Coronado-Leija Ricardo, Abdollahzadeh Ali, Lee Hong-Hsi, Coelho Santiago, Ades-Aron Benjamin, Liao Ying, Salo Raimo A, Tohka Jussi, Sierra Alejandra, Novikov Dmitry S, Fieremans Els
Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, NY, United States.
Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States.
Imaging Neurosci (Camb). 2024 Jul 2;2. doi: 10.1162/imag_a_00212. eCollection 2024.
Biophysical modeling of diffusion MRI (dMRI) offers the exciting potential of bridging the gap between the macroscopic MRI resolution and microscopic cellular features, effectively turning the MRI scanner into a noninvasive microscope. In brain white matter, the Standard Model (SM) interprets the dMRI signal in terms of axon dispersion, intra- and extra-axonal water fractions, and diffusivities. However, for SM to be fully applicable and correctly interpreted, it needs to be carefully evaluated using histology. Here, we perform a comprehensive histological validation of the SM parameters, by characterizing white matter (WM) microstructure in sham and injured rat brains using volume electron microscopy and dMRI. Sensitivity is evaluated by how well each SM metric correlates with its histological counterpart, and specificity by the lack of correlation with other, non-corresponding histological features. Compared to previously developed SM estimators with constraints, our results show that SMI is the most sensitive and specific. Furthermore, we derive the functional form of the fiber orientation distribution based on its exponentially decreasing rotational invariants. This comprehensive comparison with histology may facilitate the clinical adoption of dMRI-derived SM parameters as biomarkers for neurological disorders.
扩散磁共振成像(dMRI)的生物物理建模提供了弥合宏观MRI分辨率与微观细胞特征之间差距的令人兴奋的潜力,有效地将MRI扫描仪转变为一台非侵入性显微镜。在脑白质中,标准模型(SM)根据轴突弥散、轴突内和轴突外水分数以及扩散率来解释dMRI信号。然而,为了使SM能够完全适用并得到正确解释,需要使用组织学对其进行仔细评估。在这里,我们通过使用体积电子显微镜和dMRI对假手术和受伤大鼠脑白质(WM)微观结构进行表征,对SM参数进行了全面的组织学验证。通过每个SM指标与其组织学对应指标的相关程度来评估敏感性,通过与其他不对应的组织学特征缺乏相关性来评估特异性。与先前开发的具有约束条件的SM估计器相比,我们的结果表明SMI是最敏感和特异的。此外,我们基于其指数递减的旋转不变量推导出纤维方向分布的函数形式。这种与组织学的全面比较可能有助于将dMRI衍生的SM参数作为神经系统疾病生物标志物在临床上的应用。