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Life sciences · Journal article
Journal of Applied Clinical Medical Physics · September 23, 2026
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Abstract Background In lung cancer radiotherapy, the volume of the lung receiving a dose above 20 Gy (V 20Gy ) and the mean lung dose are widely recognized dosimetric indicators for predicting radiation pneumonitis. However, there is currently no unified model to predict the minimum achievable values of V 20Gy and mean lung dose. In modern radiotherapy, the most advanced and widely used technology in mainstream medical linear accelerators is volumetric modulated arc therapy (VMAT). This article describes, based on linear accelerator VMAT, the clinical dependency of achievable dose‐to‐volume ratios. Objective To investigate the predictive effect of the ratio of the planning target volume (PTV) to lung volume (r) on lung V 20Gy and mean lung dose (MLD) in volumetric modulated arc therapy (VMAT) for lung cancer, with the aim of optimizing radiotherapy plans for lung cancer. Methods A total of 197 samples were used, including VMAT plans covering primary lung lesions and lymphatic drainage areas, of which 149 were used for training and 48 for testing. A retrospective analysis was conducted on the relationship between the r and MLD or V 20Gy in the plans, and function fitting was performed using the least squares method. Results The r ranged from 0.0112 to 0.2811. The R 2 values of the power function and logarithmic function of MLD versus r were 0.820 and 0.805, respectively, while the R 2 values of the power function and logarithmic function of V 20Gy versus r were 0.822 and 0.816, respectively. The residual of MLD is ± 200, and the residual of V 20Gy is ± 4%, with residuals distributed randomly. Conclusion The r showed good fitting results with the power and logarithmic functions of MLD or V 20Gy. During treatment plan creation and evaluation, the power or logarithmic function relationships can be used to predict MLD and V 20Gy in the treatment plan, thereby achieving the lowest possible lung dose while conforming to radiation principles.