Microstructural breast tissue characterization: A head-to-head comparison of Diffusion Weighted Imaging and Acoustic Radiation Force Impulse elastography with clinical implications

Comparing the Diagnostic Performance of Ultrasound Elastography and Magnetic Resonance Imaging to Differentiate Benign and Malignant Breast Lesions: A Systematic Review and Meta-analysis

OBJECTIVE

The purpose of this systematic review and meta-analysis was comparing diagnostic performance of ultrasound elastography (UE), strain UE and shear wave elastography (SWE), with magnetic resonance imaging (MRI) in differentiating benign and malignant breast lesions.

METHODS

Literature search of MEDLINE, Web of Science, SCOPUS and Google Scholar was performed in June 2023. Included studies used Breast Imaging Reporting and Data System (BI-RADS) and histopathology as reference standard. A bivariate random-effects model was used to calculate sensitivity, specificity, diagnostic odds ratio (DOR), positive and negative likelihood ratios and area under the curve (AUC). Meta-regression subgroup analysis was performed.

RESULTS

Nine studies and 536 lesions were included. Pooled sensitivity was not different between MRI vs UE [MRI: 94% (95% CI: 88.2%-96.9%) vs UE: 90% (95% CI: 84.7%-93.1%); P=0.153] but a difference was found for specificity [UE: 78% (95% CI: 66.3%-86.4%) vs MRI: 71.3% (95% CI: 52.1%-85%); P=0.0065]. Strain UE showed higher specificity and similar sensitivity to SWE [strain UE: 0.85 (95% CI: 0.71-0.93) vs SWE: 0.72 (95% 0.58-0.83); P=0.017 and strain UE: 0.87 (95% CI 0.79-0.93) vs SWE: 0.91 (95% CI 0.85-0.95); P=0.311, respectively]. AUC was similar between MRI vs UE [0.91 (95% CI 0.87-0.95) vs 0.92 (95% CI 0.88-0.95); P=0.452, respectively] as was DOR [MRI: 38.083 (95% CI: 12.401-116.957) vs UE: 30.395 (95% CI: 16.572-55.75); P>0.05]. Meta-regression analysis found no significant differences in the diagnostic accuracy between MRI, strain UE and SWE.

CONCLUSION

Our results show that UE when compared to MRI has adequate performance in differentiating benign and malignant breast lesions.

Correlation of Shear-Wave Elastography and Apparent Diffusion Coefficient Values in Breast Cancer and Their Relationship with the Prognostic Factors

Background: Diffusion-weighted imaging and elastography are widely accepted methods in the evaluation of breast masses, however, there is very limited data comparing the two methods. The apparent diffusion coefficient is a measure of the diffusion of water molecules obtained by diffusion-weighted imaging as a part of breast MRI. Breast elastography is an adjunct to conventional ultrasonography, which provides a noninvasive evaluation of the stiffness of the lesion. Theoretically, increased tissue density and stiffness are related to each other. The purpose of this study is to compare MRI ADC values of the breast masses with quantitative elastography based on ultrasound shear wave measurements and to investigate their possible relation with the prognostic factors and molecular subtypes. Methods: We retrospectively evaluated histopathologically proven 147 breast lesions. The molecular classification of malignant lesions was made according to the prognostic factors. Shear wave elastography was measured in kiloPascal (kPa) units which is a quantitative measure of tissue stiffness. DWI was obtained using a 1.5-T MRI system. Results: ADC values were strongly inversely correlated with elasticity (r = −0.662, p < 0.01) according to Pearson Correlation. In our study, the cut-off value of ADC was 1.00 × 10−3 cm2/s to achieve a sensitivity of 84.6% and specificity of 75.4%, and the cut-off value of elasticity was 105.5 kPa to achieve the sensitivity of 96.3% and specificity 76.9% to discriminate between the malignant and benign breast lesions. The status of prognostic factors was not correlated with the ADC values and elasticity. Conclusions: Elasticity and ADC values are correlated. Both cannot predict the status of prognostic factors and differentiate between molecular subtypes.

Color-map virtual touch tissue imaging (CMV) combined with BI-RADS for the diagnosis of breast lesions

OBJECTIVE

To investigate the importance of color-map virtual touch tissue imaging (CMV) in assisting Breast Imaging Reporting and Data Systems (BI-RADS) in diagnosing malignant breast lesions.

METHODS

A dataset included 134 patients and 146 breast lesions was assembled. All patients underwent biopsy or surgical excision of breast lesions, and pathological results were obtained. All patients with breast lesions also underwent conventional ultrasound (US) and CMV. Each lesion was assigned a CMV score based on the color pattern of the lesion and surrounding breast tissue and a BI-RADS classification rating based on US characteristics. We compared the diagnostic performance of using BI-RADS and CMV separately and their combination.

RESULTS

BI-RADS (odds ratio [OR]: 3.665; 95% confidence interval [CI]: 2.147, 6.258) and CMV (OR: 6.616; 95% CI: 2.272, 19.270) were independent predictors of breast malignancy (all P < 0.05). The area under the receiver operating characteristic curves (AUC) for either CMV or BI-RADS alone was inferior to that of the combination (0.877 vs. 0.962; 0.938 vs. 0.962; all P < 0.05).

CONCLUSIONS

The performance of BI-RADS in diagnosing breast lesions is significantly improved by combining CMV. Therefore, we recommend CMV as an adjunct to BI-RADS.