Examining Structural Patterns and Causality in Diabetic Nephropathy using
inter-Glomerular Distance and Bayesian Graphical Models.
Authors Majumdar A, Jen KY, Jain S, Tomaszewski JE, Sarder P
Submitted By Pinaki Sarder on 6/18/2019
Status Published
Journal Proceedings of SPIE--the International Society for Optical Engineering
Year 2019
Date Published 2/1/2019
Volume : Pages 10956 : Not Specified
PubMed Reference 31186597
Abstract In diabetic nephropathy (DN), hyperglycemia drives a progressive thickening of
glomerular filtration surfaces, increased cell proliferation as well as
mesangial expansion and a constriction of capillary lumens. This leads to
progressive structural changes inside the Glomeruli. In this work, we make a
study of structural glomerular changes in DN from a graph-theoretic standpoint,
using features extracted from Minimal Spanning Trees (MSTs) constructed over
intercellular distances in order to classify the "packing signatures" of
different DN stages. We further investigate the significance of the competing
effects of Volume change measured here in 2Dimensional Pixel span area (Area) on
one hand and increased cell proliferation on the other in determining the
packing patterns. Towards that we formulate the problem as Dynamic Bayesian
Network (DBN). From our preliminary results we do postulate that volume
expansion caused by internal pressure as capillary lumens constriction has
perhaps has a greater effect in the early stages.

Investigators with authorship
Pinaki SarderSUNY at Buffalo