Adaptive Evolutionary Optimization of Deep Learning Architectures for Focused Liver Ultrasound Image Segmentation.

Liver ultrasound segmentation is challenging due to low image quality and variability. While deep learning (DL) models have been widely applied for medical segmentation, generic pre-configured models may not meet the specific requirements for targeted areas in liver ultrasound. Quantitative ultrasound (QUS) is emerging as a promising tool for liver fat measurement; however, accurately segmenting regions of interest within liver ultrasound images remains a challenge.

LI-RADS Ultrasound Surveillance Version 2024: Comparison With Version 2017 for Hepatocellular Carcinoma Detection and Risk Factors for Visualization Score C.

The LI-RADS Ultrasound Surveillance algorithm was updated in 2024, incorporating alpha-fetoprotein (AFP) and visualization score of VIS-C into management recommendations after nonpositive results. This study aimed to compare the diagnostic performance of LI-RADS Ultrasound Surveillance version 2017 (v2017) and version 2024 (v2024) for hepatocellular carcinoma (HCC) detection in at-risk patients and to identify predictors of VIS-C on follow-up surveillance examinations. This retrospective analysis included 407 patients (median age, 56 years; 230 male, 177 female) with cirrhosis who underwent rounds of semi-annual surveillance ultrasound as part of a prospective trial from November 2011 to December 2012.

Head-to-Head Comparison Between Phosphatidylethanol Versus Indirect Alcohol Biomarkers for Diagnosis of MetALD Versus MASLD: A Prospective Study.

Background: The current subclassification of steatotic liver disease (SLD) relies on validated questionnaires, such as Alcohol Use Disorders Identification Test (AUDIT) and Lifetime Drinking History (LDH), which, while useful, are impractical and lack precision for their use in routine clinical practice. Phosphatidylethanol (PEth) is a quantitative, objective alcohol biomarker with high sensitivity and specificity.

Aims: To assess the diagnostic accuracy of PEth for differentiating metabolic dysfunction and alcohol-associated liver disease (MetALD) from metabolic dysfunction-associated steatotic liver disease (MASLD) in a large, population-based, prospective, multiethnic cohort of individuals with overweight or obesity.

Do Risk Factors for HCC Impact the Association of CT/MRI LIRADS Major Features With HCC? An Individual Participant Data Meta-Analysis.

Guidelines suggest the Liver Imaging Reporting and Data System (LI-RADS) may not be applicable for some populations at risk for hepatocellular carcinoma (HCC). However, data assessing the association of HCC risk factors with LI-RADS major features are lacking. To evaluate whether the association between HCC risk factors and each CT/MRI LI-RADS major feature differs among individuals at-risk for HCC.

Common pitfalls and diagnostic challenges in the application of LI-RADS CT/MRI algorithms: a comprehensive review.

The Liver Imaging Reporting and Data System (LI-RADS) was developed to standardize the interpretation and reporting of liver observations in at-risk populations, aiding in the diagnosis of hepatocellular carcinoma (HCC). Despite its advantages, the application of LI-RADS can be challenging due to the complexity of liver pathology and imaging interpretation. This comprehensive review highlights common pitfalls encountered in LI-RADS application and offers practical strategies to enhance diagnostic accuracy and consistency among radiologists.