Characterization of arteriosclerosis based on computer-aided measurements of intra-arterial thickness.

ABSTRACT:

Purpose

Our purpose is to develop a computer vision approach to quantify intra-arterial thickness on digital pathology images of kidney biopsies as a computational biomarker of arteriosclerosis.

Approach

The severity of the arteriosclerosis was scored (0 to 3) in 753 arteries from 33 trichrome-stained whole slide images (WSIs) of kidney biopsies, and the outer contours of the media, intima, and lumen were manually delineated by a renal pathologist. We then developed a multi-class deep learning (DL) framework for segmenting the different intra-arterial compartments (training dataset: 648 arteries from 24 WSIs; testing dataset: 105 arteries from 9 WSIs). Subsequently, we employed radial sampling and made measurements of media and intima thickness as a function of spatially enc

SUBMITTER: Zhou J 

PROVIDER: S-EPMC11466048 | biostudies-literature | 2024 Sep

REPOSITORIES: biostudies-literature