Diagnostic performance of 3D automated breast ultrasound (3D-ABUS) in a clinical screening setting-a retrospective study.

OBJECTIVES: To assess the diagnostic performance of 3D automated breast ultrasound (3D-ABUS) in breast cancer screening in a clinical setting. MATERIALS AND METHODS: All patients who had 3D-ABUS between January 2014 and January 2022 for screening were included in this retrospective study. The images were reported by 1 of 6 breast radiologists based on the Breast Imaging Reporting and Data Systems (BI-RADS). The 3D-ABUS was reviewed together with the digital breast tomosynthesis (DBT). Recall rate, biopsy rate, positive predictive value (PPV) and cancer detection yield were calculated. RESULTS: In total, 3616 studies were performed in 1555 women (breast density C/D 95.5% (n = 3455/3616), breast density A/B 4.0% (n = 144/3616), density unknown (0.5% (n = 17/3616)). A total of 259 lesions were detected on 3D-ABUS (87.6% (n = 227/259) masses and 12.4% (n = 32/259) architectural distortions). The recall rate was 5.2% (n = 188/3616) (CI 4.5-6.0%) with only 36.7% (n = 69/188) cases recalled to another date. Moreover, recall declined over time. There were 3.4% (n = 123/3616) biopsies performed, with 52.8% (n = 65/123) biopsies due to an abnormality detected in 3D-ABUS alone. Ten of 65 lesions were malignant, resulting in a positive predictive value (PPV) of 15.4% (n = 10/65) (CI 7.6-26.5%)). The cancer detection yield of 3D-ABUS is 2.77 per 1000 screening tests (CI 1.30-5.1). CONCLUSION: The cancer detection yield of 3D-ABUS in a real clinical screening setting is comparable to the results reported in previous prospective studies, with lower recall and biopsy rates. 3D-ABUS also may be an alternative for screening when mammography is not possible or declined. CLINICAL RELEVANCE STATEMENT: 3D automated breast ultrasound screening performance in a clinical setting is comparable to previous prospective studies, with better recall and biopsy rates. KEY POINTS: • 3D automated breast ultrasound is a reliable and reproducible tool that provides a three-dimensional representation of the breast and allows image visualisation in axial, coronal and sagittal. • The diagnostic performance of 3D automated breast ultrasound in a real clinical setting is comparable to its performance in previously published prospective studies, with improved recall and biopsy rates. • 3D automated breast ultrasound is a useful adjunct to mammography in dense breasts and may be an alternative for screening when mammography is not possible or declined.

One-view digital breast tomosynthesis as a stand-alone modality for breast cancer detection: do we need more?

PURPOSE: To compare the performance of one-view digital breast tomosynthesis (1v-DBT) to that of three other protocols combining DBT and mammography (DM) for breast cancer detection. MATERIALS AND METHODS: Six radiologists, three experienced with 1v-DBT in screening, retrospectively reviewed 181 cases (76 malignant, 50 benign, 55 normal) in two sessions. First, they scored sequentially: 1v-DBT (medio-lateral oblique, MLO), 1v-DBT (MLO) + 1v-DM (cranio-caudal, CC) and two-view DM + DBT (2v-DM+2v-DBT). The second session involved only 2v-DM. Lesions were scored using BI-RADS® and level of suspiciousness (1-10). Sensitivity, specificity, receiver operating characteristic (ROC) and jack-knife alternative free-response ROC (JAFROC) were computed. RESULTS: On average, 1v-DBT was non-inferior to any of the other protocols in terms of JAFROC figure-of-merit, area under ROC curve, sensitivity or specificity (p>0.391). While readers inexperienced with 1v-DBT screening improved their sensitivity when adding more images (69-79 %, p=0.019), experienced readers showed similar sensitivity (76 %) and specificity (70 %) between 1v-DBT and 2v-DM+2v-DBT (p=0.482). Subanalysis by lesion type and breast density showed no difference among modalities. CONCLUSION: Detection performance with 1v-DBT is not statistically inferior to 2v-DM or to 2v-DM+2v-DBT; its use as a stand-alone modality might be sufficient for readers experienced with this protocol. KEY POINTS: • One-view breast tomosynthesis is not inferior to two-view digital mammography. • One-view DBT is not inferior to 2-view DM plus 2-view DBT. • Training may lead to 1v-DBT being sufficient for screening.

Sonographic Phenotypes of Molecular Subtypes of Invasive Ductal Cancer in Automated 3-D Breast Ultrasound.

Our aim was to investigate whether Breast Imaging Reporting and Data System-Ultrasound (BI-RADS-US) lexicon descriptors can be used as imaging biomarkers to differentiate molecular subtypes (MS) of invasive ductal carcinoma (IDC) in automated breast ultrasound (ABUS). We included 125 IDCs diagnosed between 2010 and 2014 and imaged with ABUS at two institutes retrospectively. IDCs were classified as luminal A or B, HER2 enriched or triple negative based on reports of histopathologic analysis of surgical specimens. Two breast radiologists characterized all IDCs using the BI-RADS-US lexicon and specific ABUS features. Univariate and multivariate analyses were performed. A multinomial logistic regression model was built to predict the MSs from the imaging characteristics. BI-RADS-US descriptor margins and the retraction phenomenon are significantly associated with MSs (both p < 0.001) in both univariate and multivariate analysis. Posterior acoustic features and spiculation pattern severity were only significantly associated in univariate analysis (p < 0.001). Luminal A IDCs tend to have more prominent retraction patterns than luminal B IDCs. HER2-enriched and triple-negative IDCs present significantly less retraction than the luminal subtypes. The mean accuracy of MS prediction was 0.406. Overall, several BI-RADS-US descriptors and the coronal retraction phenomenon and spiculation pattern are associated with MSs, but prediction of MSs on ABUS is limited.

Consistency of breast density categories in serial screening mammograms: A comparison between automated and human assessment.

Reliable breast density measurement is needed to personalize screening by using density as a risk factor and offering supplemental screening to women with dense breasts. We investigated the categorization of pairs of subsequent screening mammograms into density classes by human readers and by an automated system. With software (VDG) and by four readers, including three specialized breast radiologists, 1000 mammograms belonging to 500 pairs of subsequent screening exams were categorized into either two or four density classes. We calculated percent agreement and the percentage of women that changed from dense to non-dense and vice versa. Inter-exam agreement (IEA) was calculated with kappa statistics. Results were computed for each reader individually and for the case that each mammogram was classified by one of the four readers by random assignment (group reading). Higher percent agreement was found with VDG (90.4%, CI 87.9-92.9%) than with readers (86.2-89.2%), while less plausible changes from non-dense to dense occur less often with VDG (2.8%, CI 1.4-4.2%) than with group reading (4.2%, CI 2.4-6.0%). We found an IEA of 0.68-0.77 for the readers using two classes and an IEA of 0.76-0.82 using four classes. IEA is significantly higher with VDG compared to group reading. The categorization of serial mammograms in density classes is more consistent with automated software than with a mixed group of human readers. When using breast density to personalize screening protocols, assessment with software may be preferred over assessment by radiologists.

Breast cancer screening halves the risk of breast cancer death: a case-referent study.

Large-scale epidemiologic studies have consistently demonstrated the effectiveness of mammographic screening programs, however the benefits are still subject to debate. We estimated the effect of the Dutch screening program on breast cancer mortality. In a large multi-region case-referent study, we identified all breast cancer deaths in 2004 and 2005 in women aged 50-75 who had been invited for screening (cases). Cases were individually matched to referents from the population invited to screening. Conditional logistic regression was used to estimate the odds ratio (OR) of breast cancer death according to individual screening history. The OR was adjusted for self-selection bias using regional correction factors for the difference in baseline risk for breast cancer death between screened and unscreened women. A total of 1233 cases and 2090 referents were included in this study. We found a 58% reduction in breast cancer mortality in screened versus unscreened women (adjusted OR = 0.42, 95% CI 0.33-0.53). Screening, i.e. early detection and treatment, has resulted in a substantial reduction in breast cancer mortality, indicating that the Dutch breast cancer screening program is highly effective.

Generating Synthetic Mammograms From Reconstructed Tomosynthesis Volumes.

Digital breast tomosynthesis (DBT) is a promising 3-D modality that may replace mammography in the future. However, lesion search is likely to require more time in DBT volumes, while comparisons between views from different projections and prior exams might be harder to make. This may make screening with DBT cumbersome. A solution may be provided by synthesizing 2-D mammograms from DBT, which may then be used to guide the search for abnormalities. In this work we focus on synthesizing mammograms in which masses and architectural distortions are optimally visualized. Our approach first determines relevant points in a DBT volume with a computer-aided detection system and then renders a mammogram from the intersection of a surface fitted through these points and the DBT volume. The method was evaluated in a pilot observer study where three readers reported mass findings in 87 patients (25 malignant, 62 normal) for which both DBT and digital mammograms were available. We found that on average, diagnostic accuracy in the synthetic mammograms was higher (Az=0.85) than in conventional mammograms (Az=0.81), although the difference was not statistically significant. Preliminary results suggest that the synthesized mammograms are an acceptable alternative for real mammograms regarding the detection of mass lesions.

Standalone computer-aided detection compared to radiologists' performance for the detection of mammographic masses.

OBJECTIVES: We developed a computer-aided detection (CAD) system aimed at decision support for detection of malignant masses and architectural distortions in mammograms. The effect of this system on radiologists' performance depends strongly on its standalone performance. The purpose of this study was to compare the standalone performance of this CAD system to that of radiologists. METHODS: In a retrospective study, nine certified screening radiologists and three residents read 200 digital screening mammograms without the use of CAD. Performances of the individual readers and of CAD were computed as the true-positive fraction (TPF) at a false-positive fraction of 0.05 and 0.2. Differences were analysed using an independent one-sample t-test. RESULTS: At a false-positive fraction of 0.05, the performance of CAD (TPF = 0.487) was similar to that of the certified screening radiologists (TPF = 0.518, P = 0.17). At a false-positive fraction of 0.2, CAD performance (TPF = 0.620) was significantly lower than the radiologist performance (TPF = 0.736, P <0.001). Compared to the residents, CAD performance was similar for all false-positive fractions. CONCLUSIONS: The sensitivity of CAD at a high specificity was comparable to that of human readers. These results show potential for CAD to be used as an independent reader in breast cancer screening.

One-day core needle biopsy in a breast clinic: 4 years experience.

Many attempts have been made to combine the high diagnostic accuracy and conclusive rate of core needle biopsy (CNB) with the speed of fine needle aspiration cytology in evaluation of solid breast lesions. Multiple hybrid techniques have been developed to achieve this. We describe a cohort of patients for whom we used a relatively new, accelerated method of CNB processing, allowing for a definitive diagnosis the same day. All patients visiting the Radboud University Nijmegen Medical Centre breast clinic during a 4-year period were reviewed to identify all CNBs in this period performed in a same-day diagnosis track. CNB result was compared to post-operative pathology reports when available, and to follow-up when patients were not surgically treated. 1,060 patients underwent CNB of 1,383 lesions, 898 of which in a same-day diagnosis track with a sensitivity of 96.9 % and a specificity of 99.4 %. The inconclusive rate was 9.2 %. For a same-day diagnosis for solid breast lesions, we could give a conclusive diagnosis with accelerated CNB processing in 65 % of our patients requiring CNB. This technique can be used reliably in a same-day diagnosis breast clinic with a very high sensitivity, specificity, and conclusive rate.

Increase in perceived case suspiciousness due to local contrast optimisation in digital screening mammography.

OBJECTIVES: To determine the influence of local contrast optimisation on diagnostic accuracy and perceived suspiciousness of digital screening mammograms. METHODS: Data were collected from a screening region in the Netherlands and consisted of 263 digital screening cases (153 recalled,110 normal). Each case was available twice, once processed with a tissue equalisation (TE) algorithm and once with local contrast optimisation (PV). All cases had digitised previous mammograms. For both algorithms, the probability of malignancy of each finding was scored independently by six screening radiologists. Perceived case suspiciousness was defined as the highest probability of malignancy of all findings of a radiologist within a case. Differences in diagnostic accuracy of the processing algorithms were analysed by comparing the areas under the receiver operating characteristic curves (A(z)). Differences in perceived case suspiciousness were analysed using sign tests. RESULTS: There was no significant difference in A(z) (TE: 0.909, PV 0.917, P = 0.46). For all radiologists, perceived case suspiciousness using PV was higher than using TE more often than vice versa (ratio: 1.14-2.12). This was significant (P <0.0083) for four radiologists. CONCLUSIONS: Optimisation of local contrast by image processing may increase perceived case suspiciousness, while diagnostic accuracy may remain similar. KEY POINTS: Variations among different image processing algorithms for digital screening mammography are large. Current algorithms still aim for optimal local contrast with a low dynamic range. Although optimisation of contrast may increase sensitivity, diagnostic accuracy is probably unchanged. Increased local contrast may render both normal and abnormal structures more conspicuous.