AI identifies kidney damage, predicts remaining life of organ through biopsies

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 - Kidneys contrast

Researchers from the Boston University School of Medicine have developed an artificial intelligence (AI) computer model capable of identifying the progression of kidney damage and predicting the remaining life of the organ using biopsy images. Findings were published in Kidney International Reports.

"While the trained eyes of expert pathologists can gauge the severity of disease and detect nuances of kidney damage with remarkable accuracy, such expertise is not available in all locations, especially at a global level. Moreover, there is an urgent need to standardize the quantification of kidney disease severity such that the efficacy of therapies established in clinical trials can be applied to treat patients with equally severe disease in routine practice," said co-author Vijaya B. Kolachalama, PhD, assistant professor of medicine at Boston University School of Medicine. "When implemented in the clinical setting, our work will allow pathologists to see things early and obtain insights that were not previously available.”

The AI system uses a convolutional neural networks (CNN) for the recognition of kidney disease progression through the analysis of radiology images. In this study, researchers examined the feasibility of the AI program in identifying deterioration through biopsy samples of kidney sections with different amounts of fibrosis.

Results showed the CNN system was able to outperform other models developed by a nephropathologist.

"If healthcare providers around the world can have the ability to classify kidney biopsy images with the accuracy of a nephropathologist right at the point-of-care, then this can significantly impact renal practice. In essence, our model has the potential to act as a surrogate nephropathologist, especially in resource-limited settings," said Kolachalama.