A recent study has suggested that dual-energy X-ray absorptiometry (DXA) imaging could be a potentially effective method for detecting non-alcoholic fatty liver disease (NAFLD). NAFLD is the most prevalent chronic liver disease worldwide, but its detection has primarily relied on surrogate serum biomarkers, elastography, or invasive liver biopsy.
In this study, researchers analyzed data from 2959 participants in the UK biobank cohort and explored the association between DXA-derived body composition parameters and NAFLD. They used magnetic resonance imaging-proton density fat fraction (MRI-PDFF) as the reference for hepatic steatosis, which has been extensively validated in previous studies.
The findings revealed several significant associations between traditional measurements such as waist circumference, waist-to-hip ratio, and android-gynoid ratio with hepatic steatosis. Additionally, body shape index and fat mass index, categorized as overweight and obese, were significantly associated with NAFLD. DXA parameters, including visceral adipose tissue mass, trunk fat mass, and android fat mass, were highly associated with NAFLD.
To predict hepatic steatosis, the researchers trained machine learning classifiers using logistic regression and two histogram-based gradient boosting ensembles. These models achieved reasonable performance with an area under the curve (AUC) ranging from 0.83 to 0.87. The DXA parameters that contributed the most to the classifiers were those features that showed a significant association with NAFLD.
The study highlights the potential utility of DXA as a practical and potentially opportunistic method for screening hepatic steatosis. Currently, NAFLD detection often relies on invasive measures such as liver biopsy, which can be costly and impose a burden on patients. DXA imaging, on the other hand, is a non-invasive technique that has been extensively validated for assessing bone density and body composition.
Although DXA has its limitations due to the lack of a true 3D representation of the body, it has been considered a reference technique or a surrogate to CT/MRI for body composition assessment in clinical practice. With the close association between NAFLD and body composition indices such as visceral fat, DXA-derived parameters can potentially help predict individuals at risk of hepatic steatosis.
The incidence and prevalence of NAFLD are rising to epidemic proportions globally, making it a major cause of chronic liver disease and liver transplantation. It is closely associated with obesity and metabolic syndrome and is linked to increased risks of cardiovascular disease and chronic kidney disease. NAFLD is a complex disease trait influenced by a combination of genetic and environmental factors, including ethnic variability.
While lifestyle modifications are crucial for managing NAFLD, early detection plays a vital role in preventing complications such as fibrosis, cirrhosis, and hepatocellular carcinoma. Currently, liver biopsy is considered the gold standard for NASH diagnosis and NAFLD staging, but non-invasive tests that can reliably differentiate NASH from NAFL are lacking. Imaging techniques such as ultrasonography, controlled attenuated parameter (CAP), CT, and MRI-PDFF hold promise, but they have limitations in terms of sensitivity, efficiency, and cost-effectiveness.
The potential of DXA imaging for NAFLD detection opens up new possibilities for non-invasive screening and risk assessment. Further research and validation are needed to establish the use of DXA as a widely accessible tool in the surveillance and management of NAFLD. Its practicality and potential to identify individuals at risk of hepatic steatosis make it a valuable addition to the existing diagnostic strategies.
