Area-specific differences in microstructure and cell-type distribution are well-established across cortical regions in the human brain; and specific morphological changes have been identified in different disease conditions, such as cortical thinning or, at a finer level of resolution, changes in specific pyramidal or non-pyramidal cell populations. These data, however, are based on relatively small sample sizes and can be expected to benefit substantially from the development of high-throughput, high-resolution techniques. Currently, despite large scale initiatives now underway, the neuroanatomical knowledge-gap is still widely acknowledged to be a problem. In vivo MRI images are limited in resolution, but traditional histology, while offering cellular resolution, is prone to processing distortions and is notoriously labor-intensive. Optical coherence imaging (OCT) is a promising bridge approach that can provide cellular-level resolution and facilitate histology-level interpretation of in vivo MRI images, thus combining the high-resolution capacity of histology with the superior high-throughput, 3- dimensional, and longitudinal features of MRI. As an essential prerequisite, the current proposal aims to achieve a cellular-level evaluation of OCT images. Key parts of the experimental design are: 1) image small blocks of tissue (2x2x0.3mm) by OCT; 2) subsequently vibratome-section the tissue block, harvest the section corresponding to the imaged blockface, and process this by traditional histology and immunocytochemistry for markers specific to myelin, glia, or neurons; and 3) register and compare the two datasets (i.e., an identical blockface imaged by OCT, vibratome- sectioned post-imaging, and processed for histology). This is a collaborative project, which combines expertise in OCT imaging (at Massachusetts General Hospital) with expertise in cell type and microstructure analysis (MGH and Boston University School of Medicine). Success will be defined as determining that histological populations are faithfully captured in the OCT images, including identification of failure points, if any. Anticipated next steps, in an eventual R01, are to apply the same 3-step protocol to specimens of pathological cortical tissues, with the intention of establishing a resource database of morphological changes that could, for example, be used for finer interpretation of MRI images (ex vivo, but leading to in vivo) and predictive correlation with genetic or proteomic biomarkers.
Human neuroanatomy has long suffered from methodological limitations, where in vivo MRI images fall short of cellular-level resolution but traditional histology, despite better resolution, is prone to processing distortions and is almost impracticall labor-intensive at a large scale. Optical coherence tomography (OCT), in a novel application to postmortem brain tissue, is a new bridge approach that produces histology-level images and can facilitate higher-resolution interpretation of MRI images. As an essential prerequisite, the current proposal aims to achieve a cellular-level evaluation of OCT images by generating, registering, and comparing matched OCT-histology datasets, where small tissue blocks are first imaged by OCT and subsequently sectioned and processed by traditional histology and immunocytochemistry for specific cell and myelin markers.
| Magnain, Caroline; Augustinack, Jean C; Tirrell, Lee et al. (2018) Colocalization of neurons in optical coherence microscopy and Nissl-stained histology in Brodmann's area 32 and area 21. Brain Struct Funct : |
| Saygin, Z M; Kliemann, D; Iglesias, J E et al. (2017) High-resolution magnetic resonance imaging reveals nuclei of the human amygdala: manual segmentation to automatic atlas. Neuroimage 155:370-382 |
| Magnain, Caroline; Wang, Hui; Sakadži?, Sava et al. (2016) En face speckle reduction in optical coherence microscopy by frequency compounding. Opt Lett 41:1925-8 |
