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为放射组学研究清理放射治疗轮廓,是否值得?一项头颈癌研究。

Cleaning radiotherapy contours for radiomics studies, is it worth it? A head and neck cancer study.

作者信息

Fontaine Pierre, Andrearczyk Vincent, Oreiller Valentin, Abler Daniel, Castelli Joel, Acosta Oscar, De Crevoisier Renaud, Vallières Martin, Jreige Mario, Prior John O, Depeursinge Adrien

机构信息

Univ Rennes, CLCC Eugene Marquis, INSERM, LTSI - UMR 1099, F-35000 Rennes, France.

Institute of Information Systems, School of Management, HES-SO Valais-Wallis University of Applied Sciences and Arts Western Switzerland, Sierre, Switzerland.

出版信息

Clin Transl Radiat Oncol. 2022 Feb 1;33:153-158. doi: 10.1016/j.ctro.2022.01.003. eCollection 2022 Mar.

Abstract

A vast majority of studies in the radiomics field are based on contours originating from radiotherapy planning. This kind of delineation ( Gross Tumor Volume, GTV) is often larger than the true tumoral volume, sometimes including parts of other organs ( trachea in Head and Neck, H&N studies) and the impact of such over-segmentation was little investigated so far. In this paper, we propose to evaluate and compare the performance between models using two contour types: those from radiotherapy planning, and those specifically delineated for radiomics studies. For the latter, we modified the radiotherapy contours to fit the true tumoral volume. The two contour types were compared when predicting Progression-Free Survival (PFS) using Cox models based on radiomics features extracted from FluoroDeoxyGlucose-Positron Emission Tomography (FDG-PET) and CT images of 239 patients with oropharyngeal H&N cancer collected from five centers, the data from the 2020 HECKTOR challenge. Using contours demonstrated better performance for predicting PFS, where Harell's concordance indices of 061 and 069 were achieved for and contours, respectively. Using automatically contours based on a fixed intensity range was associated with a C-index of 0.63. These results illustrate the importance of using clean dedicated contours that are close to the true tumoral volume in radiomics studies, even when tumor contours are already available from radiotherapy treatment planning.

摘要

放射组学领域的绝大多数研究都是基于放射治疗计划中的轮廓。这种轮廓描绘(大体肿瘤体积,GTV)通常大于真实肿瘤体积,有时还包括其他器官的部分(头颈癌研究中的气管),到目前为止,这种过度分割的影响很少被研究。在本文中,我们建议评估和比较使用两种轮廓类型的模型之间的性能:来自放射治疗计划的轮廓,以及专门为放射组学研究描绘的轮廓。对于后者,我们修改了放射治疗轮廓以拟合真实肿瘤体积。在使用基于从五个中心收集的239例口咽头颈癌患者的氟脱氧葡萄糖正电子发射断层扫描(FDG-PET)和CT图像中提取的放射组学特征的Cox模型预测无进展生存期(PFS)时,比较了这两种轮廓类型。使用 轮廓在预测PFS方面表现更好,其中 轮廓和 轮廓的哈雷尔一致性指数分别为0.61和0.69。使用基于固定强度范围自动生成的 轮廓的C指数为0.63。这些结果说明了在放射组学研究中使用接近真实肿瘤体积的清晰专用轮廓的重要性,即使放射治疗计划中已经有肿瘤轮廓。 (注:原文中部分“ ”处内容缺失,可能影响译文完整性)

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5466/8881196/2d729d4d3840/gr1.jpg

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