Screening chest wall ultrasound in the mastectomy patient.

BACKGROUND: While there are clear guidelines regarding chest wall ultrasound in the symptomatic patient, there is conflicting evidence regarding the use of ultrasound in the screening of women post-mastectomy. OBJECTIVE: To assess the utility of screening chest wall ultrasound after mastectomy and to assess features of detected malignancies. METHODS: This IRB approved, retrospective study evaluates screening US examinations of the chest wall after mastectomy. Asymptomatic women presenting for screening chest wall ultrasound from January 2016 through May 2017 were included. Cases of known active malignancy were excluded. All patients had at least one year of clinical or imaging follow-up. 43 exams (8.5 %) were performed with a history of contralateral malignancy, 465 exams (91.3 %) were performed with a history of ipsilateral malignancy, and one exam (0.2 %) was performed in a patient with bilateral prophylactic mastectomy. RESULTS: During the 17-month period, there were 509 screening US in 389 mastectomy patients. 504 (99.0 %) exams were negative/benign. Five exams (1.0 %) were considered suspicious, with recommendation for biopsy, which was performed. Out of 509 exams, 3 (0.6 %) yielded benign results, while 2 (0.39 %) revealed recurrent malignancy, with a 95 % confidence interval (exact binomial) of 0.05 % to 1.41 % for screening ultrasound. Both patients who recurred had previously recurred, and both had initial cancer of lobular histology. CONCLUSION: Of 509 chest wall screening US exams performed in mastectomy, 2 malignancies were detected, and each patient had history of invasive lobular carcinoma and at least one prior recurrence prior to this study, suggesting benefit of screening ultrasound in these populations.

Improving the transgender patient experience in the breast imaging center.

PURPOSE: This review discusses how breast centers can optimize patient experience scores among transgender patients. FINDINGS: High patient experience scores impact patient care and compliance. Increased regulations have been enacted to ensure that health systems are effectively meeting the health concerns of sexual minorities. This will be reflected in the patient experience surveys. A leading patient survey will be assessed to help breast imaging centers optimize the transgender patient experience and question types will be provided. SUMMARY: Breast Centers can be equipped to enhance the transgender patient experience.

Suspicious Ultrasound-Occult Non-Calcified Mammographic Masses, Asymmetries, and Architectural Distortions Are Moderate Probability for Malignancy.

Suspicious non-calcified mammographic findings have not been evaluated with modern mammographic technique, and the purpose of this work is to compare the likelihood of malignancy for those findings. To do this, 5018 consecutive mammographically guided biopsies performed during 2016-2019 at a large metropolitan, community-based hospital system were retrospectively reviewed. In total, 4396 were excluded for targeting calcifications, insufficient follow-up, or missing data. Thirty-seven of 126 masses (29.4%) were malignant, 44 of 194 asymmetries (22.7%) were malignant, and 77 of 302 architectural distortions (AD, 25.5%) were malignant. The combined likelihood of malignancy was 25.4%. Older age was associated with a higher likelihood of malignancy for each imaging finding type (all p ≤ 0.006), and a possible ultrasound correlation was associated with a higher likelihood of malignancy when all findings were considered together (p = 0.012). Two-view asymmetries were more frequently malignant than one-view asymmetries (p = 0.03). There were two false-negative biopsies (98.7% sensitivity and 100% specificity). In conclusion, the 25.4% likelihood of malignancy confirms the recommendation for biopsy of suspicious, ultrasound-occult, mammographic findings. Mammographically guided biopsies were highly sensitive and specific in this study. Older patient age and a possible ultrasound correlation should raise concern given the increased likelihood of malignancy in those scenarios.

Breast Imaging Patient Demographics at a Major Comprehensive Cancer Center Before and During the COVID-19 Pandemic.

OBJECTIVE: The coronavirus disease of 2019 (COVID-19) pandemic disproportionately affected certain vulnerable communities. The purpose of our study was to determine how COVID-19 affected the socioeconomic demographics of breast imaging patients at a major comprehensive cancer center. METHODS: This retrospective cohort study compared female patients who underwent screening mammograms, diagnostic mammograms, breast ultrasound, or breast MRI during the following time periods: prepandemic (February 1, 2018, through February 29, 2020), acute pandemic (March 1, 2020, through June 30, 2020), subacute pandemic (August 1, 2020, through December 31, 2020), and chronic pandemic (January 1, 2021, through June 30, 2022). Statistics were performed using the generalized estimating equations approach. RESULTS: A total of 74,398 female patients (mean age, 55.6 ± 12.4 years) underwent 238,776 total breast imaging examinations. For screening mammograms, Hispanics represented 27.1% (9,197 of 33,960) of patients in the prepandemic time period compared with 16.7% (604 of 3,621) in the acute pandemic time period, 18.7% (1,835 of 9,830) in the subacute pandemic time period, and 24.3% (7,492 of 30,869) in the chronic pandemic time period (all P < .0001). Self-pay patients saw similar declines for screening mammograms during the same time periods: 21.7% (7,375 of 33,960), 7.9% (286 of 3,621), 9.5% (933 of 9,830), and 17.4% (5,357 of 30,869), respectively (all P < .0001, compared with the prepandemic time period). Similarly dramatic trends were not observed for race or other imaging examinations. DISCUSSION: At our cancer center, Hispanics and self-pay patients were disproportionately affected by the COVID-19 pandemic. Strategies to improve health inequities are needed.

Longitudinal dynamic contrast-enhanced MRI radiomic models for early prediction of response to neoadjuvant systemic therapy in triple-negative breast cancer.

Early prediction of neoadjuvant systemic therapy (NAST) response for triple-negative breast cancer (TNBC) patients could help oncologists select individualized treatment and avoid toxic effects associated with ineffective therapy in patients unlikely to achieve pathologic complete response (pCR). The objective of this study is to evaluate the performance of radiomic features of the peritumoral and tumoral regions from dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) acquired at different time points of NAST for early treatment response prediction in TNBC. This study included 163 Stage I-III patients with TNBC undergoing NAST as part of a prospective clinical trial (NCT02276443). Peritumoral and tumoral regions of interest were segmented on DCE images at baseline (BL) and after two (C2) and four (C4) cycles of NAST. Ten first-order (FO) radiomic features and 300 gray-level-co-occurrence matrix (GLCM) features were calculated. Area under the receiver operating characteristic curve (AUC) and Wilcoxon rank sum test were used to determine the most predictive features. Multivariate logistic regression models were used for performance assessment. Pearson correlation was used to assess intrareader and interreader variability. Seventy-eight patients (48%) had pCR (52 training, 26 testing), and 85 (52%) had non-pCR (57 training, 28 testing). Forty-six radiomic features had AUC at least 0.70, and 13 multivariate models had AUC at least 0.75 for training and testing sets. The Pearson correlation showed significant correlation between readers. In conclusion, Radiomic features from DCE-MRI are useful for differentiating pCR and non-pCR. Similarly, predictive radiomic models based on these features can improve early noninvasive treatment response prediction in TNBC patients undergoing NAST.

Deep Learning for Fully Automatic Tumor Segmentation on Serially Acquired Dynamic Contrast-Enhanced MRI Images of Triple-Negative Breast Cancer.

Accurate tumor segmentation is required for quantitative image analyses, which are increasingly used for evaluation of tumors. We developed a fully automated and high-performance segmentation model of triple-negative breast cancer using a self-configurable deep learning framework and a large set of dynamic contrast-enhanced MRI images acquired serially over the patients' treatment course. Among all models, the top-performing one that was trained with the images across different time points of a treatment course yielded a Dice similarity coefficient of 93% and a sensitivity of 96% on baseline images. The top-performing model also produced accurate tumor size measurements, which is valuable for practical clinical applications.

Diagnostic ultrasound of the chest wall in the symptomatic patient after mastectomy.

BACKGROUND: Lack of standardized imaging recommendations among mastectomy patients has led to variability in how recurrences are detected. OBJECTIVE: To describe the findings and assess the diagnostic efficacy of ultrasound in the evaluation of symptomatic post-mastectomy patients. MATERIALS AND METHODS: This single institution, retrospective study included 749 consecutive diagnostic chest wall ultrasound examinations performed in mastectomy patients, from January 2016 to June 2017. Chest wall ultrasound evaluated the mastectomy bed with or without reconstruction. Electronic health records were queried for the primary breast cancer histology prior to mastectomy, clinical symptoms prompting the diagnostic ultrasound, ultrasound findings, subsequent cytology and pathology, and follow-up data. Excluded were patients with a known recurrence, asymptomatic patients, and those with <2 years of clinical or imaging follow-up. Descriptive and comparative statistical analyses were performed. RESULTS: Among the 749 ultrasounds performed, 58 malignancies were identified for a 7.7% (58/749) malignancy rate, with a median tumor size of 20 mm. Patients diagnosed with a malignancy most often presented with a palpable abnormality (79.3%, 46/58) or skin changes (13.8%, 8/58) and rarely with pain (1.7%, 1/58). Patients who underwent a biopsy yielding a benign result most often presented with a palpable abnormality (41.5%, 287/691), pain (25.6%,177/691), or postoperative swelling/suspected fluid collection (17.8%, 123/691). Diagnostic ultrasound yielded a 91.4% sensitivity (95% CI 81.0, 97.1), 96.1% specificity (95% CI 94.4, 97.4), 66.3% PPV3 (95% CI 57.4, 74.1), and 99.3% negative predictive value (95% CI 98.3, 99.7) for cancer detection. There were 5 false negative ultrasound cases after a skin punch biopsy was performed due to clinically suspicious skin changes. CONCLUSIONS: Chest wall ultrasound has a high sensitivity and negative predictive value for detection of breast cancer recurrence in symptomatic patients after mastectomy. Skin changes remain an important clinical manifestation of a cancer recurrence.

International Interobserver Variability of Breast Density Assessment.

PURPOSE: The aim of this study was to determine variability in visually assessed mammographic breast density categorization among radiologists practicing in Indonesia, the Netherlands, South Africa, and the United States. METHODS: Two hundred consecutive 2-D full-field digital screening mammograms obtained from September to December 2017 were selected and retrospectively reviewed from four global locations, for a total of 800 mammograms. Three breast radiologists in each location (team) provided consensus density assessments of all 800 mammograms using BI-RADS® density categorization. Interreader agreement was compared using Gwet's AC2 with quadratic weighting across all four density categories and Gwet's AC1 for binary comparison of combined not dense versus dense categories. Variability of distribution among teams was calculated using the Stuart-Maxwell test of marginal homogeneity across all four categories and using the McNemar test for not dense versus dense categories. To compare readers from a particular country on their own 200 mammograms versus the other three teams, density distribution was calculated using conditional logistic regression. RESULTS: For all 800 mammograms, interreader weighted agreement for distribution among four density categories was 0.86 (Gwet's AC2 with quadratic weighting; 95% confidence interval, 0.85-0.88), and for not dense versus dense categories, it was 0.66 (Gwet's AC1; 95% confidence interval, 0.63-0.70). Density distribution across four density categories was significantly different when teams were compared with one another and one team versus the other three teams combined (P < .001). Overall, all readers placed the largest number of mammograms in the scattered and heterogeneous categories. CONCLUSIONS: Although reader teams from four different global locations had almost perfect interreader agreement in BI-RADS density categorization, variability in density distribution across four categories remained statistically significant.

Comparison of prone and upright, stereotactic, and tomosynthesis-guided biopsies with secondary analysis of ultrasound-occult architectural distortions.

OBJECTIVES: Compare prone and upright, stereotactic, and tomosynthesis-guided vacuum-assisted breast biopsies (prone DM-VABB, prone DBT-VABB, upright DM-VABB, and upright DBT-VABB) in a community-practice setting and review outcomes of ultrasound-occult architectural distortions (AD). METHODS: Consecutive biopsies performed at two community-based breast centers from 2016 to 2019 were retrospectively reviewed. Technical details of each procedure and patient outcomes were recorded. Separate analyses were performed for ultrasound-occult ADs. Two sample t-tests and Fisher's exact test facilitated comparisons. RESULTS: A total of 1133 patients underwent 369 prone DM-VABB, 324 prone DBT-VABB, 437 upright DM-VABB, and 123 upright DBT-VABB with 99.2%, 100%, 99.3%, and 99.2% success, respectively (p-values > 0.25). Mean lesion targeting times were greater for prone biopsy (minutes: 6.94 prone DM-VABB, 8.54 prone DBT-VABB, 5.52 upright DM-VABB, and 5.51 upright DBT-VABB; p-values < 0.001), yielding longer total prone procedure times for prone biopsy (p < 0.001). Compared to DM-VABB, DBT-VABB used fewer exposures (p < 0.001) and more commonly targeted AD, asymmetries, or masses (p < 0.001). Malignancy rates were similar between procedures: prone DM-VABB 22.4%, prone DBT-VABB 21.9%, upright DM-VABB 22.8%, and upright DBT-VABB 17.2% (p-values > 0.19). One hundred forty of the 1133 patients underwent 145 biopsies for ultrasound-occult AD (143 DBT-VABB and 2 DM-VABB). Biopsy yielded 27 malignancies and 47 high-risk lesions (74 of 145, 51%). Malignancy rate was 20.7% after surgical upgrade of one benign-discordant and two high-risk lesions. CONCLUSIONS: All biopsy procedure types were extremely successful. The 20.7% malignancy rate for ultrasound-occult AD confirms a management recommendation for tissue diagnosis. Upright biopsy was faster than prone biopsy, and DBT-VABB used fewer exposures than DM-VABB. CLINICAL RELEVANCE: Our results highlight important differences between prone DM-VABB, prone DBT-VABB, upright DM-VABB, and upright DBT-VABB. Moreover, the high likelihood of malignancy for ultrasound-occult AD will provide confidence in recommending tissue diagnosis in lieu of observation or clinical follow-up. KEY POINTS: • Upright and prone stereotactic and tomosynthesis-guided breast biopsies were safe and effective in the community-practice setting. • The malignancy rate for ultrasound-occult architectural distortion of 20.7% confirms the management recommendation for biopsy. • Upright procedures were faster than prone procedures, and tomosynthesis-guided biopsy used fewer exposures than stereotactic biopsy.

Assessment of Response to Neoadjuvant Systemic Treatment in Triple-Negative Breast Cancer Using Functional Tumor Volumes from Longitudinal Dynamic Contrast-Enhanced MRI.

Early assessment of neoadjuvant systemic therapy (NAST) response for triple-negative breast cancer (TNBC) is critical for patient care in order to avoid the unnecessary toxicity of an ineffective treatment. We assessed functional tumor volumes (FTVs) from dynamic contrast-enhanced (DCE) MRI after 2 cycles (C2) and 4 cycles (C4) of NAST as predictors of response in TNBC. A group of 100 patients with stage I-III TNBC who underwent DCE MRI at baseline, C2, and C4 were included in this study. Tumors were segmented on DCE images of 1 min and 2.5 min post-injection. FTVs were measured using the optimized percentage enhancement (PE) and signal enhancement ratio (SER) thresholds. The Mann-Whitney test was used to compare the performance of the FTVs at C2 and C4. Of the 100 patients, 49 (49%) had a pathologic complete response (pCR) and 51 (51%) had a non-pCR. The maximum area under the receiving operating characteristic curve (AUC) for predicting the treatment response was 0.84 (p < 0.001) for FTV at C4 followed by FTV at C2 (AUC = 0.82, p < 0.001). The FTV measured at baseline was not able to discriminate pCR from non-pCR. FTVs measured on DCE MRI at C2, as well as at C4, of NAST can potentially predict pCR and non-pCR in TNBC patients.

Nipple Discharge Imaging Evaluation with Mammography, Ultrasound, Galactography, and MRI.

RATIONALE AND OBJECTIVE: To determine the diagnostic yield of various imaging tests used to evaluate nipple discharge. MATERIALS AND METHODS: A single institution, IRB-approved, retrospective study was performed of 320 consecutive patients presenting with nipple discharge. Imaging and pathology were reviewed to determine the yield for malignancy, atypical high-risk lesions (HRLs), and intraductal papillomas (IDPs). RESULTS: Of the 320 patients, pathology or follow up confirmed 40 breast malignancies (40/320, 12.5%),14 atypical HRLs (14/320, 4.4%), 71 IDPs (71/320, 22.2%), 48 other benign pathologies (48/320,15.0%), and 147 unknown but benign cases (147/320, 45.9%). Physiologic discharge characteristics were observed in a minority of malignant cases: nonspontaneous (4/40, 10.0%); neither bloody nor clear (4/40, 10.0%); bilateral (3/40, 7.5%). Malignancy was associated with older age (p < 0.001) and bloody discharge (odds ratio 6.5, p < 0.0001). The combination of digital mammography and ultrasound had a 93% sensitivity and a 98% NPV, while contrast enhanced MRI (CE-MRI) had a 100% sensitivity and a 100% NPV for malignancy. Only three galactography examinations were performed among the malignant cohort, with minimal contribution (1 of 3) to the diagnostic evaluation. In this case, galactography findings helped determine imaging-pathology discordance, prompting a recommendation for surgical excision and subsequently a malignant diagnosis. CONCLUSION: The combination of mammography and ultrasonography detected 93% of breast malignancies associated with nipple discharge and had a 98% NPV for malignancy. The value of CE-MRI is its ability to detect the remaining malignancies, not detected on mammography or ultrasound, and its ability to obviate the need for surgical duct excision.

Deep Learning Models for Automated Assessment of Breast Density Using Multiple Mammographic Image Types.

Recently, convolutional neural network (CNN) models have been proposed to automate the assessment of breast density, breast cancer detection or risk stratification using single image modality. However, analysis of breast density using multiple mammographic types using clinical data has not been reported in the literature. In this study, we investigate pre-trained EfficientNetB0 deep learning (DL) models for automated assessment of breast density using multiple mammographic types with and without clinical information to improve reliability and versatility of reporting. 120,000 for-processing and for-presentation full-field digital mammograms (FFDM), digital breast tomosynthesis (DBT), and synthesized 2D images from 5032 women were retrospectively analyzed. Each participant underwent up to 3 screening examinations and completed a questionnaire at each screening encounter. Pre-trained EfficientNetB0 DL models with or without clinical history were optimized. The DL models were evaluated using BI-RADS (fatty, scattered fibroglandular densities, heterogeneously dense, or extremely dense) versus binary (non-dense or dense) density classification. Pre-trained EfficientNetB0 model performances were compared using inter-observer and commercial software (Volpara) variabilities. Results show that the average Fleiss' Kappa score between-observers ranged from 0.31-0.50 and 0.55-0.69 for the BI-RADS and binary classifications, respectively, showing higher uncertainty among experts. Volpara-observer agreement was 0.33 and 0.54 for BI-RADS and binary classifications, respectively, showing fair to moderate agreement. However, our proposed pre-trained EfficientNetB0 DL models-observer agreement was 0.61-0.66 and 0.70-0.75 for BI-RADS and binary classifications, respectively, showing moderate to substantial agreement. Overall results show that the best breast density estimation was achieved using for-presentation FFDM and DBT images without added clinical information. Pre-trained EfficientNetB0 model can automatically assess breast density from any images modality type, with the best results obtained from for-presentation FFDM and DBT, which are the most common image archived in clinical practice.

Mid-treatment Ultrasound Descriptors as Qualitative Imaging Biomarkers of Pathologic Complete Response in Patients with Triple-Negative Breast Cancer.

This study aimed to investigate mid-treatment breast tumor ultrasound characteristics that may predict eventual pathologic complete response (pCR) in triple-negative breast cancer; specifically, we examined associations between pCR and two parameters: tumor response pattern and tumor appearance. Ultrasound was performed at mid-treatment, defined as the completion of four cycles of anthracycline-based chemotherapy and before receiving taxane-based chemotherapy. Consensus imaging review was performed while blinded to pathology results (i.e., pCR/non-pCR) from surgery. Tumor response pattern was described as "complete," "concentric," "fragmented," "stable" or "progression." Tumor appearance was designated as "mass," "architectural distortion," "flat tumor bed" or "clip only." Univariate and multivariate regression analyses of 144 participants showed significant associations between mid-treatment response pattern and pCR (p = 0.0348 and p = 0.0173, respectively), with complete and concentric response patterns more likely to achieve pCR than other patterns. Univariate and multivariate regression analyses further showed significant associations between mid-treatment tumor appearance and pCR (p < 0.0001 for both), with persistent appearance of mass less likely than other appearances to achieve pCR. To conclude, our study demonstrated strong associations between pCR and both tumor response pattern and tumor appearance, thereby suggesting that these parameters have potential as qualitative imaging biomarkers of pCR in triple-negative breast cancer.

Axillary Nodal Metastases in Invasive Lobular Carcinoma Versus Invasive Ductal Carcinoma: Comparison of Node Detection and Morphology by Ultrasound.

BACKGROUND. Invasive lobular carcinoma is more subtle on imaging compared with invasive ductal carcinoma; nodal metastases may also differ on imaging between these two. OBJECTIVE. The purpose of this study was to determine whether invasive lobular carcinoma and invasive ductal carcinoma differ in the detection rate by ultrasound (US) of metastatic axillary nodes and in the metastatic nodes' US characteristics. METHODS. This retrospective study included 695 women (median age, 53 years) who had breast cancer in a total of 723 breasts (76 lobular, 586 ductal, 61 mixed ductal and lobular histology) with biopsy-proven axillary nodal metastases and who underwent pretreatment US. A single breast radiologist reviewed US images in patients with suspicious nodes on US and classified number of nodes, size, and morphology. Morphologic assessment used a previously described classification according to the relationship between node cortex and hilum. Nodal findings were compared between lobular and ductal carcinoma. A second radiologist independently classified node morphology in 241 cancers to assess interreader agreement. RESULTS. A total of 99 metastatic axillary nodes (15 lobular, 66 ductal, 18 mixed histology) were not visualized on US and were diagnosed by surgical biopsy. The remaining 624 metastatic nodes (61 lobular, 520 ductal, 43 mixed ductal and lobular histology) were visualized on US and diagnosed by US-guided fine-needle aspiration. US detected the metastatic nodes in 80.3% for lobular carcinoma versus 88.7% for ductal carcinoma (p = .04). Among metastatic nodes detected by US, retrospective review identified three or more abnormal nodes in 50.8% of lobular carcinoma versus 69.2% of ductal carcinoma (p = .003); node size was 2.0 cm or smaller in 65.6% for lobular carcinoma versus 47.3% for ductal carcinoma (p = .03); morphology was type III or IV (diffuse cortical thickening without hilar mass effect) rather than type V or VI (marked cortical thickening with hilar mass effect) in 68.9% for lobular carcinoma versus 28.8% for ductal carcinoma (p < .001). Interreader agreement assessment for morphology exhibited a kappa coefficient of 0.63 (95% CI, 0.54-0.73). CONCLUSION. US detects a lower percentage of nodal metastases in lobular than in ductal carcinoma. Nodal metastases in lobular carcinoma more commonly show diffuse cortical thickening and with less hilar mass effect. CLINICAL IMPACT. A lower threshold may be warranted to recommend biopsy of suspicious axillary nodes detected on US in patients with lobular carcinoma.

Prospective Comparison of Synthesized Mammography with DBT and Full-Field Digital Mammography with DBT Uncovers Recall Disagreements That may Impact Cancer Detection.

RATIONALE AND OBJECTIVES: Synthesized mammography with digital breast tomosynthesis (SM+DBT) and full-field digital mammography with DBT were prospectively evaluated for recall rate (RR), cancer detection rate (CDR), positive predictive value 1 (PPV1), lesion recall differences, and disagreements in recall for additional imaging. MATERIALS AND METHODS: From December 15, 2015 to January 15, 2017, after informed consent was obtained for this Health Insurance Portability and Accountability Act compliant study, each enrolled patient's SM+DBT and FFDM+DBT were interpreted sequentially by one of eight radiologists. RR, CDR, PPV1, and imaging findings (asymmetry, focal asymmetry, mass, architectural distortion, and calcifications) recalled were reviewed. RESULTS: For SM+DBT and FFDM+DBT in 1022 patients, RR was 7.3% and 7.9% (SM+DBT vs. FFDM+DBT: diff= -0.6%; 90% CI= -1.4%, 0.1%); CDR was 6.8 and 7.8 per 1000 (SM+DBT vs. FFDM+DBT: diff= -1.0, 95% CI= -5.5, 2.8, p = 0.317); PPV1 was 9.3% and 9.9% (relative positive predictive value for SM+DBT vs. FFDM+DBT: 0.95, 95% CI: 0.73-1.22, p = 0.669). FFDM+DBT detected eight cancers; SM+DBT detected seven (missed 1 cancer with calcifications). SM+DBT and FFDM+DBT disagreed on patient recall for additional imaging in 19 patients, with majority (68%, 13/19 patients) in the recall of patients for calcifications. For calcifications, SM+DBT recalled six patients that FFDM+DBT did not recall, and FFDM+DBT recalled seven patients that SM+DBT did not recall, even though the total number of calcifications finding recalled was similar overall for both SM+DBT and FFDM+DBT. CONCLUSION: Disagreement in recall of patients for calcifications may impact cancer detection by SM+DBT, warranting further investigation.

Responsive Web-based Breast Imaging Core Curriculum for International Radiology Residents with Self-Assessment: A Pilot Study.

RATIONALE AND OBJECTIVES: Lack of uniformity in radiology resident education is partially attributable to variable access to subspecialty education. Web-based courses improve standardization, but with growing emphasis on competency based education, more evaluation of their effectiveness is needed. We created a responsive web-based breast imaging curriculum for radiology residents including self-assessment and a satisfaction survey. MATERIALS AND METHODS: Two global academic institutions collaboratively developed a breast imaging curriculum to address radiology residents' educational needs. This virtual course comprised 11 video lectures, nine didactic (with attached pre-test and post-test assessments) and two case review sessions. In April 2020, this optional curriculum was made available to all 56 radiology residents in one residency program cluster in Singapore, to be accessed alongside the breast imaging rotation as a supplement. A voluntary anonymous satisfaction survey was provided upon completion. RESULTS: A total of 39 of the 56 radiology residents (70%) completed the course. For the average score of nine lectures (maximum score 5), there was a significant increase in mean pre and post - test scores (mean = 2.2, SD = 0.7), p < 0.001. The proportion of residents with improvement between the pre-test score and the post-test score ranged from 74% to 100% (mean, 84%). Thirty three of the 39 participants (85%) completed the satisfaction survey, and all agreed or strongly agreed that the curriculum increased their knowledge of breast imaging. CONCLUSION: This web based breast imaging curriculum supplement was viewed positively by participating residents and improved their self-assessed knowledge. Curriculum access could be expanded to improve global radiology education.