Imaging Evaluation for Steatotic Liver Disease

Area of Science:

• Hepatology
• Radiology
• Medical Imaging

Background:

• Metabolic dysfunction-associated steatotic liver disease (MASLD), formerly nonalcoholic fatty liver disease, is a rapidly growing global health concern, impacting roughly 30% of the world's population.
• Hepatic steatosis (fatty liver) is the hallmark of MASLD, while liver fibrosis progression is critical for determining patient outcomes.
• Noninvasive imaging plays a crucial role in the detection, quantification, and monitoring of both hepatic steatosis and fibrosis.

Purpose of the Study:

• To review the principles, clinical applications, effectiveness, and recent advancements in imaging modalities for noninvasively assessing hepatic steatosis and fibrosis in MASLD.
• To explore emerging diagnostic strategies for MASLD, including artificial intelligence, opportunistic screening, standardized guidelines, and therapeutic interventions.
• To emphasize the significant role of radiologists in the evolving field of MASLD diagnosis and management.

Main Methods:

• Comprehensive review of current literature on imaging techniques for MASLD.
• Focus on ultrasound, computed tomography (CT), and magnetic resonance imaging (MRI) for assessing liver fat and fibrosis.
• Exploration of machine learning, opportunistic screening, and guideline development in MASLD diagnosis.

Main Results:

• Ultrasound, CT, and MRI are established modalities for evaluating hepatic steatosis and fibrosis in MASLD.
• Advancements in imaging technology are improving accuracy and noninvasive assessment capabilities.
• Emerging approaches like machine learning show promise for enhanced diagnostic accuracy and early detection.

Conclusions:

• Imaging is indispensable for managing MASLD, from initial detection to monitoring disease progression and treatment response.
• Radiologists are central to advancing MASLD diagnostics through the application and development of innovative imaging techniques.
• The integration of new technologies and standardized approaches will likely transform MASLD care and improve patient outcomes.