Development of a non-invasive method for diagnosing fatty liver

Nonalcoholic fatty liver disease (NAFLD), also known as fatty liver disease, associated with metabolic dysfunction, is the accumulation of fat in the liver parenchyma, where scar tissue and inflammation combine with metabolic abnormalities and can progress from simple steatosis to severe conditions such as nonalcoholic steatohepatitis.

The prevalence of this condition is rapidly increasing worldwide, paralleling the epidemic of diabetes and obesity. The burden of disease is also increasing, including cardiovascular and hepatic complications such as cirrhosis and cancer. Furthermore, NAFLD poses significant challenges: diagnosis is often delayed, as symptoms are usually absent in the early stages. Moreover, liver biopsy, the current gold standard for diagnosis, is an invasive technique and is therefore only recommended for patients suspected of having fatty liver disease and cannot be used for population screening.

That’s why we’re developing non-invasive tests, such as ultrasound elastography, and imaging tests, such as MRI and CT.

However, elastography and MRI have significant limitations: the former is only useful for evaluating the entire organ, making it less reliable in morbidly obese patients, the high-risk group most likely to develop fatty liver disease.

On the other hand, MRI and CT allow for accurate assessment of the liver region, but MRI takes time to acquire images, is expensive, and has limited facilities available in health centers. Therefore, MRI protocols are less common in daily clinical practice. In addition, MRI may be contraindicated in patients with metal implants or pacemakers. Moreover, the reliability of quantified fat may be compromised in patients with hepatocellular dysfunction.

In contrast, CT imaging is a cost-effective, widely available, time-saving, and widely used technique for diagnosing a variety of medical conditions, therefore our CT-based fat quantification algorithm could enable the detection of fatty liver in adult patients undergoing examinations for other medical purposes where CT imaging is routinely performed.

Spanish researchers from different departments at the Vall d'Hebron Research Institute (VHIR) in Barcelona, ​​the Pompeu Fabra University in Barcelona and CIBER (Consortium of Carlos III Health Research Institutes) have been working on developing an algorithm that can measure fat accumulation in the liver through CT images with and without contrast agents. result Their research Medical image analysis.

Proof of concept

The researchers' algorithm makes it possible to non-invasively and quickly detect NAFLD, which is associated with metabolic dysfunction. The system automatically assesses liver fat from CT images and identifies areas of fat accumulation by analyzing the radiodensity of the liver and spleen.

To validate this new algorithm, the researchers conducted a proof-of-concept clinical trial in 39 patients with fatty liver disease diagnosed by elastography or liver biopsy who were selected according to the inclusion criteria established in the current study. Expert consensus It was used to diagnose fatty liver disease. Results showed that liver fat values ​​measured on both contrast-enhanced and non-contrast CT images had high accuracy.

“This algorithm allows us to provide detailed information about the distribution of fat in the liver, which is essential for the accurate diagnosis and effective monitoring of fatty liver disease. Moreover, unlike biopsies, which only provide information on specific areas of the liver, our technique provides data on the entire organ,” said Dr. José Raul Herrans, researcher at VHIR and leader of the study, in a press release.

Conclusion

The researchers' method addresses current limitations, such as the invasiveness of biopsies, and also avoids weaknesses associated with MRI and ultrasound elastography, including lack of automation, high cost, limited availability, reliance on contrast agents, lack of quantification of liver fat percentage, and limited information on regional and organ involvement.

“We believe that this tool represents an alternative to individual assessment of fatty liver disease by early detection of abnormal patterns of radiological density and that its implementation in clinical practice will contribute to the early detection and management of fatty liver disease,” said study author Keralt Martin Saladic, researcher at VHIR. Univadis SpainHowever, there is still a long way to go before this technology can be used in routine clinical practice: “We are aware that we need to validate this tool in larger patient cohorts to obtain more comprehensive information that will allow this new technology to prevent serious complications associated with this pathology and improve patients' health and quality of life,” said Martin Saladic.

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