Comparison of automated breast volume scanning and hand- held ultrasound in the detection of breast cancer: an analysis of 5,566 patient evaluations

A systematic review and meta-analysis comparing the diagnostic capability of automated breast ultrasound and contrast-enhanced ultrasound in breast cancer

Objective

To compare the diagnostic performance of automated breast ultrasound (ABUS) and contrast-enhanced ultrasound (CEUS) in breast cancer.

Methods

Published studies were collected by systematically searching the databases PubMed, Embase, Cochrane Library and Web of Science. The sensitivities, specificities, likelihood ratios and diagnostic odds ratio (DOR) were confirmed. The symmetric receiver operator characteristic curve (SROC) was used to assess the threshold of ABUS and CEUS. Fagan's nomogram was drawn. Meta-regression and subgroup analyses were applied to search for sources of heterogeneity among the included studies.

Results

A total of 16 studies were included, comprising 4115 participants. The combined sensitivity of ABUS was 0.88 [95% CI (0.73-0.95)], specificity was 0.93 [95% CI (0.82-0.97)], area under the SROC curve (AUC) was 0.96 [95% CI (0.94-0.96)] and DOR was 89. The combined sensitivity of CEUS was 0.88 [95% CI (0.84-0.91)], specificity was 0.76 [95% CI (0.66-0.84)], AUC was 0.89 [95% CI (0.86-0.92)] and DOR was 24. The Deeks' funnel plot showed no existing publication bias. The prospective design, partial verification bias and blinding contributed to the heterogeneity in specificity, while no sources contributed to the heterogeneity in sensitivity. The post-test probability of ABUS in BC was 75%, and the post-test probability of CEUS in breast cancer was 48%.

Conclusion

Compared with CEUS, ABUS showed higher specificity and DOR for detecting breast cancer. ABUS is expected to further improve the accuracy of BC diagnosis.

Comparative analysis of automated breast volume scanner (ABVS) combined with conventional hand-held ultrasound and mammography in female breast cancer detection

Objective and background

This study aimed to compare the diagnostic value of an automated breast volume scanner (ABVS) combined with conventional hand-held ultrasound and mammography in detecting female breast cancer. Early detection is vital in improving patient outcomes for this prevalent disease.

Methods

Seventy-eight suspicious breast lesions from 60 patients were examined between August 2019 and July 2020. Each patient underwent ABVS, conventional hand-held ultrasound, and mammography. Diagnostic values, including coincidence rate, sensitivity, specificity, positive predictive value, and negative predictive value, were calculated using histopathology results as the "gold standard."

Results

Histopathology confirmed 55 malignant (70.51%) and 23 benign lesions (29.48%). ABVS combined with conventional hand-held ultrasound identified 56 malignant (52 confirmed, 4 benign) and 22 benign nodules (3 confirmed, 19 benign). Mammography detected 48 malignant (45 confirmed, 3 benign) and 30 benign nodules (10 confirmed, 20 benign). ABVS combined with conventional hand-held ultrasound had a sensitivity of 94.5%, specificity of 82.6%, positive predictive value of 92.9%, and negative predictive value of 86.4%. Mammography showed a sensitivity of 81.8%, specificity of 87.0%, positive predictive value of 93.8%, and negative predictive value of 66.7%.

Conclusion

ABVS combined with conventional hand-held ultrasound showed high diagnostic value in detecting female breast cancer. The "convergence sign" in the coronal section played a significant role. It slightly outperformed mammography and offered advantages in terms of cost, convenience, comfort, and absence of radiation. Further promotion and implementation are supported.

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 for Breast Cancer Screening in Resource-Limited Settings: Current Practice and Future Directions

Breast cancer (BC) is the most prevalent cancer among women globally. Cancer screening can reduce mortality and improve women’s health. In developed countries, mammography (MAM) has been primarily utilized for population-based BC screening for several decades. However, it is usually unavailable in low-resource settings due to the lack of equipment, personnel, and time necessary to conduct and interpret the examinations. Ultrasound (US) with high detection sensitivity for women of younger ages and with dense breasts has become a supplement to MAM for breast examination. Some guidelines suggest using US as the primary screening tool in certain settings where MAM is unavailable and infeasible, but global recommendations have not yet reached a unanimous consensus. With the development of smart devices and artificial intelligence (AI) in medical imaging, clinical applications and preclinical studies have shown the potential of US combined with AI in BC screening. Nevertheless, there are few comprehensive reviews focused on the role of US in screening BC in underserved conditions, especially in technological, economical, and global perspectives. This work presents the benefits, limitations, advances, and future directions of BC screening with technology-assisted and resource-appropriate strategies, which may be helpful to implement screening initiatives in resource-limited countries.

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.

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.

Second-Generation 3D Automated Breast Ultrasonography (Prone ABUS) for Dense Breast Cancer Screening Integrated to Mammography: Effectiveness, Performance and Detection Rates

In our study, we added a three-dimensional automated breast ultrasound (3D ABUS) to mammography to evaluate the performance and cancer detection rate of mammography alone or with the addition of 3D prone ABUS in women with dense breasts. Our prospective observational study was based on the screening of 1165 asymptomatic women with dense breasts who selected independent of risk factors. The results evaluated include the cancers detected between June 2017 and February 2019, and all surveys were subjected to a double reading. Mammography detected four cancers, while mammography combined with a prone Sofia system (3D ABUS) doubled the detection rate, with eight instances of cancer being found. The diagnostic yield difference was 3.4 per 1000. Mammography alone was subjected to a recall rate of 14.5 for 1000 women, while mammography combined with 3D prone ABUS resulted in a recall rate of 26.6 per 1000 women. We also observed an additional 12.1 recalls per 1000 women screened. Integrating full-field digital mammography (FFDM) with 3D prone ABUS in women with high breast density increases and improves breast cancer detection rates in a significant manner, including small and invasive cancers, and it has a tolerable impact on recall rate. Moreover, 3D prone ABUS performance results are comparable with the performance results of the supine 3D ABUS system.

A multicenter, hospital-based and non-inferiority study for diagnostic efficacy of automated whole breast ultrasound for breast cancer in China

This study is the first multi-center non-inferiority study that aims to critically evaluate the effectiveness of HHUS/ABUS in China breast cancer detection. This was a multicenter hospital-based study. Five hospitals participated in this study. Women (30–69 years old) with defined criteria were invited for breast examination by HHUS, ABUS or/and mammography. For BI-RADS category 3, an additional magnetic resonance imaging (MRI) test was provided to distinguish the true negative results from false negative results. For women classified as BI-RADS category 4 or 5, either core aspiration biopsy or surgical biopsy was done to confirm the diagnosis. Between February 2016 and March 2017, 2844 women signed the informed consent form, and 1947 of them involved in final analysis (680 were 30 to 39 years old, 1267 were 40 to 69 years old).For all participants, ABUS sensitivity (91.81%) compared with HHUS sensitivity (94.70%) with non-inferior Z tests, P = 0.015. In the 40–69 age group, non-inferior Z tests showed that ABUS sensitivity (93.01%) was non-inferior to MG sensitivity (86.02%) with P < 0.001 and HHUS sensitivity (95.44%) was non-inferior to MG sensitivity (86.02%) with P < 0.001. Sensitivity of ABUS and HHUS are all superior to that of MG with P < 0.001 by superior test.For all participants, ABUS specificity (92.89%) was non-inferior to HHUS specificity (89.36%) with P < 0.001. Superiority test show that specificity of ABUS was superior to that of HHUS with P < 0.001. In the 40–69 age group, ABUS specificity (92.86%) was non-inferior to MG specificity (91.68%) with P < 0.001 and HHUS specificity (89.55%) was non-inferior to MG specificity (91.68%) with P < 0.001. ABUS is not superior to MG with P = 0.114 by superior test. The sensitivity of ABUS/HHUS is superior to that of MG. The specificity of ABUS/HHUS is non-inferior to that of MG. In China, for an experienced US radiologist, both HHUS and ABUS have better diagnostic efficacy than MG in symptomatic individuals.

First proof-of-concept evaluation of the FUSION-X-US-II prototype for the performance of automated breast ultrasound in healthy volunteers

Purpose

The FUSION-X-US-II prototype was developed to combine 3D-automated breast ultrasound (ABUS) and digital breast tomosynthesis in a single device without decompressing the breast. We evaluated the technical function, feasibility of the examination workflow, image quality, breast tissue coverage and patient comfort of the ABUS device of the new prototype.

Methods

In this prospective feasibility study, the FUSION-X-US-II prototype was used to perform ABUS in 30 healthy volunteers without history of breast cancer. The ABUS images of the prototype were interpreted by a physician with specialization in breast diagnostics. Any detected lesions were measured and classified using BI-RADS^® scores. Image quality was rated subjectively by the physician and coverage of the breast was measured. Patient comfort was evaluated by a questionnaire after the examination.

Results

One hundred and six scans were performed (61 × CC, 23 × ML, 22 × MLO) in 60 breasts. Image acquisition and processing by the prototype was fast and accurate. Breast coverage by ABUS was approximately 90.8%. Sixteen breast lesions (all benign, classified as BIRADS^® 2) were identified. The examination was tolerated by all patients.

Conclusion

The FUSION-X-US-II prototype allows a rapid ABUS scan with mostly high patient comfort. Technical developments resulted in an improvement of quality and coverage compared to previous prototype versions. The results are encouraging for a test of the prototype in a clinical setting in combination with tomosynthesis.

The added advantage of automated breast ultrasound to mammographically detected different breast lesions in patients with dense breasts

Background

Breast cancer is the most commonly diagnosed malignancy in women worldwide. Women with dense breast tend to have 15–25% lifetime risk of breast cancer due to decrease of mammographic sensitivity. Automated breast ultrasound (ABUS) is a new promising tool for detection of breast lesions masked by dense glandular tissue at mammography.

Results

The sensitivity of digital mammography in detecting breast lesions was 60.7%, specificity 91.6%, PPV 85%, NPV 75%, and accuracy 78%. The sensitivity of ABUS in detecting breast lesions was 92.86%, specificity 77.78%, PPV 76.47%, NPV 93.33%, and accuracy 84.38%. The sensitivity of handheld ultrasound (HHUS) in detecting breast lesions was 89.29%, specificity 88.89%, PPV 86.21%, NPV 91.43%, and accuracy 89.06%.

Conclusion

The sensitivity of ABUS in detecting breast lesions was much higher than mammography in dense breast while the digital mammography (DM) had higher specificity. So, implementation of both DM and ABUS to get benefit of DM specificity as well as ABUS sensitivity were highly recommended.

Preliminary study of the technical limitations of automated breast ultrasound: from procedure to diagnosis

Objective

To evaluate the main technical limitations of automated breast ultrasound and to determine the proportion of examinations excluded.

Materials and Methods

We evaluated 440 automated breast ultrasound examinations performed, over a 12-month period, by technicians using an established protocol.

Results

In five cases (1.1%), the examination was deemed unacceptable for diagnostic purposes, those examinations therefore being excluded.

Conclusion

Automated breast ultrasound is expected to overcome some of the major limitations of conventional ultrasound in breast cancer screening. In Brazil, this new method can be accepted for inclusion in routine clinical practice only after its advantages have been validated in the national context.

Automated Breast Ultrasound System for Breast Cancer Evaluation: Diagnostic Performance of the Two-View Scan Technique in Women with Small Breasts

OBJECTIVE

To comparatively evaluate the scan coverage and diagnostic performance of the two-view scan technique (2-VST) of the automated breast ultrasound system (ABUS) versus the conventional three-view scan technique (3-VST) in women with small breasts.

MATERIALS AND METHODS

Between March 2016 and May 2017, 136 asymptomatic women with small breasts (bra cup size A) suitable for 2-VST were enrolled. Subsequently, 272 breasts were subjected to bilateral whole-breast ultrasound examinations using ABUS and the hand-held ultrasound system (HHUS). During ABUS image acquisition, one breast was scanned with 2-VST, while the other breast was scanned with 3-VST. In each breast, the breast coverage and visibility of the HHUS detected lesions on ABUS were assessed. The sensitivity and specificity of ABUS were compared between 2-VST and 3-VST.

RESULTS

Among 136 breasts, eight cases of breast cancer were detected by 2-VST, and 10 cases of breast cancer were detected by 3-VST. The breast coverage was satisfactory in 94.1% and 91.9% of cases under 2-VST and 3-VST, respectively (p = 0.318). All HHUS-detected lesions were visible on the ABUS images regardless of the scan technique. The sensitivities and specificities were similar between 2-VST and 3-VST (100% [8/8] vs. 100% [10/10], and 97.7% [125/128] vs. 95.2% [120/126], respectively), with no significant difference (p > 0.05).

CONCLUSION

2-VST of ABUS achieved comparable scan coverage and diagnostic performance to that of conventional 3-VST in women with small breasts.

Automatic breast ultrasound: state of the art and future perspectives

The three-dimensional automated breast ultrasound system (3D ABUS) is a new device which represents a huge innovation in the breast ultrasound field, with several application scenarios of great interest.

ABUS's aim is to solve some of the main defects of traditional ultrasound, such as lack of standardization, high level of skill non-reproducibility, small field of view and high commitment of physician time. ABUS has proven to be an excellent non-ionising alternative to other supplemental screening options for women with dense breast tissue; also, it has appeared to be very promising in daily clinical practice.

The purpose of this paper is to present a summary of current applications of ABUS, focusing on clinical applications and future perspectives as ABUS is particularly promising for studies involving artificial intelligence, radiomics and evaluation of breast molecular subtypes.

Comparison of automated versus hand-held breast US in supplemental screening in asymptomatic women with dense breasts: is there a difference regarding woman preference, lesion detection and lesion characterization?

PURPOSE

To compare automated breast volumetric scanning (ABVS) with hand-held bilateral whole breast ultrasound (HHUS) prospectively in regards to patient workflow, woman preference, efficacy in lesion detection, and characterization.

MATERIALS AND METHODS

Supplemental screening was performed with both ABVS and HHUS to 345 women with dense breasts and negative mammograms. Acquisition and evaluation times were recorded. Lesions were classified according to BIRADS US criteria and compared one to one. Women were recalled for a secondary HHUS examination if ABVS showed any additional lesions. Findings were compared based on biopsy results and/or 36-48 months of follow-up.

RESULTS

Findings could be compared for 340 women. There were two carcinomas which were detected by both methods, with no interval cancers in the follow-up period. Recall rate was 46/340 (13.05%) for ABVS and 4/340 (1.18%) for HHUS. ABVS recalls decreased with experience. HHUS had more true negative (BIRADS 1-2) results, while ABVS had more false positive ones (p < 0.001). Positive predictive value was 4.17% for ABVS and 50% for HHUS. ABVS overdiagnosed shadowings (p < 0.01), distortions (p < 0.034), and irregular nodules (p < 0.001) in comparison to HHUS. At ABVS, 10.6% of women experienced severe pain. 59.7% stated that they would choose HHUS if they had the chance.

CONCLUSION

ABVS is as good as HHUS in lesion detection. However, the recall rate is higher and positive predictive value is lower with ABVS, which could result in more follow-ups, and more anxiety for the women. More than 50% women stated they would prefer HHUS if they were given the chance.

Preferences and Attitudes Regarding Adjunct Breast Cancer Screening Among Patients with Dense Breasts

OBJECTIVE

New breast screening modalities are being investigated to address the need for more sensitive breast cancer screening in women with dense breasts. We investigated the preferences and attitudes of these patients regarding adjunct screening modalities to help evaluate the acceptability of these exams.

METHODS

In this institutional review board-approved prospective study, patients with dense breasts on their prior mammogram were invited to complete a survey. Patients were asked to estimate their personal breast cancer risk compared with peers, indicate their level of concern related to screening callbacks, radiation exposure, and intravenous (IV) contrast allergies, and identify which factors might deter them from getting adjunct screening exams.

RESULTS

Five hundred eight patients with dense breasts presenting for screening mammography completed surveys. While most patients (304/508, 59.9%) felt it was likely or very likely that cancer could be missed on their mammogram, only 8.9% (45/508) had undergone adjunct screening exams in the past 3 years. The most commonly cited deterrents to adjunct screening were cost (340/508, 66.9%), pain (173/508, 34.1%), and concern that adjunct screening could lead to additional procedures (158/508, 31.1%). When asked to select among three hypothetical breast cancer screening modalities, patients strongly preferred the more sensitive examination, even if this involved greater cost (162/508, 31.9%) or IV-contrast administration (315/508, 62.0%).

CONCLUSION

Our data suggest that patients with dense breasts prefer adjunct screening exams that are both sensitive and inexpensive, although an increase in sensitivity could outweigh additional cost or even IV-line placement.

A Prospective Study of Automated Breast Ultrasound Screening of Women with Dense Breasts in a Digital Breast Tomosynthesis-based Practice

OBJECTIVE

To assess prospectively the interpretative performance of automated breast ultrasound (ABUS) as a supplemental screening after digital breast tomosynthesis (DBT) or as a standalone screening of women with dense breast tissue.

METHODS

Under an IRB-approved protocol (written consent required), women with dense breasts prospectively underwent concurrent baseline DBT and ABUS screening. Examinations were independently evaluated, in opposite order, by two of seven Mammography Quality Standards Act-qualified radiologists, with the primary radiologist arbitrating disagreements and making clinical management recommendations. We report results for 1111 screening examinations (598 first year and 513 second year) for which all diagnostic workups are complete. Imaging was also retrospectively reviewed for all cancers. Statistical assessments used a 0.05 significance level and accounted for correlation between participants' examinations.

RESULTS

Of 1111 women screened, primary radiologists initially "recalled" based on DBT alone (6.6%, 73/1111, CI: 5.2%-8.2%), of which 20 were biopsied, yielding 6/8 total cancers. Automated breast ultrasound increased recalls overall to 14.4% (160/1111, CI: 12.4%-16.6%), with 27 total biopsies, yielding 1 additional cancer. Double reading of DBT alone increased the recall rate to 10.7% (119/1111), with 21 biopsies, with no improvement in cancer detection. Double reading ABUS increased the recall rate to 15.2% (169/1111, CI: 13.2%-17.5%) of women, of whom 22 were biopsied, yielding the detection of 7 cancers, including one seen only on double reading ABUS. Inter-radiologist agreement was similar for recall recommendations from DBT (κ = 0.24, CI: 0.14-0.34) and ABUS (κ = 0.23, CI: 0.15-0.32). Integrated assessments from both readers resulted in a recall rate of 15.1% (168/1111, CI: 13.1%-17.4%).

CONCLUSION

Supplemental or standalone ABUS screening detected cancers not seen on DBT, but substantially increased noncancer recall rates.

Ultrasound for Breast Cancer Detection Globally: A Systematic Review and Meta-Analysis

PURPOSE

Mammography is not always available or feasible. The purpose of this systematic review and meta-analysis is to assess the diagnostic performance of ultrasound as a primary tool for early detection of breast cancer.

MATERIALS AND METHODS

For this systematic review and meta-analysis, we comprehensively searched PubMed and SCOPUS to identify articles from January 2000 to December 2018 that included data on the performance of ultrasound for detection of breast cancer. Studies evaluating portable, handheld ultrasound as an independent detection modality for breast cancer were included. Quality assessment and bias analysis were performed with the Quality Assessment of Diagnostic Accuracy Studies-2 tool. Sensitivity analyses and meta-regression were used to explore heterogeneity. The study protocol has been registered with the international prospective register of systematic reviews (PROSPERO identifier: CRD42019127752).

RESULTS

Of the 526 identified studies, 26 were eligible for inclusion. Ultrasound had an overall pooled sensitivity and specificity of 80.1% (95% CI, 72.2% to 86.3%) and 88.4% (95% CI, 79.8% to 93.6%), respectively. When only low- and middle-income country data were considered, ultrasound maintained a diagnostic sensitivity of 89.2% and specificity of 99.1%. Meta-analysis of the included studies revealed heterogeneity. The high sensitivity of ultrasound for the detection of breast cancer was not statistically significantly different in subgroup analyses on the basis of mean age, risk, symptoms, study design, bias level, and study setting.

CONCLUSION

Given the increasing burden of breast cancer and infeasibility of mammography in certain settings, we believe these results support the potential use of ultrasound as an effective primary detection tool for breast cancer, which may be beneficial in low-resource settings where mammography is unavailable.

Validation of radiologists' findings by computer-aided detection (CAD) software in breast cancer detection with automated 3D breast ultrasound: a concept study in implementation of artificial intelligence software

Background

Computer-aided detection software for automated breast ultrasound has been shown to have potential in improving the accuracy of radiologists. Alternative ways of implementing computer-aided detection, such as independent validation or preselecting suspicious cases, might also improve radiologists’ accuracy.

Purpose

To investigate the effect of using computer-aided detection software to improve the performance of radiologists by validating findings reported by radiologists during screening with automated breast ultrasound.

Material and Methods

Unilateral automated breast ultrasound exams were performed in 120 women with dense breasts that included 60 randomly selected normal exams, 30 exams with benign lesions, and 30 malignant cases (20 mammography-negative). Eight radiologists were instructed to detect breast cancer and rate lesions using BI-RADS and level-of-suspiciousness scores. Computer-aided detection software was used to check the validity of radiologists' findings. Findings found negative by computer-aided detection were not included in the readers’ performance analysis; however, the nature of these findings were further analyzed. The area under the curve and the partial area under the curve for an interval in the range of 80%–100% specificity before and after validation of computer-aided detection were compared. Sensitivity was computed for all readers at a simulation of 90% specificity.

Results

Partial AUC improved significantly from 0.126 (95% confidence interval [CI] = 0.098–0.153) to 0.142 (95% CI = 0.115–0.169) ( P = 0.037) after computer-aided detection rejected mostly benign lesions and normal tissue scored BI-RADS 3 or 4. The full areas under the curve (0.823 vs. 0.833, respectively) were not significantly different ( P = 0.743). Four cancers detected by readers were completely missed by computer-aided detection and four other cancers were detected by both readers and computer-aided detection but falsely rejected due to technical limitations of our implementation of computer-aided detection validation. In this study, validation of computer-aided detection discarded 42.6% of findings that were scored BI-RADS ≥3 by the radiologists, of which 85.5% were non-malignant findings.

Conclusion

Validation of radiologists’ findings using computer-aided detection software for automated breast ultrasound has the potential to improve the performance of radiologists. Validation of computer-aided detection might be an efficient tool for double-reading strategies by limiting the amount of discordant cases needed to be double-read.

Screening Breast Ultrasound Using Handheld or Automated Technique in Women with Dense Breasts

In women with dense breasts (heterogeneously or extremely dense), adding screening ultrasound to mammography increases detection of node-negative invasive breast cancer. Similar incremental cancer detection rates averaging 2.1-2.7 per 1000 have been observed for physician- and technologist-performed handheld ultrasound (HHUS) and automated ultrasound (AUS). Adding screening ultrasound (US) for women with dense breasts significantly reduces interval cancer rates. Training is critical before interpreting examinations for both modalities, and a learning curve to achieve optimal performance has been observed. On average, about 3% of women will be recommended for biopsy on the prevalence round because of screening US, with a wide range of 2%-30% malignancy rates for suspicious findings seen only on US. Breast Imaging Reporting and Data System 3 lesions identified only on screening HHUS can be safely followed at 1 year rather than 6 months. Computer-aided detection and diagnosis software can augment performance of AUS and HHUS; ongoing research on machine learning and deep learning algorithms will likely improve outcomes and workflow with screening US.

Diagnostic Performance of Automated Breast Ultrasound in Differentiating Benign and Malignant Breast Masses in Asymptomatic Women: A Comparison Study With Handheld Ultrasound

OBJECTIVES

Our aim was to investigate the diagnostic potential of an automated breast ultrasound (ABUS) system in differentiating benign and malignant breast masses compared with handheld ultrasound (HHUS).

METHODS

Women were randomly and proportionally selected from outpatients and underwent both HHUS and ABUS examinations. Masses with final American College of Radiology Breast Imaging Reporting and Data System categories 2 and 3 were considered benign. Masses with final Breast Imaging Reporting and Data System categories 4 and 5 were considered malignant. The diagnosis was confirmed by pathologic results or at least a 1-year follow-up. Automated breast US and HHUS were compared on the basis of their sensitivity, specificity, positive predictive value, negative predictive value, and accuracy. Diagnostic consistency and areas under the receiver operating characteristic curves were analyzed. The maximum diameters of masses were compared among HHUS, ABUS, and pathologic results.

RESULTS

A total of 599 masses in 398 women were confirmed by pathologic results or at least a 1-year follow-up; 103 of 599 masses were malignant, and 496 were benign. There were no significant differences between ABUS and HHUS in terms of diagnostic accuracy (80.1% versus 80.6%), specificity (77.62% versus 80.24%), positive predictive value (46.12% versus 46.46%), and negative predictive value (97.96% versus 95.67%). There were significant differences in sensitivity (92.23% versus 82.52%; P < .01) and areas under the curve (0.85 versus 0.81; P < .05) between ABUS and HHUS. The correlation of the maximum diameter was slightly higher between ABUS and pathologic results (r = 0.885) than between HHUS and pathologic results (r = 0.855), but the difference was not significant (P > .05).

CONCLUSIONS

Automated breast US is better than HHUS in differentiating benign and malignant breast masses, especially with respect to specificity.

Automated breast ultrasound (ABUS) as a screening tool: initial experience

Background

Breast cancer is a major health problem, being the most common cancer in women. Early detection of breast cancer aims to the reduction of mortality and morbidity rates. Conventional screening methods include mammography and ultrasonography; however, both modalities have their limitations. Automated breast ultrasound (ABUS) is a recent technological advancement in the field of breast imaging having the benefit of standardization of the scans and lack of operator dependence as in conventional handheld ultrasound scans. The aim of this work was to report our initial experience of the added value of ABUS as a breast screening tool. The study included 200 patients who had screening mammograms, ultrasound, and ABUS.

Results

A significant difference was found between the number of lesions detected by ABUS and conventional ultrasound. A significant difference was found between lesions detected by ABUS and mammography which was most evident in patients with dense breasts.

Conclusions

ABUS is a valuable tool in the screening of the breast with improved lesion detection, especially in patients with dense breasts.

Clinical Application Value of Automated Breast Volume Scanner in the Diagnosis of Abdominal External Hernia

This study investigated the clinical application value of the automated breast volume scanner (ABVS) in patients with abdominal external hernias. A total of 121 abdominal external hernias from 103 inpatients were examined with both conventional handheld ultrasound (HHUS) and the ABVS before surgery. The rate of detection of abdominal external hernias and the diagnostic accuracy of classifying inguinal hernias using the two modalities were compared between junior and senior sonographers. Additionally, the sonographic appearance of abdominal external hernias with the ABVS system was evaluated. The results revealed that junior sonographers had a higher detection rate with the ABVS (92.6%) than with HHUS (83.5%). For the classification of inguinal hernias, the accuracy of junior sonographers using the ABVS was 89.2%, which was higher than that for the HHUS system (77.6%), but there was no significant difference between HHUS (92.7%) and the ABVS (93.1%) for senior sonographers. Measurement of the hernia orifice size with the ABVS was accurate. In addition, the ABVS could provide coronal images and visually revealed the contents of the hernia, the shape of the hernia orifice and the pathway of herniation, as well as the relationship with adjacent tissues. Therefore, the clinical application value of the ABVS for abdominal external hernias is excellent.

Dedicated computer-aided detection software for automated 3D breast ultrasound; an efficient tool for the radiologist in supplemental screening of women with dense breasts

OBJECTIVES

To determine the effect of computer-aided-detection (CAD) software for automated breast ultrasound (ABUS) on reading time (RT) and performance in screening for breast cancer.

MATERIAL AND METHODS

Unilateral ABUS examinations of 120 women with dense breasts were randomly selected from a multi-institutional archive of cases including 30 malignant (20/30 mammography-occult), 30 benign, and 60 normal cases with histopathological verification or ≥ 2 years of negative follow-up. Eight radiologists read once with (CAD-ABUS) and once without CAD (ABUS) with > 8 weeks between reading sessions. Readers provided a BI-RADS score and a level of suspiciousness (0-100). RT, sensitivity, specificity, PPV and area under the curve (AUC) were compared.

RESULTS

Average RT was significantly shorter using CAD-ABUS (133.4 s/case, 95% CI 129.2-137.6) compared with ABUS (158.3 s/case, 95% CI 153.0-163.3) (p < 0.001). Sensitivity was 0.84 for CAD-ABUS (95% CI 0.79-0.89) and ABUS (95% CI 0.78-0.88) (p = 0.90). Three out of eight readers showed significantly higher specificity using CAD. Pooled specificity (0.71, 95% CI 0.68-0.75 vs. 0.67, 95% CI 0.64-0.70, p = 0.08) and PPV (0.50, 95% CI 0.45-0.55 vs. 0.44, 95% CI 0.39-0.49, p = 0.07) were higher in CAD-ABUS vs. ABUS, respectively, albeit not significantly. Pooled AUC for CAD-ABUS was comparable with ABUS (0.82 vs. 0.83, p = 0.53, respectively).

CONCLUSION

CAD software for ABUS may decrease the time needed to screen for breast cancer without compromising the screening performance of radiologists.

KEY POINTS

• ABUS with CAD software may speed up reading time without compromising radiologists' accuracy. • CAD software for ABUS might prevent non-detection of malignant breast lesions by radiologists. • Radiologists reading ABUS with CAD software might improve their specificity without losing sensitivity.

Automated Breast Ultrasound: Dual-Sided Compared with Single-Sided Imaging

The design and performance of a mammographically configured, dual-sided, automated breast ultrasound (ABUS) 3-D imaging system are described. Dual-sided imaging (superior and inferior) is compared with single-sided imaging to aid decisions on clinical implementation of the more complex, but potentially higher-quality dual-sided imaging. Marked improvement in image quality and coverage of the breast is obtained in dual-sided ultrasound over single-sided ultrasound. Among hypo-echoic masses imaged, there are increases in the mean contrast-to-noise ratio of 57% and 79%, respectively, for spliced dual-sided versus superior or inferior single-sided imaging. The fractional breast volume coverage, defined as the percentage volume in the transducer field of view that is imaged with clinically acceptable quality, is improved from 59% in both superior and inferior single-sided imaging to 89% in dual-sided imaging. Applying acoustic coupling to the breast requires more effort or sophisticated methods in dual-sided imaging than in single-sided imaging.