Noninvasive Method for Diagnosing Fatty Liver Developed

Nonalcoholic fatty liver disease (NAFLD) associated with metabolic dysfunction, also known as fatty liver disease, is a disorder characterized by the accumulation of fat in the liver parenchyma that can progress from simple steatosis to a serious condition such as nonalcoholic steatohepatitis through scar tissue and inflammation combined with metabolic abnormalities.

The prevalence of this pathology is rapidly increasing worldwide, paralleling the epidemics of diabetes and obesity. The burden of disease, which includes cardiovascular and liver complications such as cirrhosis and cancer, is also increasing. Furthermore, NAFLD presents a significant challenge: In its early stages, it usually does not cause symptoms, so it is likely underdiagnosed. Moreover, the current gold standard for diagnosis, liver biopsy, is an invasive technique, so its use is only advisable in subjects suspected of having fatty liver disease, and it cannot be used for mass screenings.

Therefore, efforts are being made to develop noninvasive tests, such as ultrasound-based elastography and imaging studies, such as MRI or CT.

However, elastography and MRI have significant limitations. The former is only useful for evaluating the entire organ and has reduced reliability for patients with morbid obesity, who form the high-risk group most likely to have fatty liver disease. 

On the other hand, MRI and CT allow for precise evaluation of liver regions, but MRI requires a long time to obtain images, is expensive, and its availability is limited in health centers. An MRI protocol is thus less common in routine clinical practice. In addition, MRI may be contraindicated in patients with metal implants or pacemakers. Furthermore, the reliability of quantified fat in patients with hepatocyte dysfunction may be compromised. 

In contrast, CT imaging is more cost-effective and widely available, takes less time, and is a widely used modality for diagnosing multiple pathologies. Therefore, CT-based fat quantification algorithms open the door to detecting liver steatosis in adult patients who have undergone tests for other medical purposes where CT imaging is routinely acquired.

Spanish researchers from the Vall d’Hebron Institute of Research in Barcelona (VHIR), Spain; Pompeu Fabra University in Barcelona, and various sections of CIBER (a consortium of the Carlos III Health Institute) have worked on developing an algorithm that allows accumulated fat in the liver to be measured through CT images with and without contrast agent. The results of their study were published in Medical Image Analysis.

Proof of Concept

The researchers’ algorithm allows for noninvasive and rapid detection of NAFLD associated with metabolic dysfunction. The system evaluates hepatic fat from CT images automatically, analyzing the radiologic density of the liver and spleen to identify areas with accumulated fat.

To validate this new algorithm, the researchers conducted a proof-of-concept clinical trial that included 39 patients diagnosed with fatty liver disease by elastography or liver biopsy. These patients were selected according to the inclusion criteria established in the current expert consensus for diagnosing fatty liver disease. The results showed high accuracy in the measured hepatic fat values, both in contrast-enhanced and noncontrast CT images. 

“With this algorithm, we can provide detailed information on the distribution of fat in the liver, which is crucial for an accurate diagnosis and effective monitoring of fatty liver disease. Furthermore, unlike biopsy, which only provides information from a specific area of the liver, our technique provides data for the entire organ,” said Dr José Raul Herance, a researcher at VHIR and leader of this study, in a press release.

Conclusions

The researchers’ method addresses current limitations, such as the invasiveness of biopsy. It also avoids the weaknesses associated with MRI and ultrasound elastography, such as lack of automation, high cost, limited availability, dependence on contrast agents, lack of quantification of liver fat percentage, and limited information on region-to-organ involvement. 

“We believe that this tool can become an alternative for individualized evaluation of fatty liver disease by early detection of abnormal patterns in radiologic density, and that its implementation in clinical practice will contribute to early detection and management of fatty liver,” study author Queralt Martín-Saladich, a researcher at VHIR, told Univadis Spain. However, there is still a long way to go before this technique can be used in daily clinical practice. “We are aware that we need to validate this tool with larger patient cohorts to have more comprehensive information that allows this new technique to prevent serious complications associated with this pathology and improve the health and quality of life of patients,” said Martín-Saladich. 

This story was translated from Univadis Spain, which is part of the Medscape Professional Network, using several editorial tools, including AI, as part of the process. Human editors reviewed this content before publication.