A research team with Boston University of Medicine have demonstrated artificial intelligence (AI) can analyze kidney biopsy images more accurately than traditional human methods. The researchers published their findings online Jan. 10 in Kidney International Reports. Renal biopsy samples were collected from 171 patients treated at Boston Medical Center. The images were analyzed by the team's AI model--a convolutional neural network (CNN)--as well as human nephropathologists. The CNN model was able to better predict kidney analysis compared to the specialists in six key classification tasks--most notably in recognizing the stage of chronic kidney disease.

Boston University School of Medicine has developed computer models based on artificial intelligence that significantly improve the analysis of routine kidney biopsy images. BU researchers, who conducted a proof-of-principle study on kidney biopsy sections, contend that their AI-based models have both diagnostic and prognostic applications and could lead to the development of software for diagnosing kidney disease as well as predicting kidney survival. In the study, images processed from renal biopsy samples were collected on 171 patients treated at the Boston Medical Center and were analyzed by convolutional neural networks (CNN) models and nephropathologists, who specialize in the analysis of kidney biopsy images. "With respect to kidney disease, biopsy is one of the gold standard procedures," says Vijaya Kolachalama, lead author and assistant professor of medicine at Boston University School of Medicine. "Most of the clinical decisions today are made based on information that nephropathologists can see from the biopsy."