Qualitative, quantitative and combination score systems in differential diagnosis of breast lesions by contrast-enhanced ultrasound

Predictive value of contrast-enhanced ultrasonography and ultrasound elastography for management of BI-RADS category 4 nonpalpable breast masses

PURPOSE

The objective of this study was to investigate the independent risk factors and associated predictive values of contrast-enhanced ultrasound (CEUS), shear wave elastography (SWE), and strain elastography (SE) for high-risk lesions (HRL) and malignant tumors (MT) among nonpalpable breast masses classified as BI-RADS category 4 on conventional ultrasound.

METHODS

This prospective study involved consecutively admitted patients with breast tumors from January 2018, aiming to explore the management of BI-RADS category 4 breast tumors using CEUS and elastography. We conducted a retrospective review of patient data, focusing on those with a history of a nonpalpable mass as the primary complaint. Pathologic findings after surgical resection served as the gold standard. The CEUS arterial-phase indices were analyzed using contrast agent arrival-time parametric imaging processing mode, while quantitative and qualitative indices were examined on ES images. Independent risk factors were identified through binary logistic regression multifactorial analysis. The predictive efficacy of different modalities was compared using a receiver operating characteristics curve. Subsequently, a nomogram for predicting the risk of HRL/MT was established based on a multifactorial logistic regression model.

RESULTS

A total of 146 breast masses from 146 patients were included, comprising 80 benign tumors, 12 HRLs, and 54 MTs based on the final pathology. There was no significant difference in pathologic size between the benign and HRL/MT groups [8.00(6.25,10.00) vs. 9.00(6.00,10.00), P = 0.506]. The diagnostic efficacy of US plus CEUS exceeded that of US plus SWE/SE for BI-RADS 4 nonpalpable masses, with an AUC of 0.954 compared to 0.798/0.741 (P ＜ 0.001). Further stratified analysis revealed a more pronounced improvement for reclassification of BI-RADS 4a masses (AUC: 0.943 vs. 0.762/0.675, P ＜ 0.001) than BI-RADS 4b (AUC:0.950 vs. 0.885/0.796, P＞0.05) with the assistance of CEUS than SWE/SE. Employing downgrade CEUS strategies resulted in negative predictive values ranging from 95.2 % to 100.0 % for BI-RADS 4a and 4b masses. Conversely, using upgrade nomogram strategies, which included the independent predictive risk factors of irregular enhanced shape, poor defined enhanced margin, earlier enhanced time, increased surrounding vessels, and presence of contrast agent retention, the diagnostic performance achieved an AUC of 0.947 with good calibration.

CONCLUSION

After investigating the potential of CEUS and ES in improving risk assessment and diagnostic accuracy for nonpalpable BI-RADS category 4 breast masses, it is evident that CEUS has a more significant impact on enhancing classification compared to ES, particularly for BI-RADS 4a subgroup masses. This finding suggests that CEUS may offer greater benefits in improving risk assessment and diagnostic accuracy for this specific subgroup of breast masses.

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.

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).

A Nomogram for Enhancing the Diagnostic Effectiveness of Solid Breast BI-RADS 3-5 Masses to Determine Malignancy Based on Imaging Aspects of Conventional Ultrasonography and Contrast-Enhanced Ultrasound

BACKGROUND

To establish and validate a nomogram model, which can incorporate clinical data, and imaging features of ultrasound (US) and contrast-enhanced ultrasound (CEUS), for improving the diagnostic efficiency of solid breast lesions.

PATIENTS AND METHODS

A total of 493 patients with solid breast lesions were randomly divided into training (n = 345) and validation (n = 148) cohorts with a ratio of 7:3 and, clinical data and image features of US and CEUS were reviewed and retrospectively analyzed. The breast lesions in both the training and validation cohorts were analyzed using the BI-RADS and nomogram models.

RESULTS

Five variables, including the shape and calcification features of conventional US, enhancement type and size after enhancement features of CEUS, and BI-RADS, were selected to construct the nomogram model. As compared to the BI-RADS model, the nomogram model demonstrated satisfactory discriminative function (area under the receiver operating characteristic [ROC] curves [AUC], 0.940; 95% confidence interval [CI], 0.909 to 0.971; sensitivity, 0.905; and specificity, 0.902 in the training cohort and AUC, 0.968; 95% CI, 0.941 to 0.995; sensitivity, 0.971; and specificity, 0.867 in the validation cohort). In addition, the nomogram model showed good consistency and clinical potential according to the calibration curve and DCA.

CONCLUSION

The nomogram model could identify benign from malignant breast lesions with good performance.

A Diagnostic Model for Breast Lesions With Enlarged Enhancement Extent on Contrast-Enhanced Ultrasound Improves Malignancy Prediction

OBJECTIVE

The aim of the work described here was to develop a diagnostic model based on contrast-enhanced ultrasound (CEUS) features to improve performance in predicting the probability of malignancy for breast lesions with an enlarged enhancement extent on CEUS.

METHODS

In total, 299 consecutive patients who underwent CEUS examination and had confirmed pathological results were retrospectively enrolled. Among the 299 patients, an enlarged enhancement extent on CEUS was found in 142 patients. In this special cohort, we analyzed the association of malignant pathologic results with perfusion patterns emphatically by reclassifying the patterns.

RESULTS

A diagnostic model was developed and presented as a nomogram, assessed with discrimination and calibration. Receiver operating characteristic (ROC) curve analysis revealed that the areas under the curves of the conventional perfusion and modified perfusion patterns were 0.58 and 0.76 (p < 0.001), respectively. A diagnostic model was built and exhibited good discrimination with a C-index of 0.95 (95% confidence interval: 0.91-0.98), which was confirmed to be 0.93 via internal bootstrapping validation.

CONCLUSION

The nomogram based on CEUS features provides radiologists with a quantitative tool to predict the probability of malignancy in this special cohort of breast lesions.

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.

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.

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.

B-Mode and Contrast-Enhanced Ultrasonography Aspects of Benign and Malignant Superficial Neoplasms in Dogs: A Preliminary Study

Simple Summary

In dogs, superficial neoplasms are common, and it is crucial to determine their malignancy, as this will have an impact on treatment and prognosis. So far, the diagnostic value of ultrasound modalities, such as B-mode and contrast enhanced ultrasound, for superficial neoplasms in dogs is still unclear, despite promising studies in humans. B-mode ultrasound enables assessment of the size, shape and arrangement of the neoplastic tissue, whereas contrast enhanced ultrasound enables the assessment of blood flow intensity and pattern. The aim of this study was to identify B-mode and contrast enhanced ultrasound characteristics that may be used to distinguish benign and malignant superficial neoplasms in dogs. Ultrasonographic characteristics, for which a significant difference was observed between benign and malignant neoplasms, were border definition, echogenicity, echotexture, blood flow pattern at wash-in and blood flow intensity during wash-out at the center of the neoplasm. Despite these significant differences, there was a considerable overlap in ultrasonographic characteristics between benign and malignant neoplasms. In conclusion, B-mode and contrast enhanced ultrasound might contribute to malignancy prediction; however, based on individual ultrasonographic characteristics, they seem unable to replace cytology or histopathology.

Abstract

Contrast-enhanced ultrasonography (CEUS) is considered a promising technique for differentiation of benign and malignant tumors in humans. However, few studies have assessed superficial neoplasms in dogs by means of CEUS. The aim of this study was to identify ultrasonographic criteria evaluated by B-mode ultrasound (US) and CEUS that may be used to distinguish benign and malignant superficial neoplasms in dogs. A total of 63 superficial neoplasms from 59 dogs were evaluated using B-mode US and CEUS prior to histopathologic examination. Qualitative and quantitative parameters were compared between benign and malignant neoplasms by Fischer’s exact test or fixed effects model. With B-mode US, a significant difference was found for border definition, echogenicity and echotexture. With CEUS, a significant difference was found for the enhancement pattern at wash-in and the wash-out area under the curve at the center of the neoplasm. Malignant neoplasms had on average a lower regional blood volume during the wash-out phase compared to benign neoplasms. Despite these significant differences, there was a considerable overlap in B-mode and CEUS parameters between benign and malignant neoplasms. In conclusion, B-mode US and CEUS might contribute to malignancy prediction; however, based on individual ultrasonographic parameters, they seem unable to replace cytology or histopathology.

Contrast-enhanced ultrasound of granular cell tumor in breast: A case report with review of the literature

Granular cell tumor is an infrequent, predominantly benign tumor originating from Schwann cells. Granular cell tumor of the breast (GCTB) can simulate breast malignant carcinoma on the clinical assessment. We herein present a rare case of GCTB which recurred in the contralateral breast. We believe the contrast-enhanced ultrasound (CEUS) findings of GCTB have never been described. The high similarity of breast malignant carcinoma makes its differential diagnosis difficult on the clinical and radiological features. In this report, we present the CEUS findings from a rare case of GCTB, explore the possible value of CEUS in differential diagnosis between benign breast lesions and malignant ones, and briefly review the literature.

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.

The value of contrast-enhanced ultrasound in the diagnosis of BI-RADS-US 4a lesions less than 2 cm in diameter

BACKGROUND: Breast cancer is the most common malignant tumor in women. Early diagnosis of benign and malignant breast tumors is of great significance. OBJECTIVE: To retrospectively analyze the value of contrast-enhanced ultrasonography (CEUS) in the diagnosis of Breast Imaging-Reporting and Data System (BI-RADS) 4a breast lesions less than 2 cm in diameter. METHODS: CEUS was performed for 143 breast masses less than 2 cm in diameter that were diagnosed as BI-RADS 4a by ultrasound and reclassified. Considering pathological diagnosis as the gold standard, the sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of reclassified lesions after CEUS for the diagnosis of benign and malignant masses were analyzed. RESULTS: BI-RADS 4a breast masses with a diameter less than 2 cm (n = 143) were confirmed by pathology; 103 and 40 were classified as benign and malignant, respectively. The sensitivity, specificity, PPV, and NPV of CEUS for the diagnosis were 90%, 86%, 72%, and 95%, respectively. The area under the receiver operating characteristic (ROC) curve of CEUS for the diagnosis of benign and malignant tumors after CEUS was 0.904. CONCLUSION: CEUS can help to improve the diagnostic accuracy of BI-RADS 4a masses with a diameter less than 2 cm.

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.

Imaging of Benign and Malignant Breast Lesions Using Contrast-Enhanced Ultrasound: A Pictorial Essay

ABSTRACT

Contrast-enhanced ultrasound is a promising noninvasive imaging technique for evaluating benign and malignant breast lesions, as contrast provides information about perfusion and microvasculature. Contrast-enhanced ultrasound is currently off-label use in the breast in the United States, but its clinical and investigational use in breast imaging is gaining popularity. It is important for radiologists to be familiar with the imaging appearances of benign and malignant breast masses using contrast-enhanced ultrasound. This pictorial essay illustrates enhancement patterns of various breast masses from our own experience. Pathologies include subtypes of invasive breast cancer, fibroadenomas, papillary lesions, fibrocystic change, and inflammatory processes. Contrast-enhanced ultrasound pitfalls and limitations are discussed.

Diagnostic value of artificial intelligence automatic detection systems for breast BI-RADS 4 nodules

BACKGROUND

The incidence rate of breast cancer has exceeded that of lung cancer, and it has become the most malignant type of cancer in the world. BI-RADS 4 breast nodules have a wide range of malignant risks and are associated with challenging clinical decision-making.

AIM

To explore the diagnostic value of artificial intelligence (AI) automatic detection systems for BI-RADS 4 breast nodules and to assess whether conventional ultrasound BI-RADS classification with AI automatic detection systems can reduce the probability of BI-RADS 4 biopsy.

METHODS

A total of 107 BI-RADS breast nodules confirmed by pathology were selected between June 2019 and July 2020 at Hwa Mei Hospital, University of Chinese Academy of Sciences. These nodules were classified by ultrasound doctors and the AI-SONIC breast system. The diagnostic values of conventional ultrasound, the AI automatic detection system, conventional ultrasound combined with the AI automatic detection system and adjusted BI-RADS classification diagnosis were statistically analyzed.

RESULTS

Among the 107 breast nodules, 61 were benign (57.01%), and 46 were malignant (42.99%). The pathology results were considered the gold standard; furthermore, the sensitivity, specificity, accuracy, Youden index, and positive and negative predictive values were 84.78%, 67.21%, 74.77%, 0.5199, 66.10% and 85.42% for conventional ultrasound BI-RADS classification diagnosis, 86.96%, 75.41%, 80.37%, 0.6237, 72.73%, and 88.46% for automatic AI detection, 80.43%, 90.16%, 85.98%, 0.7059, 86.05%, and 85.94% for conventional ultrasound BI-RADS classification with automatic AI detection and 93.48%, 67.21%, 78.50%, 0.6069, 68.25%, and 93.18% for adjusted BI-RADS classification, respectively. The biopsy rate, cancer detection rate and malignancy risk were 100%, 42.99% and 0% and 67.29%, 61.11%, and 1.87% before and after BI-RADS adjustment, respectively.

CONCLUSION

Automatic AI detection has high accuracy in determining benign and malignant BI-RADS 4 breast nodules. Conventional ultrasound BI-RADS classification combined with AI automatic detection can reduce the biopsy rate of BI-RADS 4 breast nodules.

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 ultrasound of breast fibromatosis: a case report

We herein present a rare case of breast fibromatosis, the contrast-enhanced ultrasonography (CEUS) findings of which we believe have never been described. The high similarity between the clinical and imaging manifestations of breast cancer makes its differential diagnosis difficult. In this report, we describe the CEUS findings of a less common type of fibromatosis, discuss the potential value of CEUS to differentiate it from malignant breast lesions, and briefly review the literature.

The Value of Nomograms in Pre-Operative Prediction of Lymphovascular Invasion in Primary Breast Cancer Undergoing Modified Radical Surgery: Based on Multiparametric Ultrasound and Clinicopathologic Indicators

The purpose of this study was to explore the value of pre-operative prediction of lymphovascular invasion (LVI) in primary breast cancer patients undergoing modified radical mastectomy and to develop a nomogram based on multiparametric ultrasound and clinicopathologic indicators. All patients with primary breast cancer confirmed by pre-operative biopsy underwent B-mode ultrasound and contrast-enhanced ultrasound examinations. Post-operative pathology was used as the gold standard to identify LVI. Lasso regression was used to select predictors most related to LVI. A nomogram was developed to calculate the diagnostic efficacy. We bootstrapped the data for 500 times to perform internal verification, drawing a calibration curve to verify prediction ability. A total of 244 primary breast cancer patients were included. LVI was observed in 77 patients. Ten predictors associated with LVI were selected by Lasso regression. The area under the curve, sensitivity, specificity and accuracy for the nomogram were 0.918, 92.2%, 76.7% and 81.6%, respectively. And the nomogram calibration curve showed good consistency between the predicted probability and the actual probability. The nomogram developed could be used to predict LVI in primary breast cancer patients undergoing modified radical mastectomy and to help in clinical decision-making.

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.

Adding contrast-enhanced ultrasound markers to conventional axillary ultrasound improves specificity for predicting axillary lymph node metastasis in patients with breast cancer

OBJECTIVE

To evaluate the diagnostic performance of contrast-enhanced ultrasound (CEUS) combined with conventional ultrasound of axillary lymph nodes (ALNs) in predicting metastatic ALNs in patients with breast cancer.

METHODS

This retrospective study included 259 patients with breast cancer who underwent conventional ultrasound and CEUS. The parameters and patterns evaluated on conventional ultrasound included short axis diameter (S), long axis/short axis (L/S) ratio, cortical thickness, resistive index (RI), lymph node (LN) morphology of greyscale ultrasound, hilum and vascular pattern. Meanwhile, enhancement pattern, wash-in time, time to peak (TP), maximum signal intensity, and duration of contrast enhancement were evaluated on CEUS. Univariate and multiple logistic regression analyses were performed to identify independent factors of ALN status. Three models (conventional ultrasound, CEUS, and combined parameters) were established. Receiver operating characteristic (ROC) curves were applied to evaluate the accuracy of the three predictive models.

RESULTS

On conventional axillary ultrasound, LN morphology and vascular pattern were independent factors in predicting metastatic ALNs. On CEUS, maximum signal intensity, duration of contrast enhancement, and TP were independent factors in predicting metastatic ALNs. When combining conventional ultrasound and CEUS features, five independent factors obtained from the conventional ultrasound and CEUS were associated with ALN status. ROC curve analysis showed that the use of CEUS markers combined with conventional ultrasound features (AUC = 0.965) was superior to the use of CEUS markers (AUC = 0.936) and conventional ultrasound features alone (AUC = 0.851).

CONCLUSION

Combining conventional ultrasound and CEUS features can enable discrimination of ALN status better than the use of CEUS and conventional ultrasound features alone.

ADVANCES IN KNOWLEDGE

The axillary lymph node status in breast cancer patients impacts the treatment decision. Our ultrasonic data demonstrated that CEUS features of ALNs in breast cancer patients could be image markers for predicting ALN status. Combining conventional ultrasound and CEUS features of ALNs can improve specificity discrimination of ALN status better than the use of CEUS and the conventional ultrasound features alone, which will help the treatment planning optimization.

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.

Value of contrast-enhanced ultrasound area ratio in identifying benign and malignant small breast masses

Background

Tumor size affects clinical staging and is closely related to prognosis. Therefore, early diagnosis of breast cancer is one of the most important methods to reduce mortality and improve prognosis. However, minimal breast cancer is difficult to differentiate from small benign breast masses due to insufficient typical malignant signs. The significantly increased range of enhancement can be an important indication for the prediction of malignancy; however, quantitative studies on the extent of enhancement are rarely reported. The purpose of this study was to investigate the value of contrast-enhanced ultrasound (CEUS) area ratio in finding benign and malignant small breast masses.

Methods

A retrospective analysis was conducted on 88 patients with breast masses confirmed by surgery or needle biopsy (the maximal diameter not over 1 cm). 88 breast masses were divided into the younger age group (not over 40 years old) and older age group (over 40 years old) according to the patient's age. The receiver operating characteristic (ROC) curve was used to determine the cutoff values of CEUS area ratio in diagnosing benign or malignant small breast masses in each group. The efficiency of different cutoff values in finding benign and malignant small breast masses of the distinct groups was analyzed.

Results

The CEUS area ratio of malignant mass was larger than benign masses (P<0.05). The CEUS area ratio of malignant masses in the younger age group was larger than that in the older age group (P<0.05). The results of the ROC curve analysis showed that the area under the curve (AUC) and the cutoff values of the entire group, the younger age group, and the older age group were 0.887, 1.65; 0.909, 1.95; and 0.908, 1.22, respectively. When the cutoff value of the older age group was reduced from 1.65 to 1.22, its diagnostic sensitivity was improved significantly (P<0.05).

Conclusions

CEUS area ratio has specific application value in finding benign and malignant small breast masses. Proper reduction of the cutoff value of elderly patients can further improve its diagnostic sensitivity without significantly reducing the specificity.

The clinical value of Arrival-time Parametric Imaging using contrast-enhanced ultrasonography in differentiating benign and malignant breast lesions

OBJECTIVES

To evaluate the clinical value of Arrival-time Parametric Imaging (At-PI) in the differentiation of benign and malignant breast lesions.

METHODS

For this ethics committee-approved retrospective study, a total of 184 breast lesions in 176 women were included and gray-scale ultrasound, contrast-enhanced ultrasound (CEUS) and At-PI were performed. In CEUS and At-PI, perfusion patterns, perfusion uniformity and color spatial distribution for lesions were analyzed qualitatively and the maximal diameter ratio of the lesion in accumulated parametric images and that in gray-scale images (MDRAI/GI) and area ratio of the lesion in accumuated parametric images and that in gray-scale images (ARAI/GI) were calculated quantitatively. Kappa and Intraclass Correlation Coefficient were used to evaluate the interobserver reproducibility for CEUS and At-PI and the intraobserver reproducibility for At-PI, respectively. The area under receiver operating characteristic (AUC), sensitivity, specificity, accuracy and positive and negative likelihood ratios (PPV, NPV) were calculated for MDRAI/GI and ARAI/GI.

RESULTS

Good interobserver and intraobserver reproducibility for At-PI were identified. In At-PI, there were statistically significant differences in perfusion patterns, color spatial distribution, MDRAI/GI and ARAI/GI between benign and malignant breast lesions (P < 0.05). The AUCs of MDRAI/GI and ARAI/GI were 0.895 and 0.954, respectively, with no significant difference between them (Z = 1.84, P > 0.05). By using the thresholds of 1.125 for MDRAI/GI and 1.21 for ARAI/GI, the sensitivity, specificity, accuracy, PPV and NPV of At-PI were 84.48%, 88.24%, 85.57%, 92.45% and 76.92%, respectively, for MDRAI/GI and 93.10%, 91.18%, 92.39%, 94.74% and 88.57%, respectively, for ARAI/GI.

CONCLUSIONS

At-PI is helpful to distinguish benign from malignant breast lesions. And MDRAI/GI and ARAI/GI are useful and efficient features for differential diagnosis.

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 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.

Evaluation of the Quadri-Planes Method in Computer-Aided Diagnosis of Breast Lesions by Ultrasonography: Prospective Single-Center Study

Background

Computer-aided diagnosis (CAD) is a tool that can help radiologists diagnose breast lesions by ultrasonography. Previous studies have demonstrated that CAD can help reduce the incidence of missed diagnoses by radiologists. However, the optimal method to apply CAD to breast lesions using diagnostic planes has not been assessed.

Objective

The aim of this study was to compare the performance of radiologists with different levels of experience when using CAD with the quadri-planes method to detect breast tumors.

Methods

From November 2018 to October 2019, we enrolled patients in the study who had a breast mass as their most prominent symptom. We assigned 2 ultrasound radiologists (with 1 and 5 years of experience, respectively) to read breast ultrasonography images without CAD and then to perform a second reading while applying CAD with the quadri-planes method. We then compared the diagnostic performance of the readers for the 2 readings (without and with CAD). The McNemar test for paired data was used for statistical analysis.

Results

A total of 331 patients were included in this study (mean age 43.88 years, range 17-70, SD 12.10), including 512 lesions (mean diameter 1.85 centimeters, SD 1.19; range 0.26-9.5); 200/512 (39.1%) were malignant, and 312/512 (60.9%) were benign. For CAD, the area under the receiver operating characteristic curve (AUC) improved significantly from 0.76 (95% CI 0.71-0.79) with the cross-planes method to 0.84 (95% CI 0.80-0.88; P<.001) with the quadri-planes method. For the novice reader, the AUC significantly improved from 0.73 (95% CI 0.69-0.78) for the without-CAD mode to 0.83 (95% CI 0.80-0.87; P<.001) for the combined-CAD mode with the quadri-planes method. For the experienced reader, the AUC improved from 0.85 (95% CI 0.81-0.88) to 0.87 (95% CI 0.84-0.91; P=.15). The kappa indicating consistency between the experienced reader and the novice reader for the combined-CAD mode was 0.63. For the novice reader, the sensitivity significantly improved from 60.0% for the without-CAD mode to 79.0% for the combined-CAD mode (P=.004). The specificity, negative predictive value, positive predictive value, and accuracy improved from 84.9% to 87.8% (P=.53), 76.8% to 86.7% (P=.07), 71.9% to 80.6% (P=.13), and 75.2% to 84.4% (P=.12), respectively. For the experienced reader, the sensitivity improved significantly from 76.0% for the without-CAD mode to 87.0% for the combined-CAD mode (P=.045). The NPV and accuracy moderately improved from 85.8% and 86.3% to 91.0% (P=.27) and 87.0% (P=.84), respectively. The specificity and positive predictive value decreased from 87.4% to 81.3% (P=.25) and from 87.2% to 93.0% (P=.16), respectively.

Conclusions

S-Detect is a feasible diagnostic tool that can improve the sensitivity, accuracy, and AUC of the quadri-planes method for both novice and experienced readers while also improving the specificity for the novice reader. It demonstrates important application value in the clinical diagnosis of breast cancer.

Trial Registration

ChiCTR.org.cn 1800019649; http://www.chictr.org.cn/showproj.aspx?proj=33094

Immunohistochemical index prediction of breast tumor based on multi-dimension features in contrast-enhanced ultrasound

Breast cancer is the leading killer of Chinese women. Immunohistochemistry index has great significance in the treatment strategy selection and prognosis analysis for breast cancer patients. Currently, histopathological examination of the tumor tissue through surgical biopsy is the gold standard to determine immunohistochemistry index. However, this examination is invasive and commonly causes discomfort in patients. There has been a lack of noninvasive method capable of predicting immunohistochemistry index for breast cancer patients. This paper proposes a machine learning method to predict the immunohistochemical index of breast cancer patients by using noninvasive contrast-enhanced ultrasound. A total of 119 breast cancer patients were included in this retrospective study. Each patient implemented the pathological examination of immunohistochemical expression and underwent contrast-enhanced ultrasound imaging of breast tumor. The multi-dimension features including 266 three-dimension features and 837 two-dimension dynamic features were extracted from the contrast-enhanced ultrasound sequences. Using the machine learning prediction method, 21 selected multi-dimension features were integrated to generate a model for predicting the immunohistochemistry index noninvasively. The immunohistochemical index of human epidermal growth factor receptor-2 (HER2) was predicted based on multi-dimension features in contrast-enhanced ultrasound sequence with the sensitivity of 71%, and the specificity of 79% in the testing cohort. Therefore, the noninvasive contrast-enhanced ultrasound can be used to predict the immunohistochemical index. To our best knowledge, no studies have been reported about predicting immunohistochemical index by using contrast-enhanced ultrasound sequences for breast cancer patients. Our proposed method is noninvasive and can predict immunohistochemical index by using contrast-enhanced ultrasound in several minutes, instead of relying totally on the invasive and biopsy-based histopathological examination. Graphical abstract Immunohistochemical index prediction of breast tumor based on multi-dimension features in contrast-enhanced ultrasound.

Performance of Computer-Aided Diagnosis in Ultrasonography for Detection of Breast Lesions Less and More Than 2 cm: Prospective Comparative Study

Background

Computer-aided diagnosis (CAD) is used as an aid tool by radiologists on breast lesion diagnosis in ultrasonography. Previous studies demonstrated that CAD can improve the diagnosis performance of radiologists. However, the optimal use of CAD on breast lesions according to size (below or above 2 cm) has not been assessed.

Objective

The aim of this study was to compare the performance of different radiologists using CAD to detect breast tumors less and more than 2 cm in size.

Methods

We prospectively enrolled 261 consecutive patients (mean age 43 years; age range 17-70 years), including 398 lesions (148 lesions>2 cm, 79 malignant and 69 benign; 250 lesions≤2 cm, 71 malignant and 179 benign) with breast mass as the prominent symptom. One novice radiologist with 1 year of ultrasonography experience and one experienced radiologist with 5 years of ultrasonography experience were each assigned to read the ultrasonography images without CAD, and then again at a second reading while applying the CAD S-Detect. We then compared the diagnostic performance of the readers in the two readings (without and combined with CAD) with breast imaging. The McNemar test for paired data was used for statistical analysis.

Results

For the novice reader, the area under the receiver operating characteristic curve (AUC) improved from 0.74 (95% CI 0.67-0.82) from the without-CAD mode to 0.88 (95% CI 0.83-0.93; P<.001) at the combined-CAD mode in lesions≤2 cm. For the experienced reader, the AUC improved from 0.84 (95% CI 0.77-0.90) to 0.90 (95% CI 0.86-0.94; P=.002). In lesions>2 cm, the AUC moderately decreased from 0.81 to 0.80 (novice reader) and from 0.90 to 0.82 (experienced reader). The sensitivity of the novice and experienced reader in lesions≤2 cm improved from 61.97% and 73.23% at the without-CAD mode to 90.14% and 97.18% (both P<.001) at the combined-CAD mode, respectively.

Conclusions

S-Detect is a feasible diagnostic tool that can improve the sensitivity for both novice and experienced readers, while also improving the negative predictive value and AUC for lesions≤2 cm, demonstrating important application value in the clinical diagnosis of breast cancer.

Trial Registration

Chinese Clinical Trial Registry ChiCTR1800019649; http://www.chictr.org.cn/showprojen.aspx?proj=33094

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.

Contrast-Enhanced Ultrasound Imaging of Breast Masses: Adjunct Tool to Decrease the Number of False-Positive Biopsy Results

OBJECTIVES

This pilot study evaluated use of contrast-enhanced ultrasound (CEUS) to reduce the number of benign breast masses recommended for biopsy.

METHODS

This prospective study included 131 consenting women, from October 2016 to June 2017, with American College of Radiology Breast Imaging Reporting and Data System category 4a, 4b, and 4c masses detected by mammography, conventional ultrasound (US), or both. Contrast-enhanced US examinations (using intravenous injection of perflutren lipid microspheres or sulfur hexafluoride lipid-type A microspheres) were performed before biopsy. Qualitative and quantitative CEUS parameters were compared with reference standard histopathologic results from biopsy of 131 masses.

RESULTS

There were 109 benign, 6 high-risk, and 16 malignant masses, with a median size of 12 mm (range, 4 to 48 mm) on conventional US imaging. Of 131 masses, 93 (71%) enhanced on CEUS imaging, including 73 of 109 (67%) benign, 6 of 6 (100%) high-risk, and 14 of 16 (87.5%) malignant. Thirty-eight lesions did not enhance, including 36 of 109 (33%) benign and 2 of 16 (12.5%) malignant. Prediction models using recursive petitioning revealed that CEUS may reduce 31% (95% confidence interval, 23%, 40%) of benign biopsies for masses that are: nonenhancing with circumscribed margins or enhancing with an oval shape and homogeneous enhancement. Quantitative parameters indicated that benign masses had the longest time to peak (P = .078), highest time-to-peak ratio of mass to background (P = .036), lowest peak intensity (P = .021), and smallest difference in peak intensity between the mass and background (P = .079) compared to high-risk and malignant lesions.

CONCLUSIONS

Contrast-enhanced US may be a valuable modality that can be used to predict benign pathologic results of breast masses, thereby reducing the number of biopsies.

Application of contrast-enhanced ultrasound in the diagnosis of small breast lesions

BACKGROUND

Breast cancer is the most common cancer in women worldwide. The purpose of the study was to observe the features of contrast-enhanced ultrasound (CEUS) and the combination with Breast Imaging-Reporting and Data System (BI-RADS) of conventional ultrasound for assessing small breast lesions.

OBJECTIVES

The study was to explore the small breast lesions' features of contrast-enhanced ultrasound (CEUS) and the combination with Breast Imaging-Reporting and Data System (BI-RADS) of conventional ultrasound, in order to improve the diagnostic accuracy of early breast cancer.

METHODS

105 lesions were subject to conventional US (ultrasound) and CEUS before operations or biopsies. Among 105 breast lesions, six patient diagnoses were established by thick core-needle biopsy, while the rest were all confirmed by surgery and pathology.

RESULTS

Significant differences were found between benign and malignant lesions in qualitative and quantitative indexes (peak) of CEUS (P < 0.05). The qualitative features of malignant small breast lesions were as follows: (1) enhanced intensity within the lesion was not uniform (61/61,100%); (2) the speed of wash-in was earlier than the surrounding tissue (58/61, 95.1%); (3) lesion interior and the surrounding tissues had contrast vessel performance (61/61,100%). Peak of malignant lesions (35.77±11.45) was higher than that of benign lesions (31.96±10.76) (P < 0.05). The diagnostic performance of BI-RADS-US plus qualitative indexes (method one) in terms of area under receiver operating characteristic curve (AUROC) were the highest (i.e., AUROC = 0.817), in comparison with other combined diagnostic methods. The associated sensitivity, specificity and accuracy were 78.69%, 84.09% and 80.95%, respectively. With method one, however, was similar with US-BI-RADS in specificity, 11 malignant breast lesions were regarded as a higher classification of BI-RADS and classified into malignant group, which were identified as benign on US-BI-RADS originally.

CONCLUSIONS

CEUS was useful to differentiate benign from malignant small breast lesions, and the combination of CEUS and BI-RADS-US can improve the early diagnosis of breast cancers.

Contrast Transthoracic Echocardiography Using 50% Glucose as a Contrast Agent for Screening of a Patent Foramen Ovale

A patent foramen ovale (PFO) is considered a risk factor for neurologic events. The goal of the study described here was to assess the feasibility, advantages, diagnostic sensitivity and accuracy of contrast transthoracic echocardiography examination (cTTE) using 50% glucose as a contrast agent in comparison with the use of agitated saline as contrast to screen for PFO. In our study, we found that the peak time, effective duration and duration of microbubbles produced by 50% glucose were all longer than those produced by the physiologic saline. The sensitivities for detection of PFO with cTTE using physiologic saline and 50% glucose as contrast were 83% (20/24) and 100% (24/24), respectively. TEE suggested a PFO in 24 patients in two groups. Use of 50% glucose as a contrast agent in cTTE examination enables ultrasound technicians to easily observe the right-to-left shunt across the PFO. However, the sensitivities for detection of PFO with cTTE using 50% glucose did not statistically significantly differ from those for physiologic saline.

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.

Non-Mass Breast Lesions on Ultrasound: Feature Exploration and Multimode Ultrasonic Diagnosis

The aim of this study was to analyze the features of non-mass breast lesions (NMLs) on B-mode ultrasound (US), color Doppler US, strain elastography (SE) and contrast-enhanced ultrasound (CEUS) and to develop a multimode ultrasonic method for NML differentiation. Seventy-one NMLs were included in this retrospective study. Binary logistic regression was used to identify the independent risk factors. Pathology results were used as the standard criterion. Microcalcification on US, high stiffness on SE and hyper-enhanced intensity on CEUS were identified as features correlated with malignancy. A multimode method to evaluate NMLs based on the logistic regression was developed. The sensitivity and specificity for US, US + Doppler, US + SE, US + CEUS and the multimode method were 100% and 29%, 92.5% and 41.9%, 97.5% and 58.1%, 90.0% and 58.1% and 95.0% and 77.4%, respectively. The accuracy of these methods was 69.0%, 70.4%, 80.2%, 76.1% and 87.3%, respectively. The multimode ultrasonic method is simple and exhibited high diagnostic performance, which might be helpful for predicting the potential malignancy of NMLs.

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.

Significance of microvascular evaluation of ductal lesions on breast ultrasonography: Influence on diagnostic performance

We aim to investigate the significance of microvascular ultrasonography in breast ductal lesions for distinguishing benign from malignant lesions. Sixty-two ductal lesions were evaluated with gray-scale and three Doppler techniques before biopsy, Superb Microvascular Imaging (SMI), color Doppler (CDI), and power Doppler imaging (PDI). We evaluated number, distribution, and morphology of vessels. The area under the ROC curve of combined use of Doppler imaging was greater than that of gray-scale only and SMI had higher value than CDI and PDI (p < 0.05). Microvascular ultrasonography improves diagnostic performance that distinguishes benign from malignant breast ductal lesions, and SMI is superior to CDI and PDI.

Application of computer-aided diagnosis in breast ultrasound interpretation: improvements in diagnostic performance according to reader experience

Purpose

The purpose of this study was to evaluate the usefulness of applying computer-aided diagnosis (CAD) to breast ultrasound (US), depending on the reader's experience with breast imaging.

Methods

Between October 2015 and January 2016, two experienced readers obtained and analyzed the grayscale US images of 200 cases according to the Breast Imaging Reporting and Data System (BI-RADS) lexicon and categories. They additionally applied CAD (S-Detect) to analyze the lesions and made a diagnostic decision subjectively, based on grayscale US with CAD. For the same cases, two inexperienced readers analyzed the grayscale US images using the BI-RADS lexicon and categories, added CAD, and came to a subjective diagnostic conclusion. We then compared the diagnostic performance depending on the reader's experience with breast imaging.

Results

The sensitivity values for the experienced readers, inexperienced readers, and CAD (for experienced and inexperienced readers) were 91.7%, 75.0%, 75.0%, and 66.7%, respectively. The specificity values for the experienced readers, inexperienced readers, and CAD (for experienced and inexperienced readers) were 76.6%, 71.8%, 78.2%, and 76.1%, respectively. When diagnoses were made subjectively in combination with CAD, the specificity significantly improved (76.6% to 80.3%) without a change in the sensitivity (91.7%) in the experienced readers. After subjective combination with CAD, both of the sensitivity and specificity improved in the inexperienced readers (75.0% to 83.3% and 71.8% to 77.1%). In addition, the area under the curve improved for both the experienced and inexperienced readers (0.84 to 0.86 and 0.73 to 0.80) after the addition of CAD.

Conclusion

CAD is more useful for less experienced readers. Combining CAD with breast US led to improved specificity for both experienced and inexperienced readers.

Ultrasonography methods for predicting malignancy in canine mammary tumors

The aim of this study was to evaluate and compare the efficacy of B-mode, Doppler, contrast-enhanced ultrasonography (CEUS), and Acoustic Radiation Force Impulse (ARFI) elastography in predicting malignancy in canine mammary masses. This was a prospective cohort study from 2014 to 2016, which included 153 bitches with one or more mammary masses. A total of 300 masses were evaluated by ultrasonography (B-mode, Doppler, CEUS, and ARFI) and subsequently classified as benign or malignant by histopathology. Each ultrasound parameters studied were compared between benign and malignant masses by Chi-square or Student tests and differences were considered significant when P < 0.01. For the variables that proved significant differences were estimated the cut-off point, sensitivity, specificity, accuracy, and area under curve (AUC) by receiver-operating characteristic curve (ROC) analysis in a logistic regression model using histopathological classification as reference, to assess and compare diagnostic performance of each technique. Out of 300 mammary masses evaluated 246 were classified as malignant and 54 as benign. B-mode measurements showed sensitivity 67.9%, and specificity 67.6% as malignancy predictors on canine mammary masses; Doppler indexes systolic (>21.2 m/s) and diastolic velocity (>4.8 m/s) sensitivity 79.2% and specificity 70.8%; CEUS wash-out time (<80.5 s) sensitivity 80.2% and specificity 16.7%; and ARFI elastography shear velocity (SWV > 2.57 m/s) sensitivity 94.7% and specificity 97.2% In conclusion B-mode and Doppler ultrasound evaluations may assist in malignancy prediction of canine mammary masses with moderate sensitivity and specificity, already the SWV was an great accurate predictor. Therefore, ARFI elastography exam inclusion in veterinary clinic oncology and research is highly recommended, since it allows fast, non-invasive, and complication-free malignancy prediction of canine mammary masses.

Characteristics and Echogenicity of Clinical Ultrasound Contrast Agents: An In Vitro and In Vivo Comparison Study

OBJECTIVES

To compare physicochemical characteristics and in vitro and in vivo contrast-enhanced ultrasound imaging performance of 3 commercially available ultrasound contrast agents: SonoVue (Bracco Imaging SpA, Colleretto Giacosa, Italy; also marketed as Lumason in the USA), Definity (Lantheus Medical Imaging, North Billerica, MA) and Optison (GE Healthcare AS, Oslo, Norway).

METHODS

Physicochemical characteristics were measured with a Multisizer Coulter Counter (Beckman Coulter, Fullerton, CA). Two ultrasound systems (Aplio 500; Toshiba Medical Systems Corp, Tochigi-ken, Japan; and Logiq E9; GE Healthcare, Little Chalfont, England) were used with different transducers. Contrast enhancement was measured in vitro by dose-ranging measurements using a custom-built beaker setup; in vivo imaging performances were compared in pigs (heart and liver) and rabbits (liver). Quantitative analyses were performed with VueBox quantification software (Bracco Suisse SA, Plan-les-Ouates, Switzerland).

RESULTS

Measured physicochemical characteristics were in agreement with those provided by the manufacturers. In vitro data demonstrated that the performance of SonoVue was similar to or better than that of Definity but superior to Optison (normalized scattered power 2- to 10-fold higher with SonoVue). Similar results were obtained in vivo, although the duration of enhancement in the pig heart was longer for SonoVue compared to Definity, and quantitative analysis revealed higher enhancement for SonoVue (1.5-fold increase). For liver imaging, SonoVue and Definity showed similar contrast enhancement and duration of enhancement, but compared to Optison, both peak enhancement and duration of enhancement were superior for SonoVue (up to 2-fold increase).

CONCLUSIONS

Imaging performance of SonoVue was similar to or slightly better than that of Definity, but it was superior to Optison for the conditions used in this study.