Faculty Bibliography

The Prostate Imaging Reporting and Data System version 2 (PI-RADS v2) was developed with a consensus-based process using a combination of published data, and expert observations and opinions. In the short time since its release, numerous studies have validated the value of PI-RADS v2 but, as expected, have also identified a number of ambiguities and limitations, some of which have been documented in the literature with potential solutions offered. To address these issues, the PI-RADS Steering Committee, again using a consensus-based process, has recommended several modifications to PI-RADS v2, maintaining the framework of assigning scores to individual sequences and using these scores to derive an overall assessment category. This updated version, described in this article, is termed PI-RADS v2.1. It is anticipated that the adoption of these PI-RADS v2.1 modifications will improve inter-reader variability and simplify PI-RADS assessment of prostate magnetic resonance imaging even further. Research on the value and limitations on all components of PI-RADS v2.1 is strongly encouraged.

PURPOSE/OBJECTIVE:To analyze the changes in the work profiles of radiologists and the reporting time after the implementation of professional subspecialization in the radiology department of a Swiss university hospital. METHODS:In a retrospective analysis, the overall number of different radiologic examinations performed in the department of radiology of the largest Swiss university hospital was documented for 2014 and 2016 before and after the implementation of subspecialized reporting (subspecialities: abdominal, musculoskeletal, cardiothoracic, emergency, and pediatric imaging) in May 2015. For six selected radiologists, the number and types of reported examinations as well as the related radiology report turnaround times (RTATs) were analyzed in detail and compared between the two 1-year periods. RESULTS:Overall, there was a significant increase of 10.3% in the total number of examinations performed in the whole department in 2016 compared with 2014. For four of the six radiologists, the range of different types of examinations significantly decreased with the introduction of subspecialized reporting (p < 0.05). Furthermore, there was a significant change in the subset of the ten most commonly reported types of examinations reported by each of the six radiologists. Mean overall RTATs significantly increased for five of the six radiologists (p < 0.05). CONCLUSIONS:Implementation of subspecialized reporting led to a change in the structure and a decrease in the range of different examination types reported by each radiologist. Mean RTAT increased for most radiologists. Subspecialized reporting allows the individual radiologist to focus on a special field of professional competence but can result in longer overall RTAT.

PURPOSE/OBJECTIVE:Radiologists have historically participated as individuals in CMS pay-for-performance programs, but little is known about how radiologists perform under increasingly available group participation. We aimed to assess radiologists' relative national performance on CMS quality metrics using group versus individual participation. METHODS:Radiologists' group- and individual-level 2016 performance on Physician Quality Reporting System (PQRS) and non-PQRS Qualified Clinical Data Registry (QCDR) measures were obtained from the CMS national Physician Compare database and compared. RESULTS:Radiology groups reported an average 4.6 ± 2.0 quality measures; individual radiologists reported 2.3 ± 1.2 (P < .001). At least six measures were reported by 31.5% of groups versus 1.0% of individuals. Only one measure was reported by 5.4% of groups versus 33.0% of individuals. Groups reported 21 unique measures (20 via registries and one via QCDR). For 8 of the 11 measures reported by 20 or more groups, the average group performance rate was 3% or better than the average performance rate among radiologists participating as individuals (maximum 14% improvement with group participation versus individual participation for any individual measure). Group and individual performance were similar for the remaining three such measures. For measures reported by 20 or more groups in which a higher score indicates better performance, average group performance rates ranged from 86.2% to 98.9%. CONCLUSION/CONCLUSIONS:Compared with individual participation in CMS quality performance programs, radiologists participating as a group reported larger numbers of quality measures and achieved higher performance rates on those measures. Radiology practices seeking success under Medicare's new Quality Payment Program should carefully explore group participation.

OBJECTIVE. Given recent specialty attention to workforce diversity, we aimed to characterize potential gender differences in the practice patterns of interventional radiologists (IRs). MATERIALS AND METHODS. Using Medicare claims data, we identified IRs on the basis of the distribution of their billed clinical work effort and descriptively characterized practice patterns by gender. RESULTS. Women represented 8.2% (241/2936) of all IRs identified nationally. Female representation varied geographically (≤ 2% in nine states, ≥ 20% in three states) and by career stage (9.4% among early-career IRs and 6.4% among late-career IRs; 18.8% among early-career IRs in the Northeast). For both female IRs and male IRs, interventional case mixes were similar across service categories (e.g., venous and hemodialysis access, arterial and venous interventions, biopsies and drainages) and by procedural complexity (e.g., 5.7% vs 4.3% for low-complexity procedures and 59.5% vs 61.3% for high-complexity procedures). Average patient complexity scores were also similar for female (2.7 ± 12 [SD]) and male (2.8 ± 12) IRs. Female IRs spent slightly lower portions of their work effort rendering invasive services (66.5% vs 70.0%, respectively) and noninvasive diagnostic imaging (19.0% vs 22.2%) than male IRs but spent more time in evaluation and management clinical visits (14.5% vs 7.9%). Both female IRs and male IRs rendered a majority of their services to female patients (53.4% vs 53.1%). CONCLUSION. Although women remain underrepresented in interventional radiology, female IRs' interventional case composition, procedural complexity, and patient complexity are similar to those of their male colleagues. Female IRs' higher proportion of evaluation and management clinical visits supports the specialty's increased focus on longitudinal care so that interventional radiology will thrive alongside other clinical specialties.

PURPOSE/OBJECTIVE:To evaluate the changing use of transcatheter hemodialysis conduit procedures. METHODS:Multiple Centers for Medicare & Medicaid Services datasets were used to assess hemodialysis conduit angiography. Use was normalized per 100,000 beneficiaries and stratified by specialty and site of service. RESULTS:From 2001 to 2015, hemodialysis angiography use increased from 385 to 1,045 per 100,000 beneficiaries (compound annual growth rate [CAGR], +7.4%)]. Thrombectomy use increased from 114 to 168 (CAGR, +2.8%). Angiography and thrombectomy changed, by specialty, +1.5% and -1.3% for radiologists, +18.4% and +14.4% for surgeons, and +24.0% and +17.7% for nephrologists, respectively. By site, angiography and thrombectomy changed +29.1% and +20.7% for office settings and +0.8% and -2.4% for hospital settings, respectively. Radiologists' angiography and thrombectomy market shares decreased from 81.5% to 37.0% and from 84.2% to 47.3%, respectively. Angiography use showed the greatest growth for nephrologists in the office (from 5 to 265) and the greatest decline for radiologists in the hospital (299 to 205). Across states in 2015, there was marked variation in the use of angiography (0 [Wyoming] to 1173 [Georgia]) and thrombectomy (0 [6 states] to 275 [Rhode Island]). Radiologists' angiography and thrombectomy market shares decreased in 48 and 31 states, respectively, in some instances dramatically (eg, angiography in Nevada from 100.0% to 6.7%). CONCLUSIONS:Dialysis conduit angiography use has grown substantially, more so than thrombectomy. This growth has been accompanied by a drastic market shift from radiologists in hospitals to nephrologists and surgeons in offices. Despite wide geographic variability nationally, radiologist market share has declined in most states.

PURPOSE/OBJECTIVE:To assess subspecialty mix and case volumes of general and abdominal subspecialty radiologists interpreting abdominal MRI. METHODS:The 2016 CMS Physician/Supplier Procedure Summary Master File was used to obtain billed counts of radiologist-interpreted abdominal fluoroscopy, US, CT, and MRI examinations. The CMS Physician and Other Supplier Public Use File was used to assess the subspecialty mix and case volume of the radiologists interpreting those examinations. RESULTS:The fraction of all abdominal imaging examinations interpreted by generalists and abdominal subspecialty radiologists was 70.7% and 16.5% for fluoroscopy; 68.7% and 21.0% for US; 71.4% and 19.2% for CT; and 41.9% and 52.5% for MRI. In 2016, the fraction of general and abdominal radiologists interpreting > 50 fluoroscopy examinations on Medicare fee-for-service beneficiaries was 15.1% and 16.2%. For > 50 US examinations, the fraction was 61.5% and 60.5%; for > 50 CT examinations, 91.2% and 79.6%; and for > 50 MRI examinations, 4.0% and 28.5%. The fraction of abdominal imaging examinations interpreted overall by low-volume providers (those interpreting ≤ 50 examinations in 2016) was 59.5% for fluoroscopy, 17.5% for US, 6.3% for CT, and 50.6% for MRI. CONCLUSION/CONCLUSIONS:Nationally, most abdominal fluoroscopy, US, and CT examinations are interpreted by general radiologists, who have similar annual volumes of these examinations as abdominal subspecialty radiologists. In contrast, most abdominal MRI examinations are interpreted by abdominal subspecialty radiologists, who attain considerably higher volumes. These findings have implications for workforce planning and abdominal imaging fellowship design to ensure their graduates are optimally prepared to contribute to their future practices.

High-quality evidence shows that MRI in biopsy-naive men can reduce the number of men who need prostate biopsy and can reduce the number of diagnoses of clinically insignificant cancers that are unlikely to cause harm. In men with prior negative biopsy results who remain under persistent suspicion, MRI improves the detection and localization of life-threatening prostate cancer with greater clinical utility than the current standard of care, systematic transrectal US-guided biopsy. Systematic analyses show that MRI-directed biopsy increases the effectiveness of the prostate cancer diagnosis pathway. The incorporation of MRI-directed pathways into clinical care guidelines in prostate cancer detection has begun. The widespread adoption of the Prostate Imaging Reporting and Data System (PI-RADS) for multiparametric MRI data acquisition, interpretation, and reporting has promoted these changes in practice. The PI-RADS MRI-directed biopsy pathway enables the delivery of key diagnostic benefits to men suspected of having cancer based on clinical suspicion. Herein, the PI-RADS Steering Committee discusses how the MRI pathway should be incorporated into routine clinical practice and the challenges in delivering the positive health impacts needed by men suspected of having clinically significant prostate cancer.

OBJECTIVE. The purpose of this study was to assess the percentage and characteristics of radiologists who meet criteria for facility-based measurement in the Merit-Based Incentive Payment System (MIPS). MATERIALS AND METHODS. The Provider Utilization and Payment Data: Physician and Other Supplier Public Use File was used to identify radiologists who bill 75% or more of their Medicare Part B claims in the facility setting. RESULTS. Among 31,217 included radiologists nationwide, 71.0% met the eligibility criteria for facility-based measurement as individuals in MIPS. The percentage of predicted eligibility was slightly higher for male than female radiologists (72.9% vs 64.5%). The percentage decreased slightly with increasing years in practice (from 78.8% for radiologists with < 10 years in practice to 67.3% for radiologists with ≥ 25 years in practice). The eligibility percentage was also higher for radiologists in rural as opposed to urban practices (81.6% vs 71.3%) and in academic as opposed to nonacademic practices (77.2% vs 70.3%). However, the percentages were similar across practices of varying sizes. There was also a greater degree of heterogeneity by state, ranging from 50.9% in Minnesota to 94.0% in West Virginia. By overall geographic region, the percentage of predicted eligibility was lowest in the Northeast (64.7%) and highest in the Midwest (78.3%). A higher percentage of generalists met the 75% facility-based threshold than did subspecialists (77.3% vs 65.4%). When stratified by subspecialty, however, facility-based eligibility was lowest for musculoskeletal radiologists (38.1%) and breast imagers (45.1%) and highest for cardiothoracic radiologists (85.1%). For other subspecialties, predicted eligibility ranged from 66.0% to 77.8%. CONCLUSION. Most radiologists will be eligible for facility-based reporting for MIPS in 2019, with some variation by demographic and specialty characteristics. The facility-based option provides a safety net for radiologists who face challenges accessing hospital data for reporting quality measures. In general, radiologists should not alter their current MIPS strategy but should instead consider facility-based measurement as a contingency plan that could result in a higher final score.

OBJECTIVE:To use Twitter to characterize public perspectives regarding artificial intelligence (AI) and radiology. METHODS AND MATERIALS/METHODS:Twitter was searched for all tweets containing the terms "artificial intelligence" and "radiology" from November 2016 to October 2017. Users posting the tweets, tweet content, and linked websites were categorized. RESULTS:Six hundred and five tweets were identified. These were from 407 unique users (most commonly industry-related individuals [22.6%]; radiologists only 9.3%) and linked to 216 unique websites. 42.5% of users were from the United States. The tweets mentioned machine/deep learning in 17.2%, industry in 14.0%, a medical society/conference in 13.4%, and a university in 9.8%. 6.3% mentioned a specific clinical application, most commonly oncology and lung/tuberculosis. 24.6% of tweets had a favorable stance regarding the impact of AI on radiology, 75.4% neutral, and none were unfavorable. 88.0% of linked websites leaned toward AI being positive for the field of radiology; none leaned toward AI being negative for the field. 51.9% of linked websites specifically mentioned improved efficiency for radiology with AI. 35.2% of websites described challenges for implementing AI in radiology. Of the 47.2% of websites that mentioned the issue of AI replacing radiologists, 77.5% leaned against AI replacing radiologists, 13.7% had a neutral view, and 8.8% leaned toward AI replacing radiologists. CONCLUSION/CONCLUSIONS:These observations provide an overview of the social media discussions regarding AI in radiology. While noting challenges, the discussions were overwhelmingly positive toward the transformative impact of AI on radiology and leaned against AI replacing radiologists. Greater radiologist engagement in this online social media dialog is encouraged.