Near-Infrared Hyperspectral Approach Quantifies Fat Distribution in the Liver

Researchers from Tokyo University of Science and Osaka University used near-infrared hyperspectral imaging to quantitatively analyze the distribution of lipids in a mouse liver. The ability to do so, using hyperspectral imaging, charts a course for noninvasive diagnostics of nonalcoholic fatty liver disease (NALFD), which can cause liver failure and other diseases.

The method, which is also label-free, follows research that used near-infrared hyperspectral imaging to visualize plaques in the blood vessels of rabbits and fatty acids in pork. Current methods for diagnosing NAFLD are invasive, relying on biopsy samples.

The work focused on mice that were given a normal diet or one of three distinct high-fat diets that were also rich in various types of lipids. With different sets of livers, the researchers ensured availability of test samples with diverse lipid profiles.

Team members isolated lipids from small sections of the livers (using what is called a Folch extraction method — deployed specifically to extract lipids from tissue) and weighed their samples. The imaging process followed, paired with two data analysis methods: partial-least square regression and support vector regression, the latter of which was ultimately revealed to deliver better results.

The two approaches allowed the scientists to quantitatively visualize lipid distribution. In examination they found they were able to image in gradient colors according to the different lipid levels in each sample and to generate maps of the local lipid densities of samples.

The lipid levels that were measured with hyperspectral imaging and those that were quantified from the Folch extraction process ultimately exhibited a close correlation — meaning that the actual lipid levels and those observed via the new method closely aligned.

Near-infrared spectral imaging can also be used to detect specific lipid compound types, said Kyohei Okubo, an assistant professor at Tokyo University of Science. The approach, he added, additionally applies to other types of fatty liver diseases.

The research was published in Biomedical Optics Express (www.doi.org/10.1364/BOE.413712).