Evaluation of dose delivery based on deformed CT using a commercial software for lung cancer

Author:

Chen Jihong,Chen Kaiqiang,OuYang Min,Wang Guohua,Bai Penggang,You Hongqiang

Abstract

AbstractThis study employed a commercial software velocity to perform deformable registration and dose calculation on deformed CT images, aiming to assess the accuracy of dose delivery during the radiotherapy for lung cancers. A total of 20 patients with lung cancer were enrolled in this study. Adaptive CT (ACT) was generated by deformed the planning CT (pCT) to the CBCT of initial radiotherapy fraction, followed by contour propagation and dose recalculation. There was not significant difference between volumes of GTV and CTV calculated from the ACT and pCT. However, significant differences in dice similarity coefficient (DSC) and coverage ratio (CR) between GTV and CTV were observed, with lower values for GTV volumes below 15 cc. The mean differences in dose corresponding to 95% of the GTV, GTV-P, CTV, and CTV-P between ACT and pCT were − 0.32%, 4.52%, 2.17%, and 4.71%, respectively. For the dose corresponding to 99%, the discrepancies were − 0.18%, 8.35%, 1.92%, and 24.96%, respectively. These differences in dose primarily appeared at the edges of the target areas. Notably, a significant enhancement of dose corresponding to 1 cc for spinal cord was observed in ACT, compared with pCT. There was no statistical difference in the mean dose of lungs and heart. In general, for lung cancer patients, anatomical motion may result in both CTV and GTV moving outside the original irradiation region. The dose difference within the original target area was small, but the difference in the planning target area was considerable.

Funder

Joint Funds for the innovation of science and Technology, Fujian province

Science and Technology Project of Fujian Province

Fujian Provincial Health Technology Project

Fujian Provincial Clinlical Research Center for Cancer Radiotherapy and Immunotherapy

Publisher

Springer Science and Business Media LLC

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