Incorporating Contrast-Enhanced Ultrasound into the BI-RADS Scoring System Improves Accuracy in Breast Tumor Diagnosis: A Preliminary Study in China

Meta-analysis of contrast-enhanced ultrasound in differential diagnosis of breast adenosis and breast cancer

This systematic review and meta-analysis study aimed to determine the total capacity of contrast-enhanced ultrasound (CEUS) in the differential diagnosis of breast lesions and breast cancer. For collecting papers, four groups of keywords were searched in five databases. The required information was extracted from the selected papers. In addition to the descriptive findings, a meta-analysis was also conducted. Thirty-three of thirty-six studies (91.67%) on the differential diagnosis of various degrees and types of breast lesions showed that CEUS has proper performance. The pooled values related to the sensitivity and specificity of CEUS were computed by 88.00 and 76.17.

The Application Value of Using Semiquantitative and Quantitative Parameters in Multimodal Ultrasound to Distinguish Between Benign and Malignant BI-RADS 4 Lesions

ABSTRACT

This study aims to explore the value of real-time strain elastography (RTE) and contrast-enhanced ultrasonography (CEUS) in the diagnosis of breast BI-RADS 4 lesions. It collected 85 cases (totaling 85 lesions) diagnosed with breast BI-RADS 4 through routine ultrasound from October 2020 to December 2022 in Huangshan City People's Hospital. All lesions underwent RTE and CEUS examination before surgery, and the ImageJ software was used to measure the periphery of lesion images in the enhancement peak mode and grayscale mode to calculate the contrast-enhanced ultrasound area ratio. The diagnostic capabilities of single-modal and multimodal ultrasound examination for the malignancy of breast BI-RADS 4 lesions were compared using the receiver operating characteristic curve; the Spearman correlation analysis was adopted to evaluate the correlation between multimodal ultrasound and CEUS area ratio. As a result, among the 85 lesions, 51 were benign, and 34 were malignant. The areas under the curve (AUCs) of routine ultrasound (US), US + RTE, US + CEUS, and US + RTE + CEUS were 0.816, 0.928, 0.953, and 0.967, respectively, with the combined method showing a higher AUC than the single application. The AUC of the CEUS area ratio diagnosing breast lesions was 0.888. There was a strong positive correlation (r = 0.819, P < 0.001) between the diagnostic performance of US + RTE + CEUS and the CEUS area ratio. In conclusion, based on routine ultrasound, the combination of RTE and CEUS can further improve the differential diagnosis of benign and malignant lesions in breast BI-RADS 4.

Deep learning combined with attention mechanisms to assist radiologists in enhancing breast cancer diagnosis: a study on photoacoustic imaging

Accurate prediction of breast cancer (BC) is essential for effective treatment planning and improving patient outcomes. This study proposes a novel deep learning (DL) approach using photoacoustic (PA) imaging to enhance BC prediction accuracy. We enrolled 334 patients with breast lesions from Shenzhen People's Hospital between January 2022 and January 2024. Our method employs a ResNet50-based model combined with attention mechanisms to analyze photoacoustic ultrasound (PA-US) images. Experiments demonstrated that the PAUS-ResAM50 model achieved superior performance, with an AUC of 0.917 (95% CI: 0.884 -0.951), sensitivity of 0.750, accuracy of 0.854, and specificity of 0.920 in the training set. In the testing set, the model maintained high performance with an AUC of 0.870 (95% CI: 0.778-0.962), sensitivity of 0.786, specificity of 0.872, and accuracy of 0.836. Our model significantly outperformed other models, including PAUS-ResNet50, BMUS-ResAM50, and BMUS-ResNet50, as validated by the DeLong test (p < 0.05 for all comparisons). Additionally, the PAUS-ResAM50 model improved radiologists' diagnostic specificity without reducing sensitivity, highlighting its potential for clinical application. In conclusion, the PAUS-ResAM50 model demonstrates substantial promise for optimizing BC diagnosis and aiding radiologists in early detection of BC.

The Japanese breast cancer society clinical practice guidelines for breast cancer screening and diagnosis, 2022 edition

This article provides updates to readers based on the newly published Japanese Breast Cancer Society Clinical Practice Guidelines for Breast Cancer Screening and Diagnosis, 2022 Edition. These guidelines incorporate the latest evaluation of evidence from studies of diagnostic accuracy. For each clinical question, outcomes for benefits and harms were established, and qualitative or quantitative systematic reviews were conducted. Recommendations were determined through voting by a multidisciplinary group, and guidelines were documented to facilitate shared decision-making among patients and medical professionals. The guidelines address screening, surveillance, and pre- and postoperative diagnosis of breast cancer. In an environment that demands an integrated approach, decisions are needed on how to utilize modalities, such as mammography, ultrasound, MRI, and PET/CT. Additionally, it is vital to understand the appropriate use of new technologies, such as tomosynthesis, elastography, and contrast-enhanced ultrasound, and to consider how best to adapt these methods for individual patients.

Contrast-enhanced ultrasound to predict malignant upgrading of atypical ductal hyperplasia

BACKGROUND

A malignancy might be found at surgery in cases of atypical ductal hyperplasia (ADH) diagnosed via US-guided core needle biopsy (CNB). The objective of this study was to investigate the diagnostic performance of contrast-enhanced ultrasound (CEUS) in predicting ADH diagnosed by US-guided CNB that was upgraded to malignancy after surgery.

METHODS

In this retrospective study, 110 CNB-diagnosed ADH lesions in 109 consecutive women who underwent US, CEUS, and surgery between June 2018 and June 2023 were included. CEUS was incorporated into US BI-RADS and yielded a CEUS-adjusted BI-RADS. The diagnostic performance of US BI-RADS and CEUS-adjusted BI-RADS for ADH were analyzed and compared.

RESULTS

The mean age of the 109 women was 49.7 years ± 11.6 (SD). The upgrade rate of ADH at CNB was 48.2% (53 of 110). The sensitivity, specificity, positive predictive value, and negative predictive value of CEUS for identification of malignant upgrading were 96.2%, 66.7%,72.9%, and 95.0%, respectively, based on BI-RADS category 4B threshold. The two false-negative cases were low-grade ductal carcinoma in situ. Compared with the US, CEUS-adjusted BI-RADS had better specificity for lesions smaller than 2 cm (76.7% vs. 96.7%, P = 0.031). After CEUS, 16 (10 malignant and 6 nonmalignant) of the 45 original US BI-RADS category 4A lesions were up-classified to BI-RADS 4B, and 3 (1 malignant and 2 nonmalignant) of the 41 original US BI-RADS category 4B lesions were down-classified to BI-RADS 4A.

CONCLUSIONS

CEUS is helpful in predicting malignant upgrading of ADH, especially for lesions smaller than 2 cm and those classified as BI-RADS 4A and 4B on ultrasound.

A Nomogram Based on Conventional and Contrast-Enhanced Ultrasound for Pre-operative Prediction of Nipple-Areola Complex Involvement in Breast Cancer: A Prospective Study

OBJECTIVE

Accurately predicting nipple-areola complex (NAC) involvement in breast cancer is essential for identifying eligible patients for a nipple-sparing mastectomy. This study was aimed at developing a pre-operative nomogram for NAC involvement in breast cancer using conventional ultrasound (US) and contrast-enhanced ultrasound (CEUS).

METHODS

All patients with primary breast cancer confirmed by pre-operative biopsy underwent US and CEUS examinations. Post-operative pathology was used as the gold standard in assessing NAC involvement. Lasso regression was used to select the predictors most associated with NAC involvement. A nomogram was constructed to calculate the diagnostic efficacy. The data were internally verified with 500 bootstrapped replications, and a calibration curve was generated to validate the predictive capability.

RESULTS

Seventy-six patients with primary breast cancer were included in this study, which included 16 patients (21.1%) with NAC involvement and 60 patients (78.9%) without NAC involvement. Among the 23 features of US and CEUS, Lasso regression selected one US feature and two CEUS features, namely, ductal echo extending from the lesion, ductal enhancement extending to the nipple and focal nipple enhancement. A nomogram was constructed, and the results revealed that the area under the curve, sensitivity, specificity and accuracy were 0.891, 81.3%, 86.7% and 85.5%, respectively. The calibration curve exhibited good consistency between the predicted probability and the actual probability.

CONCLUSION

The nomogram developed based on US and CEUS had good performance in predicting NAC involvement in breast cancer before surgery, which may facilitate the selection of suitable patients for NAC preservation with greater oncological safety.

Neoadjuvant chemotherapy for breast cancer: an evaluation of its efficacy and research progress

Neoadjuvant chemotherapy (NAC) for breast cancer is widely used in the clinical setting to improve the chance of surgery, breast conservation and quality of life for patients with advanced breast cancer. A more accurate efficacy evaluation system is important for the decision of surgery timing and chemotherapy regimen implementation. However, current methods, encompassing imaging techniques such as ultrasound and MRI, along with non-imaging approaches like pathological evaluations, often fall short in accurately depicting the therapeutic effects of NAC. Imaging techniques are subjective and only reflect macroscopic morphological changes, while pathological evaluation is the gold standard for efficacy assessment but has the disadvantage of delayed results. In an effort to identify assessment methods that align more closely with real-world clinical demands, this paper provides an in-depth exploration of the principles and clinical applications of various assessment approaches in the neoadjuvant chemotherapy process.

Head-to-head comparison of perfluorobutane contrast-enhanced US and multiparametric MRI for breast cancer: a prospective, multicenter study

BACKGROUND

Multiparametric magnetic resonance imaging (MP-MRI) has high sensitivity for diagnosing breast cancers but cannot always be used as a routine diagnostic tool. The present study aimed to evaluate whether the diagnostic performance of perfluorobutane (PFB) contrast-enhanced ultrasound (CEUS) is similar to that of MP-MRI in breast cancer and whether combining the two methods would enhance diagnostic efficiency.

PATIENTS AND METHODS

This was a head-to-head, prospective, multicenter study. Patients with breast lesions diagnosed by US as Breast Imaging Reporting and Data System (BI-RADS) categories 3, 4, and 5 underwent both PFB-CEUS and MP-MRI scans. On-site operators and three reviewers categorized the BI-RADS of all lesions on two images. Logistic-bootstrap 1000-sample analysis and cross-validation were used to construct PFB-CEUS, MP-MRI, and hybrid (PFB-CEUS + MP-MRI) models to distinguish breast lesions.

RESULTS

In total, 179 women with 186 breast lesions were evaluated from 17 centers in China. The area under the receiver operating characteristic curve (AUC) for the PFB-CEUS model to diagnose breast cancer (0.89; 95% confidence interval [CI] 0.74, 0.97) was similar to that of the MP-MRI model (0.89; 95% CI 0.73, 0.97) (P = 0.85). The AUC of the hybrid model (0.92, 95% CI 0.77, 0.98) did not show a statistical advantage over the PFB-CEUS and MP-MRI models (P = 0.29 and 0.40, respectively). However, 90.3% false-positive and 66.7% false-negative results of PFB-CEUS radiologists and 90.5% false-positive and 42.8% false-negative results of MP-MRI radiologists could be corrected by the hybrid model. Three dynamic nomograms of PFB-CEUS, MP-MRI and hybrid models to diagnose breast cancer are freely available online.

CONCLUSIONS

PFB-CEUS can be used in the differential diagnosis of breast cancer with comparable performance to MP-MRI and with less time consumption. Using PFB-CEUS and MP-MRI as joint diagnostics could further strengthen the diagnostic ability. Trial registration Clinicaltrials.gov; NCT04657328. Registered 26 September 2020. IRB number 2020-300 was approved in Chinese PLA General Hospital. Every patient signed a written informed consent form in each center.

Evaluation of diagnostic efficacy of multimode ultrasound in BI-RADS 4 breast neoplasms and establishment of a predictive model

Objectives

To explore the diagnostic efficacy of ultrasound (US), two-dimensional and three-dimensional shear-wave elastography (2D-SWE and 3D-SWE), and contrast-enhanced ultrasound (CEUS) in breast neoplasms in category 4 based on the Breast Imaging Reporting and Data System (BI-RADS) from the American College of Radiology (ACR) and to develop a risk-prediction nomogram based on the optimal combination to provide a reference for the clinical management of BI-RADS 4 breast neoplasms.

Methods

From September 2021 to April 2022, a total of 104 breast neoplasms categorized as BI-RADS 4 by US were included in this prospective study. There were 78 breast neoplasms randomly assigned to the training cohort; the area under the receiver-operating characteristic curve (AUC), 95% confidence interval (95% CI), sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of 2D-SWE, 3D-SWE, CEUS, and their combination were analyzed and compared. The optimal combination was selected to develop a risk-prediction nomogram. The performance of the nomogram was assessed by a validation cohort of 26 neoplasms.

Results

Of the 78 neoplasms in the training cohort, 16 were malignant and 62 were benign. Among the 26 neoplasms in the validation cohort, 6 were malignant and 20 were benign. The AUC values of 2D-SWE, 3D-SWE, and CEUS were not significantly different. After a comparison of the different combinations, 2D-SWE+CEUS showed the optimal performance. Least absolute shrinkage and selection operator (LASSO) regression was used to filter the variables in this combination, and the variables included Emax, Eratio, enhancement mode, perfusion defect, and area ratio. Then, a risk-prediction nomogram with BI-RADS was built. The performance of the nomogram was better than that of the radiologists in the training cohort (AUC: 0.974 vs. 0.863). In the validation cohort, there was no significant difference in diagnostic accuracy between the nomogram and the experienced radiologists (AUC: 0.946 vs. 0.842).

Conclusions

US, 2D-SWE, 3D-SWE, CEUS, and their combination could improve the diagnostic efficiency of BI-RADS 4 breast neoplasms. The diagnostic efficacy of US+3D-SWE was not better than US+2D-SWE. US+2D-SWE+CEUS showed the optimal diagnostic performance. The nomogram based on US+2D-SWE+CEUS performs well.

Multi-parameter ultrasonography-based predictive model for breast cancer diagnosis

OBJECTIVES

To develop, validate, and evaluate a predictive model for breast cancer diagnosis using conventional ultrasonography (US), shear wave elastography (SWE), and contrast-enhanced US (CEUS).

MATERIALS AND METHODS

This retrospective study included 674 patients with 674 breast lesions. The data, a main and an independent datasets, were divided into three cohorts. Cohort 1 (80% of the main dataset; n = 448) was analyzed by logistic regression analysis to identify risk factors and establish the predictive model. The area under the receiver operating characteristic curve (AUC) was analyzed in Cohort 2 (20% of the main dataset; n = 119) to validate and in Cohort 3 (the independent dataset; n = 107) to evaluate the predictive model.

RESULTS

Multivariable regression analysis revealed nine independent breast cancer risk factors, including age > 40 years; ill-defined margin, heterogeneity, rich blood flow, and abnormal axillary lymph nodes on US; enhanced area enlargement, contrast agent retention, and irregular shape on CEUS; mean SWE higher than the cutoff value (P < 0.05 for all). The diagnostic performance of the model was good, with AUC values of 0.847, 0.857, and 0.774 for Cohorts 1, 2, and 3, respectively. The model increased the diagnostic specificity (from 31% to 81.3% and 7.3% to 73.1% in cohorts 2 and 3, respectively) without a significant loss in sensitivity (from 100.0% to 90.1% and 100.0% to 81.8% in cohorts 2 and 3, respectively).

CONCLUSION

The multi-parameter US-based model showed good performance in breast cancer diagnosis, improving specificity without a significant loss in sensitivity. Using the model could reduce unnecessary biopsies and guide clinical diagnosis and treatment.

The clinical value of conventional ultrasound combined with contrast-enhanced ultrasound in the evaluation of BI-RADS 4 lesions detected by magnetic resonance imaging

OBJECTIVE

To determine the value of conventional ultrasound combined with contrast-enhanced ultrasound (CEUS) in Breast Imaging Reporting and Data System (BI-RADS) Category 4 lesions as detected by MRI.

METHODS

A total of 176 breast lesions from 171 patients were detected by MRI and categorised as BI-RADS 4. All patients also underwent ultrasound and CEUS scans. The combination of ultrasound-BI-RADS and CEUS 5-point scoring system created the Rerated BI-RADS (referred to as CEUS-BI-RADS). The diagnostic performances of ultrasound and CEUS-BI-RADS were then compared. A χ2 test was used to compare the CEUS features of mass-like and non-mass-like enhancement types of MRI-BI-RADS 4 lesions.

RESULTS

There were 167 (167/176) breast lesions detected by ultrasound, with a detection rate of 94.89%, while all were subsequently detected by "second-look" ultrasound combined with CEUS, with a detection rate of 100%. The areas under the receiver operating characteristic curves for ultrasound and CEUS-BI-RADS were 0.810 and 0.940, respectively. The diagnostic efficiency of CEUS-BI-RADS was significantly higher than that of ultrasound alone (z = 3.264, p = 0.001). For both mass-like and non-mass-like enhancement types of MRI-BI-RADS 4 lesions, CEUS-BI-RADS demonstrated satisfactory sensitivity and accuracy. Moreover, 29 (29/176) category 4 lesions were downgraded to 3 by CEUS-BI-RADS.

CONCLUSION

Ultrasound combined with CEUS can allow reclassification, reduce biopsy rates, and facilitate pre-surgical localisation for biopsy or surgery for MRI-BI-RADS 4 lesions.

ADVANCES IN KNOWLEDGE

For MRI-BI-RADS Category 4 lesions with a wide range of malignancies, ultrasound combined with CEUS is a promising diagnostic approach with high clinical utility.

Differentiation Between Granulomatous Lobular Mastitis and Breast Cancer Using Quantitative Parameters on Contrast-Enhanced Ultrasound

Objective

To investigate the Contrast-enhanced ultrasound (CEUS) imaging characteristics of granulomatous lobular mastitis (GLM) and the value of differentiating GLM from breast cancer.

Materials and methods

The study included 30 women with GLM (mean age 36.7 ± 5 years [SD]) and 58 women with breast cancer (mean age 48. ± 8 years [SD]) who were scheduled for ultrasound-guided tissue biopsy. All patients were evaluated with conventional US and CEUS prior to the biopsy. In both groups, the parameters of the quantitative and qualitative analysis of the CEUS were recorded and compared. The receiver-operating-characteristics curves (ROC) were created. Sensitivity, specificity, cut-off, and area under the curve (AUC) values were calculated.

Results

TTP values in GLM were statistically higher than in breast cancer (mean, 27.63 ± 7.29 vs. 20.10 ± 6.11), but WIS values were lower (mean, 0.16 ± 0.05 vs. 0.28 ± 0.17). Rich vascularity was discovered in 54.45% of breast cancer patients, but only 30.00% of GLM patients had rich vascularity. The AUC for the ROC test was 0.791 and 0.807, respectively. The optimal cut-off value for TTP was 24.5s, and the WIS cut-off value was 0.185dB/s, yielding 73.33% sensitivity, 84.48% specificity, and 86.21% sensitivity, 70% specificity respectively in the diagnosis of GLM. The lesion scores reduced from 4 to 3 with the addition of CEUS for the patients with GLM. However, the scores did not change for the patients with breast cancer.

Conclusion

CEUS could help distinguish GLM from breast cancer by detecting higher TTP and WIS values, potentially influencing clinical decision-making for additional biopsies.

Ultrasonic multimodality imaging features and the classification value of nonpuerperal mastitis

OBJECTIVE

To explore the value of ultrasonic multimodality imaging for characterizing nonpuerperal mastitis (NPM) lesions and feasibility of distinguishing different subtypes.

METHODS

Thirty-eight NPM lesions were assessed using conventional ultrasonography (US), strain elastography (SE), and contrast-enhanced ultrasound (CEUS). The lesions were confirmed pathologically and classified as granulomatous lobular mastitis (GLM), plasma cell mastitis (PCM), or nonspecific mastitis (NSM). Furthermore, diagnostic indicators were evaluated. The diagnostic performances of the modalities were compared using the area under the receiver operating characteristic curve (AUC).

RESULTS

The overall morphological features on US differed significantly between the GLM and PCM groups (p = 0.002). Lesion size (≤10 mm) (p = 0.003) and mean SE score (p = 0.001) differed significantly between the PCM and NSM groups. The frequent NPM characteristic on CEUS was hyperenhancement with (or without) increased lesion size; intergroup differences were not significant. Breast Imaging Reporting and Data System > 3 was considered to indicate malignancy; accordingly, the accuracy of US alone, US with CEUS, and US with SE was 10.5%, 21.1%, and 65.8%, respectively. Moreover, the AUC for US with SE for classifying GLM and PCM was 0.616.

CONCLUSION

CEUS cannot accurately classify NPM subtypes, while US and SE are valuable for classification.

Quantification and Classification of Contrast Enhanced Ultrasound Breast Cancer Data: A Preliminary Study

This study aimed to investigate which of the two frequently adopted perfusion models better describes the contrast enhanced ultrasound (CEUS) perfusion signal in order to produce meaningful imaging markers with the goal of developing a machine-learning model that can classify perfusion curves as benign or malignant in breast cancer data. Twenty-five patients with high suspicion of breast cancer were analyzed with exponentially modified Gaussian (EMG) and gamma variate functions (GVF). The adjusted R² metric was the criterion for assessing model performance. Various classifiers were trained on the quantified perfusion curves in order to classify the curves as benign or malignant on a voxel basis. Sensitivity, specificity, geometric mean, and AUROC were the validation metrics. The best quantification model was EMG with an adjusted R² of 0.60 ± 0.26 compared to 0.56 ± 0.25 for GVF. Logistic regression was the classifier with the highest performance (sensitivity, specificity, G_mean, and AUROC = 89.2 ± 10.7, 70.0 ± 18.5, 77.1 ± 8.6, and 91.0 ± 6.6, respectively). This classification method obtained similar results that are consistent with the current literature. Breast cancer patients can benefit from early detection and characterization prior to biopsy.

Papillary breast lesions detected using conventional ultrasound and contrast-enhanced ultrasound: Imaging characteristics and associations with malignancy

OBJECTIVE

This study aimed to evaluate the imaging features of papillary breast lesions detected using conventional ultrasonography (US) and contrast-enhanced ultrasound (CEUS) and to correlate the pathological results. Furthermore, the diagnostic efficiencies of these imaging features to predict the malignancy potential of papillary lesions were explored.

METHODS

The findings of the conventional US and CEUS of 74 consecutive papillary breast lesions were assessed retrospectively. The obtained data were analyzed using univariate and multivariate logistic regressions to evaluate the ability of each parameter and combined parameters in distinguishing the benign and atypical or malignant papillary lesions.

RESULTS

Among the imaging features of breast papillary lesions on conventional US and CEUS, two sonographic features (lesion size ≥1 cm and not circumscribed margin) on conventional US and four enhancement features (irregular enhancement, heterogeneous enhancement, enlargement of scope, and perfusion defect) on CEUS were found to be significantly different between the benign and atypical or malignant papillary lesions (P < 0.05). A multivariate logistic regression analysis further showed that only heterogeneous enhancement and enlarged enhancement scope were associated with malignancy. The sensitivity and specificity of heterogeneous enhancement, enlarged enhancement scope, and combined analysis for predicting atypical and malignant papillary lesions were 78.6 % and 39.1 %, 75 % and 37 %, and 75 % and 82.6 %, respectively. The combination of enhancement homogeneity and enhancement scope improved the diagnostic accuracy (AUC = 0.875).

CONCLUSIONS

The results suggested that the imaging features on conventional US and CEUS could help in identifying benign and malignant papillary lesions and predict their malignancy potential.

Contrast-Enhanced Ultrasonography in the Diagnosis and Treatment Modulation of Breast Cancer

The aim of this paper is to highlight the role of contrast-enhanced ultrasound in breast cancer in terms of diagnosis, staging and follow-up of the post-treatment response. Contrast-enhanced ultrasound (CEUS) is successfully used to diagnose multiple pathologies and has also clinical relevance in breast cancer. CEUS has high accuracy in differentiating benign from malignant lesions by analyzing the enhancement characteristics and calculating the time-intensity curve’s quantitative parameters. It also has a significant role in axillary staging, especially when the lymph nodes are not suspicious on clinical examination and have a normal appearance on gray-scale ultrasound. The most significant clinical impact consists of predicting the response to neoadjuvant chemotherapy, which offers the possibility of adjusting the therapy by dynamically evaluating the patient. CEUS is a high-performance, feasible, non-irradiating, accessible, easy-to-implement imaging method and has proven to be a valuable addition to breast ultrasound.

Diagnostic Value of Contrast-Enhanced Ultrasonography With SonoVue in the Differentiation of Benign and Malignant Breast Lesions: A Meta-Analysis

PURPOSE

A meta-analysis was conducted to evaluate the diagnostic performance of contrast-enhanced ultrasonography using the contrast agent SonoVue to differentiate benign from malignant breast lesions.

METHOD

A comprehensive search of the literature was performed using the Embase, PubMed, and Web of Science databases to retrieve studies published before February 2020. Data were extracted, and pooled sensitivity, specificity, and diagnostic odds ratios were calculated with meta-analysis software. Heterogeneity was evaluated via the Q test and I² statistic. Meta-regression and subgroup analyses were applied to evaluate potential sources of heterogeneity. Publication bias was assessed using the Deeks' funnel plot asymmetry test. A summary receiver operating characteristic curve (SROC) was constructed.

RESULTS

A total of 27 studies including 5378 breast lesions subjected to CEUS examination with SonoVue were included in the meta-analysis. The pooled sensitivity and specificity values were 0.90 (95% confidence interval [CI], 0.88-0.91; inconsistency index [I²] = 75.7%) and 0.83 (95% CI, 0.82-0.85; I² = 91.0%), respectively. The pooled diagnostic odds ratio was 48.35% (95% CI, 31.22-74.89; I² = 77.6%). The area under the summary receiver operating characteristic curve (AUC) was 0.9354. Meta-regression analysis revealed the region of patient residence and dose of contrast agent as potential sources of heterogeneity (P < .01). Subgroup analysis showed a higher area under the summary receiver operating characteristic curve for European and higher contrast agent dose subgroups (P < .05).

CONCLUSION

Contrast-enhanced ultrasonography with SonoVue displays high sensitivity, specificity, and accuracy when differentiating benign from malignant breast lesions. Despite its current limitations, this technique presents a promising tool for diagnosing breast lesions in clinical practice.

Multimodal Ultrasound Imaging in Breast Imaging-Reporting and Data System 4 Breast Lesions: A Prediction Model for Malignancy

The purpose of this study was to develop, validate and test a prediction model for discriminating malignant from benign breast lesions using conventional ultrasound (US), US elastography of strain elastography and contrast-enhanced ultrasound (CEUS). The study included 454 patients with breast imaging-reporting and data system (BI-RADS) category 4 breast lesions identified on histologic examinations. Firstly, 228 breast lesions (cohort 1) were analyzed by logistic regression analysis to identify the risk factors, and a breast malignancy prediction model was created. Secondly, the prediction model was validated in cohort 2 (84 patients) and tested in cohort 3 (142 patients) by using analysis of the area under the receiver operating characteristic curve (AUC). Univariate regression indicated that age ≥40 y, taller than wide shape on US, early hyperenhancement on CEUS and enlargement of enhancement area on CEUS were independent risk factors for breast malignancy (all p < 0.05). The logistic regression equation was established as follows: p = 1/1+Exp∑[-5.066 + 3.125 x (if age ≥40 y) + 1.943 x (if taller than wide shape) + 1.479 x (if early hyperenhancement) + 4.167 x (if enlargement of enhancement area). The prediction model showed good discrimination performance with an AUC of 0.967 in cohort 1, 0.948 in cohort 2 and 0.920 in cohort 3. By using the prediction model to selectively downgrade category 4a lesions, the re-rated BI-RADS yield an AUC of 0.880 (95% confidence interval [CI], 0.794-0.965) in cohort 2 and 0.870 (95% CI, 0.801-0.939) in cohort 3. The specificity increased from 0.0% (0/35) to 80.0% (28/35) without loss of sensitivity (from 100.0% to 95.9%, p = 0.153) in cohort 2. Similarly, the specificity increased from 0.0% (0/58) to 77.6% (45/58) without loss of sensitivity (from 100.0% to 96.4%, p = 0.081) in cohort 3. Multimodal US showed good diagnostic performance in predicting breast malignancy of BI-RADS category 4 lesions. Although the loss of sensitivity was existing, the addition of multimodal US to US BI-RADS could improve the specificity in BI-RADS category 4 lesions, which reduced unnecessary biopsies.

Value of multimodality imaging in the diagnosis of breast lesions with calcification: A retrospective study

PURPOSE

To assess the value of conventional ultrasound (US), contrast-enhanced ultrasound (CEUS) and mammography in the diagnosis of breast lesions with calcifications.

METHODS

A total of 87 breast lesions with calcification were subjected to US, CEUS and mammography and divided into 3 groups: Group A (all cases), Group A1 (31 cases who underwent US and CEUS first followed by mammography), and Group A2 (56 cases who underwent mammography first followed by US and CEUS). A receiver operating characteristic (ROC) curve analysis was performed to evaluate the diagnostic efficacy of different methods in different groups.

RESULTS

In Group A, the area under the ROC curve (AUROC) of CEUS were 0.937, which were significantly higher than that of mammography (p < 0.05). In Group A1, the AUROC of CEUS were 0.842, which were not significantly different from that of US and mammography (p > 0.05). In Group A2, the AUROC of CEUS were 0.987, which were significantly higher than that of mammography and US (p < 0.05).

CONCLUSION

Based on the mammography results, the combination of US and CEUS might improve the diagnostic efficacy in breast lesions with calcification.

Value of contrast-enhanced ultrasound in the diagnosis of breast US-BI-RADS 3 and 4 lesions with calcifications

AIM

To evaluate the diagnostic performance of contrast-enhanced ultrasound (CEUS) for Breast Imaging-Reporting and Data System for Ultrasound (US-BI-RADS) 3 and 4 lesions with calcifications.

MATERIALS AND METHODS

A retrospective study of 168 breast lesions with calcifications detected on both mammography and conventional ultrasonography (US) in 152 patients were categorised as US-BI-RADS 3-4 at US between June 2009 and June 2018. CEUS scores were obtained based on a CEUS five-point scoring system. The combination of US-BI-RADS and CEUS scores created the Rerated BI-RADS (referred to as CEUS-BI-RADS). All results were compared with the histological findings. The diagnostic performances of US and CEUS-BI-RADS were compared.

RESULTS

The diagnostic sensitivity, specificity, and accuracy of US were 81.8% (95% confidence interval [CI]: 71.6%, 92%), 85% (95% CI: 78.4%, 91.5%), and 83.9% (95% CI: 78.4%, 89.5%), respectively, while those for CEUS-BI-RADS were 98.2% (95% CI: 94.7%, 100%), 90.3% (95% CI: 84.8%, 95.7%), and 92.9% (95% CI: 89%, 96.8%), respectively. The diagnostic sensitivity and accuracy values of CEUS-BI-RADS greatly improved compared with those of US (p=0.003 and p=0.004, respectively). The areas under the receiver operating characteristic (ROC) curves for US and CEUS-BI-RADS were 0.888 (95% CI: 0.840, 0.936) and 0.963 (95% CI: 0.936, 0.989), respectively. The diagnostic efficacy of CEUS-BI-RADS was significantly higher than that of US alone (p=0.004).

CONCLUSION

CEUS-BI-RADS significantly improves the diagnostic accuracy for breast US-BI-RADS 3 and 4 lesions with calcifications compared with US.

Incorporation of contrast-enhanced ultrasound in the differential diagnosis for breast lesions with inconsistent results on mammography and conventional ultrasound

OBJECTIVE

To identify the efficacy of contrast-enhanced ultrasound (CEUS) in re-evaluating masses with inconsistent Breast Imaging Reporting and Data System (BI-RADS) on mammography (MG) and conventional ultrasound (US).

MATERIALS AND METHODS

A total of 637 breast lesions were evaluated with MG, US, and CEUS within 6 months and assessed as BI-RADS MG and US. CEUS was used as an additional screening to rerate BI-RADS US according to a five-point system. Lesions were divided into consistent or inconsistent group on the basis of BI-RADS MG and US assessment. The performance of MG, US, and CEUS in the overall and inconsistent group as well as the clinicopathological differences between consistent and inconsistent group were compared using Z test, Mann-Whitney U test, and t-test.

RESULTS

The respective AUCs of MG and US were 0.742, 0.843 for overall group and 0.412, 0.789 for inconsistent group. The corresponding values of rerated CEUS BI-RADS were 0.958 and 0.950, which were significantly prior to those of MG and US (p < 0.001). Younger age, negative lymph node status, and dense breast were significantly associated with inconsistent group.

CONCLUSION

Incorporation of CEUS to re-evaluate lesions can improve the diagnostic efficacy comparing to MG or US alone especially when disagreement occurred.

Does contrast-enhanced ultrasound (CEUS) play a better role in diagnosis of breast lesions with calcification? A comparison with MRI

OBJECTIVE

To compare the efficacy of contrast-enhanced ultrasound enabled reclassification of Breast Imaging Reporting and Data System (CEUS-BI-RADS) with MRI in the diagnosis of breast lesions with calcification.

METHODS

A total of 52 breast lesions with calcification from 51 patients were detected by ultrasound as hyperechoic foci and categorized as BI-RADS 3-5. The 51 patients further underwent CEUS scan and MRI. The ultrasound-BI-RADS combined with CEUS 5-point score system redefined the classification of BI-RADS which was called CEUS-BI-RADS. The diagnostic efficacy of three methods was assessed by receiver operating characteristic (ROC) curve analysis. Histopathological assessment used as the gold-standard.

RESULTS

The sensitivities of Ultrasound-BI-RADS, MRI classification of BI-RADS (MRI-BI-RADS) and CEUS-BI-RADS were 85%, 90% and 95% without significant difference among the three modalities (p > 0.05). The diagnostic specificities of ultrasound-BI-RADS, MRI-BI-RADS and CEUS-BI-RADS were 78.1%, 78.1% and 96.8%, respectively (p < 0.05); and the accuracy were 80.7%, 82.6% and 96.1% for ultrasound-BI-RADS, MRI-BI-RADS and CEUS-BI-RADS, respectively (p < 0.05). The area under ROC (AUROC) in differentiation of breast lesions with calcification was 0.945 for CEUS-BI-RADS, 0.907 for MRI-BI-RADS and 0.853 for ultrasound-BI-RADS, with no significant difference among the three modalities (p > 0.05).

CONCLUSION

The CEUS-BI-RADS has a better diagnostic efficiency than MRI-BI-RADS in the differentiation of the breast lesions with calcification.

ADVANCES IN KNOWLEDGE

•CEUS is a better method in differentiation of breast lesions with calcification.•CEUS-BI-RADS increases the efficiency of diagnosis compared to MRI.

Breast non-mass-like lesions on contrast-enhanced ultrasonography: Feature analysis, breast image reporting and data system classification assessment

BACKGROUND

Breast non-mass-like lesions (NMLs) account for 9.2% of all breast lesions. The specificity of the ultrasound diagnosis of NMLs is low, and it cannot be objectively classified according to the 5^th Edition of the Breast Imaging Reporting and Data System (BI-RADS). Contrast-enhanced ultrasound (CEUS) can help to differentiate and classify breast lesions but there are few studies on NMLs alone.

AIM

To analyze the features of benign and malignant breast NMLs in grayscale ultrasonography (US), color Doppler flow imaging (CDFI) and CEUS, and to explore the efficacy of the combined diagnosis of NMLs and the effect of CEUS on the BI-RADS classification of NMLs.

METHODS

A total of 51 breast NMLs verified by pathology were analyzed in our hospital from January 2017 to April 2019. All lesions were examined by US, CDFI and CEUS, and their features from those examinations were analyzed. With pathology as the gold standard, binary logic regression was used to analyze the independent risk factors for malignant breast NMLs, and a regression equation was established to calculate the efficiency of combined diagnosis. Based on the regression equation, the combined diagnostic efficiency of US combined with CEUS (US + CEUS) was determined. The initial BI-RADS-US classification of NMLs was adjusted according to the independent risk factors identified by CEUS, and the diagnostic efficiency of CEUS combined with BI-RADS (CEUS + BI-RADS) was calculated based on the results. ROC curves were drawn to compare the diagnostic values of the three methods, including US, US + CEUS, and CEUS + BI-RADS, for benign and malignant NMLs.

RESULTS

Microcalcification, enhancement time, enhancement intensity, lesion scope, and peripheral blood vessels were significantly different between benign and malignant NMLs. Among these features, microcalcification, higher enhancement, and lesion scope were identified as independent risk factors for malignant breast NMLs. When US, US + CEUS, and CEUS + BI-RADS were used to identify the benign and malignant breast NMLs, their sensitivity rates were 82.6%, 91.3%, and 87.0%, respectively; their specificity rates were 71.4%, 89.2%, and 92.9%, respectively; their positive predictive values were 70.4%, 87.5%, and 90.9%, respectively; their negative predictive values were 83.3%, 92.6%, and 89.7%, respectively; their accuracy rates were 76.5%, 90.2%, and 90.2%, respectively; and their corresponding areas under ROC curves were 0.752, 0.877 and 0.903, respectively. Z tests showed that the area under the ROC curve of US was statistically smaller than that of US + CEUS and CEUS + BI-RADS, and there was no statistical difference between US + CEUS and CEUS + BI-RADS.

CONCLUSION

US combined with CEUS can improve diagnostic efficiency for NMLs. The adjustment of the BI-RADS classification according to the features of contrast-enhanced US of NMLs enables the diagnostic results to be simple and intuitive, facilitates the management of NMLs, and effectively reduces the incidence of unnecessary biopsy.

Radiomics With Attribute Bagging for Breast Tumor Classification Using Multimodal Ultrasound Images

OBJECTIVES

We aimed to develop radiomics with attribute bagging, which leverages multimodal ultrasound (US) images to improve the classification accuracy of breast tumors.

METHODS

A retrospective study was conducted. B-mode US, shear wave elastographic, and contrast-enhanced US images of 178 patients with 181 tumors (67 malignant and 114 benign) were included. Radiomics with attribute bagging consisted of extraction of 1226 radiomic features and analysis of them with attribute bagging. Histologic examination results acted as the reference standard. Radiomics with several feature selection algorithms were used for comparison. Cross-validation and a holdout test were performed to evaluate their performances.

RESULTS

The accuracy, sensitivity, specificity, and area under the receiver operating characteristic curve of radiomics with attribute bagging with the multimodal US images were 84.12%, 92.86%, 78.80%, and 0.919, respectively, exceeding all the comparison methods.

CONCLUSIONS

Radiomics with attribute bagging combined with multimodal US images has the potential to be used for accurate diagnosis of breast tumors in the clinic.

Quantitative Multiparametric Breast Ultrasound: Application of Contrast-Enhanced Ultrasound and Elastography Leads to an Improved Differentiation of Benign and Malignant Lesions

OBJECTIVES

The aim of this study was to evaluate breast multiparametric ultrasound (mpUS) and its potential to reduce unnecessary breast biopsies with 1, 2, or 3 additional quantitative parameters (Doppler, elastography, and contrast-enhanced ultrasound [CEUS]) to B-mode and investigate possible variations with different reader experience.

MATERIALS AND METHODS

This prospective study included 124 women (age range, 18-82 years; mean, 52 years), each with 1 new breast lesion, scheduled for ultrasound-guided biopsy between October 2015 and September 2016. Each lesion was examined with B-mode, elastography (Virtual Touch IQ [VTIQ]), Doppler, and CEUS, and different quantitative parameters were recorded for each modality. Four readers (2 experienced breast radiologists and 2 in-training) independently evaluated B-mode images of each lesion and assigned a BI-RADS (Breast Imaging Reporting and Data System) score. Using the area under the receiver operating characteristic curve (AUC), the most accurate quantitative parameter for each modality was chosen. These were then combined with the BI-RADS scores of all readers. Descriptive statistics and AUC were used to evaluate the diagnostic performance of mpUS.

RESULTS

Sixty-five lesions were malignant. MpUS with B-mode and 2 additional quantitative parameters (VTIQ and CEUS or Doppler) showed the highest diagnostic performance for all readers (averaged AUCs, 0.812-0.789 respectively vs 0.683 for B-mode, P = 0.0001). Both combinations significantly reduced the number of false-positive findings up to 46.9% (P < 0.0001).

CONCLUSIONS

Quantitative mpUS with 2 different triple assessment modalities (B-mode, VTIQ elastography, CEUS, or Doppler) shows the best diagnostic performance for breast cancer diagnosis and leads to a significant reduction of false-positive biopsy recommendations, for both experienced and inexperienced readers.

The added value of contrast-enhanced ultrasound to conventional ultrasound in differentiating benign and malignant solid breast lesions: a systematic review and meta-analysis

AIM

To investigate the added value of contrast-enhanced ultrasound (CEUS) to the conventional ultrasound (US) in the diagnosis of breast lesions.

MATERIALS AND METHODS

PubMed, EMBASE, and Web of Science were searched for relevant studies published between 24 May 2005, and 29 October 2017. Studies incorporating CEUS into the conventional US were included. The reference standard was set by means of histopathological findings. The quality assessment of diagnostic studies (QUADAS) instrument was used to assess the quality of the included studies. Meta-Disc version 1.4. was used to calculate the sensitivity, specificity, summary receiver-operating characteristic (sROC) curves, and area under the curve (AUC). Meta-regression with Stata 12.0 was used to compare the diagnostic accuracy of the two techniques.

RESULTS

Five studies, comprising 992 patients, were eligible for this meta-analysis. For conventional US, the pooled sensitivity and specificity for were 0.87 (95% confidence interval [CI]: 0.84-0.91) and 0.80 (95% CI: 0.76-0.84), respectively, the AUC was 0.9049. For CEUS-rerated US, the pooled sensitivity and specificity were 0.93 (95% CI: 0.90-0.95) and 0.87 (95% CI: 0.84-0.90). The AUC was 0.9482. Meta-regression showed the sensitivity of CEUS-rerated US did not differ from conventional US (p=0.29), while specificity showed significant difference (p<0.01). There was evidence of between-study heterogeneity regarding sensitivity and specificity for both assessments.

CONCLUSIONS

Adding CEUS to conventional US could improve the diagnostic performance in differentiating benign from malignant solid breast lesions, whilst retaining high sensitivity, especially in Breast Imaging-Reporting and Data System (BI-RADS) 3-5 lesions. A uniform standard to distinguish benign from malignant lesions might be needed for further clinical application.

Angiogenesis Research in Mouse Mammary Cancer Based on Contrast-enhanced Ultrasonography: Exploratory Study

RATIONALE AND OBJECTIVES

The objective of this study was to investigate the contrast-enhanced ultrasound (CEUS) characteristics of tumor angiogenesis in mouse mammary cancer.

MATERIALS AND METHODS

Twenty-four mice were examined with ultrasound and CEUS at 2-12 days after implantation. Four to five mice were assessed daily, and one to three mice were then sacrificed for histology. All of the histologic slides were reviewed and correlated with CEUS findings.

RESULTS

A total of 46 cases of ultrasound examination had been performed in 24 mice. The mice were classified into three groups according to the tumor growth: group 1 (2~6 days after implantation, n = 20 cases), group 2 (7~9 days after implantation, n = 15 cases), and group 3 (10~12 days after implantation, n = 11 cases). In group 1, all tumors presented as a homogeneous hypoechoic mass with no color Doppler signals. However, three CEUS patterns were observed: 14 tumors presented as type I (peripheral ring enhancement with no enhancement within the tumor), 4 tumors presented as type II (peripheral ring enhancement with deep penetration), and 2 tumors presented as type III (homogeneous or heterogeneous enhancement in the entire tumor). In group 2, there was only difference in the echo (heterogeneous or not) and color Doppler signals (with or without) among the tumors in conventional ultrasound, but four CEUS patterns were observed and most presented as type III (53.3%, 8/15). In group 3, most tumors presented as a heterogeneous solid mass (81.8%, 9/11) with color signals (100%, 11/11), and almost all tumors presented as enhancement of type IV (peripheral ring enhancement with focal nodular enhancement) (90.9%, 10/11).The histologic results showed that the enhanced areas mainly corresponded to tumor cells, large tortuous vessels, and an inflammatory cell infiltrate. Nonenhanced areas corresponded to large areas of necrotic tissue or tumor cells, which arranged loosely with the small zone of necrosis.

CONCLUSIONS

CEUS could image the progression of vessel formation. Moreover, most importantly, CEUS is able to identify angiogenesis before the change of tumor color Doppler, and presents different enhanced patterns at different tumor growth times, which corresponded to tumor histologic features.