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多发性硬化症和视神经脊髓炎谱系疾病的放射组学。

Radiomics in multiple sclerosis and neuromyelitis optica spectrum disorder.

机构信息

Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, 100050, People's Republic of China.

Tiantan Image Research Center, China National Clinical Research Center for Neurological Diseases, Beijing, 100050, People's Republic of China.

出版信息

Eur Radiol. 2019 Sep;29(9):4670-4677. doi: 10.1007/s00330-019-06026-w. Epub 2019 Feb 15.

Abstract

OBJECTIVE

To develop and validate an individual radiomics nomogram for differential diagnosis between multiple sclerosis (MS) and neuromyelitis optica spectrum disorder (NMOSD).

METHODS

We retrospectively collected 67 MS and 68 NMOSD with spinal cord lesions as a primary cohort and prospectively recruited 28 MS and 26 NMOSD patients as a validation cohort. Radiomic features were extracted from the spinal cord lesions. A prediction model for differentiating MS and NMOSD was built by combining the radiomic features with several clinical and routine MRI measurements. The performance of the model was assessed with respect to its calibration plot and clinical discrimination in the primary and validation cohorts.

RESULTS

Nine radiomics features extracted from an initial set of 485, predominantly reflecting lesion heterogeneity, combined with lesion length, patient sex, and EDSS, were selected to build the model for differentiating MS and NMOSD. The areas under the ROC curves (AUC) for differentiating the two diseases were 0.8808 and 0.7115, for the primary and validation cohort, respectively. This model demonstrated good calibration (C-index was 0.906 and 0.802 in primary and validation cohort).

CONCLUSIONS

A validated nomogram that incorporates the radiomic signature of spinal cord lesions, as well as cord lesion length, sex, and EDSS score, can usefully differentiate MS and NMOSD.

KEY POINTS

• Radiomic features of spinal cord lesions in MS and NMOSD were different. • Radiomic signatures can capture pathological alterations and help differentiate MS and NMOSD.

摘要

目的

开发和验证用于鉴别多发性硬化症(MS)和视神经脊髓炎谱系障碍(NMOSD)的个体化放射组学列线图。

方法

我们回顾性收集了 67 例 MS 和 68 例 NMOSD 的脊髓病变作为主要队列,并前瞻性招募了 28 例 MS 和 26 例 NMOSD 患者作为验证队列。从脊髓病变中提取放射组学特征。通过将放射组学特征与几个临床和常规 MRI 测量值相结合,构建用于区分 MS 和 NMOSD 的预测模型。通过校准图和主要及验证队列中的临床鉴别能力来评估模型的性能。

结果

从最初的 485 个特征中提取了 9 个放射组学特征,主要反映病变异质性,结合病变长度、患者性别和 EDSS,用于构建区分 MS 和 NMOSD 的模型。用于区分两种疾病的 ROC 曲线下面积(AUC)分别为 0.8808 和 0.7115,分别用于主要和验证队列。该模型显示出良好的校准(主要和验证队列的 C 指数分别为 0.906 和 0.802)。

结论

纳入脊髓病变放射组学特征、脊髓病变长度、性别和 EDSS 评分的验证列线图可有效区分 MS 和 NMOSD。

关键点

• MS 和 NMOSD 的脊髓病变放射组学特征不同。• 放射组学特征可捕捉病理改变,有助于区分 MS 和 NMOSD。

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