Evelyn F. McKnight Brain Institute, University of Arizona, Tucson, AZ.
Department of Psychology, University of California, Davis, CA.
Hippocampus. 2019 May;29(5):409-421. doi: 10.1002/hipo.22809. Epub 2017 Nov 17.
Identification of primate hippocampal subfields in vivo using structural MRI imaging relies on variable anatomical guidelines, signal intensity differences, and heuristics to differentiate between regions (Yushkevich et al., 2015a). Thus, a clear anatomically-driven basis for subfield demarcation is lacking. Recent work, however, has begun to develop methods to use ex vivo histology or ex vivo MRI (Adler et al., 2014; Iglesias et al., 2015) that have the potential to inform subfield demarcations of in vivo images. For optimal results, however, ex vivo and in vivo images should ideally be matched within the same healthy brains, with the goal to develop a neuroanatomically-driven basis for in vivo structural MRI images. Here, we address this issue in young and aging rhesus macaques (young n = 5 and old n = 5) using ex vivo Nissl-stained sections in which we identified the dentate gyrus, CA3, CA2, CA1, subiculum, presubiculum, and parasubiculum guided by morphological cell properties (30 μm thick sections spaced at 240 μm intervals and imaged at 161 nm/pixel). The histologically identified boundaries were merged with in vivo structural MRIs (0.625 × 0.625 × 1 mm) from the same subjects via iterative rigid and diffeomorphic registration resulting in probabilistic atlases of young and old rhesus macaques. Our results indicate stability in hippocampal subfield volumes over an age range of 13 to 32 years, consistent with previous results showing preserved whole hippocampal volume in aged macaques (Shamy et al., 2006). Together, our methods provide a novel approach for identifying hippocampal subfields in non-human primates and a potential 'ground truth' for more accurate identification of hippocampal subfield boundaries on in vivo MRIs. This could, in turn, have applications in humans where accurately identifying hippocampal subfields in vivo is a critical research goal.
使用结构磁共振成像(MRI)在体识别灵长类动物海马亚区,依赖于可变的解剖学指南、信号强度差异和启发式方法来区分不同区域(Yushkevich 等人,2015a)。因此,缺乏明确的解剖学亚区划分基础。然而,最近的工作已经开始开发使用离体组织学或离体 MRI(Adler 等人,2014 年;Iglesias 等人,2015 年)的方法,这些方法有可能为在体图像的亚区划分提供信息。然而,为了获得最佳结果,离体和在体图像应在同一健康大脑中进行理想匹配,目的是为在体结构 MRI 图像开发神经解剖学驱动的基础。在这里,我们使用离体 Nissl 染色切片解决了这个问题,在这些切片中,我们根据形态学细胞特征(30μm 厚的切片,间隔 240μm,以 161nm/pixel 的分辨率成像)识别了齿状回、CA3、CA2、CA1、下托、前下托和副下托。通过迭代刚性和弥散变形配准,将组织学上确定的边界与来自同一对象的在体结构 MRI(0.625×0.625×1mm)合并,从而得到年轻和年老恒河猴的概率图谱。我们的结果表明,在 13 至 32 年的年龄范围内,海马亚区体积稳定,这与先前的结果一致,即老年猕猴的整个海马体积保持不变(Shamy 等人,2006 年)。总之,我们的方法为非人类灵长类动物的海马亚区识别提供了一种新方法,并且为更准确地识别在体 MRI 上的海马亚区边界提供了潜在的“真实基准”。这反过来又可以应用于人类,在人类中,准确地识别在体海马亚区是一个关键的研究目标。