Université d'Angers, Laboratoire Angevin de Recherche en Ingénierie des Systèmes (LARIS) EA7315, Angers, 49000, France.
Université de Rennes 1, Laboratoire Traitement du Signal et de l'Image (LTSI), INSERM U1099, Rennes, F-35000, France.
Ann Clin Transl Neurol. 2021 May;8(5):1024-1037. doi: 10.1002/acn3.51292. Epub 2021 Mar 30.
Studies of motor outcome after Neonatal Arterial Ischemic Stroke (NAIS) often rely on lesion mapping using MRI. However, clinical measurements indicate that motor deficit can be different than what would solely be anticipated by the lesion extent and location. Because this may be explained by the cortical disconnections between motor areas due to necrosis following the stroke, the investigation of the motor network can help in the understanding of visual inspection and outcome discrepancy. In this study, we propose to examine the structural connectivity between motor areas in NAIS patients compared to healthy controls in order to define the cortical and subcortical connections that can reflect the motor outcome.
Thirty healthy controls and 32 NAIS patients with and without Cerebral Palsy (CP) underwent MRI acquisition and manual assessment. The connectome of all participants was obtained from T1-weighted and diffusion-weighted imaging.
Significant disconnections in the lesioned and contra-lesioned hemispheres of patients were found. Furthermore, significant correlations were detected between the structural connectivity metric of specific motor areas and manuality assessed by the Box and Block Test (BBT) scores in patients.
Using the connectivity measures of these links, the BBT score can be estimated using a multiple linear regression model. In addition, the presence or not of CP can also be predicted using the KNN classification algorithm. According to our results, the structural connectome can be an asset in the estimation of gross manual dexterity and can help uncover structural changes between brain regions related to NAIS.
新生儿大脑中动脉缺血性卒中(NAIS)后的运动功能研究通常依赖于 MRI 进行病灶定位。然而,临床测量表明,运动缺陷可能与病灶的范围和位置所预期的不完全一致。由于这可能是由于卒中后坏死导致运动区之间的皮质连接中断所致,因此研究运动网络有助于理解视觉检查和结果差异。在这项研究中,我们拟在 NAIS 患者和健康对照者之间检查运动区之间的结构连通性,以确定能够反映运动结果的皮质和皮质下连接。
30 名健康对照者和 32 名伴有或不伴有脑瘫(CP)的 NAIS 患者接受了 MRI 采集和手动评估。所有参与者的连接组都来自 T1 加权和弥散加权成像。
在患者的病灶和对侧半球中发现了明显的连接中断。此外,还检测到患者特定运动区的结构连通性度量与使用箱式和块状测试(BBT)评估的手灵活性之间存在显著相关性。
使用这些连接的连通性度量,可以使用多元线性回归模型估计 BBT 评分。此外,还可以使用 KNN 分类算法预测 CP 的存在与否。根据我们的结果,结构连接组可以用于估计总体手动灵巧性,并有助于揭示与 NAIS 相关的脑区之间的结构变化。