Integrated Physical and Radiobiological Evaluation of Radiotherapy for Brain Cancer Using Matlab-Based Outcome Modeling
Abstract
Purpose
Accurate radiotherapy for brain tumors requires highly conformal dose delivery to maximize tumor control while limiting damage to adjacent critical neural structures. Although intensity-modulated radiotherapy (IMRT) is routinely employed, plan evaluation is commonly based only on physical dose parameters. This study aimed to establish and apply an integrated assessment approach combining advanced physical quality indices with radiobiological outcome modeling to enhance the clinical relevance of IMRT plan evaluation.
Methods
Ten clinically approved IMRT brain tumor plans were created using Eclipse treatment planning software (version 13.6) with seven to nine optimized beam arrangements and a prescription of 60 Gy in 30 fractions. Plan quality was assessed using multiple physical metrics derived from RTOG, SALT, Lomax and Scheib, and van’t Riet models, including indices of conformity, homogeneity, target coverage, and healthy-tissue sparing. Radiobiological evaluation was performed independently using a custom MATLAB-based tool that extracted cumulative dose–volume histogram data to compute Equivalent Uniform Dose–based Tumor Control Probability and Normal Tissue Complication Probability.
Results
All IMRT plans demonstrated clinically acceptable target coverage and dose homogeneity consistent with established recommendations. Conformity indices indicated highly precise dose shaping around target volumes. Slight reductions in quality metrics were observed for targets located near the skin, attributable to anatomical constraints. SALT-based parameters confirmed effective sparing of normal tissues in most cases. Radiobiological modeling revealed high predicted tumor control probabilities and low complication risks for organs at risk, supporting the biological robustness of the physically optimized plans.
Conclusion
The proposed framework enables comprehensive evaluation of IMRT plans by integrating physical and radiobiological metrics. The results confirm that high geometric precision in IMRT for brain tumors can be accompanied by favorable predicted biological outcomes. Incorporating TCP and NTCP modeling into routine plan assessment may improve clinical decision-making and future treatment optimization.