Clinical validation of using a commercial synthetic-computed tomography solution for brain MRI-only radiotherapy treatment planning

临床验证使用商业合成计算机断层扫描解决方案进行仅基于脑部MRI的放射治疗计划

阅读:2

Abstract

BACKGROUND AND PURPOSE: MRI-only radiotherapy treatment planning (RTP) relies on synthetic-CT (sCT) images for dose calculation. This study evaluates the clinical feasibility of using a commercial sCT solution in brain RTP, MRCAT Brain, focusing on dosimetric accuracy and patient setup verification. METHOD AND MATERIALS: For dosimetric evaluation, 93 patients with brain cancer who were treated with volumetric modulated arc therapy (VMAT) using a CT/MRI fusion workflow were included. sCT images were generated using MRCAT Brain. The sCT images were rigidly co-registered to the CT images. The clinical plan produced on the CT was recalculated on the sCT. Dosimetric accuracy was assessed by comparing dose differences in dose volume histogram (DVH) statistics for the planning target volume (PTV) and organs at risk (OARs).For patient setup verification, 70 patients were included, and total of 572 cone beam CT (CBCT) registrations were performed with sCT and CT as reference images. The sCT matching accuracy was validated by comparing the translational and rotational differences between sCT-CBCT and CT-CBCT registrations. RESULTS: The PTV mean dose difference between CT and sCT were 0.3 %, 0.4 %, and 0.2 % for D50%, D2%, and D98%, respectively. The OAR mean dose differences were less than 0.3 % for all OARs. 4 of 93 patients (4.3 %) showed gross dosimetric errors of greater than ± 2 %. 3/4 were caused by sCT error. For positioning verification, all results were between ± 1 mm and ± 1°. CONCLUSION: This study demonstrates the clinical feasibility of the MRCAT solution for brain MRI-only RTP, with dosimetric differences being clinically acceptable, along with submillimetre and sub-degree accuracy in patient setup verification.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。