There are currently no noninvasive imaging methods available for astrogliosis assessment or mapping in the central nervous system despite its essential role in the response to many disease states, such as infarcts, neurodegenerative conditions, traumatic brain injury, and infection. Multidimensional MRI is an increasingly employed imaging modality that maximizes the amount of encoded chemical and microstructural information by probing relaxation (T1 and T2) and diffusion mechanisms simultaneously. Here, we harness the exquisite sensitivity of this imagining modality to derive a signature of astrogliosis and disentangle it from normative brain at the individual level using machine learning. We investigated ex vivo cerebral cortical tissue specimens derived from seven subjects who sustained blast induced injuries, which resulted in scar-border forming astrogliosis without being accompanied by other types of neuropathologic abnormality, and from seven control brain donors. By performing a combined postmortem radiology and histopathology correlation study we found that astrogliosis induces microstructural and chemical changes that are robustly detected with multidimensional MRI, and which can be attributed to astrogliosis because no axonal damage, demyelination, or tauopathy were histologically observed in any of the cases in the study. Importantly, we showed that no one-dimensional T1, T2, or diffusion MRI measurement can disentangle the microscopic alterations caused by this neuropathology. Based on these finding, we developed a within-subject anomaly detection procedure that generates MRI-based astrogliosis biomarker maps ex vivo, which were significantly and strongly correlated with co-registered histological images of increased glial fibrillary acidic protein deposition (r = 0.856, p < 0.0001; r = 0.789, p < 0.0001; r = 0.793, p < 0.0001, for diffusion-T2, diffusion-T1, and T1-T2 multidimensional datasets, respectively). Our findings elucidate the underpinning of MRI signal response from astrogliosis, and the demonstrated high spatial sensitivity and specificity in detecting reactive astrocytes at the individual level, and if reproduced in vivo, will significantly impact neuroimaging studies of injury, disease, repair, and aging, in which astrogliosis has so far been an invisible process radiologically.

中文翻译：

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使用多维 MRI 绘制人脑星形胶质细胞增生图


尽管星形胶质细胞增生在应对许多疾病状态（如梗死、神经退行性疾病、创伤性脑损伤和感染）中发挥着重要作用，但目前还没有可用于中枢神经系统星形胶质细胞增生评估或绘图的无创成像方法。多维 MRI 是一种越来越多使用的成像方式，它通过同时探测弛豫（T1 和 T2）和扩散机制来最大化编码的化学和微观结构信息量。在这里，我们利用这种想象方式的精致敏感性来得出星形胶质细胞增生的特征，并使用机器学习将其与个体水平的规范大脑分开。我们研究了来自七名遭受爆炸诱发损伤的受试者的离体大脑皮质组织标本，这些受试者导致疤痕边缘形成星形胶质细胞增生，但不伴有其他类型的神经病理异常，以及来自七名对照脑供体的标本。通过进行死后放射学和组织病理学相结合的相关研究，我们发现星形胶质细胞增生会引起微观结构和化学变化，这些变化可以通过多维 MRI 可靠地检测到，并且可以归因于星形胶质细胞增生，因为在任何组织学上都没有观察到轴突损伤、脱髓鞘或 tau 病。研究中的案例。重要的是，我们表明，任何一维 T1、T2 或扩散 MRI 测量都无法解开这种神经病理学引起的微观变化。 基于这些发现，我们开发了一种体内异常检测程序，可在体外生成基于 MRI 的星形胶质细胞增生生物标志物图，该图与神经胶质原纤维酸性蛋白沉积增加的共同配准组织学图像显着且强相关（r = 0.856，p对于扩散-T2、扩散-T1 和 T1-T2 多维数据集，分别为 < 0.0001；r = 0.789，p < 0.0001；r = 0.793，p < 0.0001。我们的研究结果阐明了星形胶质细胞增生的 MRI 信号反应的基础，以及在个体水平上检测反应性星形胶质细胞所表现出的高空间敏感性和特异性，如果在体内复制，将显着影响损伤、疾病、修复和衰老的神经影像学研究，其中星形胶质细胞增生迄今为止在放射学上是一种看不见的过程。