Automated deep learning segmentation of high-resolution 7 T postmortem MRI for quantitative analysis of structure-pathology correlations in neurodegenerative diseases

Postmortem MRI allows brain anatomy to be examined at high resolution and to link pathology measures with morphometric measurements. However, automated segmentation methods for brain mapping in postmortem MRI are not well developed, primarily due to limited availability of labeled datasets, and heterogeneity in scanner hardware and acquisition protocols. In this work, we present a high resolution of 135 postmortem human brain tissue specimens imaged at 0.3 mm$^{3}$ isotropic using a T2w sequence on a 7T whole-body MRI scanner. We developed a deep learning pipeline to segment the cortical mantle by benchmarking the performance of nine deep neural architectures, followed by post-hoc topological correction. We then segment four subcortical structures (caudate, putamen, globus pallidus, and thalamus), white matter hyperintensities, and the normal appearing white matter. We show generalizing capabilities across whole brain hemispheres in different specimens, and also on unseen images acquired at 0.28 mm^3 and 0.16 mm^3 isotropic T2*w FLASH sequence at 7T. We then compute localized cortical thickness and volumetric measurements across key regions, and link them with semi-quantitative neuropathological ratings. Our code, Jupyter notebooks, and the containerized executables are publicly available at: https://pulkit-khandelwal.github.io/exvivo-brain-upennComment: Preprint submitted to NeuroImage Project website: https://pulkit-khandelwal.github.io/exvivo-brain-upen

Multi-Center Repeatability of Macular Capillary Perfusion Density Using Optical Coherence Tomography Angiography

Background/Aims: This study was to determine the test-retest repeatability in quantifying macular capillary perfusion density (CPD, expressed as fractal dimension) using optical coherence tomography angiography (OCTA) in a multi-center setting.Methods: OCTA data were obtained in self-reported healthy subjects from Bascom Palmer Eye Institute at the University of Miami (UM, N = 18) and the University of Pennsylvania (UPenn, N = 22). The right eye of each subject was imaged twice at the first visit and then again at an interval of one week to assess intra-visit and inter-visit repeatability. The macular area of the OCTA-derived capillary perfusion density (OCTA-CPD) was analyzed by custom-made image processing and fractal analysis software. Fractal analysis was performed on the skeletonized microvascular network to yield OCTA-CPD by box-counting to the fractal dimension (Dbox) in the superficial vascular plexus (SVP). Repeatability was assessed by three measures: within-subject standard deviation (Sw), coefficient of variation (CoV) of repeated measures, and intraclass correlation coefficient (ICC).Results: OCTA-CPD from both sites (UM and UPENN) showed good to excellent intra-visit repeatability, as demonstrated by the Sw 0.61. Similarly, both sites had good to excellent inter-visit repeatability, as shown by the Sw 0.61. The Bland-Altman plots of the intra-visit and inter-visit measurements showed excellent agreements between the paired measurements with minimal biases.Conclusion: Our data showed that comparable high repeatability of OCTA-CPD can be achieved in both research sites using the same device, scan protocol, and image analysis