complication probability (NTCP) including Lyman-Kutcher-Burman (LKB), Relative Seriality, Logit and Parallel. The program required dose-volume histogram (DVH) data, number of fractions and the total RT dose. Other user inputs include a number of model parameters which are available in separate sheets. The program also calculates biological effective dose (BED), equivalent uniform dose (EUD) and biological equivalent uniform dose (BEUD). To evaluate the program, its results from sixteen patients were compared against previously validated software codes. Each model’s results were compared for various parameters. The computed NTCP, BED, EUD and BEUD values were compared with the expected values using a spreadsheet.
There was a good agreement between the results of our program and the standard software. Different model parameters resulted in different predicted values depending on the model and the parameters used. All calculated dose response outputs were calculated exactly the same as the standard codes.
The results presented here indicate that the developed program is validated. This free and user friendly software can help physicists and clinicians to evaluate treatment plans on a radiobiological basis using different models directly and easily.