Visualizing Cortical Microstructures by Optical Coherence Tomography (OCT)

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 DESCRIPTION (provided by applicant): 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.