Innovative Optical Imaging Technique Enhances Detection of Diabetic Kidney Disease

Scientists from the University of California San Diego and Washington University School of Medicine have introduced a groundbreaking imaging technology that allows detailed, three-dimensional visualization of kidney tissues without the need for staining or destroying samples. This new method, called label-free multimodal optical biopsy, utilizes laser-based imaging to detect subtle structural and chemical changes within the kidney, crucially identifying early signs of diabetic nephropathy often missed by conventional techniques.

Published in Nature Communications, the study showcases an advanced system that captures precise images of kidney biopsies, revealing excess fat deposits, protein alterations, and tissue scarring—hallmarks of diabetic kidney disease. Co-author Lingyan Shi, Ph.D., a Professor of Bioengineering at UC San Diego, likened the technology to a high-tech camera capable of 'seeing' inside tissues in 3D without damaging or staining them.

This innovative approach offers significant advantages over traditional biopsy methods, which typically involve slicing tissue into sections, applying chemical stains, and post-processing to co-register images. The label-free system preserves the tissue, maintaining its integrity for further analyses if needed, especially when sample availability is limited. Furthermore, the team integrated artificial intelligence to automatically detect disease markers in the imaging data, paving the way for more rapid and accurate diagnoses.

The technology holds promise not only for improving early detection and monitoring of diabetic kidney disease but also for broad applications in studying other conditions where tissue metabolism and structure are critical. Its ability to provide comprehensive insights into kidney health could revolutionize how clinicians approach diagnosis, treatment planning, and disease management.

According to Dr. Shi, this method provides a more complete picture of kidney pathology in 3D, enabling better understanding of disease progression. Professor Sanjay Jain from Washington University emphasizes its potential in personalized medicine, particularly during early stages when intervention can be most effective.

First author Anthony A. Fung, involved in developing the imaging platform and analysis pipeline, highlights the non-destructive nature of this technique, which retains tissue integrity without chemical stains or slicing. Looking ahead, the team aims to further incorporate AI for automatic detection, potentially transforming clinical workflows and treatment strategies for kidney disorders.

For further details, refer to the study: Anthony A. Fung et al., "Label-free multimodal optical biopsy reveals biomolecular and morphological features of diabetic kidney tissue in 2D and 3D," Nature Communications, 2025.