A Review of Supplemental Screening Ultrasound for Breast Cancer: Certain Populations of Women with Dense Breast Tissue May Benefit

Pearls and Pitfalls of Interpretation of Automated Breast US

Dense breast tissue is an independent risk factor for breast cancer and reduces the sensitivity of mammography. Patients with dense breast tissue are more likely to present with interval cancers and higher-stage disease. Successful breast cancer screening outcomes rely on detection of early-stage breast cancers; therefore, several supplemental screening modalities have been developed to improve cancer detection in dense breast tissue. US is the most widely used supplemental screening modality worldwide and has been proven to demonstrate additional mammographically occult cancers that are predominantly invasive and node negative. According to the American College of Radiology, intermediate-risk women with dense breast tissue may benefit from adjunctive screening US due to the limitations of mammography. Several studies have demonstrated handheld US (HHUS) and automated breast US (AUS) to be comparable in the screening setting. The advantages of AUS over HHUS include lack of operator dependence and a formal training requirement, image reproducibility, and ability for temporal comparison. However, AUS exhibits unique features that can result in high false-positive rates and long interpretation times for new users. Familiarity with the common appearance of benign mammographic findings and artifacts, technical challenges, and unique AUS features is essential for fast, efficient, and accurate interpretation. The goals of this article are to (a) examine the role of AUS as a supplemental screening modality and (b) review the pearls and pitfalls of AUS interpretation. ©RSNA, 2023 Quiz questions for this article are available in the supplemental material.

Ultrasound and clinicopathological characteristics of breast cancer for predicting axillary lymph node metastasis

OBJECTIVES

The goal of this study was to assess the clinicopathological and ultrasound (US) features of breast cancer for predicting the risk of axillary lymph node metastasis.

METHODS

Patients with breast cancer were included in this retrospective, monocentric, observational study. Their preoperative ultrasound features, clinical data, laboratory results and postoperative pathologic results and immunophenotyping were collected. The association of these factors of breast cancer with axillary lymph node metastasis was evaluated by univariate and multivariate analysis.

RESULTS

In this study, 471 patients diagnosed with breast cancer at the First Affiliated Hospital of Xi'an Jiaotong University between July 2016 and September 2019 were collected, with a total of 471 nodules, of which 231(49.0%) had axillary lymph node metastasis, and 240(51.0%) did not. The parameters of hyperechoic halo, posterior acoustic decrease, microcalcification, carcinogenic embryonic antigen (CEA), cancer antigen-153 (CA153), CK5/6 (+), Ki67 (≥40%), AR (+) and histological grade (grade II and grade III) were significantly and independently associated with axillary lymph node metastasis (p < 0.05 for all).

CONCLUSIONS

The combination of ultrasound features, tumor markers, pathology, and immunohistochemistry can predict axillary lymph node metastasis in breast cancer patients.

Breast ultrasound in Chinese hospitals: A cross-sectional study of the current status and influencing factors of BI-RADS utilization and diagnostic accuracy

BACKGROUND

With the growing demand for breast screening in public health services and clinical care, ultrasound departments in China are facing tremendous challenges.

METHODS

A cross-sectional nationwide survey was conducted in 5,460 departments providing ultrasound diagnoses in mainland China from 2020 to 2021. The survey included general information about the ultrasound department, the characteristics of sonologists, the use of Breast Imaging Reporting and Data System (BI-RADS) templates, and the diagnostic accuracy rate of breast cancer ultrasound.

FINDINGS

There were on average 2.25 sonologists per 10,000 patients in mainland China per year. The average utilization rate of BI-RADS in Chinese hospitals was 87.02%. The GDP per capita of the province (P = 0.008), whether the hospital was specialized (P = 0.002) or a Tier 3 facility (P < 0.001), the percentage of doctors with master's and doctoral degrees (P < 0.001) and doctors ≤35 years (P = 0.005) were significantly and independently associated with the utilization rate of BI-RADS. The average diagnostic accuracy rate of breast cancer ultrasound in Chinese hospitals was 73.64%, and we observed significant positive associations between GDP per capita (P = 0.02), BI-RADS utilization rate (P = 0.019), and breast cancer ultrasound diagnostic accuracy.

INTERPRETATION

The utilization of BI-RADS templates effectively improved the diagnostic accuracy of ultrasound. Moreover, the survey summarized the current situation of departments and sonologists providing breast ultrasound diagnosis in mainland China, which helped monitor the development of the discipline and provide information for administrators to meet the growing demand.

FUNDING

This work was supported by Natural Science Foundation of Beijing (7202156) and Foundation of ihecc (2019-C-0646-2).

Deep learning applied to breast imaging classification and segmentation with human expert intervention

PURPOSE

Automatic classification and segmentation of tumors in breast ultrasound images enables better diagnosis and planning treatment strategies for breast cancer patients.

METHODS

We collected 953 breast ultrasound images from two open-source datasets and classified them with help of an expert radiologist according to BI-RADS criteria. The data was split into normal, benign and malignant classes. We then used machine learning to develop classification and segmentation algorithms.

RESULTS

We found 3.92% of the images across the open-source datasets had erroneous classifications. Post-radiologist intervention, three algorithms were developed based on the classification categories. Classification algorithms distinguished images with healthy breast tissue from those with abnormal tissue with 96% accuracy, and distinguished benign from malignant images with 85% accuracy. Both algorithms generated robust F1 and AUROC metrics. Finally, the masses within images were segmented with an 80.31% DICE score.

CONCLUSIONS

Our work illustrates the potential of deep learning algorithms to improve the accuracy of breast ultrasound assessments and to facilitate automated assessments.

Supine versus Prone 3D Abus Accuracy in Breast Tumor Size Evaluation

Breast-conserving surgery (BCS) with negative resection margins decreases the locoregional recurrence rate. Breast cancer size is one of the main determinants of Tumor-Node-Metastasis (TNM) staging. Our study aimed to investigate the accuracy of supine 3D automated breast ultrasound (3D ABUS) compared to prone 3D ABUS in the evaluation of tumor size in breast cancer patient candidates for BCS. In this prospective two-center study (Groups 1 and 2), we enrolled patients with percutaneous biopsy-proven early-stage breast cancer, in the period between June 2019 and May 2020. Patients underwent hand-held ultrasound (HHUS), contrast-enhanced magnetic resonance imaging (CE-MRI) and 3D ABUS—supine 3D ABUS in Group 1 and prone 3D ABUS in Group 2. Histopathological examination (HE) was considered the reference standard. Bland–Altman analysis and plots were used. Eighty-eight patients were enrolled. Compared to prone, supine 3D ABUS showed better agreement with HE, with a slight tendency toward underestimation (mean difference of −2 mm). Supine 3D ABUS appears to be a useful tool and more accurate than HHUS in the staging of breast cancer.

Comparison of the background echotexture between automated breast ultrasound and handheld breast ultrasound

This study aimed to compare the background echotexture (BE) between automated breast ultrasound (ABUS) and handheld breast ultrasound (HHUS) and evaluate the correlation of BE with mammographic (MG) density and background parenchymal enhancement (BPE) on magnetic resonance imaging (MRI). A total of 212 women with newly diagnosed breast cancer who had undergone preoperative ABUS, HHUS, MG, and MRI were included. Two breast radiologists blinded to the menopausal status analyzed the BE of the contralateral breasts of the patients with breast cancer in consensus. The MG density and BPE of breast MRI on the radiologic reports were compared with the BE in the ultrasound. We used the cumulative link mixed model to compare the BE and Spearman rank correlation to evaluate the association between BE with MG density and BPE. BE was more heterogeneous in ABUS than in HHUS (P < .001) and in the premenopausal group than in the postmenopausal group (P < .001). The heterogeneity of BE in the premenopausal group was higher with ABUS than with HHUS (P = .013). BE and MG density showed a moderate correlation in the postmenopausal group, but a weak correlation in the premenopausal group. BE and BPE showed moderate correlations only in the premenopausal group. ABUS showed a more heterogeneous BE, especially in the premenopausal group. Therefore, more attention is required to interpret ABUS screening in premenopausal women.

Gail model and fifth edition of ultrasound BI-RADS help predict axillary lymph node metastasis in breast cancer-A multicenter prospective study

RATIONALE AND OBJECTIVES

We aim to assess the performance of the Gail model and the fifth edition of ultrasound BI-RADS (Breast Imaging Reporting and Data System) in breast cancer for predicting axillary lymph node metastasis (ALNM).

MATERIALS AND METHODS

We prospectively studied 958 female patients with breast cancer between 2018 and 2019 from 35 hospitals in China. Based on B-mode, color Doppler, and elastography, radiologists classified the degree of suspicion based on the fifth edition of BI-RADS. Individual breast cancer risk was assessed with the Gail model. The association between the US BI-RADS category and the Gail model in terms of ALNM was analyzed.

RESULTS

We found that US BI-RADS category was significantly and independently associated with ALNM (P < 0.001). The sensitivity, specificity, and accuracy of BI-RADS category 5 for predicting ALNM were 63.6%, 71.6%, and 68.6%, respectively. Combining the Gail model with the BI-RADS category showed a significantly higher sensitivity than using the BI-RADS category alone (67.8% vs. 63.6%, P < 0.001). The diagnostic accuracy of the BI-RADS category combined with the Gail model was better than that of the Gail model alone (area under the curve: 0.71 vs. 0.50, P < 0.001).

CONCLUSION

Based on the conventional ultrasound and elastography, the fifth edition of ultrasound BI-RADS category could be used to predict the ALNM of breast cancer. ALNM was likely to occur in patients with BI-RADS category 5. The Gail model could improve the diagnostic sensitivity of the US BI-RADS category for predicting ALNM in breast cancer.

Review on Multispectral Photoacoustic Analysis of Cancer: Thyroid and Breast

In recent decades, photoacoustic imaging has been used widely in biomedical research, providing molecular and functional information from biological tissues in vivo. In addition to being used for research in small animals, photoacoustic imaging has also been utilized for in vivo human studies, achieving a multispectral photoacoustic response in deep tissue. There have been several clinical trials for screening cancer patients by analyzing multispectral responses, which in turn provide metabolomic information about the underlying biological tissues. This review summarizes the methods and results of clinical photoacoustic trials available in the literature to date to classify cancerous tissues, specifically of the thyroid and breast. From the review, we can conclude that a great potential exists for photoacoustic imaging to be used as a complementary modality to improve diagnostic accuracy for suspicious tumors, thus significantly benefitting patients’ healthcare.

Evaluation of Diagnostic Performance of Automatic Breast Volume Scanner Compared to Handheld Ultrasound on Different Breast Lesions: A Systematic Review

Objective: To compare the diagnostic performance of the automatic breast volume scanner (ABVS) against the handheld ultrasound (HHUS) in the differential diagnosis of benign and malignant breast lesions. Methods: A systematic search and review of studies involving ABVS and HHUS for breast cancer screening were performed. The search involved the data taken from Scopus, PubMed, and science direct databases and was conducted between the year 2011 to 2020. The prospective method was used in determining the inclusion and exclusion criteria while the evidence level was determined using the BI-RADS categories for diagnostic studies. In addition, the parameters of specificity, mean age, sensitivity, tumor number, and diagnostic accuracy of the ABVS and HHUS were summarized. Results: No systematic review or randomized controlled trial were identified in the systematic search while one cross-sectional study, eight retrospective studies, and 10 prospective studies were found. Sufficient follow-up of the subjects with benign and malignant findings were made only in 10 studies, in which only two had used ABVS and HHUS after performing mammographic screening and MRI. Analysis was made of 21 studies, which included 5448 lesions (4074 benign and 1374 malignant) taken from 6009 patients. The range of sensitivity was (0.72–1.0) for ABVS and (0.62–1.0) for HHUS; the specificity range was (0.52–0.98)% for ABVS and (0.49–0.99)% for HHUS. The accuracy range among the 11 studies was (80–99)% and (59–98)% for the HHUS and ABVS, respectively. The identified tumors had a mean size of 2.1 cm, and the detected cancers had a mean percentage of 94% (81–100)% in comparison to the non-cancer in all studies. Conclusions: The evidence available in the literature points to the fact that the diagnostic performance of both ABVS and HHUS are similar with reference to the differentiation of malignant and benign breast lesions.

Gail Model Improves the Diagnostic Performance of the Fifth Edition of Ultrasound BI-RADS for Predicting Breast Cancer: A Multicenter Prospective Study

RATIONALE AND OBJECTIVES

The sonographic appearance of benign and malignant breast nodules overlaps to some extent, and we aimed to assess the performance of the Gail model as an adjunctive tool to ultrasound (US) Breast Imaging Reporting and Data System (BI-RADS) for predicting the malignancy of nodules.

MATERIALS AND METHODS

From 2018 to 2019, 2607 patients were prospectively enrolled by 35 health care facilities. An individual breast cancer risk was assessed by the Gail model. Based on B-mode US, color Doppler, and elastography, all nodules were evaluated according to the fifth edition of BI-RADS, and these nodules were all confirmed later by pathology.

RESULTS

We demonstrated that the Gail model, age, tumor size, tumor shape, growth orientation, margin, contour, acoustic shadowing, microcalcification, presence of duct ectasia, presence of architectural distortion, color Doppler flow, BI-RADS, and elastography score were significantly related to breast cancer (all p < 0.001). The sensitivity, specificity, positive predictive value, negative predictive value, accuracy, and area under the curve (AUC) for combining the Gail model with the BI-RADS category were 95.6%, 91.3%, 85.0%, 97.6%, 92.8%, and 0.98, respectively. Combining the Gail model with the BI-RADS showed better diagnostic efficiency than the BI-RADS and Gail model alone (AUC 0.98 vs 0.80, p < 0.001; AUC 0.98 vs 0.55, p < 0.001) and demonstrated a higher specificity than the BI-RADS (91.3% vs 59.4%, p < 0.001).

CONCLUSION

The Gail model could be used to differentiate malignant and benign breast lesions. Combined with the BI-RADS category, the Gail model was adjunctive to US for predicting breast lesions for malignancy. For the diagnosis of malignancy, more attention should be paid to high-risk patients with breast lesions.

Application of preoperative ultrasound features combined with clinical factors in predicting HER2-positive subtype (non-luminal) breast cancer

BACKGROUND

Human epidermal growth factor receptor2+ subtype breast cancer has a high degree of malignancy and a poor prognosis. The aim of this study is to develop a prediction model for the human epidermal growth factor receptor2+ subtype (non-luminal) of breast cancer based on the clinical and ultrasound features related with estrogen receptor, progesterone receptor, and human epidermal growth factor receptor2.

METHODS

We collected clinical data and reviewed preoperative ultrasound images of enrolled breast cancers from September 2017 to August 2020. We divided the data into in three groups as follows. Group I: estrogen receptor ± , Group II: progesterone receptor ± and Group III: human epidermal growth factor receptor2 ± . Univariate and multivariate logistic regression analyses were used to analyze the clinical and ultrasound features related with biomarkers among these groups. A model to predict human epidermal growth factor receptor2+ subtype was then developed based on the results of multivariate regression analyses, and the efficacy was evaluated using the area under receiver operating characteristic curve, accuracy, sensitivity, specificity.

RESULTS

The human epidermal growth factor receptor2+ subtype accounted for 138 cases (11.8%) in the training set and 51 cases (10.1%) in the test set. In the multivariate regression analysis, age ≤ 50 years was an independent predictor of progesterone receptor + (p = 0.007), and posterior enhancement was a negative predictor of progesterone receptor + (p = 0.013) in Group II; palpable axillary lymph node, round, irregular shape and calcifications were independent predictors of the positivity for human epidermal growth factor receptor-2 in Group III (p = 0.001, p = 0.007, p = 0.010, p < 0.001, respectively). In Group I, shape was the only factor related to estrogen receptor status in the univariate analysis (p < 0.05). The area under receiver operating characteristic curve, accuracy, sensitivity, specificity of the model to predict human epidermal growth factor receptor2+ subtype breast cancer was 0.697, 60.14%, 72.46%, 58.49% and 0.725, 72.06%, 64.71%, 72.89% in the training and test sets, respectively.

CONCLUSIONS

Our study established a model to predict the human epidermal growth factor receptor2-positive subtype with moderate performance. And the results demonstrated that clinical and ultrasound features were significantly associated with biomarkers.

Association between lesion enhancement and breast cancer in contrast-enhanced spectral mammography

BACKGROUND

Contrast-enhanced spectral mammography (CESM) may help to determine the malignancy potential of lesions according to the degree of enhancement.

PURPOSE

To investigate the correlation between the degree of contrast enhancement of the lesions in contrast-enhanced spectral mammography (CESM) and the final histopathological diagnosis in patients with BI-RADS 4 and 5 lesions.

MATERIAL AND METHODS

CESM was performed in 128 patients who had BI-RADS 4 and 5 lesions on mammography and underwent histopathological examination. A total of 128 index lesions were scored using a 4-point scale regarding the degree of contrast enhancement (0 = no contrast enhancement, 1 = minimal, 2 = moderate, 3 = marked), a score of 2 and 3 was accepted as suggestive of malignancy. The study was approved in our institutional scientific committee.

RESULTS

In total, 76 (59.4%) of the lesions had benign histopathological results, whereas 52 of them had malignant results. Contrast enhancement was not observed in 22.7% of the lesions while 24.2% had minimal enhancement, 18.8% had moderate enhancement, and 34.4% had marked enhancement in CESM. The sensitivity of the degree of contrast enhancement in CESM was 98.1%, when the specificity was 77.6%, positive predictive value was 75%, negative predictive value was 98.3%, and accuracy was 85.9%.

CONCLUSION

This study demonstrated that the degree of contrast enhancement of the lesions in CESM may be used in daily practice with easily performing a visual scale in predicting the malignancy potential of the lesions.

Supplemental Cancer Screening for Women With Dense Breasts: Guidance for Health Care Professionals

Mammography is the standard for breast cancer screening. The sensitivity of mammography in identifying breast cancer, however, is reduced for women with dense breasts. Thirty-eight states have passed laws requiring that all women be notified of breast tissue density results in their mammogram report. The notification includes a statement that differs by state, encouraging women to discuss supplemental screening options with their health care professionals (HCPs). Several supplemental screening tests are available for women with dense breast tissue, but no established guidelines exist to direct HCPs in their recommendation of preferred supplemental screening test. Tailored screening, which takes into consideration the patient's mammographic breast density and lifetime breast cancer risk, can guide breast cancer screening strategies that are more comprehensive. This review describes the benefits and limitations of the various available supplemental screening tests to guide HCPs and patients in choosing the appropriate breast cancer screening.

Analysis of breast cancer subtypes and their correlations with receptors and ultrasound

The study aim was to evaluate the ultrasound (US) signs of the mammary lesions classified in the Breast Imaging-Reporting and Data System (BI-RADS) score category 3, 4, and 5, corresponding to US BI-RADS. It also followed the correlation between US changes of lesions suggestive for malignancy with the histopathological results and evaluated the proper management of those lesions. There were correlations of breast cancer (BC) subtypes with the receptors [estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2)], and Ki67 index, and the signs of conventional ultrasonography and US elastography. We selected 108 female patients examined with US, mammography and fine-needle biopsy who presented suspicions for malignancy lesions. Following the immunohistochemical analysis, they were classified in one of the BC subtypes. According to chi-squared analysis of molecular cancer subtypes correlation to receptors and Ki67 index, we found significant associations between both luminal A and luminal B HER2-negative subtypes and hormone receptors (ER, PR). These have an inverse relationship with Ki67 index elevated values; luminal B HER2-positive subtype has a direct association with HER2 presence; HER2-enriched subtype was statistically significant associated to HER2 presence and elevated Ki67 index values but had an inverse relationship to hormone receptors (ER, PR); triple-negative subtype was strongly associated to Ki67 index values and inversely correlated to ER and PR. We found luminal A subtype as being the most common and luminal B HER2-positive subtype as having the fewer cases.

Pros and Cons for Automated Breast Ultrasound (ABUS): A Narrative Review

Automated breast ultrasound (ABUS) is an ultrasound technique that tends to be increasingly used as a supplementary technique in the evaluation of patients with dense glandular breasts. Patients with dense breasts have an increased risk of developing breast cancer compared to patients with fatty breasts. Furthermore, for this group of patients, mammography has a low sensitivity in detecting breast cancers, especially if it is not associated with architectural distortion or calcifications. ABUS is a standardized examination with many advantages in both screening and diagnostic settings: it increases the detection rate of breast cancer, improves the workflow, and reduces the examination time. On the other hand, like any imaging technique, ABUS has disadvantages and even some limitations. Many disadvantages can be diminished by additional attention and training. Disadvantages regarding image acquisition are the inability to assess the axilla, the vascularization, and the elasticity of a lesion, while concerning the interpretation, the disadvantages are the artifacts due to poor positioning, lack of contact, motion or lesion related. This article reviews and discusses the indications, the advantages, and disadvantages of the method and also the sources of error in the ABUS examination.

Contrast-enhanced spectral mammography without and with a delayed image for diagnosing malignancy among mass lesions in dense breast

Aim of the study

To analyse the diagnostic performance of contrast-enhanced spectral mammography (CESM) based on morphologic and enhancement patterns of mass lesions in dense breast using different protocols: CESM without delayed image and CESM with delayed image.

Material and methods

A total of 151 informed women with suspicious for malignancy mass lesions in dense breast were included in this study. All of them underwent CESM using 2 protocols. A total of 155 lesions were pathomorphologically verified. We analysed morphologic patterns on low-energy (LE) images and recombined images (RI) by defining the shape, margin, and dynamic patterns based on delayed images.

Results

The comparative analysis revealed that the shape and margins on RI were more significant than those on LE images. The dynamic indicators of CESM were found to be highly significant in dense breasts. The correlation between kinetic curve and histological results demonstrated that a persistent type of curve was common for benign lesions, accounting for 15/22 (68.1%); plateau and washout – for malignant lesions, accounting for 24/89 (26.9%) and 61/89 (68.5%), respectively. Delayed image leads to an increase of specificity up to 12.4%, which is statistically significant. The area under the curve (AUC) in CESM with delayed image is larger than that in CESM without delayed image (p < 0.01).

Conclusions

CESM is sensitive for the differential diagnosis of breast lesions. CESM with delayed image has higher specificity than CESM without delayed image. Delayed images with plateau and washout are typical for malignancy.

Detecting Vasodilation as Potential Diagnostic Biomarker in Breast Cancer Using Deep Learning-Driven Thermomics

Breast cancer is the most common cancer in women. Early diagnosis improves outcome and survival, which is the cornerstone of breast cancer treatment. Thermography has been utilized as a complementary diagnostic technique in breast cancer detection. Artificial intelligence (AI) has the capacity to capture and analyze the entire concealed information in thermography. In this study, we propose a method to potentially detect the immunohistochemical response to breast cancer by finding thermal heterogeneous patterns in the targeted area. In this study for breast cancer screening 208 subjects participated and normal and abnormal (diagnosed by mammography or clinical diagnosis) conditions were analyzed. High-dimensional deep thermomic features were extracted from the ResNet-50 pre-trained model from low-rank thermal matrix approximation using sparse principal component analysis. Then, a sparse deep autoencoder designed and trained for such data decreases the dimensionality to 16 latent space thermomic features. A random forest model was used to classify the participants. The proposed method preserves thermal heterogeneity, which leads to successful classification between normal and abnormal subjects with an accuracy of 78.16% (73.3-81.07%). By non-invasively capturing a thermal map of the entire tumor, the proposed method can assist in screening and diagnosing this malignancy. These thermal signatures may preoperatively stratify the patients for personalized treatment planning and potentially monitor the patients during treatment.

Availability Versus Utilization of Supplemental Breast Cancer Screening Post Passage of Breast Density Legislation

Objective: Despite the lack of evidence that supplemental screening in women with dense breasts reduces breast cancer mortality, 38 states have passed breast density legislation, with some including recommendations for supplemental screening. The objective of this study is to compare the availability versus use of supplemental breast cancer screening modalities and determine factors driving use of supplemental screening in rural versus urban settings. Methods: A 50-item mailed survey using the Tailored Design Method was sent to American College of Radiology mammography-accredited facilities in North Carolina in 2017. Respondents included 94 facilities (48 rural and 46 urban locations). Survey questions focused on breast cancer and supplemental screening services, breast density, risk factors/assessment, and facility demographics. Results: The survey response rate was 60.3% (94/156). Among the 94 respondents, 64.0% (n = 60) reported availability of any type of supplemental screening (digital breast tomosynthesis [DBT], ultrasound, or magnetic resonance imaging [MRI]). In facilities where supplemental screening modalities were available, the most commonly utilized supplemental screening modality was DBT (96.4%), compared with ultrasound (35.7%) and MRI (46.7%). Facilities reported using supplemental screening based on patient breast density (48.3%), referring physician recommendation (63.3%), reading radiologist recommendation (63.3%), breast cancer risk factors (48.3%), and patient request (40.0%). Urban facilities were more likely than rural facilities to base supplemental screening on breast cancer risk factors (62.5% vs. 32.1%; p-value = 0.019), referring physician (75.0% vs. 50.0%; p-value = 0.045), and reading radiologist (78.1% vs. 46.4%; p-value = 0.011). Conclusion: In our study, supplemental screening modalities were widely available, with facilities more likely to use DBT for supplemental screening compared to other modalities.

Supplemental breast cancer-screening ultrasonography in women with dense breasts: a systematic review and meta-analysis

Background

Mammography is not effective in detecting breast cancer in dense breasts.

Methods

A search in Medline, Cochrane, EMBASE and Google Scholar databases was conducted from January 1, 1980 to April 10, 2019 to identify women with dense breasts screened by mammography (M) and/or ultrasound (US). Meta-analysis was performed using the random-effect model.

Results

A total of 21 studies were included. The pooled sensitivity values of M alone and M + US in patients were 74% and 96%, while specificity of the two methods were 93% and 87%, respectively. Screening sensitivity was significantly higher in M + US than M alone (risk ratio: M alone vs. M + US = 0.699, P < 0.001), but the slight difference in specificity was statistically significant (risk ratio = 1.060, P = 0.001). Pooled diagnostic performance of follow-up US after initial negative mammography demonstrated a high pooled sensitivity (96%) and specificity (88%). The findings were supported by subgroup analysis stratified by study country, US method and timing of US.

Conclusions

Breast cancer screening by supplemental US among women with dense breasts shows added detection sensitivity compared with M alone. However, US slightly decreased the diagnostic specificity for breast cancer. The cost-effectiveness of supplemental US in detecting malignancy in dense breasts should be considered additionally.

Magnetic resonance imaging features for predicting axillary lymph node metastasis in patients with breast cancer

PURPOSE

The purpose of this study was to assess the clinical value of conventional magnetic resonance imaging (MRI) and intravoxel incoherent motion (IVIM) features for predicting the risk of axillary lymph node (ALN) metastasis in patients with breast cancer.

METHODS

This retrospective study involved 265 patients with breast cancer who underwent 3.0 T breast magnetic resonance imaging examinations prior to surgery and other treatment. Of these, 119 underwent IVIM examination. The features of MRI and IVIM and postoperative pathologic results were collected. The association of MRI features of breast cancer with ALN metastasis were determined by univariate and multivariate analyses. Comparison of IVIM parameters between breast cancer patients with and without ALN metastasis was performed using the Mann-Whitney U test.

RESULTS

Among the 265 patients, 144 (54.3%) had ALN metastasis, and 121 (45.7%) did not. The size and shape of the tumours, T2WI signal, inhomogeneous enhancement, washout intensity-time curves and the values of slow ADC, fast ADC and fraction of fast ADC parameters were significantly associated with ALN metastasis. The AUC of conventional MRI for diagnosing axillary lymph node metastasis was 0.722. The AUC of MRI combined with slow ADC, fast ADC and fraction of fast ADC parameters that were used to diagnose breast cancer with ALN metastasis were 0.814, 0.803 and 0.900, respectively.

CONCLUSIONS

The features of IVIM parameters and conventional MRI can be used to predict the ALN metastasis in patients with breast cancer. MRI combined with fraction of fast ADC showed higher diagnostic efficiency for ALN metastasis in breast cancer than MRI did.

Predicting Axillary Lymph Node Metastasis in Patients With Breast Invasive Ductal Carcinoma With Negative Axillary Ultrasound Results Using Conventional Ultrasound and Contrast-Enhanced Ultrasound

OBJECTIVES

The purpose of this study was to establish a scoring system for predicting axillary lymph node metastasis (ALNM) in patients with breast invasive ductal carcinoma with negative axillary ultrasound (US) results.

METHODS

In this retrospective study, 156 breast invasive ductal carcinoma lesions from 156 women were retrospectively enrolled. The features of conventional US and contrast-enhanced ultrasound (CEUS) qualitative enhancement patterns and quantitative enhancement parameters were analyzed. Subsequently, a scoring system was created by a multivariate logistic regression analysis.

RESULTS

The results found that 60 patients (38%) showed ALNM. A scoring system was defined as risk score = 1.75 × (if lesion size ≥20 mm) + 1.93 × (if uncircumscribed margin shown on conventional US) + 1.77 × (if coarse or twisting penetrating vessels shown on CEUS). When the risk scores were less than 1.75, 1.75 to 1.93, 1.94 to 3.70, and 3.70 or higher, the risk rates of ALNM were 0% (0 of 9), 10.7% (5 of 46), 29.2% (14 of 48) and 77.4% (41 of 53), respectively. In comparison with conventional US alone, the scoring system using the combination of conventional US and CEUS showed better discrimination ability in terms of the area under the curve (0.830 versus 0.777; P = .037).

CONCLUSIONS

A scoring system based on conventional US and CEUS may improve the prediction of ALNM.

Positron emission tomography/computed tomography using 2-deoxy-2-fluoro-18-fluoro-D-glucose peri-tumoral halo uptake layer method outperforms magnetic resonance imaging and ultrasound methods in tumor size measurement of breast cancer

As a non-invasive method, positron emission tomography (PET)/computed tomography (CT) using 2-deoxy-2-fluoro-18-fluoro-D-glucose (18F-FDG) is applied as a useful modality in the diagnosis of breast cancer. By evaluating glucose metabolism, this method can also be used in staging, restaging and post-therapeutic response evaluation. To evaluate the reliability of the ¹⁸F-FDG PET/CT-based peri-tumoral halo uptake layer (PHL) method for assessing tumor size, a total of 79 female patients with breast cancer who underwent ¹⁸F-FDG PET/CT, breast ultrasound and magnetic resonance imaging (MRI) evaluations were included in the present study. Upon examination by two independent nuclear medicine radiologists, tumor sizes were estimated by ¹⁸F-FDG PET/CT using margins defined as the inner line of the PHL. Pathological tumor sizes were evaluated on the direction of largest diameter indicated by previous imaging examination, which were also utilized as final standards. Statistical analysis of the results suggested that ¹⁸F-FDG PET/CT had a more linear correlation with pathology compared with breast ultrasound (r²=0.89 vs. 0.73) and MRI (r²=0.89 vs. 0.69) in terms of tumor size estimation, including a significantly lower bias in size difference relative to pathology. ¹⁸F-FDG PET/CT also exhibited improved performance compared with breast ultrasound and MRI in T stage assessment. These results indicated that the ¹⁸F-FDG PET/CT-based PHL method was superior to breast ultrasound and MRI, and that it provides sufficient reliability and high accuracy for measuring tumor size in patients with breast cancer.

Ultrasound and Clinical Characteristics of False-negative Results in Mammography Screening of Dense Breasts

OBJECTIVE

We analyzed the clinical and ultrasound characteristics associated with false-negative mammography results in women with dense breasts.

MATERIALS AND METHODS

The present study included 191 women (mean age, 54.47 ± 11.61 years; range, 31-75 years) who had presented from July 2015 to June 2018 with pathologically confirmed breast cancer. The mammography, conventional ultrasound, and elastography imaging results of these patients were reviewed. Breast density and screening cancer probability from mammography and conventional ultrasound imaging were scored using the Breast Imaging Reporting and Data System. Multivariate logistic regression analysis was performed to identify the factors independently associated with the false-negative results on breast mammographic screening.

RESULTS

Of 191 confirmed breast cancer cases, 55 (28.8%) were assigned to category ≤ 3, and 136 (71.2%) were assigned to category ≥ 4a according to the mammography findings. All the breasts were graded mammographically as dense. A rougher margin (odds ratio [OR], 8.123; 95% confidence interval [CI], 1.731-38.127) was the strongest independent factor associated with negative results, followed by a lower stiffness ratio (OR, 7.773; 95% CI, 2.574-23.473), negative axillary lymph node status (OR, 5.066; 95% CI, 1.028-24.955), and softer lesions (OR, 1.037; 95% CI, 1.001-1.075).

CONCLUSION

Women with dense breasts, a lower lesion/glandular tissue stiffness ratio, and softer cancer can easily lead to a misdiagnosis using mammography. By giving sufficient attention to the margin, earlier stage cancer with negative lymph node status are more likely to benefit from supplemental ultrasound imaging.

Diagnostic value of an automated breast volume scanner compared with a hand-held ultrasound: a meta-analysis

Background

The diagnostic performance of an automated breast volume scanner (ABVS) compared with that of a hand-held ultrasound (HHUS) for breast cancer remains unclear. We performed a meta-analysis to compare the diagnostic performances of the ABVS and HHUS for breast cancer.

Methods

We searched PubMed, EMBASE, Cochrane, and SinoMed databases to identify eligible studies up until November 14, 2018. Studies comparing ABVS and HHUS for differentiating benign and malignant breast tumors were included. A meta-analysis was performed to generate pooled diagnostic accuracy parameters [sensitivity, specificity, diagnostic odds ratio (DOR), area under the curve (AUC), and the Q* index] and detection rates for ABVS and HHUS.

Results

Nine studies involving 1,376 patients and 1,527 lesions were included in the meta-analysis for diagnostic accuracy. The pooled sensitivity was 0.93 [95% confidence interval (CI), 0.91-0.95] for ABVS and 0.90 (95% CI, 0.88-0.92) for HHUS, and the pooled specificity was 0.86 (95% CI, 0.83-0.88) for ABVS and 0.82 (95% CI, 0.79-0.84) for HHUS. The pooled DOR was 88.66 (95% CI, 51.44-152.78) for ABVS and 41.06 for HHUS (95% CI, 26.58-63.42). The AUC of the summary receiver operating characteristic (SROC) was 0.9496 for ABVS and 0.9143 for HHUS, and the Q* index was 0.8899 for ABVS and 0.8469 for HHUS. Meta-regression showed no significant difference between the diagnostic accuracy of ABVS and HHUS (P=0.0771). No publication bias was found. Thirteen published studies involving 1,047 pathologically confirmed malignant lesions were included to generate a pooled detection rate. The pooled detection rate was 1.00 (95% CI, 1.00-1.00) for both ABVS and HHUS, for which a publication bias was found.

Conclusions

ABVS can be used as an appropriate screening tool for breast cancer as well as HHUS in diagnostic accuracy and detection rate. Considering other advantages of ABVS including non-radioactivity, sensitivity to dense breast, three-dimensional reconstruction, time-saving and repeatability, it might be a promising screening tool for young or dense-breast women in the future.

Initial clinical results with a fusion prototype for mammography and three-dimensional ultrasound with a standard mammography system and a standard ultrasound probe

BACKGROUND

Combinations *Equal contributors. of different imaging techniques in fusion devices appear to be associated with improvements in diagnostic assessment.

PURPOSE

The aim of this study was to test the feasibility of using an automated standard three-dimensional (3D) ultrasound (US) device fused with standard mammography for the first time in breast cancer patients.

MATERIAL AND METHODS

Digital mammograms and 3D automated US images were obtained in 23 patients with highly suspicious breast lesions. A recently developed fusion machine consisting of an ABVS 3D US transducer from an Acuson S2000 machine and a conventional Mammomat Inspiration device (both Siemens Healthcare GmbH, Erlangen, Germany) were used for the purpose. The feasibility of the examinations, imaging coverage, and patients' experience of the procedure were examined.

RESULTS

In 15 out of 19 patients, the region of interest (ROI) with the tumor marked in the mammogram was visible on US. The examination was experienced positively by the patients, with no unexpected pain or injury. The examination was time-saving and well tolerated.

CONCLUSION

In conclusion, we have shown initial clinical feasibility of an US/radiography fusion prototype with good localization and evaluation of the ROIs. The combined examination was well tolerated. The simultaneous evaluation with mammography and US imaging may be able to improve detection and reduce examiner-related variability.

Should This Woman With Dense Breasts Receive Supplemental Breast Cancer Screening?: Grand Rounds Discussion From Beth Israel Deaconess Medical Center

Breast cancer will develop in 12% of women during their lifetime and is the second leading cause of cancer death among U.S. women. Mammography is the most commonly used tool to screen for breast cancer. Considerable uncertainty exists regarding the age at which to begin screening and the optimal screening interval. Breast density is a risk factor for breast cancer. In addition, for women with dense breasts, small tumors may be missed on mammography and the sensitivity of screening is diminished. At the time of publication, 35 states had passed laws mandating that breast density be reported in the letters that radiologists send to women with their mammogram results. The mandated language may be challenging for patients to understand, and such reporting may increase worry for women who are told that their risk for breast cancer is higher than average on the basis of breast density alone. The U.S. Preventive Services Task Force and the American College of Radiology (ACR) have each issued guidelines that address breast cancer screening for women with dense breasts. Both organizations found insufficient evidence to recommend for or against magnetic resonance screening, whereas the ACR advises consideration of ultrasonography for supplemental screening. In this Beyond the Guidelines, 2 experts-a radiologist and a general internist-discuss these controversies. In particular, the discussants review the role of supplemental breast cancer screening, including breast ultrasonography or magnetic resonance imaging for women with dense breasts. Finally, the experts offer specific advice for a patient who finds her mammography reports confusing.

Ultrasound Features of Breast Cancer for Predicting Axillary Lymph Node Metastasis

OBJECTIVES

The purpose of this study was to assess the clinical value of ultrasound (US) features of breast lesions for predicting the risk of axillary lymph node metastasis in patients with breast cancer.

METHODS

In this retrospective study, 425 patients with breast cancer were recruited, and their preoperative US features and postoperative pathologic results were collected. The association of these US features of breast cancer with axillary lymph node metastasis was determined by univariate and multivariate analyses.

RESULTS

Among the 425 patients, 200 (47.1%) had axillary lymph node metastasis, and 225 (52.9%) did not. The parameters of tumor shape, color Doppler flow imaging grades, histologic grade, and E-cadherin level were significantly and independently associated with axillary lymph node metastasis (P < .05 for all).

CONCLUSIONS

Axillary lymph node metastasis was prone to happen in patients with US features of an irregular tumor shape and higher color Doppler flow imaging grades. Ultrasound imaging provides a promising tool for predicting axillary lymph node metastasis in patients with breast cancer.

The Role of Affordable, Point-of-Care Technologies for Cancer Care in Low- and Middle-Income Countries: A Review and Commentary

As the burden of non-communicable diseases such as cancer continues to rise in low- and middle-income countries (LMICs), it is essential to identify and invest in promising solutions for cancer control and treatment. Point-of-care technologies (POCTs) have played critical roles in curbing infectious disease epidemics in both high- and low-income settings, and their successes can serve as a model for transforming cancer care in LMICs, where access to traditional clinical resources is often limited. The versatility, cost-effectiveness, and simplicity of POCTs warrant attention for their potential to revolutionize cancer detection, diagnosis, and treatment. This paper reviews the landscape of affordable POCTs for cancer care in LMICs with a focus on imaging tools, in vitro diagnostics, and treatment technologies and aspires to encourage innovation and further investment in this space.