Rajagopalan Venkateswaran, Pioro Erik P
Department of Electrical and Electronics Engineering, Birla Institute of Technology and Science Pilani, Hyderabad Campus, Hyderabad 500078, India.
Neuromuscular Center, Department of Neurology, Neurological Institute, Cleveland Clinic, Cleveland, OH 44195, USA; Department of Neurosciences, Lerner Research Institute, Cleveland Clinic, Cleveland, OH 44195, USA; Department of Medicine (Neurology), University of British Columbia, Mowafaghian Centre for Brain Health, Vancouver, BC V6T 1Z3, Canada.
J Neurol Sci. 2024 Apr 15;459:122945. doi: 10.1016/j.jns.2024.122945. Epub 2024 Mar 1.
The pathological hallmarks of amyotrophic lateral sclerosis (ALS) are degeneration of the primary motor cortex grey matter (GM) and corticospinal tract (CST) resulting in upper motor neuron (UMN) dysfunction. Conventional brain magnetic resonance imaging (MRI) shows abnormal CST hyperintensity in some UMN-predominant ALS patients (ALS-CST+) but not in others (ALS-CST-). In addition to the CST differences, we aimed to determine whether GM degeneration differs between ALS-CST+ and ALS-CST- patients by cortical thickness (CT), voxel-based morphometry (VBM) and fractal dimension analyses. We hypothesized that MRI multifractal (MF) measures could differentiate between neurologic controls (n = 14) and UMN-predominant ALS patients as well as between patient subgroups (ALS-CST+, n = 21 vs ALS-CST-, n = 27). No significant differences were observed in CT or GM VBM in any brain regions between patients and controls or between ALS subgroups. MF analyses were performed separately on GM of the whole brain, of frontal, parietal, occipital, and temporal lobes as well as of cerebellum. Estimating MF measures D (Q = 0), D (Q = 1), D (Q = 2), Δf, Δα of frontal lobe GM classified neurologic controls, ALS-CST+ and ALS-CST- groups with 98% accuracy and > 95% in F1, recall, precision and specificity scores. Classification accuracy was only 74% when using whole brain MF measures and < 70% for other brain lobes. We demonstrate that MF analysis can distinguish UMN-predominant ALS subgroups based on GM changes, which the more commonly used quantitative approaches of CT and VBM cannot.
肌萎缩侧索硬化症(ALS)的病理特征是初级运动皮层灰质(GM)和皮质脊髓束(CST)变性,导致上运动神经元(UMN)功能障碍。传统的脑磁共振成像(MRI)显示,在一些以UMN为主的ALS患者(ALS-CST+)中CST有异常高信号,但在其他患者(ALS-CST-)中则没有。除了CST的差异外,我们旨在通过皮质厚度(CT)、基于体素的形态学测量(VBM)和分形维数分析来确定ALS-CST+和ALS-CST-患者之间的GM变性是否存在差异。我们假设MRI多重分形(MF)测量可以区分神经学对照者(n = 14)和以UMN为主的ALS患者,以及患者亚组(ALS-CST+,n = 21 vs ALS-CST-,n = 27)。在患者与对照者之间或ALS亚组之间,任何脑区的CT或GM VBM均未观察到显著差异。对全脑、额叶、顶叶、枕叶和颞叶以及小脑的GM分别进行MF分析。估计额叶GM的MF测量值D(Q = 0)、D(Q = 1)、D(Q = 2)、Δf、Δα可将神经学对照者、ALS-CST+和ALS-CST-组区分开来,准确率为98%,F1、召回率、精确率和特异性评分均> 95%。使用全脑MF测量时分类准确率仅为74%,其他脑叶的分类准确率< 70%。我们证明,MF分析可以根据GM变化区分以UMN为主的ALS亚组,而CT和VBM这些更常用的定量方法则无法做到。