Diagnostic and prognostic values of contrast-enhanced ultrasound in breast cancer: a retrospective study

Contrast-Enhanced Ultrasound in the Evaluation of Complex Cystic and Solid Breast Masses-A Feasibility Study

OBJECTIVE

Complex cystic and solid breast mass (CCSBM) is a radiological diagnosis based on grayscale B-mode sonographic features. Because of potential for malignancy, biopsy is typically recommended. We examined the feasibility of contrast-enhanced US (CEUS) as a tool to identify benign CCSBMs.

METHODS

This Institutional Review Board-approved prospective observational study performed targeted CEUS of 14 CCSBMs that were subsequently biopsied. CEUS images were independently reviewed by two readers blinded to other sonographic features, noting presence or absence of enhancement and time to perceived optimal enhancement. Interobserver agreement for presence or absence of enhancement was analyzed using Cohen's kappa coefficient. From retrospective review of initial diagnostic US examinations, descriptive CCSBM sizes, subtypes, and Doppler information were recorded. Histopathologies were categorized as benign, benign with upgrade potential (BWUP), and malignant. Measures of diagnostic accuracy and 95% CIs were calculated for CEUS enhancement.

RESULTS

Of 14 CCSBMs, 12 were nonmalignant (9 benign, 3 BWUP) and 2 were malignant. There was perfect interobserver agreement (Cohen's kappa 1.00) between the 2 readers for CEUS enhancement. CEUS was 100% sensitive, 25% specific, with an area under the receiver operating characteristic curve (AUROC) of 0.625 (95% CI, 0.50-0.75) in differentiating nonmalignant from malignant lesions. It was 100% sensitive, 33.3% specific, with an AUROC of 0.667 (95% CI, 0.50-0.85) in differentiating benign from surgically significant (BWUP and malignant) CCSBMs.

CONCLUSION

This small feasibility study highlighted the potential of CEUS as a safe noninvasive tool to identify the proportion of CCSBMs that are benign and can avoid tissue biopsy.

Contrast-enhanced ultrasound for the preoperative prediction of pathological characteristics in breast cancer

Objective

We aimed to investigate the value of contrast-enhanced ultrasound (CEUS) in the preoperative prediction of the histological grades and molecular subtypes of breast cancer.

Methods

A total of 183 patients with pathologically confirmed breast cancer were included. Contrast enhancement patterns and quantitative parameters were compared in different groups. The receiver operating characteristic (ROC) curve was used to analyze the efficacy of CEUS in the preoperative prediction of pathological characteristics, including histologic grade and molecular subtypes.

Results

Heterogeneous enhancement, perfusion defects, and peripheral radial vessels were mostly observed in higher histologic grade (grade III) breast cancer. Heterogeneous enhancement and perfusion defect were the most effective indicators for grade III breast cancer, with the areas under the ROC curve of 0.768 and 0.756, respectively. There were significant differences in the enhancement intensity, post-enhanced margin, perfusion defects, and peripheral radial vessel among the different molecular subtypes of breast cancer (all P < 0.01). Perfusion defects and clear edge after enhancement were the best qualitative criteria for the diagnosis of HER-2 overexpressed and triple-negative breast cancers, and the corresponding areas under the ROC curves were 0.804 and 0.905, respectively. There were significant differences in PE, WiR, WiPI, and WiWoAUC between grade III vs grade I and II breast cancer (P < 0.05). PE, WiR, WiPI, and WiWoAUC had good efficiency in the diagnosis of high-histologic-grade breast cancer. PE had the highest diagnostic efficiency in Luminal A, while WiPI had the highest diagnostic efficiency in Luminal B subtype breast cancer, and the areas under the ROC curve were 0.825 and 0.838, respectively. WiWoAUC and WiR were the most accurate parameters for assessing triple-negative subtype breast cancers, and the areas under the curve were 0.932 and 0.922, respectively.

Conclusion

Qualitative and quantitative perfusion analysis of contrast-enhanced ultrasound may be useful in the non-invasive prediction of the histological grade and molecular subtypes of breast cancers.

Spatiotemporal analysis of contrast-enhanced ultrasound for differentiating between malignant and benign breast lesions

OBJECTIVES

The aim of this study was to apply spatiotemporal analysis of contrast-enhanced ultrasound (CEUS) loops to quantify the enhancement heterogeneity for improving the differentiation between benign and malignant breast lesions.

MATERIALS AND METHODS

This retrospective study included 120 women (age range, 18-82 years; mean, 52 years) scheduled for ultrasound-guided biopsy. With the aid of brightness-mode images, the border of each breast lesion was delineated in the CEUS images. Based on visual evaluation and quantitative metrics, the breast lesions were categorized into four grades of different levels of contrast enhancement. Grade-1 (hyper-enhanced) and grade-2 (partly-enhanced) breast lesions were included in the analysis. Four parameters reflecting enhancement heterogeneity were estimated by spatiotemporal analysis of neighboring time-intensity curves (TICs). By setting the threshold on mean parameter, the diagnostic performance of the four parameters for differentiating benign and malignant lesions was evaluated.

RESULTS

Sixty-four of the 120 patients were categorized as grade 1 or 2 and used for estimating the four parameters. At the pixel level, mutual information and conditional entropy present significantly different values between the benign and malignant lesions (p < 0.001 in patients of grade 1, p = 0.002 in patients of grade 1 or 2). For the classification of breast lesions, mutual information produces the best diagnostic performance (AUC = 0.893 in patients of grade 1, AUC = 0.848 in patients of grade 1 or 2).

CONCLUSIONS

The proposed spatiotemporal analysis for assessing the enhancement heterogeneity shows promising results to aid in the diagnosis of breast cancer by CEUS.

CLINICAL RELEVANCE STATEMENT

The proposed spatiotemporal method can be developed as a standardized software to automatically quantify the enhancement heterogeneity of breast cancer on CEUS, possibly leading to the improved diagnostic accuracy of differentiation between benign and malignant lesions.

KEY POINTS

• Advanced spatiotemporal analysis of ultrasound contrast-enhanced loops for aiding the differentiation of malignant or benign breast lesions. • Four parameters reflecting the enhancement heterogeneity were estimated in the hyper- and partly-enhanced breast lesions by analyzing the neighboring pixel-level time-intensity curves. • For the classification of hyper-enhanced breast lesions, mutual information produces the best diagnostic performance (AUC = 0.893).

Ceusia-Breast: computer-aided diagnosis with contrast enhanced ultrasound image analysis for breast lesions

BACKGROUND

In recent years, contrast-enhanced ultrasonography (CEUS) has been used for various applications in breast diagnosis. The superiority of CEUS over conventional B-mode imaging in the ultrasound diagnosis of the breast lesions in clinical practice has been widely confirmed. On the other hand, there have been many proposals for computer-aided diagnosis of breast lesions on B-mode ultrasound images, but few for CEUS. We propose a semi-automatic classification method based on machine learning in CEUS of breast lesions.

METHODS

The proposed method extracts spatial and temporal features from CEUS videos and breast tumors are classified as benign or malignant using linear support vector machines (SVM) with combination of selected optimal features. In the proposed method, tumor regions are extracted using the guidance information specified by the examiners, then morphological and texture features of tumor regions obtained from B-mode and CEUS images and TIC features obtained from CEUS video are extracted. Then, our method uses SVM classifiers to classify breast tumors as benign or malignant. During SVM training, many features are prepared, and useful features are selected. We name our proposed method "Ceucia-Breast" (Contrast Enhanced UltraSound Image Analysis for BREAST lesions).

RESULTS

The experimental results on 119 subjects show that the area under the receiver operating curve, accuracy, precision, and recall are 0.893, 0.816, 0.841 and 0.920, respectively. The classification performance is improved by our method over conventional methods using only B-mode images. In addition, we confirm that the selected features are consistent with the CEUS guidelines for breast tumor diagnosis. Furthermore, we conduct an experiment on the operator dependency of specifying guidance information and find that the intra-operator and inter-operator kappa coefficients are 1.0 and 0.798, respectively.

CONCLUSION

The experimental results show a significant improvement in classification performance compared to conventional classification methods using only B-mode images. We also confirm that the selected features are related to the findings that are considered important in clinical practice. Furthermore, we verify the intra- and inter-examiner correlation in the guidance input for region extraction and confirm that both correlations are in strong agreement.

Contrast-enhanced echocardiographic diagnosis of benign and malignant cardiac tumors and its correlation with pathology

Background

This study aimed to explore the diagnostic value of contrast-enhanced echocardiography (CEE) in benign and malignant cardiac tumors and detect the correlation of CEE parameters and immunohistochemistry (IHC) markers.

Methods

The data of 44 patients with cardiac tumors confirmed by pathology were reviewed. Lesions were examined before surgery using transthoracic echocardiography (TTE) and CEE with time-intensity curve analysis. The expression of CD31, VEGF and Ki67 was measured by IHC staining. Microvessel density (MVD) was quantified via IHC for CD31. The clinical variables, TTE, CEE and IHC parameters were compared between benign and malignant cardiac tumors. Receiver operating characteristic curve were used to analyze the value of factors in predicting malignant cardiac tumors. The correlation between CEE and IHC parameters was analyzed.

Results

Among 44 cardiac tumors, 34 were benign and 10 were malignant. There were significant differences in the TTE parameters (pericardial effusion, tumor boundary, diameter, basal width), CEE parameters (tumor peak intensity (TPI), peak intensity ratio of tumor to myocardium (TPI/MPI), area under time-intensity curve (AUTIC)) and IHC parameters (Ki67, MVD, CD31, VEGF) between the benign and malignant tumor groups (all P < 0.05). Receiver operating characteristic curve analysis showed that the CEE and IHC parameters had diagnostic value in malignant cardiac tumors. There was a correlation between TPI/MPI and Ki67 (r = 0.62), AUTIC and Ki67 (r = 0.50), and AUTIC and CD31 (r = 0.56).

Conclusion

TTE and CEE parameters were different between benign and malignant cardiac tumors. CEE is helpful to differentiate the properties of cardiac tumors. There is a correlation between CEE parameters and IHC markers. AUTIC and TPI/MPI can reflect the proliferation and invasion of tumors.

Conventional ultrasound and contrast-enhanced ultrasound radiomics in breast cancer and molecular subtype diagnosis

Objectives

This study aimed to explore the value of conventional ultrasound (CUS) and contrast-enhanced ultrasound (CEUS) radiomics to diagnose breast cancer and predict its molecular subtype.

Method

A total of 170 lesions (121 malignant, 49 benign) were selected from March 2019 to January 2022. Malignant lesions were further divided into six categories of molecular subtype: (non-)Luminal A, (non-)Luminal B, (non-)human epidermal growth factor receptor 2 (HER2) overexpression, (non-)triple-negative breast cancer (TNBC), hormone receptor (HR) positivity/negativity, and HER2 positivity/negativity. Participants were examined using CUS and CEUS before surgery. Regions of interest images were manually segmented. The pyradiomics toolkit and the maximum relevance minimum redundancy algorithm were utilized to extract and select features, multivariate logistic regression models of CUS, CEUS, and CUS combined with CEUS radiomics were then constructed and evaluated by fivefold cross-validation.

Results

The accuracy of the CUS combined with CEUS model was superior to CUS model (85.4% vs. 81.3%, p<0.01). The accuracy of the CUS radiomics model in predicting the six categories of breast cancer is 68.2% (82/120), 69.3% (83/120), 83.7% (100/120), 86.7% (104/120), 73.5% (88/120), and 70.8% (85/120), respectively. In predicting breast cancer of Luminal A, HER2 overexpression, HR-positivity, and HER2 positivity, CEUS video improved the predictive performance of CUS radiomics model [accuracy=70.2% (84/120), 84.0% (101/120), 74.5% (89/120), and 72.5% (87/120), p<0.01].

Conclusion

CUS radiomics has the potential to diagnose breast cancer and predict its molecular subtype. Moreover, CEUS video has auxiliary predictive value for CUS radiomics.

Multimodal ultrasound features of breast cancers: correlation with molecular subtypes

OBJECTIVES

To investigate whether multimodal intratumour and peritumour ultrasound features correlate with specific breast cancer molecular subtypes.

METHODS

From March to November 2021, a total of 85 patients with histologically proven breast cancer underwent B-mode, real-time elastography (RTE), colour Doppler flow imaging (CDFI) and contrast-enhanced ultrasound (CEUS). The time intensity curve (TIC) of CEUS was obtained, and the peak and time to peak (TTP) were analysed. Chi-square and binary logistic regression were used to analyse the connection between multimodal ultrasound imaging features and breast cancer molecular subtype.

RESULTS

Among 85 breast cancers, the subtypes were as follows: luminal A (36 cases, 42.4%), luminal B (20 cases, 23.5%), human epidermal growth factor receptor-2 positive (HER2+) (16 cases, 18.8%), and triple negative breast cancer (TNBC) (13 cases, 15.3%). Binary logistic regression models showed that RTE (P < 0.001) and CDFI (P = 0.036) were associated with the luminal A cancer subtype (C-index: 0.741), RTE (P = 0.016) and the peak ratio between intratumour and corpus mamma (P = 0.036) were related to the luminal B cancer subtype (C-index: 0.788). The peak ratio between peritumour and intratumour (P = 0.039) was related to the HER2 + cancer subtype (C-index: 0.859), and CDFI (P = 0.002) was associated with the TNBC subtype (C-index: 0.847).

CONCLUSIONS

Multimodal ultrasound features could be powerful predictors of specific breast cancer molecular subtypes. The intra- and peritumour CEUS features play assignable roles in separating luminal B and HER2 + breast cancer subtypes.

Management of Intraductal Papilloma of the Breast Diagnosed on Core Needle Biopsy: Latest Controversies

Intraductal papillomas (IDPs), including central papilloma and peripheral papilloma, are common in the female population. Due to the lack of specific clinical manifestations of IDPs, it is easy to misdiagnose or miss diagnose. The difficulty of differential diagnosis using imaging techniques also contributes to these conditions. Histopathology is the gold standard for the diagnosis of IDPs while the possibility of under sample exists in the percutaneous biopsy. There have been some debates about how to treat asymptomatic IDPs without atypia diagnosed on core needle biopsy (CNB), especially when the upgrade rate to carcinoma is considered. This article concludes that further surgery is recommended for IDPs without atypia diagnosed on CNB who have high-risk factors, while appropriate imaging follow-up may be suitable for those without risk factors.

Non-mass Breast Lesions: Could Multimodal Ultrasound Imaging Be Helpful for Their Diagnosis?

Objective: To develop a prediction model for discriminating malignant from benign breast non-mass-like lesions (NMLs) using conventional ultrasound (US), strain elastography (SE) of US elastography and contrast-enhanced ultrasound (CEUS). Methods: A total of 101 NMLs from 100 patients detected by conventional US were enrolled in this retrospective study. The characteristics of NMLs in conventional US, SE and CEUS were compared between malignant and benign NMLs. Histopathological results were used as the reference standard. Binary logistic regression analysis was performed to identify the independent risk factors. A multimodal method to evaluate NMLs based on logistic regression was developed. The diagnostic performance of conventional US, US + SE, US + CEUS and the combination of these modalities was evaluated and compared. Results: Among the 101 lesions, 50 (49.5%) were benign and 51 (50.5%) were malignant. Age ≥45 y, microcalcifications in the lesion, elasticity score >3, earlier enhancement time and hyper-enhancement were independent diagnostic indicators included to establish the multimodal prediction method. The area under the receiver operating characteristic curve (AUC) of US + SE + CEUS was significantly higher than that of US (p < 0.0001) and US + SE (p < 0.0001), but there was no significant difference between the AUC of US + SE + CEUS and the AUC of US + CEUS (p = 0.216). Conclusion: US + SE + CEUS and US + CEUS could significantly improve the diagnostic efficiency and accuracy of conventional US in the diagnosis of NMLs.

Radiomic Signatures Derived from Hybrid Contrast-Enhanced Ultrasound Images (CEUS) for the Assessment of Histological Characteristics of Breast Cancer: A Pilot Study

The purpose of this study was to evaluate the diagnostic performance of radiomic features extracted from standardized hybrid contrast-enhanced ultrasound (CEUS) data for the assessment of hormone receptor status, human epidermal growth factor receptor 2 (HER2) status, tumor grade and Ki-67 in patients with primary breast cancer.

METHODS

This prospective study included 72 patients with biopsy-proven breast cancer who underwent CEUS examinations between October 2020 and September 2021.

RESULTS

A radiomic analysis found the WavEnHH_s_4 parameter as an independent predictor associated with the HER2+ status with 76.92% sensitivity, and 64.41% specificity and a prediction model that could differentiate between the HER2 entities with 76.92% sensitivity and 84.75% specificity. The RWavEnLH_s-4 parameter was an independent predictor for estrogen receptor (ER) status with 55.93% sensitivity and 84.62% specificity, while a prediction model (RPerc01, RPerc10 and RWavEnLH_s_4) could differentiate between the progesterone receptor (PR) status with 44.74% sensitivity and 88.24% specificity. No texture parameter showed statistically significant results at the univariate analysis when comparing the Nottingham grade and the Ki-67 status.

CONCLUSION

Our preliminary data indicate a potential that hybrid CEUS radiomic features allow the discrimination between breast cancers of different receptor and HER2 statuses with high specificity. Hybrid CEUS radiomic features might have the potential to provide a noninvasive, easily accessible and contrast-agent-safe method to assess tumor biology before and during treatment.

Association Between Contrast-Enhanced Ultrasound Characteristics and Molecular Subtypes of Breast Cancer

OBJECTIVE

This study aimed to investigate the correlation between contrast-enhanced ultrasound (CEUS) features and molecular subtypes of breast cancer (BC).

METHODS

A total of 116 patients (116 lesions) with pathologically diagnosed BC who received conventional ultrasound and CEUS before surgery were enrolled in this study. BC molecular subtypes were identified by postoperative pathological and immunohistochemical analysis as Luminal A (LA), Luminal B (LB), HER2 (H2) over-expression, and triple-negative (TN). Qualitative and quantitative CEUS characteristics were analyzed by one-way analysis of variance (continuous variables) or Pearson's χ² test or Fisher's exact probability method (categorical variables).

RESULTS

There were significant differences in enhancement speed and enhancement degree among the four subtypes (P < .05). The area under the curve (AUC), time to peak (TTP), and peak intensity (PI) differed among the four subtypes (P < .05). The AUC of the LA subtype (305.1 ± 188.4) was significantly smaller compared with the H2 (535.7 ± 222.0, P = .007) and TN subtypes (496.6 ± 254.7, P = .019). In addition, TTP was shorter in the H2 subtype (19.8 ± 4.9) compared with the other subtypes, and was significantly shorter than in the LA subtype (26.3 ± 7.2, P = .008) and LB subtype (23.1 ± 6.7, P = .036). The PI of the LA subtype (4.7 ± 2.3) was significantly lower than that of the LB (6.6 ± 2.3, P = .027), H2 (7.4 ± 2.2, P = .005), and TN subtypes (6.9 ± 2.6, P = .014).

CONCLUSIONS

CEUS features differed significantly among different molecular subtypes of BC. The enhancement patterns and parameters may be important predictive features of different subtypes of BC.

Comparison of Linear and Convex-Array Transducers in Assessing the Enhancement Characteristics of Suspicious Breast Lesions at Contrast-Enhanced Ultrasound (CEUS)

The purpose of this study was to determine the observer agreement in assessing the enhancement pattern of suspicious breast lesions with contrast-enhanced ultrasound (CEUS) using high and low frequency transducers. Methods: This prospective study included 70 patients with suspicious breast lesions detected at mammography and/or ultrasound and classified according to the American College of Radiology (ACR) Breast Imaging-Reporting and Data System (BI-RADS) in 4A, 4B, 4C, or 5, who underwent CEUS examinations between October 2020 and August 2021. Results: Participants’ ages ranged from 28 to 83 years (48.5 + 6.36, mean age + SD). We obtained a substantial agreement for the first reader (kappa = 0.614, p < 0.001) and a perfect agreement for the second and third reader (kappa = 1, p < 0.001) between the two transducers for the uptake pattern. A moderate agreement for the second and third reader (kappa = 0.517 and 0.538, respectively, p < 0.001) and only a fair agreement (kappa = 0.320, p < 0.001) in the case of the first reader for the perilesional enhancement was observed. We obtained an excellent inter-observer agreement (Cronbach’s Alpha coefficient = 0.960, p < 0.001) for the degree of enhancement, a good inter-observer agreement for the uptake pattern and perilesional enhancement (Cronbach’s Alpha coefficient = 0.831 and 0.853, respectively, p < 0.001), and a good and acceptable inter-observer agreement for internal homogeneity, perfusion defects and margins of the lesions (Cronbach’s Alpha coefficient = 0.703, 0.703 and 0.792, respectively, p < 0.001) concerning the evaluation of breast lesions with the linear-array transducer. Conclusions: The evaluation of suspicious breast lesions by three experts with high-frequency linear-array transducer and low-frequency convex-array transducer was comparable in terms of uptake pattern and perilesional enhancement. The agreement regarding the evaluation of the degree of enhancement, the internal homogeneity, and the perfusion defects varied between fair and substantial. For all CEUS characteristics, the inter-observer agreement was superior for linear-array transducer, which leads to more a homogeneous and reproducible interpretation.

Domain Knowledge Powered Deep Learning for Breast Cancer Diagnosis Based on Contrast-Enhanced Ultrasound Videos

In recent years, deep learning has been widely used in breast cancer diagnosis, and many high-performance models have emerged. However, most of the existing deep learning models are mainly based on static breast ultrasound (US) images. In actual diagnostic process, contrast-enhanced ultrasound (CEUS) is a commonly used technique by radiologists. Compared with static breast US images, CEUS videos can provide more detailed blood supply information of tumors, and therefore can help radiologists make a more accurate diagnosis. In this paper, we propose a novel diagnosis model based on CEUS videos. The backbone of the model is a 3D convolutional neural network. More specifically, we notice that radiologists generally follow two specific patterns when browsing CEUS videos. One pattern is that they focus on specific time slots, and the other is that they pay attention to the differences between the CEUS frames and the corresponding US images. To incorporate these two patterns into our deep learning model, we design a domain-knowledge-guided temporal attention module and a channel attention module. We validate our model on our Breast-CEUS dataset composed of 221 cases. The result shows that our model can achieve a sensitivity of 97.2% and an accuracy of 86.3%. In particular, the incorporation of domain knowledge leads to a 3.5% improvement in sensitivity and a 6.0% improvement in specificity. Finally, we also prove the validity of two domain knowledge modules in the 3D convolutional neural network (C3D) and the 3D ResNet (R3D).

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.

The role of contrast-enhanced ultrasound in the diagnosis of malignant non-mass breast lesions and exploration of diagnostic criteria

OBJECTIVES

To assess the value of contrast-enhanced ultrasound (CEUS) for diagnosing malignant non-mass breast lesions (NMLs) and to explore the CEUS diagnostic criteria.

METHODS

A total of 116 patients with 119 NMLs detected by conventional US were enrolled. Histopathological results were used as the reference standard. The enhancement characteristics of NMLs in CEUS were compared between malignant and benign NMLs. The CEUS diagnostic criteria for malignant NMLs were established using independent diagnostic indicators identified by binary logistic regression analysis. The diagnostic performance of Breast Imaging Reporting and Data System-US (BI-RADS-US), CEUS, and BI-RADS-US combined with CEUS was evaluated and compared.

RESULTS

Histopathological results showed 63 and 56 benign and malignant NMLs. Enhancement degree (OR = 5.75, p = 0.003), enhancement area (OR = 4.25, p = 0.005), and radial or penetrating vessels (OR = 7.54, p = 0.003) were independent diagnostic indicators included to establish the CEUS diagnostic criteria. The sensitivity and specificity of BI-RADS-US, CEUS, and BI-RADS-US combined with CEUS were 100 and 30.2%, 80.4 and 74.6%, and 94.6 and 77.8%, respectively; the corresponding areas under the receiver operating characteristic curve (AUC) were 0.819, 0.775, and 0.885, respectively.

CONCLUSIONS

CEUS has a high specificity in malignant NML diagnosis based on the diagnostic criteria including enhancement degree, enhancement area, and radial or penetrating vessels, but with lower sensitivity than BI-RADS-US. The combination of CEUS and BI-RADS-US is an effective diagnostic tool with both high sensitivity and specificity for the diagnosis of malignant NMLs.

ADVANCES IN KNOWLEDGE

In this study, we assessed the diagnostic value of CEUS for malignant NMLs and constructed a feasible diagnostic criterion. We further revealed that the combination of CEUS and BI-RADS-US has a high diagnostic value for malignant NMLs.

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.

Breast Ultrasound Microvascular Imaging and Radiogenomics

Microvascular ultrasound (US) techniques are advanced Doppler techniques that provide high sensitivity and spatial resolution for detailed visualization of low-flow vessels. Microvascular US imaging can be applied to breast lesion evaluation with or without US contrast agents. Microvascular US imaging without a contrast agent uses a sophisticated wall filtering system to selectively obtain low-flow Doppler signals from overlapped artifacts. Microvascular US imaging with second-generation contrast agents amplifies flow signals and makes them last longer, which facilitates hemodynamic evaluation of breast lesions. In this review article, we will introduce various microvascular US techniques, explain their clinical applications in breast cancer diagnosis and radiologic-histopathologic correlation, and provide a summary of a recent radiogenomic study using microvascular US.

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.

Correlation between the contrast-enhanced ultrasound image features and axillary lymph node metastasis of primary breast cancer and its diagnostic value

PURPOSE

To analyze the correlation between contrast-enhanced ultrasound image features and axillary lymph node metastasis of primary breast cancer and its diagnostic value.

METHODS

In this study, 64 patients with axillary lymph node metastasis of primary breast cancer diagnosed and treated in our hospital from February 2011 to March 2013 were collected as an observation group, and 54 patients without axillary lymph node metastasis were collected as a control group. All patients underwent a contrast-enhanced ultrasound examination, and the correlation between the contrast-enhanced ultrasound image features and axillary lymph node metastasis and its diagnostic value were analyzed. They were divided into two groups according to their survival conditions: the group with good efficacy and group with poor efficacy, and the prognostic factors of breast cancer in the two groups were analyzed.

RESULTS

There were statistical differences in the peripheral acoustic halo, blood flow classification, ratio of length to diameter (L/D), maximum cortical thickness, and enhancement mode of lymph nodes between the two groups (p < 0.05). The area under ROC curve for diagnosis of axillary lymph node metastasis by contrast-enhanced ultrasound was 0.854, sensitivity was 83.33%, and specificity was 87.5%; L/D and enhancement mode were independent prognostic factors for breast cancer.

CONCLUSIONS

Contrast-enhanced ultrasound image features have diagnostic and prognostic value for axillary lymph node metastasis of breast cancer.

Correlation of contrast-enhanced ultrasound features with prognostic factors in invasive ductal carcinomas of the breast

OBJECTIVES

To correlate contrast-enhanced ultrasound (CEUS) features with pathological prognostic factors of breast invasive ductal carcinomas (IDCs).

METHODS

169 patients who were admitted to our hospital with confirmed IDCs diagnosed between August 2017 and June 2019 were selected. CEUS indicators included the time of contrast agent entered the lesion, the degree of enhancement, the boundary of the lesion, whether there was perfusion defect and nourishing blood vessels, and etc. These parameters correlated with traditional prognostic factors (tumour size, histological grade, axillary lymph node status) and immunohistochemical biomarkers (ER, PR, c-erbB-2, Ki-67, and TOPO-II).

RESULTS

Perfusion defects after enhancement were predictive factors of PR negative expression (r = - 0.318, OR = 0.239) and TOPO-II overexpression (r = 0.284, OR = 3.577). Centripetal enhancement was negatively correlated with ER expression (r = - 0.350, OR = 0.246). The lesions with a larger range after enhancement than the conventional ultrasound had a higher histological grade (r = 0.215). Perfusion defects were positively correlated with lymph node metastasis (r = 0.221) and negatively correlated with the expression of ER and PR (r = - 0.342, r = - 0.318).

CONCLUSIONS

Contrast-enhanced ultrasound features of IDCs have a certain correlation with pathological prognostic factors, which is conducive in assessing the prognosis of these patients.

Multimode ultrasonic technique is recommended for the differential diagnosis of thyroid cancer

Background

B-mode ultrasound is one of the most commonly used imaging techniques for evaluating thyroid nodules due to its noninvasive property and excellent performance in terms of discriminating between benign and malignant nodules. However, the accuracy of differential diagnosis strongly depends on the experience of ultrasonographers. In addition to B-mode ultrasound, the elastic mode and contrast-enhanced mode have shown complimentary value in the diagnosis of thyroid nodules. The combination of multiple modes in ultrasonic techniques may effectively undermine diagnostic subjectiveness and improve accuracy. In this study, we evaluated the diagnostic value of combining the three ultrasonic modes for differentiating thyroid cancers.

Methods

In this retrospective study, we analyzed a total of 196 thyroid nodules with suspected malignancies from 185 patients who gave informed consent. Xi’an Jiaotong University granted ethical approval (No. 2018200) to carry out the study within its facilities. All the patients received ultrasonic examinations with the B mode, elastic mode and contrast-enhanced mode, followed by histopathological confirmation by fine-need aspiration or surgery. A predictive multivariate logistic regression model was selected to integrate the variety of data obtained from the three modes.

Results

The combination of three ultrasonic techniques for differentiating malignant from benign thyroid nodules showed the highest diagnostic accuracy of 0.985 compared to the B mode alone (0.841) and the two-mode combination. The accuracy of the B mode combined with the elastic technique was 0.954, and the accuracy of the B mode combined with the contrast-enhanced technique was 0.960.

Discussion

Multimode ultrasonic techniques should be recommended to patients with suspected malignant thyroid nodules in routine clinical practice.

Characteristics of contrast-enhanced ultrasonography and strain elastography of locally advanced breast cancer

Background

Locally advanced breast cancer (LABC) is one of the subgroups of invasive breast cancer. The treatment of LABC is neoadjuvant chemotherapy (NAC) before surgery, which is different from the others. The study aimed to analyze and compare the characteristics of conventional ultrasound, contrast-enhanced ultrasonography (CEUS) and strain elastography (SE) in LABC patients who have different treatment outcomes, and to provide help for LABC in the imaging diagnosis and clinic treatment.

Methods

From May 2018 to April 2019, 36 patients (40 lesions) of LABC were enrolled, which diagnosed by puncture biopsy. According to the clinical evaluation, these patients were recommended to undergo pre-operative NAC followed by surgery. All patients underwent conventional ultrasound, CEUS and SE before puncture. According to postoperative pathological grading and follow-up, the patients were divided into effective and ineffective groups. We summarized and compared the features of conventional ultrasound, CEUS and SE of patients in two groups. The correlation between the imaging characteristics and the postoperative pathological grading was also analyzed.

Results

Conventional ultrasonic features of LABC: the most lesions of LABC were mass type (32/40, 80.0%), and all lesions were irregular. Most of lesions showed unclear boundaries (39/40, 97.5%), heterogeneous echoes (38/40, 95.0%), and internal calcifications (24/40, 60.0%). Most of lesions had hyperechoic halos (31/40, 77.5%), aspect ratio less than or equal to 1 (34/40, 85.0%), and blood flow grading was III (36/40, 90.0%). CEUS features of LABC: compared with the surrounding normal tissues, all the lesions (40/40,100.0%) were highly enhanced. Most of lesions (35/40, 87.5%) were uneven enhanced. The main enhancement mode was "fast in and slow out" (39/40, 97.5%). There were totally 25 lesions which had "solar sign" (25/40, 62.5%). SE features of LABC: the average visual elastography score of the lesions was 4.28±0.67, the maximum strain rate (E1) of the lesions averaged 4.88±0.54, and the overall strain rate of the lesion averaged 4.14±0.72. There was no significant difference between effective and ineffective groups in the characteristics of conventional ultrasound, CEUS and SE. There was a correlation between the appearance of "solar sign" in CEUS and postoperative pathological grading, and the contingency coefficient was 0.564 (P<0.05). The pathological grading of patients without solar sign was higher. The other characteristics of conventional ultrasound, CEUS and SE in LABC patients had no correlation with postoperative pathological grading.

Conclusions

In LABC, the conventional ultrasound usually shows irregular shape and unclear boundaries. The aspect ratio is less than or equal to 1. CEUS showed uneven enhancement of "fast in and slow out", and "solar sign" was often seen. Elastography showed that the texture of the lesion was significantly stiffer than the surrounding normal tissue. Ultrasound imaging before NAC had no relationship with pathological complete response or not. However, "solar sign" in CEUS was an important feature and had correlation with postoperative pathological grading.

Factors influencing the performance of a diagnostic model including contrast-enhanced ultrasound in 1023 breast lesions: comparison with histopathology

Background

We aimed to investigate the influence of patient and lesion characteristics on our diagnostic model for contrast-enhanced ultrasound (CEUS) of the breast, comparing its accuracy with that of histopathology.

Methods

Conducting a study with eight medical centers, we compared 1,023 breast lesions categorized as BI-RADS 4 or 5 with the score from our newly-established CEUS-based diagnostic model, comparing the results with pathological outcomes. Univariate and multivariate logistic regression analyses were conducted to determine the influence of clinicopathological characteristics on the performance of this CEUS model.

Results

Logistic regression analysis showed that patients' age, maximum lesion diameter, and distance from the lesion's deep edge to the pectoralis major were significant independent influencing factors. The model's diagnostic accuracy was greater for patients >35 y (P=0.005), for maximum lesion diameter >20 mm, and for distance from the lesion's deep edge to the pectoralis major ≤3.05 mm. There was no significant difference in accuracy between lesions with maximum lesion diameter 10-20 and <10 mm (P=0.393).

Conclusions

The diagnostic performance of the proposed CEUS model for breast lesions is influenced by patients' age, maximum lesion diameter, and distance from the lesion's deep edge to the pectoralis major. Consideration of influencing factors is required to optimize clinical use of the CEUS model.

BI-RADS 4 breast lesions: could multi-mode ultrasound be helpful for their diagnosis?

Background

The malignant probability of Breast Imaging Reporting and Data System (BI-RADS) 4 breast lesions is 3-94%, which is a very large span, and thus leads to a high rate of unnecessary biopsy. Therefore, the differential diagnosis of benign and malignant BI-RADS 4 breast lesions has become extremely important. Thus, in this paper, we investigated the diagnostic value of conventional ultrasonography (US), contrast-enhanced ultrasound (CEUS) and shear wave elastography (SWE) for BI-RADS 4 breast lesions, and tried to figure out a multi-mode ultrasonic method for them.

Methods

From March 2016 to May 2017, 118 breast lesions that were categorized as BI-RADS 4 lesions by US were studied with CEUS and SWE. All the lesions were confirmed by pathology via surgery or vacuum-assisted biopsy. The sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of US, CEUS and SWE were analyzed. Then the diagnostic efficacies of US, CEUS, SWE and the combination of these modalities were compared. Logistic regression analysis was performed to identify the independent risk factors. A multi-mode method to evaluate BI-RADS 4 lesions based on the logistic regression was developed.

Results

Of the 118 BI-RADS 4 lesions, 74 lesions (62.7%) were benign and 44 lesions (37.3%) were malignant. The diagnostic sensitivity and specificity for US, US + CEUS, US + SWE, US + CEUS + SWE were 88.6% and 75.7%, 86.4% and 94.6%, 88.6% and 90.5%, 97.7% and 93.2%, respectively. The area under the ROC curve (AUC) of US + SWE + CEUS was significantly higher than that of US (P<0.0001), US + CEUS (P=0.020), but there was no significant difference between the AUC of US + SWE + CEUS and the AUC of US + SWE.

Conclusions

US + CEUS + SWE and US + SWE could significantly improve the diagnostic efficiency and accuracy of US in the diagnosis of BI-RADS 4 breast lesions.

A multicenter study of a contrast-enhanced ultrasound diagnostic classification of breast lesions

Purpose

To evaluate a classification model of contrast-enhanced ultrasound (CEUS) and examine the characteristics of patients with false-negative diagnosis.

Patients and methods

A retrospective secondary analysis of a multicenter trial of CEUS for breast cancer diagnosis (from August 2015 to April 2017) was undertaken. Patients (n=1,023) with Breast Imaging Reporting and Data System 4-5 lesions on B-mode ultrasound underwent CEUS. Pathological diagnoses were available from surgical or biopsy specimens for correlation. Lesion maximum diameter (LMD), distance to the papilla (DtP), distance from the superficial edge of the lesion to the skin (DtS), distance from the deep edge of the lesion to the pectoralis muscle (DtPM), and body mass index (BMI) were evaluated.

Results

Median age and BMI were 48.0 and 41.2 years and 23.2 and 22.4 kg/m² for patients with malignant and benign lesions, respectively. Overall sensitivity, specificity, and accuracy of CEUS for malignancy were 89.4%, 65.3%, and 75.8%, respectively. The patients with true-positive and false-negative diagnosis (ie, with malignant lesion) were older than those with false-positive and true-negative diagnosis (ie, with benign lesion). Patients with true-positive and false-positive diagnoses had higher BMI than patients with true-negative and false-negative diagnoses (P=0.004). Patients with true-positive and false-negative diagnoses had larger LMD and DtP, as well as smaller DtS and DtPM.

Conclusion

Older age, higher BMI, larger LMD and DtP, and smaller DtS and DtPM were associated with malignant lesions on CEUS. Patients with these characteristics should undergo further imaging.

Correlation Between Contrast-enhanced Ultrasound Characteristics (Qualitative and Quantitative) and Pathological Prognostic Factors in Breast Cancer

BACKGROUND/AIM

Little is known about the correlation between contrast-enhanced ultrasound (CEUS) characteristics and pathological prognostic factors in breast cancer. The aim of this study was to explore the correlation between CEUS characteristics and pathological prognostic factors.

PATIENTS AND METHODS

A retrospective study with 34 malignant breast lesions was conducted. CEUS characteristics included qualitative characteristics (e.g. lesion's enhancement degree and order, internal lesion homogeneity etc.) and quantitative characteristics (e.g. peak intensity, time to peak etc.). Also, pathological prognostic factors were included (e.g. tumor grade, estrogen receptor status etc.).

RESULTS

Blurred lesion margins were observed more often in tumors of high histological grade (p=0.01) and in estrogen receptor-negative tumors (p=0.049). Furthermore, perilesional enhancement was associated with positive Ki-67 expression (p=0.049), while heterogeneous internal sentinel lymph node enhancement was associated with malignant infiltration of the node (p=0.002).

CONCLUSION

CEUS has the potential to provide a prevision of pathological prognostic factors in malignant breast lesions, helping in the better early patient management.

Serum microRNA as potential biomarker to detect breast atypical hyperplasia and early-stage breast cancer

AIM

The present study aimed to identify microRNA (miRNA) that can be used for not only detecting early-stage breast cancer (BC) but also diagnosing atypical hyperplasia (AH).

MATERIALS & METHODS

RT-qPCR detected the expression levels of miRNAs and receiver operating characteristic curves were constructed to evaluate sensitivity and specificity of the assay.

RESULTS

miR-24 and miR-103a were expressed in an upward trend in serum of benign proliferative tumor subjects, while they were downregulated significantly in serum of AH (p < 0.005) and early-stage BC subjects (p < 0.005) with high sensitivity and specificity as compared with controls. Bioinformatics analysis also revealed the potential molecular mechanism through which miR-24 and miR-103a regulate tumorigenesis in BC.

CONCLUSION

miR-24 and miR-103a were valuable biomarkers for distinguishing AH and early-stage BC from healthy individuals/benign proliferative tumor patients.

Correlation Between Contrast-enhanced Ultrasound Characteristics (Qualitative and Quantitative) and Pathological Prognostic Factors in Breast Cancer

BACKGROUND/AIM

Little is known about the correlation between contrast-enhanced ultrasound (CEUS) characteristics and pathological prognostic factors in breast cancer. The aim of this study was to explore the correlation between CEUS characteristics and pathological prognostic factors.

PATIENTS AND METHODS

A retrospective study with 34 malignant breast lesions was conducted. CEUS characteristics included qualitative characteristics (e.g. lesion's enhancement degree and order, internal lesion homogeneity etc.) and quantitative characteristics (e.g. peak intensity, time to peak etc.). Also, pathological prognostic factors were included (e.g. tumor grade, estrogen receptor status etc.).

RESULTS

Blurred lesion margins were observed more often in tumors of high histological grade (p=0.01) and in estrogen receptor-negative tumors (p=0.049). Furthermore, perilesional enhancement was associated with positive Ki-67 expression (p=0.049), while heterogeneous internal sentinel lymph node enhancement was associated with malignant infiltration of the node (p=0.002).

CONCLUSION

CEUS has the potential to provide a prevision of pathological prognostic factors in malignant breast lesions, helping in the better early patient management.

Preoperative dynamic breast magnetic resonance imaging kinetic features using computer-aided diagnosis: Association with survival outcome and tumor aggressiveness in patients with invasive breast cancer

Objectives

To evaluate whether preoperative breast dynamic contrast-enhanced (DCE) magnetic resonance (MR) imaging kinetic features, assessed using computer-aided diagnosis (CAD), can predict survival outcome and tumor aggressiveness in patients with invasive breast cancer.

Materials and methods

Between March and December 2011, 301 women who underwent preoperative DCE MR imaging for invasive breast cancer, with CAD data, were identified. All MR images were retrospectively evaluated using a commercially available CAD system. The following kinetic parameters were prospectively recorded for each lesion: initial peak enhancement, the proportion of early phase medium and rapid enhancement, and the proportion of delayed phase persistent, plateau, and washout enhancement. The Cox proportional hazards model was used to determine the association between the kinetic features assessed by CAD and disease-free survival (DFS). The peak signal intensity and kinetic enhancement profiles were compared with the clinical-pathological variables.

Results

There were 32 recurrences during a mean follow-up time of 55.2 months (range, 5–72 months). Multivariate analysis revealed that a higher peak enhancement (DFS hazard ratio, 1.004 [95% confidence interval (CI): 1.001, 1.006]; P = .013) on DCE MR imaging and a triple-negative subtype (DFS hazard ratio, 21.060 [95% CI: 2.675, 165.780]; P = .004) were associated with a poorer DFS. Higher peak enhancement was significantly associated with a higher tumor stage, clinical stage, and histologic grade.

Conclusions

Patients with breast cancer who showed higher CAD-derived peak enhancement on breast MR imaging had worse DFS. Peak enhancement and volumetric analysis of kinetic patterns were useful for predicting tumor aggressiveness.

Diagnostic and prognostic values of contrast‑enhanced ultrasound combined with diffusion‑weighted magnetic resonance imaging in different subtypes of breast cancer

The present study aimed to investigate the diagnostic and prognostic values of contrast-enhanced ultrasound (CEUS) combined with diffusion-weighted magnetic resonance imaging (DW-MRI) in different subtypes of breast cancer (BC). CEUS and DW-MRI were conducted in 232 patients with BC prior to surgical treatment. Patients were categorized as having the luminal A subtype, the luminal B subtype, triple-negative subtype or the human epidermal growth factor receptor 2 (Her-2)-positive subtype according to their expression of the estrogen receptor (ER), progesterone receptor (PR) and Her-2, as detected by immunohistochemistry. The CEUS and DW-MRI parameters of patients with different subtypes of BC were obtained and analyzed. The risk factors for the prognosis of patients with different subtypes of BC were analyzed using Kaplan-Meier and COX regression analyses. The diagnostic accuracy rate of CEUS combined with DW-MRI (93.10%) was higher than that of CEUS (88.79%) or DW-MRI (82.33%) alone. The local recurrence rate and distant metastasis rate of the Her-2-positive subtype were the highest among all the subtypes. Furthermore, patients with Her-2-positive BC exhibited a higher proportion of lesions with indistinct margins and histological grade III. Lymph node metastasis and BC subtype were independent risk factors for the prognosis of BC. The overall survival and disease-free survival of patients with the luminal A subtype were higher than those of patients with the Her-2-positive subtype. The results of the current study therefore indicate that CEUS combined with DW-MRI is more effective at diagnosing the different subtypes of BC than either CEUS or DW-MRI alone.