Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy.
Vita-Salute San Raffaele University, Milan, Italy.
J Neurol. 2022 Mar;269(3):1546-1556. doi: 10.1007/s00415-021-10727-y. Epub 2021 Jul 30.
To apply a deep-learning algorithm to brain MRIs of seronegative patients with neuromyelitis optica spectrum disorders (NMOSD) and NMOSD-like manifestations and assess whether their structural features are similar to aquaporin-4-seropositive NMOSD or multiple sclerosis (MS) patients.
We analyzed 228 T2- and T1-weighted brain MRIs acquired from aquaporin-4-seropositive NMOSD (n = 85), MS (n = 95), aquaporin-4-seronegative NMOSD [n = 11, three with anti-myelin oligodendrocyte glycoprotein antibodies (MOG)], and aquaporin-4-seronegative patients with NMOSD-like manifestations (idiopathic recurrent optic neuritis and myelitis, n = 37), who were recruited from February 2010 to December 2019. Seventy-three percent of aquaporin-4-seronegative patients with NMOSD-like manifestations also had a clinical follow-up (median duration of 4 years). The deep-learning neural network architecture was based on four 3D convolutional layers. It was trained and validated on MRI scans of aquaporin-4-seropositive NMOSD and MS patients and was then applied to aquaporin-4-seronegative NMOSD and NMOSD-like manifestations. Assignment of unclassified aquaporin-4-seronegative patients was compared with their clinical follow-up.
The final algorithm differentiated aquaporin-4-seropositive NMOSD and MS patients with an accuracy of 0.95. All aquaporin-4-seronegative NMOSD and 36/37 aquaporin-4-seronegative patients with NMOSD-like manifestations were classified as NMOSD. Anti-MOG patients had a similar probability of being NMOSD or MS. At clinical follow-up, one unclassified aquaporin-4-seronegative patient evolved to MS, three developed NMOSD, and the others did not change phenotype.
Our findings support the inclusion of aquaporin4-seronegative patients into NMOSD and suggest a possible expansion to aquaporin-4-seronegative unclassified patients with NMOSD-like manifestations. Anti-MOG patients are likely to have intermediate brain features between NMOSD and MS.
应用深度学习算法分析抗水通道蛋白 4 抗体阴性的视神经脊髓炎谱系疾病（NMOSD）及 NMOSD 样表现患者的脑 MRI 并评估其结构特征与抗水通道蛋白 4 抗体阳性 NMOSD 或多发性硬化（MS）患者是否相似。
我们分析了 2010 年 2 月至 2019 年 12 月期间招募的抗水通道蛋白 4 抗体阳性 NMOSD（n=85）、MS（n=95）、抗水通道蛋白 4 抗体阴性 NMOSD（n=11，3 例为抗髓鞘少突胶质细胞糖蛋白抗体阳性）和抗水通道蛋白 4 抗体阴性 NMOSD 样表现（特发性复发性视神经炎和脊髓炎，n=37）患者的 228 例 T2 加权和 T1 加权脑 MRI。73%的抗水通道蛋白 4 抗体阴性 NMOSD 样表现患者具有临床随访（中位随访时间 4 年）。该深度学习神经网络架构基于 4 个 3D 卷积层。该模型在抗水通道蛋白 4 抗体阳性 NMOSD 和 MS 患者的 MRI 上进行训练和验证，然后应用于抗水通道蛋白 4 抗体阴性 NMOSD 和 NMOSD 样表现患者。将未分类的抗水通道蛋白 4 抗体阴性患者的结果与他们的临床随访进行比较。
最终算法对抗水通道蛋白 4 抗体阳性 NMOSD 和 MS 患者的区分准确率为 0.95。所有抗水通道蛋白 4 抗体阴性 NMOSD 和 37 例抗水通道蛋白 4 抗体阴性 NMOSD 样表现患者均被分类为 NMOSD。抗髓鞘少突胶质细胞糖蛋白抗体阳性患者被分类为 NMOSD 或 MS 的可能性相似。在临床随访中，1 例未分类的抗水通道蛋白 4 抗体阴性患者进展为 MS，3 例发展为 NMOSD，其余患者表型未发生改变。
我们的研究结果支持将抗水通道蛋白 4 抗体阴性患者纳入 NMOSD，并提示可能将抗水通道蛋白 4 抗体阴性 NMOSD 样表现患者扩展纳入 NMOSD。抗髓鞘少突胶质细胞糖蛋白抗体阳性患者的脑 MRI 特征可能介于 NMOSD 和 MS 之间。
