BMC Cancer (Feb 2024)
Using a combination of superb microvascular imaging and other auxiliary ultrasound techniques to increase the accuracy of gray-scale ultrasound for breast masses
Abstract
Abstract Background Breast ultrasound is highly sensitive, but its specificity is not as high for detecting malignant lesions. Auxiliary modalities like elastography, Color and Power Doppler ultrasound are used as adjuncts to yield both a high sensitivity and specificity. Superb microvascular imaging (SMI) is a newer modality with more accuracy for detecting breast lesions. In this study, our goal was to investigate the role of SMI as an adjunct to ultrasound and find a suitable combination model for the evaluation of breast masses. Methods In this cross-sectional study, 132 women with 172 breast masses who underwent ultrasound-guided biopsy were included.. The ultrasound features of the lesion, the strain ratio in strain elastography, the number of vessels for each lesion, their morphology and distribution in Doppler and Power Doppler ultrasound and SMI were recorded for each lesion. A vascular score and a vascular ratio were defined. Results In the histologic examination, 31 lesions (18%) were malignant and 141 lesions (82%) were benign. The vascular score was more accurate than the vascular ratio in all three modalities. The predictive ability of strain ratio was higher than Doppler and Power Doppler ultrasound and SMI. Adding SMI alone to ultrasound increased the specificity from 46.10% to 61.2% and the accuracy from 55.80% to 70.11%. In the combination of ultrasound with other modalities, the best was the combination of ultrasound, strain elastography, and SMI; which yielded a specificity and sensitivity of 100% and 74.4%, respectively. Conclusion Adding SMI and STE modalities as adjuncts to ultrasound lowers the chance of missing malignant lesions and reduces unnecessary biopsies of breast lesions. A study with a larger sample size using this combination model to evaluate the accuracy with greater precision is recommended.
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