Non-invasive detection of fatty liver in dairy cows by digital analyses of hepatic ultrasonograms

Abstract

During early lactation, many dairy cows develop fatty liver, which is associated with decreased health and reproductive performance. Currently, fatty liver can be detected reliably only by using liver biopsy followed by chemical or histological analysis, which is not practical in most on-farm situations. We tested whether digital analyses of hepatic ultrasonograms can be used to detect non-invasively fatty liver and estimate liver triacylglycerol content. A total of 49 liver biopsies and ultrasonograms were taken from 29 dairy cows within 2 weeks postpartum. The usefulness of 17 first- or second-order parameters from digital analysis of B-mode ultrasonograms were evaluated by discriminant, correlation, and regression analyses. A group of linear combinations of the 17 parameters correctly classified 40 of 49 samples into normal liver as well as mild, moderate and severe fatty liver when cut-off values were 1%, 5% and 10% and correctly classified 45 of 49 samples when cut-off values were 5% and 10% triacylglycerol of wet weight. A linear combination of 16 image parameters estimated triacylglycerol concentrations of 38 of the 39 liver samples below the cut-off value of 10% within 2.5% of liver wet weight, and a linear combination of 3 parameters estimated triacylglycerol concentrations of the 10 liver samples above the cut-off value of 10% within 2% of liver wet weight. Therefore, ultrasound imaging followed by digital analysis of sonograms has potential to non-invasively detect fatty liver and estimate liver triacylglycerol content.