In diabetic nephropathy (DN), hyperglycemia drives a progressive thickening of and damage to the glomerular filtration surfaces, as well as mesangial expansion and a constriction of capillary lumens. This leads at first to high blood pressure, increased glomerular filtration and micro-proteinuria, and later (if untreated) to severe proteinuria and end-stage renal disease (ESRD). Though, it is well known that DN is accompanied by marked histopathological changes, the assessment of these structural changes is to a degree subjective and hence varies between pathologists. In this work, we make a first study of glomerular changes in DN from a graph-theoretical and distance-based standpoint, using minimal spanning trees (MSTs) and distance matrices to generate statistical distributions that can potentially provide a “fingerprint” of DN. We apply these tools to detect notable differences between normal and DN glomeruli in both human disease and in a streptozotocin-induced (STZ) mouse model. We also introduce an automated pipeline for rapidly generating MSTs and evaluating their properties with respect to DN, and make a first pass at three-dimensional MST structures. We envision these approaches may provide a better understanding not only of the processes underway in DN progression, but of key differences between actual human disease and current experimental models.
Olivier Simon, Rabi Yacoub, Sanjay Jain, John E. Tomaszewski, and Pinaki Sarder, "Examining structural changes in diabetic nephropathy using inter-nuclear distances in glomeruli: a comparison of variously automated methods," Proc. SPIE 10581, Medical Imaging 2018: Digital Pathology, 105810B (Presented at SPIE Medical Imaging: February 11, 2018; Published: 6 March 2018); https://doi.org/10.1117/12.2295225.
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