The Vascular Index of Superb Microvascular Imaging Can Improve the Diagnostic Accuracy for Breast Imaging Reporting and Data System Category 4 Breast Lesions

Evaluation of nipple vascularity using superb microvascular imaging in patients with reduction mammoplasty

We aimed to investigate the effect of the chosen pedicle on nipple vascularity by evaluating changes in the microvascular circulation of the nipples in patients undergoing reduction mammoplasty through superb microvascular imaging study (SMI). 70 nipples were included in this retrospective study. There were 15 patients (30 nipples) in Group A using the inferior pedicle and 20 patients (40 nipples) in Group B using the superomedial pedicle. The vascular index (VI) of each nipple were evaluated preoperatively and at the third postoperative month using SMI. The mean VI in Group A was 1.25 (0.5-3.6) preoperatively and 1.3 (0.4-3.2) at the third postoperative month (P > .05). The mean VI in Group B was 1.65 (0.7/2.9) preoperatively and 1.15 (0.2/1.9) at the third postoperative month (P < .05). While the VI increased by 11.3% in Group A, it decreased by 30.6% in Group B (P < .001). The changing of the VI was analyzed between comparable groups, and decreasing microvascular circulation of the nipple with use of the superomedial pedicle was detected by quantitative values, which can be useful in at-risk patient groups, the planning of surgical procedures, and early revisions at postoperative month 3.

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.

Translating new breast ultrasound techniques into clinical practice: evaluating their intended uses and describing other unexpected uses for them

Several new ultrasound tools have been developed to further evaluate breast lesions detected on B-mode ultrasound. Strain elastography (SRE) was developed to assess the likelihood of malignancy of lesions based on their stiffness. This has been incorporated into the latest edition of the American College of Radiology (ACR) Breast Imaging Reporting and Data System (BI-RADS) lexicon and atlas. However, no agreed cut-off stiffness values have been established to distinguish benign from malignant lesions making the translation into routine clinical practice difficult. Superb microvascular imaging (SMI) was developed to better evaluate the vascularity within sonographic lesions and assess their likelihood of malignancy. However, there is also no agreed cut-off value for vascular index (VI) to distinguish between benign and malignant lesions. MicroPure was developed to better visualize and evaluate calcifications seen on ultrasound. Its effective use in breast screening and evaluating the calcifications detected for likelihood of malignancy have not been established. This article describes the original intended uses of these applications and reviews the studies evaluating them, showing the varying success of the translation of these tools into routine clinical practice. Also described are some other uses of these tools for which they were not originally intended. This illustrates the importance of being perceptive to alternative uses of imaging tools in their translation from bench to bedside.

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.

Recent Advances in Ultrasound Breast Imaging: From Industry to Clinical Practice

Breast ultrasound (US) has undergone dramatic technological improvement through recent decades, moving from a low spatial resolution, grayscale-limited technique to a highly performing, multiparametric modality. In this review, we first focus on the spectrum of technical tools that have become commercially available, including new microvasculature imaging modalities, high-frequency transducers, extended field-of-view scanning, elastography, contrast-enhanced US, MicroPure, 3D US, automated US, S-Detect, nomograms, images fusion, and virtual navigation. In the subsequent section, we discuss the broadened current application of US in breast clinical scenarios, distinguishing among primary US, complementary US, and second-look US. Finally, we mention the still ongoing limitations and the challenging aspects of breast US.

Prospective analysis of breast masses using the combined score for quantitative ultrasonography parameters

To investigate the diagnostic value of combined SWE, SMI, and B-mode US scores for distinguishing between benign and malignant masses. A total of 450 breast masses that underwent US-guided core needle biopsies were prospectively enrolled. The breast masses were assessed based on the BI-RADS and quantitative SWE and SMI parameters. The SWEmax, SWEratio, and SMI_VI cutoff value were determined using Youden’s index by comparison to the pathological results. The BI-RADS categories were scored on a scale from 1 to 5, and SWEmax, SWEratio, and SMI_VI were dichotomized based on each cutoff values (0 or 1). The combined scores (1 to 8) were calculated as the sum of the BI-RADS score and the quantitative scores and compared to the pathologic results using AUROC analysis. The cutoff values were 52.25 kPa for SWEmax, 5.03 for SWEratio, and 2.15% for SMI_VI. In AUROC, the combined scores showed significantly better diagnostic performance compared to BI-RADS alone (p < 0.001). The combined score showed significantly increased than BI-RADS alone in specificity (p < 0.001) and accuracy (p < 0.001), but a sensitivity decreased without significance (p = 0.082). When a combined score cutoff value of 4 was used, the false negative rate was 2.7%. Using the combined score, 76.4% of the C4a lesions were considered benign also pathologically diagnosed as benign. The combined scores showed improved diagnostic performance in differentiating between benign and malignant breast masses, which could be helpful for determining a breast biopsy eligibility.

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.

An Improved Nomogram to Reduce False-Positive Biopsy Rates of Breast Imaging Reporting and Data System Ultrasonography Category 4A Lesions

BACKGROUND

The NCCN clinical guidelines recommended core needle biopsy for breast lesions classified as Breast Imaging Reporting and Data System (BI-RADS) 4, while category 4A lesions are only 2-10% likely to be malignant. Thus, a large number of biopsies of BI-RADS 4A lesions were ultimately determined to be benign, and those unnecessary biopsies may incur additional costs and pains. However, it is important to emphasize that the current risk prediction model focuses primarily on the details and complex risk features of US or MG findings, which may be difficult to apply in order to benefit from the model. To stratify and manage BI-RADS 4A lesions effectively and efficiently, a more effective and practical predictive model must be developed.

METHODS

We retrospectively analyzed 465 patients with BI-RADS ultrasonography (US) category 4A lesions, diagnosed between January 2019 and July 2019 in Tianjin Medical University Cancer Institute and Hospital and National Clinical Research Center for Cancer. Univariate and multivariate logistic regression analyses were conducted to identify risk factors. To stratify and predict the malignancy of BI-RADS 4A lesions, a nomogram combining the risk factors was constructed based on the multivariate logistic regression results. In order to determine the predictive performance of our predictive model, we used the concordance index (C-index), calibration curve, and receiver operating characteristic (ROC), and the decision curve analysis (DCA) to assess the clinical benefits.

RESULTS

Based on our analysis, 16.3% (76 out of 465) of patients were pathologically diagnosed with malignant lesions, while 83.6% (389 out of 465) were diagnosed with benign lesions. According to univariate and multivariate logistic regression analysis, age (OR = 3.414, 95%CI:1.849-6.303), nipple discharge (OR = .326, 95%CI:0.157-.835), palpable lesions (OR = 1.907, 95%CI:1.004-3.621), uncircumscribed margin (US) (OR = 1.732, 95%CI:1.033-2.905), calcification (mammography, MG) (OR = 2.384, 95%CI:1.366-4.161), BI-RADS(MG) (OR = 5.345, 95%CI:2.934-9.736) were incorporated into the predictive nomogram (C-index = .773). There was good agreement between the predicted risk and the observed probability of recurrence. Furthermore, we determined that 153 was the best cutoff score for distinguishing between patients in the low- and high-risk groups. Malignant lesions were significantly more prevalent in high-risk patients than in low-risk patients.

CONCLUSION

Based on clinical, US, and MG features, we present a predictive nomogram to reliably predict the malignancy risk of BI-RADS(US) 4A lesions, which may assist clinicians in the selection of patients at low risk of malignancy and reduce the number of false-positive biopsies.

Role of Superb Microvascular Imaging in Differentiating Between Malignant and Benign Solid Breast Masses

INTRODUCTION

The purpose of this study was to evaluate the diagnostic performance of superb microvascular imaging (SMI) in breast lesions.

MATERIALS AND METHODS

Eighty-five solid breast lesions were studied with color Doppler flow imaging (CDFI), power Doppler imaging (PDI), monochromatic SMI (mSMI), and contrast-enhanced ultrasonography (CEUS). The penetrating vessels (PVs) and microvascular morphologic and distribution features of the breast tumors were evaluated for each modality.

RESULTS

The diagnostic accuracies of CDFI, PDI, mSMI, and CEUS were calculated and compared. Surgical pathologic analysis showed 47 benign and 38 malignant lesions. Compared with CDFI and PDI, mSMI and CEUS detected more PVs in breast lesions. The microvascular architecture showed significant differences between benign and malignant lesions. Benign lesions mainly displayed avascular, line-like, and branch-like patterns, and malignant lesions tended to display root hair-like and crab claw-like patterns. mSMI and CEUS identified more root hair-like and crab claw-like patterns in malignant lesions than CDFI and PDI. The sensitivity, negative predictive value, and accuracy of mSMI findings in diagnosing malignancy based on PVs and vascular patterns were both higher than those of CDFI and PDI.

CONCLUSIONS

mSMI is equal to CEUS and superior to CDFI and PDI in identifying microvascular and discriminating malignant and benign breast masses.