Strain-compounding technique with ultrasound Nakagami imaging for distinguishing between benign and malignant breast tumors

Authors


Abstract

Purpose

: The scatterer properties of breast tissues are related to the presence of collagen structures, while the elasticity properties of breast tissues depend on their structural organization; these two characteristics are functionally complementary in ultrasound-based tissue characterizations. This study investigated the use of a strain-compounding technique with Nakagami imaging to provide information associated with the scatterer and elasticity characteristics of tissues when attempting to identify benign and malignant breast tumors.

Methods

: The efficacy of the proposed method was tested by collecting raw data of ultrasound backscattered signals from 50 clinical cases (25 benign tumors and 25 malignant tumors, as verified by histology biopsies). The different strain conditions were created by applying manual compression. For each region in which breast tumors were suspected, estimates of the full width at half maximum (FWHM) from the Gaussian fitting curve for the Nakagami-parameter histogram in the strain-compounding Nakagami images were divided by those of the corresponding reference Nakagami images (uncompressed images); this parameter was denoted as the FWHM ratio. Receiver operating characteristic (ROC) curve analysis was adopted to assess the diagnostic performance.

Results

: The results demonstrated that the difference in scatterer distributions between before and after compounding was greater for benign tumors than for malignant tumors. The FWHM ratio estimates for benign and malignant tumors were 0.76 ± 0.14 and 0.96 ± 0.06 (mean ± standard deviation), respectively (p < 0.01). The mean area under the ROC curve using the FWHM ratio estimates was 0.92, with a 95% confidence interval of 0.83–1.00.

Conclusions

: These findings indicate that the strain-compounding Nakagami imaging method based on the acquisition of multiple frames under different strain states could provide objective information that would improve the ability to classify benign and malignant breast tumors.

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