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视神经脊髓炎谱系障碍和多发性硬化症中的脑年龄差距。

Brain age gap in neuromyelitis optica spectrum disorders and multiple sclerosis.

作者信息

Wei Ren, Xu Xiaolu, Duan Yunyun, Zhang Ningnannan, Sun Jie, Li Haiqing, Li Yuxin, Li Yongmei, Zeng Chun, Han Xuemei, Zhou Fuqing, Huang Muhua, Li Runzhi, Zhuo Zhizheng, Barkhof Frederik, H Cole James, Liu Yaou

机构信息

Department of Radiology, Beijing Tiantan Hospital, Beijing, China.

Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China.

出版信息

J Neurol Neurosurg Psychiatry. 2023 Jan;94(1):31-37. doi: 10.1136/jnnp-2022-329680. Epub 2022 Oct 10.

DOI:10.1136/jnnp-2022-329680
PMID:36216455
Abstract

OBJECTIVE

To evaluate the clinical significance of deep learning-derived brain age prediction in neuromyelitis optica spectrum disorder (NMOSD) relative to relapsing-remitting multiple sclerosis (RRMS).

METHODS

This cohort study used data retrospectively collected from 6 tertiary neurological centres in China between 2009 and 2018. In total, 199 patients with NMOSD and 200 patients with RRMS were studied alongside 269 healthy controls. Clinical follow-up was available in 85 patients with NMOSD and 124 patients with RRMS (mean duration NMOSD=5.8±1.9 (1.9-9.9) years, RRMS=5.2±1.7 (1.5-9.2) years). Deep learning was used to learn 'brain age' from MRI scans in the healthy controls and estimate the brain age gap (BAG) in patients.

RESULTS

A significantly higher BAG was found in the NMOSD (5.4±8.2 years) and RRMS (13.0±14.7 years) groups compared with healthy controls. A higher baseline disability score and advanced brain volume loss were associated with increased BAG in both patient groups. A longer disease duration was associated with increased BAG in RRMS. BAG significantly predicted Expanded Disability Status Scale worsening in patients with NMOSD and RRMS.

CONCLUSIONS

There is a clear BAG in NMOSD, although smaller than in RRMS. The BAG is a clinically relevant MRI marker in NMOSD and RRMS.

摘要

目的

评估相对于复发缓解型多发性硬化症(RRMS),深度学习衍生的脑年龄预测在视神经脊髓炎谱系障碍(NMOSD)中的临床意义。

方法

这项队列研究使用了2009年至2018年期间从中国6个三级神经科中心回顾性收集的数据。总共对199例NMOSD患者、200例RRMS患者以及269名健康对照者进行了研究。对85例NMOSD患者和124例RRMS患者进行了临床随访(平均病程:NMOSD = 5.8±1.9(1.9 - 9.9)年,RRMS = 5.2±1.7(1.5 - 9.2)年)。使用深度学习从健康对照者的MRI扫描中学习“脑年龄”,并估计患者的脑年龄差距(BAG)。

结果

与健康对照者相比,NMOSD组(5.4±8.2岁)和RRMS组(13.0±14.7岁)的BAG显著更高。两组患者中,较高的基线残疾评分和更严重的脑体积损失与BAG增加相关。RRMS患者中,病程较长与BAG增加相关。BAG显著预测了NMOSD和RRMS患者扩展残疾状态量表的恶化情况。

结论

NMOSD存在明显的BAG,尽管比RRMS小。BAG是NMOSD和RRMS中具有临床相关性的MRI标志物。

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