Neuroinflammation Imaging Lab (NIL), Institute of NeuroScience, Université catholique de Louvain, Brussels, Belgium; ICTEAM Institute, Université catholique de Louvain, Louvain-la-Neuve, Belgium.
Neuroinflammation Imaging Lab (NIL), Institute of NeuroScience, Université catholique de Louvain, Brussels, Belgium.
Neuroimage Clin. 2024;42:103593. doi: 10.1016/j.nicl.2024.103593. Epub 2024 Mar 18.
In multiple sclerosis (MS), accurate in vivo characterization of the heterogeneous lesional and extra-lesional tissue pathology remains challenging. Marshalling several advanced imaging techniques - quantitative relaxation time (T1) mapping, a model-free average diffusion signal approach and four multi-shell diffusion models - this study investigates the performance of multi-shell diffusion models and characterizes the microstructural damage within (i) different MS lesion types - active, chronic active, and chronic inactive - (ii) their respective periplaque white matter (WM), and (iii) the surrounding normal-appearing white matter (NAWM). In 83 MS participants (56 relapsing-remitting, 27 progressive) and 23 age and sex-matched healthy controls (HC), we analysed a total of 317 paramagnetic rim lesions (PRL+), 232 non-paramagnetic rim lesions (PRL-), 38 contrast-enhancing lesions (CEL). Consistent with previous findings and histology, our analysis revealed the ability of advanced multi-shell diffusion models to characterize the unique microstructural patterns of CEL, and to elucidate their possible evolution into a resolving (chronic inactive) vs smoldering (chronic active) inflammatory stage. In addition, we showed that the microstructural damage extends well beyond the MRI-visible lesion edge, gradually fading out while moving outward from the lesion edge into the immediate WM periplaque and the NAWM, the latter still characterized by diffuse microstructural damage in MS vs HC. This study also emphasizes the critical role of selecting appropriate diffusion models to elucidate the complex pathological architecture of MS lesions and their periplaque. More specifically, multi-compartment diffusion models based on biophysically interpretable metrics such as neurite orientation dispersion and density (NODDI; mean auc=0.8002) emerge as the preferred choice for MS applications, while simpler models based on a representation of the diffusion signal, like diffusion tensor imaging (DTI; mean auc=0.6942), consistently underperformed, also when compared to T1 mapping (mean auc=0.73375).
在多发性硬化症 (MS) 中，准确地对异质病变和病变外组织病理学进行体内特征描述仍然具有挑战性。本研究整合了多种先进的成像技术——定量弛豫时间 (T1) 映射、无模型平均扩散信号方法和四种多壳扩散模型——来研究多壳扩散模型的性能，并对以下结构进行微观结构损伤特征分析：(i) 不同的 MS 病变类型——活动、慢性活跃和慢性非活跃；(ii) 其相应的斑块周围白质 (WM)；和 (iii) 周围正常表现的白质 (NAWM)。在 83 名 MS 参与者（56 名复发缓解型，27 名进展型）和 23 名年龄和性别匹配的健康对照者（HC）中，我们总共分析了 317 个顺磁性边缘病变 (PRL+)、232 个非顺磁性边缘病变 (PRL-)、38 个对比增强病变 (CEL)。与之前的发现和组织学一致，我们的分析表明，先进的多壳扩散模型能够对 CEL 的独特微观结构模式进行特征描述，并阐明其从活动向缓解（慢性非活跃）或潜伏（慢性活跃）炎症阶段的可能演变。此外，我们表明，微观结构损伤远远超出了 MRI 可见的病变边缘，当从病变边缘向外移到斑块周围 WM 和 NAWM 时，逐渐消退，后者在 MS 与 HC 中仍表现为弥漫性微观结构损伤。本研究还强调了选择合适的扩散模型来阐明 MS 病变及其斑块周围的复杂病理结构的关键作用。具体而言，基于神经纤维方向分散和密度 (NODDI；平均 auc=0.8002) 等生物物理可解释指标的多区室扩散模型成为 MS 应用的首选，而基于扩散信号表示的更简单模型，如扩散张量成像 (DTI；平均 auc=0.6942)，表现始终较差，即使与 T1 映射 (平均 auc=0.73375) 相比也是如此。
