Artificial Intelligence Assessment of Renal Scarring (AIRS Study)

The goal of the Artificial Intelligence in Renal Scarring (AIRS) study is to develop machine learning tools for noninvasive quantification of kidney fibrosis from imaging scans. We conducted a retrospective analysis of patients who had one or more abdominal computed tomography (CT) scans within 6 mo...

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Bibliographic Details
Published in:Kidney360 2022-01, Vol.3 (1), p.83-90
Main Authors: Chantaduly, Chanon, Troutt, Hayden R, Perez Reyes, Karla A, Zuckerman, Jonathan E, Chang, Peter D, Lau, Wei Ling
Format: Article
Language:English
Subjects:
Artificial Intelligence
Cicatrix - diagnosis
Humans
Kidney Diseases - pathology
Original Investigation
Prospective Studies
Retrospective Studies
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Summary:The goal of the Artificial Intelligence in Renal Scarring (AIRS) study is to develop machine learning tools for noninvasive quantification of kidney fibrosis from imaging scans. We conducted a retrospective analysis of patients who had one or more abdominal computed tomography (CT) scans within 6 months of a kidney biopsy. The final cohort encompassed 152 CT scans from 92 patients, which included images of 300 native kidneys and 76 transplant kidneys. Two different convolutional neural networks (slice-level and voxel-level classifiers) were tested to differentiate severe versus mild/moderate kidney fibrosis (≥50% versus
ISSN:2641-7650
2641-7650
DOI:10.34067/KID.0003662021