
This study leverages deep-learning models to analyze hematoxylin & eosin-stained sections from 2431 deceased-donor kidneys. It establishes a Kidney Donor Quality Score (KDQS) based on features like Sclerotic Glomeruli and Arterial Intimal Fibrosis. The KDQS, combined with recipient and peri-transplant factors, predicts graft loss, aiding in organ utilization decisions. The models could mitigate unnecessary kidney discard, enhancing risk stratification.
Like
Save
Share