Development and Validation of a Deep Learning Model to Quantify Interstitial Fibrosis and Tubular Atrophy From Kidney Ultrasonography Images.

ABSTRACT:

Importance

Interstitial fibrosis and tubular atrophy (IFTA) is a strong indicator of decline in kidney function and is measured using histopathological assessment of kidney biopsy core. At present, a noninvasive test to assess IFTA is not available.

Objective

To develop and validate a deep learning (DL) algorithm to quantify IFTA from kidney ultrasonography images.

Design, setting, and participants

This was a single-center diagnostic study of consecutive patients who underwent native kidney biopsy at John H. Stroger Jr. Hospital of Cook County, Chicago, Illinois, between January 1, 2014, and December 31, 2018. A DL algorithm was trained, validated, and tested to classify IFTA from kidney ultrasonography images. Of 6135 Crimmins-filtered ultrasonography images, 5523 we

SUBMITTER: Athavale AM 

PROVIDER: S-EPMC8144924 | biostudies-literature | 2021 May

REPOSITORIES: biostudies-literature