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基于容积式双能 CT 放射组学分析的胸内淋巴结组织病理学鉴别。

Differentiation of intrathoracic lymph node histopathology by volumetric dual energy CT radiomic analysis.

机构信息

Department of Radiology, NYU Grossman School of Medicine, NYU Langone Health, United States of America; Department of Radiology, University of Vermont, United States of America.

Department of Radiology, NYU Grossman School of Medicine, NYU Langone Health, United States of America.

出版信息

Clin Imaging. 2024 Oct;114:110252. doi: 10.1016/j.clinimag.2024.110252. Epub 2024 Aug 10.

Abstract

PURPOSE

To determine the performance of volumetric dual energy low kV and iodine radiomic features for the differentiation of intrathoracic lymph node histopathology, and influence of contrast protocol.

MATERIALS AND METHODS

Intrathoracic lymph nodes with histopathologic correlation (neoplastic, granulomatous sarcoid, benign) within 90 days of DECT chest imaging were volumetrically segmented. 1691 volumetric radiomic features were extracted from iodine maps and low-kV images, totaling 3382 features. Univariate analysis was performed using 2-sample t-test and filtered for false discoveries. Multivariable analysis was used to compute AUCs for lymph node classification tasks.

RESULTS

129 lymph nodes from 72 individuals (mean age 61 ± 15 years) were included, 52 neoplastic, 51 benign, and 26 granulomatous-sarcoid. Among all contrast enhanced DECT protocol exams (routine, PE and CTA), univariable analysis demonstrated no significant differences in iodine and low kV features between neoplastic and non-neoplastic lymph nodes; in the subset of neoplastic versus benign lymph nodes with routine DECT protocol, 199 features differed (p = .01- < 0.05). Multivariable analysis using both iodine and low kV features yielded AUCs >0.8 for differentiating neoplastic from non-neoplastic lymph nodes (AUC 0.86), including subsets of neoplastic from granulomatous (AUC 0.86) and neoplastic from benign (AUC 0.9) lymph nodes, among all contrast protocols.

CONCLUSIONS

Volumetric DECT radiomic features demonstrate strong collective performance in differentiation of neoplastic from non-neoplastic intrathoracic lymph nodes, and are influenced by contrast protocol.

摘要

目的

确定容积双能低千伏和碘放射组学特征在鉴别胸内淋巴结组织病理学中的性能,以及对比剂方案的影响。

材料与方法

对 DECT 胸部成像后 90 天内具有组织病理学相关性(肿瘤性、肉芽肿性结节病、良性)的胸内淋巴结进行容积分割。从碘图和低千伏图像中提取了 1691 个容积放射组学特征,总共有 3382 个特征。使用两样本 t 检验进行单变量分析,并进行假发现率过滤。多变量分析用于计算淋巴结分类任务的 AUC。

结果

纳入了 72 名患者(平均年龄 61±15 岁)的 129 个淋巴结,52 个为肿瘤性,51 个为良性,26 个为肉芽肿性结节病。在所有增强 DECT 对比剂方案检查(常规、PE 和 CTA)中,单变量分析显示肿瘤性和非肿瘤性淋巴结之间的碘和低千伏特征没有显著差异;在常规 DECT 协议的肿瘤性与良性淋巴结亚组中,有 199 个特征存在差异(p=0.01-<0.05)。使用碘和低千伏特征的多变量分析得出,区分肿瘤性和非肿瘤性淋巴结的 AUC>0.8(AUC 0.86),包括常规方案中所有肿瘤性与肉芽肿性(AUC 0.86)和肿瘤性与良性(AUC 0.9)淋巴结的亚组。

结论

容积 DECT 放射组学特征在区分胸内肿瘤性和非肿瘤性淋巴结方面具有很强的综合性能,并且受对比剂方案的影响。

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