US-based scientists have developed a new less-invasive diagnostic tool to identify kidney diseases and assess its severity level using Raman Spectroscopy. Physicians traditionally use renal biopsy to directly observe kidney function.
"Raman spectroscopy provides molecular fingerprints that enable non-invasive or minimal invasive and label-free detection for the quantification of subtle molecular changes," researchers said. It has the potential to largely reduce the complexity in diagnosing and monitoring anti-GBM (glomerular basement membrane) diseases.
Professor Chandra Mohan of the University of Houston and his colleague Wei-Chuan Shih have found that there is a difference in signals obtained from a healthy and a diseased kidney, which helps to diagnose the status of a kidney in a patient.
"There are some molecules that must be responsible for these different Raman signals, but we don't need to know what those molecules may be. As long as there's a difference in the signal, that's good enough — you can easily differentiate between a diseased kidney's Raman signal and a healthy kidney's Raman signal," said Mohan.
Mohan added that, being minimal invasive and often non-invasive, the new diagnostic method also enables a label-free detection for the quantification of subtle molecular changes.
"By adapting multivariate analysis to Raman spectroscopy, we have successfully differentiated between the diseased and the non-diseased with up to 100% accuracy, and among the severely diseased, the mildly diseased and the healthy with up to 98% accuracy," said researchers Mohan and Shih.