Manninen Eppu, Bao Shunxing, Landman Bennett A, Yang Yihong, Topgaard Daniel, Benjamini Dan
Multiscale Imaging and Integrative Biophysics Unit, National Institute on Aging, NIH, Baltimore, MD, United States.
Department of Electrical and Computer Engineering, Vanderbilt University, Nashville, TN, United States.
Imaging Neurosci (Camb). 2024 Dec 11;2. doi: 10.1162/imag_a_00387. eCollection 2024.
Diffusion-relaxation correlation multidimensional MRI (MD-MRI) replaces voxel-averaged diffusion tensor quantities and and relaxation rates with their multidimensional distributions, enabling the selective extraction and mapping of specific diffusion-relaxation spectral ranges that correspond to different cellular features. This approach has the potential of achieving high sensitivity and specificity in detecting subtle changes that would otherwise be averaged out. Here, the whole brain characterization of MD-MRI distributions and derived parameters is presented and the intrascanner test-retest reliability, repeatability, and reproducibility are evaluated to promote the further development of these quantities as neuroimaging biomarkers. We compared white matter tracts and cortical and subcortical gray matter regions, revealing notable variations in their diffusion-relaxation profiles, indicative of unique microscopic morphological characteristics. We found that the reliability and repeatability of MD-MRI-derived diffusion and relaxation mean parameters were comparable with values expected in conventional diffusion tensor imaging and relaxometry studies. Importantly, the estimated signal fractions of intravoxel spectral components in the MD-MRI distribution, corresponding to white matter, gray matter, and cerebrospinal fluid, were found to be reproducible. This underscores the viability of employing a spectral analysis approach to MD-MRI data. Our results show that a clinically feasible MD-MRI protocol can reliably deliver information of the rich structural and chemical variety that exists within each imaging voxel, creating potential for new MRI biomarkers with enhanced sensitivity and specificity.
扩散-弛豫相关多维磁共振成像（MD-MRI）用多维分布取代了体素平均扩散张量量和弛豫率，能够选择性提取和映射与不同细胞特征相对应的特定扩散-弛豫谱范围。这种方法在检测否则会被平均掉的细微变化方面具有实现高灵敏度和特异性的潜力。在此，展示了MD-MRI分布和导出参数的全脑特征，并评估了扫描仪内重测可靠性、重复性和再现性，以促进这些量作为神经影像学生物标志物的进一步发展。我们比较了白质束以及皮质和皮质下灰质区域，揭示了它们扩散-弛豫谱的显著差异，这表明了独特的微观形态特征。我们发现，MD-MRI导出的扩散和弛豫平均参数的可靠性和重复性与传统扩散张量成像和弛豫测量研究中预期的值相当。重要的是，发现MD-MRI分布中对应于白质、灰质和脑脊液的体素内谱成分的估计信号分数是可再现的。这强调了对MD-MRI数据采用谱分析方法的可行性。我们的结果表明，一种临床可行的MD-MRI方案能够可靠地提供每个成像体素内丰富的结构和化学多样性信息，为具有更高灵敏度和特异性的新型MRI生物标志物创造了潜力。
