Comparison of the Effectiveness of Shear Wave Elastography and Superb Microvascular Imaging in the Evaluation of Breast Masses

Ultrasonographic Assessment of Tissue Stiffness: Recent Progress in Transient Elastography and Shear Wave Elastography in the Liver and Various Organs

Ultrasonography is a noninvasive and widely accessible modality in clinical practice. Recently, ultrasonography has been used to evaluate tissue stiffness; the two representative techniques are transient elastography (FibroScan®) and shear wave elastography. These modalities are now generally used for the assessment of liver fibrosis, the prediction of hepatocarcinogenesis, and determining prognosis. In addition, shear wave elastography is available, not only for the liver but also for various other organs, including the breast and brain. In the breast and brain, shear wave elastography distinguishes malignant lesions from benign ones. Moreover, shear wave elastography can be useful for differentiating between ischemic and hemorrhagic strokes. This review summarizes the recent progress in transient elastography and shear wave elastography of the liver and introduces the advantages of ultrasonographic assessment of tissue stiffness in various organs, including the breast, brain, kidney, heart, thyroid, pancreas, muscle, and bone.

Using a combination of superb microvascular imaging and other auxiliary ultrasound techniques to increase the accuracy of gray-scale ultrasound for breast masses

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.

A ultrasonic nomogram of quantitative parameters for diagnosing breast cancer

This study aimed to develop a nomogram through the collection of quantitative ultrasound parameters to predict breast cancer. From March 2021 to September 2022, a total of 313 breast tumors were included with pathological results. Through collecting quantitative ultrasound parameters of breast tumors and multivariate regression analysis, a nomogram was developed. The diagnostic performances, calibration and clinical usefulness of the nomogram for predicting breast cancer were assessed. A total of 182 benign and 131 malignant breast tumors were included in this study. The nomogram indicated excellent predictive properties with an AUC of 0.934, sensitivity of 0.881, specificity of 0.848, PPV of 0.795 and NPV of 0.841. The calibration curve showed the predicted values are basically consistent with the actual observed values. The optimum cut-off for the nomogram was 0.310 for predicting cancer. The decision curve analysis results corroborated good clinical usefulness. The model including BI-RADS score, SWE and VI is potentially useful for predicting breast cancer.

Superb Microvascular Imaging for the Differentiation of Benign and Malignant Breast Lesions: A System Review and Meta-Analysis

OBJECTIVE

To evaluate the diagnostic performance of SMI in the diagnosis of benign and malignant breast lesions.

METHODS

A systematic search of PubMed, EMBASE, Cochrane, OVID, SCI, and SCOPUS was performed to find relevant studies which applied SMI to differentiate benign and malignant breast lesions. All the studies were published before October 10, 2022. Only studies published in English were collected. Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) tool was applied to assess the quality of the included studies. Summary receiver operating characteristic (SROC) modeling was also performed to the diagnostic performance of SMI in the diagnosis of benign and malignant breast lesions. Subgroup analyses and meta-regression were performed to find out the heterogeneity.

RESULTS

Twenty studies which include a total of 2873 lesions (1748 benign and 1125 malignant) in 2740 patients were evaluated in this meta-analysis. The summary sensitivity and specificity were 0.82 (95% confidence interval [CI]: 0.76-0.86), 0.70 (95% CI: 0.64-0.76) for SMI vascular degree, 0.77 (95% CI: 0.67-0.84), 0.79 (95% CI: 0.75-0.83) for SMI vascular distribution, 0.78 (95% CI: 0.70-0.84), 0.75 (95% CI: 0.69-0.80) for SMI vascular morphology, 0.81 (95% CI: 0.72-0.87), 0.80 (95% CI: 0.75-0.85) SMI penetration vessel. For SMI overall vascular features, the summary sensitivity and summary specificity were 0.74 (95% CI: 0.61-0.84) and 0.80 (95% CI: 0.76-0.84). The result of subgroup analysis and meta-analysis showed malignant rate and country might be the cause of heterogeneity of diagnostic accuracy of vascular grade and morphology.

CONCLUSION

SMI vascular features have high sensitivity and specificity in the differentiation of benign and malignant lesions. Future international multicenter studies in various regions with large sample size are required to confirm these findings.

Quantitative analysis of superb microvascular imaging for monitoring tumor response to chemoradiotherapy in locally advanced cervical cancer

Objectives

As an ultrasound (US) image processing method, superb microvascular imaging (SMI) extracts and visualizes flow signals from vessels through advanced clutter suppression technology. We investigated the feasibility of SMI in monitoring treatment response in patients with locally advanced cervical cancer (LACC) undergoing chemoradiotherapy (CRT).

Methods

Forty-nine patients underwent CRT and received SMI examination at 3 time points: before therapy (baseline), 3 weeks during, and 1 month after CRT. The maximum tumor diameter (Dmax), vascularity index (VI), and their percentage changes (ΔDmax and ΔVI) were calculated. ΔDmax was compared with MRI results as the reference standard.

Results

Based on the MRI findings, 44 were classified as complete response (CR) group and 5 as partial response (PR) group. The Dmax and ΔDmax showed decrease in CR and PR groups at 3 weeks during CRT (P< 0.05), but no significant difference between the two groups (P > 0.05). Compared to the baseline, significant decrease in VI and ΔVI were observed at during and after treatment in the two groups (P< 0.05). Moreover, there were significant differences in VI and ΔVI at 3 weeks during CRT between the CR and PR groups (P< 0.05). ΔVI at 3 weeks during CRT showed a better predictive performance for responder prognosis than VI (AUC = 0.964, AUC = 0.950, respectively, P = 0.001), with a cut-off value of 41.6% yielding 100% sensitivity and 86.4% specificity.

Conclusions

The SMI parameters (VI and ΔVI) have potential for monitoring treatment response in LACC.

Association Between Vascular Index Measured via Superb Microvascular Imaging and Molecular Subtype of Breast Cancer

Background

To determine whether vascular index (VI; defined as the ratio of Doppler signal pixels to pixels in the total lesion) measured via superb microvascular imaging in breast cancer correlates with immunohistochemically defined subtype and is able to predict molecular subtypes.

Methods

This prospective study involved 225 patients with 225 mass-type invasive breast cancers (mean size 2.6 ± 1.4 cm, range 0.4~5.9 cm) who underwent ultrasound and superb microvascular imaging (SMI) at Peking Union Medical College Hospital before breast surgery from December 2016 to June 2018. The correlations between primary tumor VI measured via SMI, clinicopathological findings, and molecular subtype were analyzed. The performance of VI for prediction of molecular subtypes in invasive breast cancer was investigated.

Results

The median VI of the 225 tumors was 7.3% (4.2%~11.8%) (range 0%~54.4%). Among the subtypes of the 225 tumors, 41 (18.2%) were luminal A, 91 (40.4%) were luminal B human epidermal growth factor receptor-2 (HER-2)-negative, 26 (11.6%) were luminal B HER-2-positive, 17 (7.6%) were HER-2-positive, and 50 (22.2%) were triple-negative, and the corresponding median VI values were 5.9% (2.6%~11.6%) (range 0%~47.1%), 7.3 (4.4%~10.5%) (range 0%~29.5%), 6.3% (3.9%~11.3%) (range 0.6%~22.2%), 8.2% (4.9%~15.6%) (range 0.9%~54.4%), and 9.2% (5.1%~15.3%) (range 0.7%~32.9%), respectively. Estrogen receptor (ER) negativity, higher tumor grade, and higher Ki-67 index (≥20%) were significantly associated with a higher VI value. Tumor size, ER status, and Ki-67 index were shown to independently influence VI. A cutoff value of 4.1% yielded 79.9% sensitivity and 41.5% specificity with an area under the receiver operating characteristic curve (AUC) of 0.58 for predicting that a tumor was of the luminal A subtype. A cutoff value of 16.4% yielded 30.0% sensitivity and 90.3% specificity with an AUC of 0.60 for predicting a triple-negative subtype.

Conclusions

VI, as a quantitative index obtained by SMI examination, could reflect histologic vascular changes in invasive breast cancer and was found to be higher in more biologically aggressive breast tumors. VI shows a certain degree of correlation with the molecular subtype of invasive breast cancer and plays a limited role in predicting the luminal A with high sensitivity and triple-negative subtype with high specificity.

Shear Wave Elastography-Assisted Ultrasound Breast Image Analysis and Identification of Abnormal Data

In this paper, shear wave elastography was used to study and analyze the images of the breast in-depth and identify the abnormal image data. Sixty breast lesions were evaluated, and quantitative metrics were reproducible in the static and dynamic modes of shear wave elastography with a higher interobserver agreement in dynamic qualitative metrics than in the static mode. There were no statistically significant differences between the two modes of imaging in quantitative metrics, and quantitative metrics were more effective than qualitative metrics. Postoperative immunohistochemical expression of ER, PR, HER-2, Ki-67, molecular typing, pathological type, histological grading, and axillary lymph node status of breast cancer was obtained based on pathological results. The correlation between mass size, patient age, and WiMAX values of breast cancer masses was analyzed using Pearson correlation, and the differences in SWVmax values of breast cancer masses between different expressions of immunohistochemical parameters ER, PR, HER-2, Ki-67, and axillary lymph node status were compared using tests. The variables with correlations and differences were included in the multiple linear regression analysis to assess the factors influencing the SWVmax values. The performance of TDPM, SPM, and TSPM was compared using PVA body models with different freeze-thaw cycles. The results showed that TSPM performed better than SPM in general, and TDPM showed excellent performance because of high temporal resolution and low random error, especially when the number of freeze-thaw cycles increased and the hardness of the PVA body mold increased. Measurements at different depths of inhomogeneous body models also showed that the TDPM method was less affected by depth, and the results were more stable. Finally, the reliability of the shear wave velocity (SWS) measured by the TDPM and SPM methods was investigated using porcine ligament tissue, and the results showed that the mean values of SWS goodness of fit for TDPM and SPM were 0.94 and 0.87, respectively, and the estimated elastic modulus of TDPM was very close to the mechanical test results.