▲ Professor Jun Ki Kim of the Department of Convergence Medicine, Asan Medical Center

Asan Medical Center (AMC) team led by Professor Jun Ki Kim of the Department of Convergence Medicine developed a technology that can provide an accurate and prompt diagnosis of acute kidney failure using Raman spectroscopy and a machine learning algorithm. Surface-enhanced Raman spectroscopy (SERS) is a method of distinguishing a material’s components through observation of the light scattered on the material.

The research team took the blood and urine of rats that have developed acute kidney failure and placed them on a Raman chip. The team used SERS to amplify and obtain the Raman signal that was later combined with the partial least squares-based discriminant analysis (PLS-DA) mechanism to evaluate kidney function.

According to the SERS analysis of the blood and urine, biomarkers were detected as phenylalanine (Phe) and tyrosine (Tyr) which can be used to evaluate kidney function for the diagnosis of acute kidney damage. The research team confirmed that, unlike amino type III, phenylalanine and tyrosine are factors that can evaluate kidney function and also found that the evaluation accuracy improved when a larger Raman signal area was used. From the conventional PCA statistical analysis, Raman signals’ data distribution and diagnostic potential were not analyzed. However, when the Raman signals were combined with the PLS-DA mechanism for analysis, it was confirmed that kidney function evaluation was possible with 99.3% and 99.9% accuracy from the blood and urine, respectively.

This research was conducted as one of the Korea Health Technology R&D Projects supported by the Ministry of Trade, Industry and Energy and Ministry of Health and Welfare and also with the support of the Ministry of Science and ICT. Research findings were recently published in ‘Analytical Chemistry,’ an internationally renowned chemical analytics journal published by the American Chemical Society.