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

A Prospective Multicenter Study on the Additive Value of Contrast-Enhanced Ultrasound for Biopsy Decision of Ultrasound BI-RADS 4 Breast Lesions

OBJECTIVE

The main aim of this study was to determine whether the use of contrast-enhanced ultrasound (CEUS) could improve the categorization of suspicious breast lesions based on the Breast Imaging Reporting and Data System (BI-RADS), thereby reducing the number of benign breast lesions referred for biopsy.

METHODS

This prospective study, conducted between January 2017 and December 2018, enrolled consenting patients from eight teaching hospitals in China, who had been diagnosed with solid breast lesions classified as BI-RADS 4 using conventional ultrasound. CEUS was performed within 1 wk of diagnosis for reclassification of breast lesions. Histopathological results obtained from core needle biopsies or surgical excision samples served as the reference standard. The simulated biopsy rate and cancer-to-biopsy yield were used to compare the accuracy of CEUS and conventional ultrasound (US).

RESULTS

Among the 1490 lesions diagnosed as BI-RADS 4 with conventional ultrasound, 486 malignant and 1004 benign lesions were confirmed based on histology. Following CEUS, 2, 395, and 211 lesions were reclassified as CEUS-based BI-RADS 2, 3, and 5, respectively, while 882 (59%) remained as BI-RADS 4. The actual cancer-to-biopsy yield based on US was 32.6%, which increased to 43.4% when CEUS-based BI-RADS 4A was used as the cut-off point to recommend biopsy. The simulated biopsy rate decreased to 73.4%. Overall, in this preselected BI-RADS 4 population, only 2.5% (12/486) of malignant lesions would have been miscategorized as BI-RADS 3 using CEUS-based reclassification. The diagnostic accuracy, sensitivity, and specificity of contrast-enhanced ultrasound reclassification were 57.65%, 97.53%, and 38.35%, respectively.

CONCLUSION

Our collective findings indicate that CEUS is a valuable tool in further triage of BI-RADS category 4 lesions and facilitates a reduction in the number of biopsies while increasing the cancer-to-biopsy yield.

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.

Determining whether the diagnostic value of B-ultrasound combined with contrast-enhanced ultrasound and shear wave elastography in breast mass-like and non-mass-like lesions differs: a diagnostic test

Background

Mass-like (ML) and non-mass-like (NML) are two manifestations of breast lesions on ultrasound. Contrast-enhanced ultrasound (CEUS) can make up for the limitation of B-ultrasound (US) in the observation of focal blood flow, and shear wave elastography (SWE) can supplement the hardness information of the lesion. The present study aimed to analyze the characteristic manifestations of US, CEUS, and SWE in NML and ML breast and evaluate whether the diagnostic performance of these three ultrasound techniques differs in terms of differentiating between benign and malignant breast lesions.

Methods

From January to August 2021, 382 patients (417 breast lesions) underwent US, CEUS, and SWE examinations. Of these, 204 women (218 breast lesions) were included in our study due to subsequent biopsy or surgery with pathological findings. The patients were divided into ML and NML groups according to the ultrasound characteristics, and the differences in multimodal ultrasound performance between benign and malignant NML and benign and malignant ML breast lesions were compared. The diagnostic performance of US, US + CEUS, US + SWE, US + CEUS + SWE for ML, NML and all breast lesions was evaluated by analyzing sensitivity, specificity and area under receiver operating characteristic (ROC) curve (AUC).

Results

Pathologically, the 218 lesions included 96 malignant and 122 benign breast lesions. The sensitivity and specificity of US + CEUS + SWE in all lesion groups, ML group and NML group were 92.7% and 90.2%, 95.9% and 90.3%, 91.3% and 79.3%, respectively. In all breast group, AUCs of US + CEUS, US + SWE, US + CEUS + SWE were statistically different from AUC of US (P=0.0010, 0.0001, 0.0001). In the ML group, the AUC of US + CEUS, US + SWE, US + CEUS + SWE were statistically different from that of US (P=0.0120, 0.0008, 0.0002). In the NML group, there was a statistical difference between US + SWE and US AUC (P=0.0149).

Conclusions

US, CEUS, and SWE have an important diagnostic value for benign and malignant ML and NML breast lesions. Multimodal ultrasound combined with US, CEUS, and SWE can improve the diagnostic efficacy in distinguishing between benign and malignant ML and NML lesions.

Accuracy of conventional ultrasound, contrast-enhanced ultrasound and dynamic contrast-enhanced magnetic resonance imaging in assessing the size of breast cancer

OBJECTIVE

This study was performed to investigate the accuracy of conventional ultrasound (US), contrast-enhanced US (CEUS), and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in assessing the size of breast cancer.

METHODS

In total, 49 breast cancer lesions of 48 patients were included in this study. The inclusion criteria were the performance of total mastectomy or breast-conserving surgery for treatment of breast cancer in our hospital from January 2017 to December 2020 with complete pathological results, as well as the performance of conventional US, CEUS, and DCE-MRI examinations with complete results. The exclusion criteria were non-mass breast cancer shown on conventional US or DCE-MRI, including that found on CEUS with no boundary with surrounding tissues and no confirmed tumor scope; a tumor too large to be completely displayed in the US section, thus affecting the measurement results; the presence of two nodules in the same breast that were too close to each other to be distinguished by any of the three imaging methods; and treatment with preoperative chemotherapy. Preoperative conventional US, CEUS, and DCE-MRI examinations were performed. The postoperative pathological results were taken as the gold standard. The lesion size was represented by its maximum diameter. The accuracy, overestimation, and underestimation rates of conventional US, CEUS, and DCE-MRI were compared.

RESULTS

The maximum lesion diameter on US, CEUS, DCE-MRI and pathology were 1.62±0.63 cm (range, 0.6-3.5 cm), 2.05±0.75 cm (range, 1.0-4.0 cm), 1.99±0.74 cm (range, 0.7-4.2 cm) and 1.92±0.83 cm (range, 0.5-4.0 cm), respectively. The lesion size on US was significantly smaller than that of postoperative pathological tissue (P <  0.05). However, there was no significant difference between the CEUS or DCE-MRI results and the pathological results. The underestimation rate of conventional US (55.1%, 27/49) was significantly higher than that of CEUS (20.4%, 10/49) and DCE-MRI (24.5%, 12/49) (P <  0.001 and P = 0.002, respectively). There was no significant difference in the accuracy of CEUS (36.7%, 18/49) and DCE-MRI (34.7%, 17/49) compared with conventional US (26.5%, 13/49); however, the accuracy of both groups tended to be higher than that of conventional US. The overestimation rate of CEUS (42.9%, 21/49) and DCE-MRI (40.8%, 20/49) was significantly higher than that of conventional US (18.4%, 9/49) (P = 0.001 and P = 0.015, respectively).

CONCLUSIONS

CEUS and DCE-MRI show similar performance when evaluating the size of breast cancer. However, CEUS is more convenient, has a shorter operation time, and has fewer restrictions on its use. Notably, conventional US is more prone to underestimate the size of lesions, whereas CEUS and DCE-MRI are more prone to overestimate the size.

Modified Model for Diagnosing Breast Imaging Reporting and Data System Category 3 to 5 Breast Lesions: Retrospective Analysis and Nomogram Development

OBJECTIVES

The aim of this study was to explore a modified model to simplify the diagnostic process for American College of Radiology Breast Imaging Reporting and Data System category 3 to 5 breast lesions and evaluate the model's diagnostic efficacy.

METHODS

A retrospective review was conducted of breast lesions examined by B-mode ultrasound (US) and contrast-enhanced ultrasound (CEUS) and diagnosed by histopathologic examination from October 2016 to August 2019. The US characteristics of a combined model (US + CEUS model) with relatively high diagnostic value were selected by a lasso regression analysis to establish a modified model. Two nomograms were developed. The results were internally validated by bootstrap resampling.

RESULTS

Overall, 206 breast lesions in 198 patients, 136 benign and 70 malignant, were included. Ultrasound characteristics included in the modified model were shape, margin, microcalcification, enhanced intensity, enhanced scope, and enhanced time. For the US + CEUS model and modified model, sensitivities were 94.3% and 93.3%; specificities were 85.9% and 81.4%; accuracies were 89.3% and 88.7% and areas under the curve were 0.957 and 0.944, respectively. No statistically significant differences were seen in the diagnostic efficacies of the models (P = .097). Bootstrap-corrected sensitivities, specificities. and accuracies of the models were consistent with these results. Bootstrap-corrected areas under the curve for the US + CEUS model and the modified model were 0.955 and 0.940, respectively.

CONCLUSIONS

The modified model with fewer indicators conveniently and effectively diagnosed the malignancy of Breast Imaging Reporting and Data System category 3 to 5 breast lesions without reducing diagnostic efficacy.

Prospective evaluation of contrast-enhanced ultrasound of breast BI-RADS 3-5 lesions

BACKGROUND

To determine the benefit of contrast-enhanced ultrasound (CEUS) in the assessment of breast lesions.

METHODS

A standardized contrast-enhanced ultrasound was performed in 230 breast lesions classified as BI-RADS category 3 to 5. All lesions were subjected to qualitative and quantitative analysis. MVI (MicroVascular Imaging) technique was used to derive qualitative analysis parameters; blood perfusion of the lesions was assessed (perfusion homogeneity, type of vascularization, enhancement degree). Quantitative analysis was conducted to estimate perfusion changes in the lesions within drawn regions of interest (ROI); parameters TTP (time to peak), PI (peak intensity), WIS (wash in slope), AUC (area under curve) were obtained from time intensity (TI) curves. Acquired data were statistically analyzed to assess the ability of each parameter to differentiate between malignant and benign lesions. The combination of parameters was also evaluated for the possibility of increasing the overall diagnostic accuracy. Biological nature of the lesions was verified by a pathologist. Benign lesions without histopathological verification (BI-RADS 3) were followed up for at least 24 months.

RESULTS

Out of 230 lesions, 146 (64%) were benign, 67 (29%) were malignant, 17 (7%) lesions were eliminated. Malignant tumors showed statistically significantly lower TTP parameters (sensitivity 77.6%, specificity 52.7%) and higher WIS values (sensitivity 74.6%, specificity 66.4%) than benign tumors. Enhancement degree also proved to be statistically well discriminating as 55.2% of malignant lesions had a rich vascularity (sensitivity 89.6% and specificity 48.6%). The combination of quantitative analysis parameters (TTP, WIS) with enhancement degree did not result in higher accuracy in distinguishing between malignant and benign breast lesions.

CONCLUSIONS

We have demonstrated that contrast-enhanced breast ultrasound has the potential to distinguish between malignant and benign lesions. In particular, this method could help to differentiate lesions BI-RADS category 3 and 4 and thus reduce the number of core-cut biopsies performed in benign lesions. Qualitative analysis, despite its subjective element, appeared to be more beneficial. A combination of quantitative and qualitative analysis did not increase the predictive capability of CEUS.

Diagnostic efficacy of contrast-enhanced ultrasound for breast lesions of different sizes: a comparative study with magnetic resonance imaging

OBJECTIVE

This study aimed to compare the diagnostic performance of contrast-enhanced ultrasound (CEUS), MRI, and the combined use of the two modalities for differentiating breast lesions of different sizes.

METHODS

A total of 406 patients with 406 solid breast masses detected by conventional ultrasound underwent both CEUS and MRI scans. Histological results were used as reference standards. The lesions were categorized into three groups according to size (Group 1, ≤ 20 mm; Group 2, > 20 mm, Group 3: total lesions). Sensitivity, specificity, accuracy, and receiver operating characteristic (ROC) curve analysis were used to assess the diagnostic performance of these imaging methods for breast lesions.

RESULTS

There were 194 benign and 212 malignant breast lesions according to the histological diagnosis. Compared with MRI, CEUS demonstrated similar sensitivity in detecting breast cancer (p = 1.0000 for all) in all the three groups. With regard to specificity, accuracy, and the area under the ROC curve (Az) values, MRI showed a better performance than that shown by CEUS (p ＜0.05 for all), and the combination of the two modalities improved the diagnostic performance of CEUS alone significantly (p ＜0.05 for all) in all the three groups. However, the diagnostic specificity and accuracy of the combined method was not superior to that of MRI alone except for Group 2.

CONCLUSION

CEUS demonstrated good sensitivity in detecting breast cancer, and the combined use with MRI can optimize the diagnostic specificity and accuracy in breast cancer prediction.

ADVANCES IN KNOWLEDGE

Few studies have compared the diagnostic efficacy of CEUS and MRI, and this study is the first attempt to seek out the diagnostic values for breast lesions of variable sizes (lesions with ≤20 mm and >20 mm).

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.