Lambe Jeffrey, Thompson Nicolas R, Li Yadi, Nakamura Kunio, Ontaneda Daniel
Mellen Center for Multiple Sclerosis Treatment and Research, Neurology Department, Cleveland Clinic Lerner College of Medicine of Case Western Reserve University, Cleveland, Ohio, USA.
Department of Quantitative Health Sciences, Cleveland Clinic, Cleveland, Ohio, USA.
J Neuroimaging. 2025 Sep-Oct;35(5):e70089. doi: 10.1111/jon.70089.
Spinal cord pathology underpins disability accumulation in people with multiple sclerosis (pwMS). Visual inspection of spinal cord magentic resonance imaging (MRI) often fails to reliably detect injury. Radiomics analyzes signal intensities in images to identify pathological changes that may be imperceptible to the human eye. This study evaluated the application of radiomics to spinal cord MRI to distinguish subgroups of pwMS and disability correlations.
Radiomic features were extracted from upper cervical cord coverage on cross-sectional 3.0T brain noncontrasted T1-weighted MRI scans in pwMS and healthy controls (HCs). Ninety-three radiomic features-predominantly gray-level matrices-were extracted using Pyradiomics, with pixel heterogeneity considered to reflect neuroaxonal pathology. T2 lesion and brain substructure volumes were segmented from 3D fluid-attenuated inversion recovery and magnetization-prepared rapid gradient-echo sequences using an in-house 2.5D U-Net convolutional neural network to encapsulate neuroinflammation and neurodegeneration. Cervical cross-sectional area (C1-C3) was measured using in-house atlas-based segmentation. Imaging features were compared between pwMS and HCs, and pwMS by phenotype (relapsing vs. progressive), age, and race. Associations of imaging features with Patient-Determined Disease Steps (PDDS) were examined.
Among 2966 pwMS and 41 HCs, we identified radiomic features distinguishing pwMS from HCs, and pwMS by phenotype, age, and race. Radiomic features exhibited stronger correlations with PDDS than conventional MRI measures.
Radiomics identified pathological changes in pwMS in varying stages of the disease course that are undetectable by conventional spinal cord MRI. Radiomics may increase the yield of spinal cord MRI in pwMS and serve as biomarkers predicting disability worsening.
脊髓病理学是多发性硬化症（pwMS）患者残疾累积的基础。脊髓磁共振成像（MRI）的视觉检查常常无法可靠地检测到损伤。放射组学分析图像中的信号强度，以识别肉眼可能无法察觉的病理变化。本研究评估了放射组学在脊髓MRI中的应用，以区分pwMS的亚组及其与残疾的相关性。
从pwMS患者和健康对照（HCs）的横断面3.0T脑部非增强T1加权MRI扫描的上颈段脊髓覆盖区域提取放射组学特征。使用Pyradiomics提取了93个放射组学特征（主要是灰度矩阵），像素异质性被认为可反映神经轴突病理学。使用内部的2.5D U-Net卷积神经网络从三维液体衰减反转恢复序列和磁化准备快速梯度回波序列中分割出T2病变和脑亚结构体积，以概括神经炎症和神经退行性变。使用基于内部图谱的分割方法测量颈段横截面积（C1-C3）。比较了pwMS患者与HCs之间以及按表型（复发型与进展型）、年龄和种族分类的pwMS患者之间的影像特征。研究了影像特征与患者确定的疾病阶段（PDDS）之间的关联。
在2966例pwMS患者和41例HCs中，我们识别出了可区分pwMS与HCs以及按表型、年龄和种族分类的pwMS患者的放射组学特征。与传统MRI测量相比，放射组学特征与PDDS的相关性更强。
放射组学识别出了pwMS在疾病病程不同阶段的病理变化，而这些变化是传统脊髓MRI无法检测到的。放射组学可能会提高pwMS患者脊髓MRI的诊断价值，并可作为预测残疾恶化的生物标志物。
