Hepatorenal Index and Attenuation Imaging: Are They Friends or Foes in Assessing MASLD?

Background Ultrasound attenuation imaging (ATI) is increasingly used to evaluate liver tissue and diagnose conditions such as metabolic dysfunction-associated steatotic liver disease (MASLD). MASLD, previously known as non-alcoholic fatty liver disease (NAFLD), is a leading cause of chronic liver disease globally. While the hepatorenal index (HRI) is commonly used, it has limitations, including operator variability. This study evaluates the diagnostic potential of ATI compared to HRI, with a focus on the impact of measurement depth and region-of-interest (ROI) size.

Methods This prospective single-institution study included 33 healthy volunteers (19 females, 14 males, aged 24.5-63.3 years). Ultrasound images were acquired using a TUS-AI800 scanner with a convex probe. Measurements were taken at depths of 2-5 cm below the liver capsule, using both small and large ROIs. The hepatorenal index was also measured for comparison. Statistical analysis included unpaired t-tests and linear regression, with a significance threshold of p<0.05.

Results Attenuation coefficient values decreased with increasing depth, at a rate of 0.05 dB/cm/MHz. Both small and large ROIs showed significant depth-related differences. Correlation between ATI and HRI was weak, with R² values of 0.18 and 0.24 for the two operators. Subcutaneous fat had a statistically significant but weak correlation with HRI values, accounting for only 2.5% of the variability. Similarly, subcutaneous fat explained 7.3% and 8.9% of variability in ATI measurements for the two operators.

Conclusion ATI offers a promising non-invasive alternative for assessing liver steatosis, with depth and ROI size significantly impacting measurements. However, the weak correlation with HRI and the influence of subcutaneous fat highlight the need for standardised protocols and further research. These findings support the potential of ATI in clinical diagnostics, emphasising the importance of addressing variability factors to improve reliability.

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Artikel online veröffentlicht:
16. Oktober 2025