Differentiation of benign and malignant breast lesions by ultrasound localization microscopy.

OBJECTIVE

We investigated the role of ultrasound localization microscopy (ULM) qualitative and quantitative parameters in distinguishing benign from malignant breast lesions.

METHODS

The ULM qualitative and quantitative parameters of breast lesions were recorded. A receiver operating characteristic (ROC) curve was applied to assess the diagnostic performance of ULM. Intra- and inter-operator reliabilities of quantitative parameters were assessed.

RESULTS

Thirty-one breast lesions were verified by pathologic results, 14 of which were benign and 17 were malignant. Benign lesions were associated with dot-like, line-like, or branch-like patterns (93% vs 6%), whereas malignant lesions were associated with chaotic patterns (94% vs 7%) (p < 0.001). The microvasculature morphology had an area under the curve (AUC) of 0.935, a sensitivity of 94.1%, and a specificity of 92.9%. The microvasculature density, mean diameter, largest diameter, and max tortuosity of malignant lesions were significantly greater than those of benign lesions (p < 0.05, p < 0.001, p < 0.001, p < 0.05). The microvasculature mean flow velocity of benign lesions was significantly greater than that of malignant lesions (p < 0.05). For the quantitative parameters, the AUC was highest for the microvasculature's largest diameter (0.962), with a sensitivity of 88.2% and a specificity of 92.9%. The intra- and inter-operator reliabilities of quantitative parameters were excellent (ICC greater than 0.90).

CONCLUSIONS

ULM is useful for distinguishing benign from malignant breast lesions. ULM can offer a new diagnostic method for breast lesions, which deserves further research.

CRITICAL RELEVANCE STATEMENT

This study suggests that ULM is a new technology with super-resolution that is helpful for distinguishing benign from malignant breast lesions.

TRIAL REGISTRATION

ChiCTR, ChiCTR2100048361. Registered 6 July 2021, https://www.chictr.org.cn/ .

KEY POINTS

ULM is an emerging technology that can detect highly detailed networks of microvasculature. Microvasculature morphology based on ULM can be a good indicator for the differential diagnosis of breast lesions. Among quantitative parameters extracted from ULM, microvasculature largest diameter was the best for the classification of breast lesions.