Enhancing Liver Nodule Visibility and Diagnostic Classification Using Ultrasound Local Attenuation Coefficient Slope Imaging

Objective

B-mode ultrasound (US) presents challenges in accurately detecting and distinguishing between benign and malignant liver nodules. This study utilized quantitative US local attenuation coefficient slope (LACS) imaging to address these limitations.

Materials and Methods

This is a prospective, cross-sectional study in adult patients with definable solid liver nodules at US conducted from March 2021 to December 2023. The composite reference standard included histopathology when available or magnetic resonance imaging. LACS images were obtained using a phantom-free method. Nodule visibility was assessed by computing the contrast-to-noise ratio (CNR). Classification accuracy for differentiating benign and malignant lesions was assessed with the area under the receiver operating characteristic curve (AUC), along with sensitivity and specificity.

Results

The study enrolled 97 patients (age: 62 y ± 13 [standard deviation]), with 57.0% malignant and 43.0% benign observations (size: 26.3 ± 18.9 mm). LACS images demonstrated higher CNR (12.3 dB) compared to B-mode (p < 0.0001). The AUC for differentiating nodules and liver parenchyma was 0.85 (95% confidence interval [CI]: 0.79–0.90), with higher values for malignant (0.93, CI: 0.88–0.97) than benign nodules (0.76, CI: 0.66–0.87). A LACS threshold of 0.94 dB/cm/MHz provided a sensitivity of 0.83 (CI: 0.74–0.89) and a specificity of 0.82 (CI: 0.73–0.88). LACS mean values were higher (p < 0.0001) in malignant (1.28 ± 0.27 dB/cm/MHz) than benign nodules (0.98 ± 0.19 dB/cm/MHz).

Conclusion

LACS imaging improves nodule visibility and provides better differentiation between benign and malignant liver nodules, showing promise as a diagnostic tool.