Volume-based algorithm of lung dose optimization in novel dynamic arc radiotherapy for esophageal cancer

• Published in: Scientific reports Vol. 11; no. 1; pp. 4360 - 9
• Main Authors: Lin, Kuan-Heng, Hsu, Chen-Xiong, Wang, Shan-Ying, Mok, Greta S. P., Chang, Chiu-Han, Tien, Hui-Ju, Shueng, Pei-Wei, Wu, Tung-Hsin
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 23.02.2021; Nature Publishing Group; Nature Portfolio
• Subjects: 692/4028/67/1504/1477; 692/699/67/1059/485; Algorithms; Correlation coefficient; Esophageal cancer; Esophagus; Heart; Humanities and Social Sciences; Lungs; multidisciplinary; Radiation therapy; Science; Science (multidisciplinary); Spinal cord
• ISSN: 2045-2322; 2045-2322
• DOI: 10.1038/s41598-021-83682-3

This study aims to develop a volume-based algorithm (VBA) that can rapidly optimize rotating gantry arc angles and predict the lung V 5 preceding the treatment planning. This phantom study was performed in the dynamic arc therapy planning systems for an esophageal cancer model. The angle of rotation of the gantry around the isocenter as defined as arc angle (θ A ), ranging from 360° to 80° with an interval of 20°, resulting in 15 different θ A of treatment plans. The corresponding predicted lung V 5 was calculated by the VBA, the mean lung dose, lung V 5 , lung V 20 , mean heart dose, heart V 30 , the spinal cord maximum dose and conformity index were assessed from dose–volume histogram in the treatment plan. Correlations between the predicted lung V 5 and the dosimetric indices were evaluated using Pearson’s correlation coefficient. The results showed that the predicted lung V 5 and the lung V 5 in the treatment plan were positively correlated (r = 0.996 , p  < 0.001). As the θ A decreased, lung V 5 , lung V 20 , and the mean lung dose decreased while the mean heart dose, V 30 and the spinal cord maximum dose increased. The V 20 and the mean lung dose also showed high correlations with the predicted lung V 5 ( r  = 0.974, 0.999, p  < 0.001). This study successfully developed an efficient VBA to rapidly calculate the θ A to predict the lung V 5 and reduce the lung dose, with potentials to improve the current clinical practice of dynamic arc radiotherapy.