Faculty Bibliography

OBJECTIVE. Most peer review programs focus on error detection, numeric scoring, and radiologist-specific error rates. The effectiveness of this method on learning and systematic improvement is uncertain at best. Radiologists have been pushing for a transition from an individually punitive peer review system to a peer-learning model. This national questionnaire of U.S. radiologists aims to assess the current status of peer review and opportunities for improvement. MATERIALS AND METHODS. A 21-question multiple-choice questionnaire was developed and face validity assessed by the ARRS Performance Quality Improvement subcommittee. The questionnaire was e-mailed to 17,695 ARRS members and open for 4 weeks; two e-mail reminders were sent. Response collection was anonymous. Only responses from board-certified, practicing radiologists participating in peer review were analyzed. RESULTS. The response rate was 4.2% (742/17,695), and 73.7% (547/742) met inclusion criteria. Most responders were in private practice (51.7%, 283/547) with a group size of 11-50 radiologists (50.5%) and in an urban setting (61.6%). Significant diversity was noted in peer review systems, with RADPEER used by less than half (45.0%) and cases selected most commonly by commercial software (36.2%) or manually (31.2%). There was no consensus on the number of required peer reviews per month (10-20 cases, 32.1%; > 20 cases, 29.1%; < 10 cases, 21.7%). Less than half (43.7%) did not use peer review for group education. Whereas most (67.7%) were notified of their peer review results individually, 21.5% were not notified at all. Around half were dissatisfied (44.5%) because of insufficient learning (94.0%) and inaccurate representation of their performance improvement (75.5%). Overall, the group discrepancy rates were unknown to most radiologists who participate in peer review (54.3%). Submission bias was the main reason for underreporting of serious discrepancies (49.0%). Most found four peer-learning methods feasible in daily practice: incidental observation, 65.1%; focused practice review, 52.9%; professional auditing, 45.8%; and blinded double reading, 35.4%. CONCLUSION. More than half of participants reported that peer review data are used for educational purposes. However, significant diversity remains in current peer review practice with no agreement on number of required reviews, method of case selection, and oversight of results. Nearly half of the radiologists reported insufficient learning, although most feel a better system would be feasible in daily practice.

Architectural distortion on digital breast tomosynthesis (

OBJECTIVE. The purpose of this study is to describe screening updates for women with average and high risk for breast cancer, compare different screening strategies, and describe new approaches in risk prediction, including radiomics. CONCLUSION. All women are at substantial risk for breast cancer. For women with average risk, annual mammography beginning at 40 years old maximizes the life-extending benefits and provides improved treatment options. Women at higher risk need earlier and more intense screening. Delaying initiation or decreasing frequency of mammographic screening adversely affects breast cancer detection.

RATIONALE AND OBJECTIVES/OBJECTIVE:The Breast Imaging-Reporting and Data System (BI-RADS) atlas defines category 5 assessments as appropriate only for lesions that are almost certainly cancer, with a positive predictive value (PPV) of ≥95%. This study aims to demonstrate the feasibility of classifying lesions at diagnostic breast imaging with sufficiently high PPV to merit category 5 assessments, and to identify those lesion descriptors that yield such a high PPV. MATERIALS AND METHODS/METHODS:(biopsy performed) was calculated, and the BI-RADS descriptors for each lesion were analyzed. RESULTS:97.5% and 95% confidence interval: 96.2%-98.8%). The most common lesion types were mass (170) and calcifications (116). Of the 220 examinations involving both mammography and ultrasound, no category 5 lesions had <3 suspicious BI-RADS descriptors, only three lesions had three suspicious descriptors, but the remaining 217 lesions (98.6%) had ≥4 suspicious descriptors. CONCLUSION/CONCLUSIONS:In clinical practice, it is feasible to make BI-RADS category 5 assessments with the intended ≥95% PPV. To justify a category 5 assessment, at least four suspicious BI-RADS descriptors should be identified at the combination of diagnostic mammography and ultrasound examinations.

OBJECTIVE:The purpose of this article is to compare commonly used breast cancer risk assessment models, describe the machine learning approach and big data in risk prediction, and summarize the potential benefits and harms of restrictive risk-based screening. CONCLUSION/CONCLUSIONS:The commonly used risk assessment models for breast cancer can be complex and cumbersome to use. Each model incorporates different sets of risk factors, which are weighted differently and can produce different results for the same patient. No model is appropriate for all subgroups of the general population and only one model incorporates mammographic breast density. Future development of risk prediction tools that are generalizable and simpler to use are needed in guiding clinical decisions.

PURPOSE/OBJECTIVE:The National Mammography Database (NMD) contains nearly 20 million examinations from 693 facilities; it is the largest information source for use and effectiveness of breast imaging in the United States. NMD collects demographic, imaging, interpretation, biopsy, and basic pathology results, enabling facility and physician comparison for quality improvement. However, NMD lacks treatment and clinical outcomes data. The network of state cancer registries (CRs) contains detailed pathologic, treatment, and clinical outcomes data. This pilot study assessed electronic linkage of NMD and CR data at a multicenter institution as proof of concept. MATERIALS AND METHODS/METHODS:We obtained Quality Oversight Committee approval for this retrospective study. Data of patients diagnosed with breast cancer in 2014 and 2015 were retrieved from our NMD-approved radiology information system (RIS) and matched with reportable patients in our CR using social security number (SSN), first name (fname), last name (lname), and date of birth (DOB). Matching was repeated without SSN. Percentage and reasons for mismatch were evaluated. RESULTS:The RIS query identified 1,316 patients. CR linkage was 99.2% successful (n = 1,305 of 1,316) using SSN, fname, lname, and DOB. Eleven mismatches included four CR case-finding failures, one NMD fname error, five nonreportable in the CR, and one with correct identifiers in both databases. Without SSN, linkage was 97.3% successful (n = 1,281 of 1,316); name errors accounted for 19 and DOB accounted for 5 additional mismatches. CONCLUSION/CONCLUSIONS:Using common data elements, linkage between the NMD and state CRs may be feasible and could provide critical outcomes information to advance accurate assessment of breast imaging in the United States.

The Revised International Staging System (R-ISS) and the International Myeloma Working Group 2014 (IMWG 2014) are newer staging systems used to prognosticate multiple myeloma (MM) outcomes. We hypothesized that these would provide better prognostic differentiation for newly diagnosed multiple myeloma (MM) compared with ISS. We analyzed the Center for International Blood and Marrow Transplant Research database from 2008 to 2014 to compare the 3 systems (N = 628) among newly diagnosed MM patients undergoing upfront autologous hematopoietic cell transplantation (AHCT). The median follow-up of survivors was 48 (range, 3 to 99) months. The R-ISS provided the greatest differentiation between survival curves for each stage (for overall survival [OS], the differentiation was 1.74 using the R-ISS, 1.58 using ISS, and 1.60 using the IMWG 2014) . Univariate analyses at 3 years for OS showed R-ISS I at 88% (95% confidence interval [CI], 83% to 93%), II at 75% (95% CI, 70% to 80%), and III at 56% (95% CI, 3% to 69%; P < .001). An integrated Brier score function demonstrated the R-ISS had the best prediction for PFS, though all systems had similar prediction for OS. Among available systems, the R-ISS is the most optimal among available prognostic tools for newly diagnosed MM undergoing AHCT. We recommend that serum lactate dehydrogenase and cytogenetic data be performed on every MM patient at diagnosis to allow accurate prognostication.

OBJECTIVE:High-quality screening mammography has been shown to substantially reduce mortality from breast cancer. Recall rate is a principal performance metric for screening mammography because it directly relates to the rate of false-positive examinations. This study aims to compare the recall rate derived using two sources-the claims-based Hospital Compare (HC) dataset from the Centers for Medicare & Medicaid Services versus the National Mammography Database (NMD) from the American College of Radiology-to understand the implications in pay-for-performance and quality improvement activities. MATERIALS AND METHODS/METHODS:This study retrospectively compared the recall rate reported by NMD facilities with that reported in the HC dataset. Site matching was performed by facility name and zip code, followed by manual verification. Scatterplots, correlations, a paired t test, and Bland-Altman analysis were performed to assess association between the two measures. RESULTS:During the period from October 1 to December 1, 2016, 92 facilities were unambiguously matched using 2014-2015 records in both datasets. The recall rates were positively correlated (r = 0.428, p < 0.001), but the mean HC recall rate (8.5% ± 2.86% [SD]) was significantly (p < 0.001) lower than the mean NMD recall rate (10.6% ± 3.90%). CONCLUSION/CONCLUSIONS:The NMD and HC are two commonly used datasets for measuring screening mammography recall rate. Although recall rates are correlated at the individual facility level, there are important differences that have implications for quality improvement and pay-for-performance.