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

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.

Contrast-enhanced ultrasound (CEUS) for the characterization of intra-scrotal lesions

Contrast-enhanced ultrasound (CEUS) has emerged as a promising imaging modality for the characterization of hepatic and renal lesions. However, there is a paucity of data describing the use of CEUS for the evaluation of intra-scrotal pathology. In the following review, we describe the clinical utility of CEUS for the characterization and differentiation of common and uncommon intra-scrotal conditions, including testicular torsion, infection, trauma, and benign and malignant intratesticular and extratesticular neoplasms. In addition, we outline key principles of CEUS and provide case examples from our institution.

Augmentation of tumour perfusion by ultrasound and microbubbles: A preclinical study

BACKGROUND

Hypoperfusion and the resulting hypoxia in solid tumours are critical causes of treatment resistance. Ultrasound-stimulated microbubbles (USMB) enhance tumour perfusion in a mechanism named the "sononeoperfusion" effect, which may relieve tumour hypoperfusion and hypoxia. The aim of this study was to determine the optimal mechanical index (MI) and therapeutic ultrasound exposure time for the sononeoperfusion effect and preliminarily explore the mechanism of sononeoperfusion and its effect on tumours.

METHODS

A total of 155 mice bearing MC38 tumours were included in this study. A modified diagnostic ultrasound and microbubbles (Zhifuxian) was used for USMB treatment. Tumour perfusion was evaluated by contrast-enhanced ultrasound (CEUS) and Hoechst 33342. The therapeutic pulse was operated with MIs of 0.1 to 0.5. The ultrasound exposure time was set from 150 s to 600 s. Endothelial nitric oxide synthase (eNOS) inhibition and NO, ATP, and phospho-eNOS (p-eNOS) detection were performed to explore the mechanisms of sononeoperfusion. Hypoxia-inducible factor-1α (HIF-1α) and tumour oxygen partial pressure (pO2) represent hypoxic tumour conditions.

RESULTS

Tumour perfusion was increased after USMB treatment at MIs of 0.1-0.4 and ultrasound exposure times of 150 s to 600 s, with optimal augmentation achieved at an MI of 0.3 and ultrasound exposure time of 450 s. The mean fluorescence intensity of Hoechst 33342 after USMB treatment was stronger than that of the control group. Biochemical assays showed a significant increase in ATP, p-eNOS and NO after USMB treatment. PO2 in tumour tissue increased significantly after USMB treatment and was maintained for more than 20 min.

CONCLUSIONS

The best sononeoperfusion effect was obtained with an MI of 0.3 and an ultrasound exposure time of 450 s. The effect is most likely related to NO and ATP increases. The sononeoperfusion effect might be a novel way to ameliorate tumour hypoperfusion and hypoxia.

Advantages of contrast-enhanced ultrasound in the localization and diagnostics of sentinel lymph nodes in breast cancer

Sentinel lymph nodes (SLNs) are the first station of lymph nodes that extend from the breast tumor to the axillary lymphatic drainage. The pathological status of these LNs can predict that of the entire axillary lymph node. Therefore, the accurate identification of SLNs is necessary for sentinel lymph node biopsy (SLNB) to replace axillary lymph node dissection (ALND). The quality of life and prognosis of breast cancer patients are related to proper surgical treatment after the precise identification of SLNs. Some of the SLN tracers that have been identified include radioisotope, nano-carbon, indocyanine green (ICG), and methylene blue (MB). However, these tracers have certain limitations, such as pigmentation, radiation dangers, and the requirement for costly detection equipment. Ultrasound contrast agents (UCAs) have good specificity and sensitivity, and thus can compensate for some shortcomings of the mentioned tracers. This technique is also being applied to SLNB in patients with breast cancer, and can even provide an initial judgment on SLN status. Contrast-enhanced ultrasound (CEUS) has the advantages of high distinguishability, simple operation, no radiation harm, low cost, and accurate localization; therefore, it is expected to replace the traditional biopsy methods. In addition, it can significantly enhance the accuracy of SLN localization and shorten the operation time.

A new sonoablation using acoustic droplet vaporization and focused ultrasound: A feasibility study

BACKGROUND

Histotripsy and boiling histotripsy are two methods of mechanical ablation that use high-pressure focused ultrasound (FUS).

PURPOSE

Here, a new bubble sonoablation technique was investigated using low-pressure FUS in combination with local injection of perfluoropentane (PFP) in rabbit liver.

METHODS

Fifteen healthy New Zealand white rabbits were treated with FUS alone, FUS + PFP or PFP alone. FUS was performed using a single-element focused transducer (frequency 596 kHz, 0.27 ms pulses, 0.54% duty cycle, and peak negative pressure 2.0 MPa). Ten minutes before FUS treatment, the PFP droplet was locally injected into the rabbit liver, where the ultrasound was focused. Contrast-enhanced ultrasound (CEUS) of the liver was performed, and the temperature at the liver surface in the targeted liver region was recorded during treatment. The livers were collected for pathological examination. Statistical significance was set at p < 0.05. Paired t-tests were used to compare the pre- and post-treatment values. One-way analysis of variance was performed to compare multiple groups, and the least significant difference method was used for further comparisons between the two groups.

RESULTS

Analysis of CEUS data showed that the values of area under the curve (AUC) were significantly different in the PFP + FUS group pre- (10453.644 ± 1182.93) and post-treatment (4058.098 ± 2720.41), and the AUC values of PFP + FUS post-treatment (4058.098 ± 2720.41) were also significantly lower than those of the FUS (9946.694 ± 1071.54) and the PFP (10364.794 ± 2181.53) groups. The peak intensity values also showed the same results, the value of peak intensity of PFP+FUS post-treatment was 82.958 ± 13.99, whereas there was no difference between FUS (106.61 ± 7.61) and PFP (104.136 ± 10.55). Hematoxylin and eosin (H&E) staining revealed that the pathological damage ratings of the PFP + FUS, PFP, and FUS groups were grade 3, grade 1, and grade 0, respectively. Specifically, the area of liver necrosis in the PFP + FUS group (0.99 ± 0.29 cm2 ) was 198 times higher than that in the PFP group (0.005 ± 0.008 cm2 ), whereas no necrosis was observed in the livers treated with FUS alone. Simultaneously, the number of vacuoles in the liver of the PFP + FUS group (35.50 ± 23.31) was approximately five times that of the PFP group (7.00 ± 12.88), whereas no vacuoles were found in the liver treated with FUS alone.

CONCLUSION

PFP droplets combined with FUS can destroy liver tissue and cause tissue necrosis in the droplet injection area, without affecting the structure of surrounding tissue.

The Clinical Application of Artificial Intelligence Assisted Contrast-Enhanced Ultrasound on BI-RADS Category 4 Breast Lesions

RATIONALE AND OBJECTIVES

To propose a novel deep learning method incorporating multiple regions based on contrast-enhanced ultrasound and grayscale ultrasound, evaluate its performance in reducing false positives for Breast Imaging Reporting and Data System (BI-RADS) category 4 lesions, and compare its diagnostic performance with that of ultrasound experts.

MATERIALS AND METHODS

This study enrolled 163 breast lesions in 161 women from November 2018 to March 2021. Contrast-enhanced ultrasound and conventional ultrasound were performed before surgery or biopsy. A novel deep learning model incorporating multiple regions based on contrast-enhanced ultrasound and grayscale ultrasound was proposed for minimizing the number of false-positive biopsies. The area under the receiver operating characteristic curve (AUC), sensitivity, specificity, and accuracy were compared between the deep learning model and ultrasound experts.

RESULTS

The AUC, sensitivity, specificity, and accuracy of the deep learning model in BI-RADS category 4 lesions were 0.910, 91.5%, 90.5%, and 90.8%, respectively, compared with those of ultrasound experts were 0.869, 89.4%, 84.5%, and 85.9%, respectively.

CONCLUSION

The novel deep learning model we proposed had a diagnostic accuracy comparable to that of ultrasound experts, showing the potential to be clinically useful in minimizing the number of false-positive biopsies.

Modern Imaging Techniques in the Study and Disease Diagnosis of the Mammary Glands of Animals

The study of the structure and function of the animals' mammary glands is of key importance, as it reveals pathological processes at their onset, thus contributing to their immediate treatment. The most frequently studied mammary diseases are mastitis in cows and ewes and mammary tumours in dogs and cats. Various imaging techniques such as computed tomography, positron emission tomography, magnetic resonance imaging, and ultrasonographic techniques (Doppler, contrast-enchanced, three-dimensional and elastography) are available and can be applied in research or clinical practice in order to evaluate possible abnormalities in mammary glands, as well as to assist in the differential diagnosis. In this review, the above imaging technologies are described, and the perspectives of each method are highlighted. It is inferred that ultrasonographic modalities are the most frequently used imaging techniques for the diagnosis of clinical or subclinical mastitis and treatment guidance on a farm. In companion animals, a combination of imaging techniques should be applied for a more accurate diagnosis of mammary tumours. In any case, the confirmation of the diagnosis is provided by laboratory techniques.

Optimal treatment occasion for ultrasound stimulated microbubbles in promoting gemcitabine delivery to VX2 tumors

Ultrasound stimulated microbubbles (USMB) is a widely used technology that can promote chemotherapeutic delivery to tumors yet the best treatment occasion for USMB is unknown or ignored. We aimed to determine the optimal treatment occasion for USMB treatment to enhance tumor chemotherapy to achieve the highest drug concentration in tumors. Experiments were conducted on VX2 tumors implanted in 60 rabbits. Gemcitabine (GEM) was intravenously infused as a chemotherapeutic agent and USMB was administered before, during or after chemotherapy. USMB was conducted with a modified diagnostic ultrasound at 3 MHz employing short bursts (5 cycles and 0.125% duty cycle) at 0.26 MPa in combination with a lipid microbubble. Subsequently, tumor blood perfusion quantitation, drug concentration detection, and fluorescence microscopy were performed. The results showed that the group that received USMB treatment immediately after GEM infusion had the highest drug concentration in tumors, which was 2.83 times that of the control group. Fifteen tumors were then treated repeatedly with the optimal USMB-plus-GEM combination, and along with the GEM and the control groups, were studied for tumor growth, tumor cell proliferation, apoptosis, and related cytokine contents. The combined treatment significantly inhibited tumor growth and promoted apoptosis. The levels of related cytokines, including HIF-1α, decreased after six combination therapies. These results suggest that the optimal treatment occasion for USMB occurs immediately after chemotherapy and tumor hypoxia improves after multiple combination therapies.

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.

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

OBJECTIVES

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

MATERIALS AND METHODS

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

RESULTS

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

CONCLUSION

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

Ultrasound super-resolution imaging for differential diagnosis of breast masses

OBJECTIVE

Ultrasound imaging has been widely used in breast cancer screening. Recently, ultrasound super-resolution imaging (SRI) has shown the capability to break the diffraction limit to display microvasculature. However, the application of SRI on differential diagnosis of breast masses remains unknown. Therefore, this study aims to evaluate the feasibility and clinical value of SRI for visualizing microvasculature and differential diagnosis of breast masses.

METHODS

B mode, color-Doppler flow imaging (CDFI) and contrast-enhanced ultrasound (CEUS) images of 46 patients were collected respectively. SRI were generated by localizations of each possible contrast signals. Micro-vessel density (MVD) and microvascular flow rate (MFR) were calculated from SRI and time to peak (TTP), peak intensity (PI) and area under the curve (AUC) were obtained by quantitative analysis of CEUS images respectively. Pathological results were considered as the gold standard. Independent chi-square test and multivariate logistic regression analysis were performed using these parameters to examine the correlation.

RESULTS

The results showed that SRI technique could be successfully applied on breast masses and display microvasculature at a significantly higher resolution than the conventional CDFI and CEUS images. The results showed that the PI, AUC, MVD and MFR of malignant breast masses were significantly higher than those of benign breast masses, while TTP was significantly lower than that of benign breast masses. Among all five parameters, MVD showed the highest positive correlation with the malignancy of breast masses.

CONCLUSIONS

SRI is able to successfully display the microvasculature of breast masses. Compared with CDFI and CEUS, SRI can provide additional morphological and functional information for breast masses. MVD has a great potential in assisting the differential diagnosis of breast masses as an important imaging marker.

Ultrasound high-definition microvasculature imaging with novel quantitative biomarkers improves breast cancer detection accuracy

OBJECTIVES

To overcome the limitations of power Doppler in imaging angiogenesis, we sought to develop and investigate new quantitative biomarkers of a contrast-free ultrasound microvasculature imaging technique for differentiation of benign from malignant pathologies of breast lesion.

METHODS

In this prospective study, a new high-definition microvasculature imaging (HDMI) was tested on 521 patients with 527 ultrasound-identified suspicious breast masses indicated for biopsy. Four new morphological features of tumor microvessels, microvessel fractal dimension (mvFD), Murray's deviation (MD), bifurcation angle (BA), and spatial vascularity pattern (SVP) as well as initial biomarkers were extracted and analyzed, and the results correlated with pathology. Multivariable logistic regression analysis was used to study the performance of different prediction models, initial biomarkers, new biomarkers, and combined new and initial biomarkers in differentiating benign from malignant lesions.

RESULTS

The new HDMI biomarkers, mvFD, BA, MD, and SVP, were statistically significantly different in malignant and benign lesions, regardless of tumor size. Sensitivity and specificity of the new biomarkers in lesions > 20 mm were 95.6% and 100%, respectively. Combining the new and initial biomarkers together showed an AUC, sensitivity, and specificity of 97% (95% CI: 95-98%), 93.8%, and 89.2%, respectively, for all lesions regardless of mass size. The classification was further improved by adding the Breast Imaging Reporting and Data System (BI-RADS) score to the prediction model, showing an AUC, sensitivity, and specificity of 97% (95% CI: 95-98%), 93.8%, and 89.2%, respectively.

CONCLUSION

The addition of new quantitative HDMI biomarkers significantly improved the accuracy in breast lesion characterization when used as a complementary imaging tool to the conventional ultrasound.

KEY POINTS

• Novel quantitative biomarkers extracted from tumor microvessel images increase the sensitivity and specificity in discriminating malignant from benign breast masses. • New HDMI biomarkers Murray's deviation, bifurcation angles, microvessel fractal dimension, and spatial vascularity pattern outperformed the initial biomarkers. • The addition of BI-RADS scores based on US descriptors to the multivariable analysis using all biomarkers remarkably increased the sensitivity, specificity, and AUC in all size groups.

Characterizing breast masses using an integrative framework of machine learning and CEUS-based radiomics

AIMS

We evaluated the performance of contrast-enhanced ultrasound (CEUS) based on radiomics analysis to distinguish benign from malignant breast masses.

METHODS

131 women with suspicious breast masses (BI-RADS 4a, 4b, or 4c) who underwent CEUS examinations (using intravenous injection of perflutren lipid microsphere or sulfur hexafluoride lipid-type A microspheres) prior to ultrasound-guided biopsies were retrospectively identified. Post biopsy pathology showed 115 benign and 16 malignant masses. From the cine clip of the CEUS exams obtained using the built-in GE scanner software, breast masses and adjacent normal tissue were then manually segmented using the ImageJ software. One frame representing each of the four phases: precontrast, early, peak, and delay enhancement were selected post segmentation from each CEUS clip. 112 radiomic metrics were extracted from each segmented tissue normalized breast mass using custom Matlab® code. Linear and nonlinear machine learning (ML) methods were used to build the prediction model to distinguish benign from malignant masses. tenfold cross-validation evaluated model performance. Area under the curve (AUC) was used to quantify prediction accuracy.

RESULTS

Univariate analysis found 35 (38.5%) radiomic variables with p < 0.05 in differentiating between benign from malignant masses. No feature selection was performed. Predictive models based on AdaBoost reported an AUC = 0.72 95% CI (0.56, 0.89), followed by Random Forest with an AUC = 0.71 95% CI (0.56, 0.87).

CONCLUSIONS

CEUS based texture metrics can distinguish between benign and malignant breast masses, which can, in turn, lead to reduced unnecessary breast biopsies.

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 association between conventional ultrasound and contrast-enhanced ultrasound appearances and pathological features in small breast cancer

OBJECTIVE

To investigate the association between ultrasound appearances and pathological features in small breast cancer.

MATERIALS AND METHODS

A total of 186 small breast cancers in 186 patients were analyzed in this retrospective study from January 2015 to December 2019 according to pathological results. Forty-seven cases of axillary lymph node metastasis were found. All patients underwent radical axillary surgery following conventional ultrasound (US) and contrast-enhanced ultrasound (CEUS) examinations. The association between ultrasound appearances and pathological features was analyzed using univariate distributions and multivariate analysis. Then, a logistic regression model was established using the pathological diagnosis of lymph node metastasis and biochemical indicators as the dependent variable and the ultrasound appearances as independent variables.

RESULTS

In small breast cancer, risk factors of axillary lymph node metastasis were crab claw-like enhancement on CEUS and abnormal axillary lymph nodes on US. The logistic regression model was established as follows: (axillary lymph node metastasis) = 1.100×(crab claw-like enhancement of CEUS) + 2.749×(abnormal axillary lymph nodes of US) -5.790. In addition, irregular shape on CEUS and posterior echo attenuation on US were risk factors for both positive estrogen receptor and progesterone receptor expression, whereas calcification on US was a risk factor for positive Her-2 expression. A specific relationship could be found using the following logistic models: (positive ER expression) = 1.367×(irregular shape of CEUS) + 1.441×(posterior echo attenuation of US) -5.668; (positive PR expression) = 1.265×(irregular shape of CEUS) + 1.136×(posterior echo attenuation of US) -4.320; (positive Her-2 expression) = 1.658×(calcification of US) -0.896.

CONCLUSION

Logistic models were established to provide significant value for the prediction of pre-operative lymph node metastasis and positive biochemical indicators, which may guide clinical treatment.

Quantification of dynamic contrast-enhanced ultrasound (CEUS) in non-cystic breast lesions using external perfusion software

The aim of this present clinical pilot study is the display of typical perfusion results in patients with solid, non-cystic breast lesions. The lesions were characterized using contrast enhanced ultrasound (CEUS) with (i) time intensity curve analyses (TIC) and (ii) parametric color maps. The 24 asymptomatic patients included were genetically tested for having an elevated risk for breast cancer. At a center of early detection of familial ovary and breast cancer, those patients received annual MRI and grey-scale ultrasound. If lesions remained unclear or appeared even suspicious, those patients also received CEUS. CEUS was performed after intravenous application of sulfur hexafluoride microbubbles. Digital DICOM cine loops were continuously stored for one minute in PACS (picture archiving and communication system). Perfusion images and TIC analyses were calculated off-line with external perfusion software (VueBox). The lesion diameter ranged between 7 and 15 mm (mean 11 ± 3 mm). Five hypoechoic irregular lesions were scars, 6 lesions were benign and 12 lesions were highly suspicious for breast cancer with irregular enhancement at the margins and a partial wash out. In those 12 cases, histopathology confirmed breast cancer. All the suspicious lesions were correctly identified visually. For the perfusion analysis only Peak Enhancement (PE) and Area Under the Curve (AUC) added more information for correctly identifying the lesions. Typical for benign lesions is a prolonged contrast agent enhancement with lower PE and prolonged wash out, while scars are characterized typically by a reduced enhancement in the center. No differences (p = 0.428) were found in PE in the center of benign lesions (64.2 ± 28.9 dB), malignant lesions (88.1 ± 93.6 dB) and a scar (40.0 ± 17.0 dB). No significant differences (p = 0.174) were found for PE values at the margin of benign lesions (96.4 ± 144.9 dB), malignant lesions (54.3 ± 86.2 dB) or scar tissue (203.8 ± 218.9 dB). Significant differences (p < 0.001) were found in PE of the surrounding tissue when comparing benign lesions (33.6 ± 25.2 dB) to malignant lesions (15.7 ± 36.3 dB) and scars (277.2 ± 199.9 dB). No differences (p = 0.821) were found in AUC in the center of benign lesions (391.3 ± 213.7), malignant lesions (314.7 ± 643.9) and a scar (213.1 ± 124.5). No differences (p = 0.601) were found in AUC values of the margin of benign lesions (313.3 ± 372.8), malignant lesions (272.6 ± 566.4) or scar tissue (695.0 ± 360.6). Significant differences (p < 0.01) were found in AUC of the surrounding tissue for benign lesions (151.7 ± 127.8), malignant lesions (177.9 ± 1345.6) and scars (1091 ± 693.3). There were no differences in perfusion evaluation for mean transit time (mTT), rise time (RT) and time to peak (TTP) when comparing the center to the margins and the surrounding tissue. The CEUS perfusion parameters PE and AUC allow a very good assessment of the risk of malignant breast lesions and thus a downgrading of BI-RADS 4 lesions. The use of the external perfusion software (VueBox, Bracco, Milan, Italy) did not lead to any further improvement in the diagnosis of suspicious breast lesions and does appears not to have any additional diagnostic value in breast lesions.

BI-RADS 3 on Screening Breast Ultrasound: What Is It and What Is the Appropriate Management?

US is widely used in breast imaging for diagnostic purposes and is also used increasingly for supplemental screening in women with dense breasts. US frequently depicts masses that are occult on mammography, even after tomosynthesis, and the vast majority of such masses are benign. Many masses seen only on screening US are easily recognized as benign simple cysts. Probably benign, BI-RADS 3, or low suspicion, BI-RADS 4A masses are also common and often prompt short-interval follow-up or biopsy, respectively, yet the vast majority of these are benign. This review details appropriate characterization, classification, and new approaches to the management of probably benign masses seen on screening US that can reduce false positives and, thereby, reduce costs and patient anxiety.

Contrast-enhanced ultrasound perfusion imaging of organs

In multimodal radiologic imaging, contrast-enhanced ultrasound (CEUS) is increasingly used. One of the advantages of CEUS is the possibility of repeated application of contrast media without decreasing renal function or affecting the thyroid gland. Small solid liver lesions can be diagnosed and detected with high accuracy. Moreover, solid lesions in other abdominal organs can also be characterized. Frequent applications for solid lesions in the near field concern thyroid tumors and lymph nodes. For prostate diagnostics, CEUS can be used with an endorectal probe and perfusion imaging. This review explains how the additional (semi-)quantitative perfusion analysis, especially time-intensity curve (TIC) analyses, and wash-in/wash-out kinetics of integrated or external perfusion software programs facilitate new options in dynamic assessment of microvascularization during tumor follow-up care and even minimally invasive tumor therapy.

Correlation analysis between rim enhancement features of contrast-enhanced ultrasound and lymph node metastasis in breast cancer

OBJECTIVE

To explore the correlation between rim enhancement features of contrast-enhanced ultrasound and lymphatic metastasis, and to provide theoretical support for clinical treatment of breast cancer.

METHODS

387 breast cancer patients (748 axillary lymph nodes in total) treated in our hospital from January 2017 to January 2020 were selected and analyzed by contrast-enhanced ultrasound. Pathological examination showed that 540 axillary lymph nodes showed metastasis whereas 208 axillary lymph nodes did not show metastasis. Univariate analysis and Logistic stepwise regression were used to analyze the correlation between rim enhancement features of contrast-enhanced ultrasound and axillary lymph node metastasis of breast cancer.

RESULTS

Peripheral halo, peripheral convergence, rim enhancement, enhancement mode, enhancement amplitude, enhancement sequence, expansion after enhancement, peak intensity, time to peak, area under curve, thrombolysis in myocardial infarction, perfusion sequence, aspect ratio, and maximum cortical thickness were all related to lymph node metastasis of breast cancer by univariate analysis, and the difference was statistically significant (P < 0.05). Multivariate analysis showed that enhancement mode, enhancement amplitude, extension after enhancement, maximum cortical thickness, peak intensity and time to peak were all related to lymph node metastasis of breast cancer.

CONCLUSION

Rim enhancement features of contrast-enhanced ultrasound of breast cancer are related to lymph node metastasis, which will provide a guidance for clinical treatment of breast cancer.

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 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.

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.