Detecting Portal Venous Blood Flow in Metabolic Dysfunction-Associated Fatty Liver Disease Using Non-Invasive Doppler...

Area of Science:

• Hepatology
• Medical Imaging
• Cardiovascular Physiology

Background:

• Metabolic dysfunction-associated fatty liver disease (MAFLD) is a prevalent condition linked to metabolic syndrome and insulin resistance.
• MAFLD can alter portal venous blood flow and pressure before cirrhosis development, necessitating accurate measurement for early detection of portal hypertension and fibrosis risk.
• Evaluating non-invasive techniques for portal venous blood flow assessment is crucial for clinical applications.

Purpose of the Study:

• To compare non-invasive transcutaneous Doppler ultrasound with invasive direct techniques for measuring portal venous blood flow in a rat model of MAFLD.
• To assess the ability of Doppler ultrasound to detect changes in portal venous blood flow between fed and fasted states.

Main Methods:

• MAFLD was induced in male Sprague Dawley rats using a high-fat diet (HFD) for 10 weeks.
• Portal venous blood flow was measured non-invasively using transcutaneous Doppler ultrasound and invasively via a direct flow probe.
• Peak portal venous blood flow was compared between fed and fasted states using non-invasive ultrasound.

Main Results:

• Direct measurements revealed significantly higher portal venous blood flow in HFD rats compared to standard chow diet (STD) rats (p<0.05).
• Transcutaneous Doppler ultrasound did not detect significant differences in absolute portal venous blood flow between HFD and STD rats (p=0.74).
• Non-invasive ultrasound successfully identified a significant increase in peak portal venous blood flow in the fed state versus the fasted state (p<0.05).

Conclusions:

• Non-invasive Doppler ultrasound is currently insufficient for detecting absolute portal flow differences in this MAFLD rat model.
• The technique shows promise for monitoring dynamic hemodynamic changes, such as those related to feeding status.
• Further research with larger sample sizes, diverse models, and refined imaging techniques is required for clinical translation.