Author: Rama Bhawani, Mary Joan, Ajay Katake, Munish Kumar, Chhape Ram, Megha Sharma, Balbir Singh, Vikram Singh 👨🔬
Affiliation: SLBSGMC & HOSPITAL, MOHANDAI OSWAL HOSPITAL, WOCKHARDT HOSPITAL, Christian Medical College and Hospital,, AMERICAN ONCOLOGY INSTITUTE 🌍
Purpose: This study aims to evaluate the utility of voxel-based radiobiological modelling in assessing IMRT radiotherapy treatment plans concerning radiation-induced acute mucosal toxicity, specifically oral and pharyngeal mucositis, in patients with head-and-neck carcinoma by calculating normal tissue complication probability (NTCP).
Methods: The research was conducted as a single-institutional study involving thirty patients diagnosed with head-and-neck carcinoma and undergoing radiotherapy. Voxel-based modelling techniques were employed to predict the incidence and severity of mucosal toxicity by integrating dose distribution data with radiobiological parameters. Radiobiological parameters, including n, m, TD50, and γ50, were derived from the fitted SDR curve based on clinical data from the head-and-neck cancer cohort.
Results: Preliminary findings demonstrated a significant correlation between high-dose regions and the incidence of severe mucositis. The radiobiological parameters n, m, TD50, and γ50 derived from the SDR curve for Grade 1 and Grade 2 oral mucositis were determined to be [0.15, 0.35, 13.15 ± 2.55 (95% confidence interval [CI]), and 1.35] and [0.12, 0.36, 21.38 ± 5.16 (95% CI), and 1.42], respectively. Similarly, for pharyngeal mucositis, the parameters for Grade 1 and Grade 2 were found to be [0.17, 0.39, 14.37 ± 4.24 (95% CI), and 1.34] and [0.09, 0.37, 40.36 ± 7.72 (95% CI), and 1.48], respectively. NTCP for grade 1 and grade 2 oral mucositis were 99.07± 0.72 and 88.12±1.28, and NTCP for grade 1 and grade 2 pharyngeal mucositis were 99.11± 0.63 and 87.52±1.58, respectively.
Conclusion: Voxel-based radiobiological modelling is a promising tool for evaluating and improving radiotherapy treatment plans in head-and-neck carcinoma by predicting the various radiobiological parameters. By predicting the risk and severity of acute mucosal toxicity, this approach may enhance personalised treatment planning, reduce patient morbidity, and improve overall therapeutic outcomes. Further research is warranted to validate these findings in larger, multi-institutional cohorts.