Abstract

Posterior acoustic shadowing is a key diagnostic feature in ultrasound imaging of calcified lesions, such as gallbladder and kidney stones. However, conventional assessment relies primarily on qualitative interpretation, and its underlying structural characteristics remain insufficiently quantified. This study aimed to quantitatively characterize posterior acoustic shadows using wavelet-based texture analysis and to investigate their diagnostic relevance across different expert-defined shadow confidence groups. Ultrasound B-mode images were analyzed from gallbladder stone and kidney stone datasets. Regions of interest (ROIs) were extracted from gallbladder and kidney stone images across three shadow confidence levels (50–60%, 60–80%, and >80%), and multi-scale wavelet features were computed. The results demonstrated a substantial reduction in high-frequency components with increasing attenuation. Total detail energy decreased by approximately 80% in the gallbladder group and 55–60% in the kidney group from low to high shadow confidence levels. Similarly, normalized ratios (Edetail/approx and Edetail/total showed consistent decreases, with inter-group differences of approximately 2.3–2.5-fold at 50–60%, which converged to negligible levels (<2.4% difference) at >80%. These findings suggest that wavelet-based energy distributions may provide acoustically interpretable quantitative descriptors of posterior shadow formation in ultrasound stone imaging.

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