Determinants of ultrasound visualization quality in hepatocellular carcinoma surveillance: implications for clinical
Carolina Broco Fernández1, Sandra Borrego Rivas2, Víctor Blázquez Ávila2
1Gastrenterology, Complejo Asistencial Universitario de León, España.
Background:
Semiannual ultrasound is the recommended technique for hepatocellular carcinoma surveillance in patients with chronic liver disease. The aim of this study was to analyze the factors associated with ultrasound quality in routine clinical practice.
Methods:
A prospective cross-sectional study was conducted in patients enrolled in a surveillance program. Demographic variables, etiology, body mass index (BMI), and waist circumference were collected. Technical limitations were recorded, and ultrasound assessment of abdominal fat distribution was performed. Quality was classified according to US LI-RADS.
Results:
240 patients were included (70.4% male; mean age 65 years). Mean BMI was 28.9 kg/m² (SD 4.9). Obesity was present in 23.4% and abnormal waist circumference in 56.3%. The main etiologies were alcohol-related liver disease (42.1%) and metabolic dysfunction-associated steatotic liver disease (19.6%). Ultrasound quality was classified as VIS A in 42.9%, VIS B in 48.3%, and VIS C in 8.8%. Meteorism was the most frequent limiting factor (51.7%). Higher BMI and waist circumference were associated with progressively poorer visualization (p<0.001). Preperitoneal visceral fat thickness differed significantly across VIS categories (p<0.001), whereas subcutaneous fat thickness did not show significant overall differences (p=0.052). In multivariable analysis, waist circumference was the only independent predictor of impaired visualization (OR 1.074 per 1-cm increase, 95% CI 1.047-1.103; p < 0.001).
Conclusions:
More than half of ultrasound examinations showed moderate or severe visualization limitations, mainly associated with measures of central adiposity. Incorporating simple anthropometric measures, particularly waist circumference, may help identify patients at risk of suboptimal visualization and support a more individualized surveillance strategy.
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