Contouring practices and artefact management within a synthetic CT-based radiotherapy workflow for the central nervous system.

IF 3.3 2区 医学 Q2 ONCOLOGY
Elia Rossi, Sevgi Emin, Michael Gubanski, Giovanna Gagliardi, Mattias Hedman, Fernanda Villegas
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引用次数: 0

Abstract

Background: The incorporation of magnetic resonance (MR) imaging in radiotherapy (RT) workflows improves contouring precision, yet it introduces geometrical uncertainties when registered with computed tomography (CT) scans. Synthetic CT (sCT) images could minimize these uncertainties and streamline the RT workflow. This study aims to compare the contouring capabilities of sCT images with conventional CT-based/MR-assisted RT workflows, with an emphasis on managing artefacts caused by surgical fixation devices (SFDs).

Methods: The study comprised a commissioning cohort of 100 patients with cranial tumors treated using a conventional CT-based/MR-assisted RT workflow and a validation cohort of 30 patients with grade IV glioblastomas treated using an MR-only workflow. A CE-marked artificial-intelligence-based sCT product was utilized. The delineation accuracy comparison was performed using dice similarity coefficient (DSC) and average Hausdorff distance (AHD). Artefacts within the commissioning cohort were visually inspected, classified and an estimation of thickness was derived using Hausdorff distance (HD). For the validation cohort, boolean operators were used to extract artefact volumes adjacent to the target and contrasted to the planning treatment volume.

Results: The combination of high DSC (0.94) and low AHD (0.04 mm) indicates equal target delineation capacity between sCT images and conventional CT scans. However, the results for organs at risk delineation were less consistent, likely because of voxel size differences between sCT images and CT scans and absence of standardized delineation routines. Artefacts observed in sCT images appeared as enhancements of cranial bone. When close to the target, they could affect its definition. Therefore, in the validation cohort the clinical target volume (CTV) was expanded towards the bone by 3.5 mm, as estimated by HD analysis. Subsequent analysis on cone-beam CT scans showed that the CTV adjustment was enough to provide acceptable target coverage.

Conclusion: The tested sCT product performed on par with conventional CT in terms of contouring capability. Additionally, this study provides both the first comprehensive classification of metal artefacts on a sCT product and a novel method to assess the clinical impact of artefacts caused by SFDs on target delineation. This methodology encourages similar analysis for other sCT products.

中枢神经系统合成 CT 放射治疗工作流程中的轮廓处理和伪影管理。
背景:将磁共振(MR)成像纳入放射治疗(RT)工作流程可提高轮廓绘制的精确度,但在与计算机断层扫描(CT)对比时会产生几何不确定性。合成 CT(sCT)图像可以最大限度地减少这些不确定性,简化 RT 工作流程。本研究旨在比较 sCT 图像与传统的基于 CT/MR 辅助 RT 工作流程的轮廓绘制能力,重点是处理手术固定装置(SFD)造成的伪影:研究包括一个由100名使用传统CT/MR辅助RT工作流程治疗的头颅肿瘤患者组成的调试队列和一个由30名使用纯MR工作流程治疗的IV级胶质母细胞瘤患者组成的验证队列。使用的是获得 CE 认证的基于人工智能的 sCT 产品。使用骰子相似系数(DSC)和平均豪斯多夫距离(AHD)对划线准确性进行比较。使用豪斯多夫距离(HD)对试运行队列中的伪影进行目测、分类和厚度估算。对于验证队列,使用布尔运算器提取邻近目标的伪影体积,并与规划治疗体积进行对比:结果:高 DSC(0.94)和低 AHD(0.04 毫米)的组合表明,sCT 图像和传统 CT 扫描的靶点划分能力相当。然而,危险器官的划定结果却不太一致,这可能是因为 sCT 图像和 CT 扫描的体素大小不同,而且缺乏标准化的划定程序。在 sCT 图像中观察到的伪影表现为颅骨的增强。当接近目标时,它们会影响目标的定义。因此,在验证队列中,根据高清分析的估计,临床靶区(CTV)向骨骼方向扩展了 3.5 毫米。随后的锥形束 CT 扫描分析表明,CTV 调整足以提供可接受的目标覆盖范围:结论:测试的 sCT 产品在轮廓能力方面与传统 CT 不相上下。此外,这项研究还首次对 sCT 产品上的金属伪影进行了全面分类,并提供了一种新方法来评估 SFD 造成的伪影对靶区划分的临床影响。这种方法鼓励对其他 sCT 产品进行类似的分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Radiation Oncology
Radiation Oncology ONCOLOGY-RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING
CiteScore
6.50
自引率
2.80%
发文量
181
审稿时长
3-6 weeks
期刊介绍: Radiation Oncology encompasses all aspects of research that impacts on the treatment of cancer using radiation. It publishes findings in molecular and cellular radiation biology, radiation physics, radiation technology, and clinical oncology.
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