Pub Date : 2025-02-01DOI: 10.1016/j.jacr.2024.11.024
Ali H. Dhanaliwala MD, PhD , Amanda J. Deutsch MD , Jeffrey Moon MD , Darco Lalevic MCIT , Charles Chambers MCIT, MHCI , Tessa S. Cook MD, PhD
Purpose
The status of radiology examinations affects the flow of patients through the emergency department (ED). Yet this information is not readily available to ED physicians, nurses, and staff members (collectively referred to as ED staff members) or patients. The aim of this study was to improve ED workflow by providing real-time information about the status of radiology reports to ED staff members.
Methods
A dashboard displaying real-time information on the status of pending radiology examinations as extracted from the electronic medical record and radiology information system was developed for display in the ED. An algorithm based on historical trends was developed for predicting expected turnaround times (TATs). Focus groups, surveys, and dashboard use data were used to gather feedback and understand utility.
Results
The ED radiology dashboard was successfully deployed to four EDs within the health system. The dashboard received an average of 9,397 unique views per week the first year and 802 views per week in the following 2 years after deployment. Most examinations had TATs better than the estimated time, and fewer than 1% had TATs greater than 2 hours from the estimated time. No differences were found between pre- and postsurvey opinion results.
Conclusions
A web-based dashboard that displays radiologic imaging study status is a low-cost, high-yield method to improve communication between radiology and ED staff members.
{"title":"Development and Deployment of an Emergency Department Radiology Dashboard to Improve Communication and Transparency of Radiologic Imaging and Report Status","authors":"Ali H. Dhanaliwala MD, PhD , Amanda J. Deutsch MD , Jeffrey Moon MD , Darco Lalevic MCIT , Charles Chambers MCIT, MHCI , Tessa S. Cook MD, PhD","doi":"10.1016/j.jacr.2024.11.024","DOIUrl":"10.1016/j.jacr.2024.11.024","url":null,"abstract":"<div><h3>Purpose</h3><div>The status of radiology examinations affects the flow of patients through the emergency department (ED). Yet this information is not readily available to ED physicians, nurses, and staff members (collectively referred to as ED staff members) or patients. The aim of this study was to improve ED workflow by providing real-time information about the status of radiology reports to ED staff members.</div></div><div><h3>Methods</h3><div>A dashboard displaying real-time information on the status of pending radiology examinations as extracted from the electronic medical record and radiology information system was developed for display in the ED. An algorithm based on historical trends was developed for predicting expected turnaround times (TATs). Focus groups, surveys, and dashboard use data were used to gather feedback and understand utility.</div></div><div><h3>Results</h3><div>The ED radiology dashboard was successfully deployed to four EDs within the health system. The dashboard received an average of 9,397 unique views per week the first year and 802 views per week in the following 2 years after deployment. Most examinations had TATs better than the estimated time, and fewer than 1% had TATs greater than 2 hours from the estimated time. No differences were found between pre- and postsurvey opinion results.</div></div><div><h3>Conclusions</h3><div>A web-based dashboard that displays radiologic imaging study status is a low-cost, high-yield method to improve communication between radiology and ED staff members.</div></div>","PeriodicalId":49044,"journal":{"name":"Journal of the American College of Radiology","volume":"22 2","pages":"Pages 191-199"},"PeriodicalIF":4.0,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142775241","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-02-01DOI: 10.1016/j.jacr.2024.11.002
Matthew D. Phelps MD , Diana L. Lam MD
{"title":"Planning for the Future: Modeling Growth and Attrition in the Radiologist Workforce","authors":"Matthew D. Phelps MD , Diana L. Lam MD","doi":"10.1016/j.jacr.2024.11.002","DOIUrl":"10.1016/j.jacr.2024.11.002","url":null,"abstract":"","PeriodicalId":49044,"journal":{"name":"Journal of the American College of Radiology","volume":"22 2","pages":"Pages 170-171"},"PeriodicalIF":4.0,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143395640","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-01DOI: 10.1016/j.jacr.2024.09.006
Lucas Corallo HBSc , D. Blair Macdonald MD, FRCPC , Fatma Eldehimi MD , Anirudh Venugopalan Nair MD, FRCR, MBA , Simeon Mitchell MD, CM, MScHQ
Purpose
To identify the published standards for the classification and communication of critical actionable findings in emergency radiology and the associated facilitators and barriers to communication and message management or dissemination of such findings.
Materials and methods
Search terms for resources pertaining to critical findings (CFs) in emergency radiology were applied to two databases (PubMed, Embase). Screening of hits using the following pre-established inclusion and exclusion criteria were performed by three analysts with subsequent consensus discussion for discrepancies: (1) the resources include any standards for the classification and communication of imaging findings as critical, or (2) the resource discusses any facilitators to the communication of CFs, or (3) the resource discusses any barriers to the communication of CFs. Resources with explicit focus on a pediatric population or predominant focus on artificial intelligence or natural language processing were omitted. Accompanying gray literature search was used to expand included resources. Data extraction included year, country, resource type, scope or purpose, participants, context, standards to identifying or communicating CFs, facilitators and barriers, method type, recommendations, applicability, and disclosures.
Results
Seventy-six resources were included in the final analysis, including 16 societal or commission guidelines. Among the guidelines, no standardized list of CFs was identified, with typical recommendations suggesting application of a local policy. Communication standards included direct closed-loop communication for high acuity findings, with more flexible communication channels for less acute findings. Applied interventions for CFs management most frequently fell into four categories: electronic (n = 10), hybrid (ie, electronic or administrative) (n = 3), feedback or education (n = 5), and administrative (n = 4).
Conclusion
There are published standards, policies, and interventions for the management of CFs in emergency radiology. Three-tier stratification (eg, critical, urgent, incidental) based on time sensitivity and severity is most common with most CFs necessitating closed-loop communication. Awareness of systemic facilitators and barriers should inform local policy development. Electronic and administrative communication pathways are useful adjuncts. Further research should offer comparative analyses of different CF interventions with regard to cost-effectiveness, notification time, and user feedback.
{"title":"Classification and Communication of Critical Findings in Emergency Radiology: A Scoping Review","authors":"Lucas Corallo HBSc , D. Blair Macdonald MD, FRCPC , Fatma Eldehimi MD , Anirudh Venugopalan Nair MD, FRCR, MBA , Simeon Mitchell MD, CM, MScHQ","doi":"10.1016/j.jacr.2024.09.006","DOIUrl":"10.1016/j.jacr.2024.09.006","url":null,"abstract":"<div><h3>Purpose</h3><div>To identify the published standards for the classification and communication of critical actionable findings in emergency radiology and the associated facilitators and barriers to communication and message management or dissemination of such findings.</div></div><div><h3>Materials and methods</h3><div>Search terms for resources pertaining to critical findings (CFs) in emergency radiology were applied to two databases (PubMed, Embase). Screening of hits using the following pre-established inclusion and exclusion criteria were performed by three analysts with subsequent consensus discussion for discrepancies: (1) the resources include any standards for the classification and communication of imaging findings as critical, <em>or</em> (2) the resource discusses any <em>facilitators</em> to the communication of CFs, <em>or</em> (3) the resource discusses any <em>barriers</em> to the communication of CFs. Resources with explicit focus on a pediatric population or predominant focus on artificial intelligence or natural language processing were omitted. Accompanying gray literature search was used to expand included resources. Data extraction included year, country, resource type, scope or purpose, participants, context, standards to identifying or communicating CFs, facilitators and barriers, method type, recommendations, applicability, and disclosures.</div></div><div><h3>Results</h3><div>Seventy-six resources were included in the final analysis, including 16 societal or commission guidelines. Among the guidelines, no standardized list of CFs was identified, with typical recommendations suggesting application of a local policy. Communication standards included direct closed-loop communication for high acuity findings, with more flexible communication channels for less acute findings. Applied interventions for CFs management most frequently fell into four categories: electronic (n = 10), hybrid (ie, electronic or administrative) (n = 3), feedback or education (n = 5), and administrative (n = 4).</div></div><div><h3>Conclusion</h3><div>There are published standards, policies, and interventions for the management of CFs in emergency radiology. Three-tier stratification (eg, critical, urgent, incidental) based on time sensitivity and severity is most common with most CFs necessitating closed-loop communication. Awareness of systemic facilitators and barriers should inform local policy development. Electronic and administrative communication pathways are useful adjuncts. Further research should offer comparative analyses of different CF interventions with regard to cost-effectiveness, notification time, and user feedback.</div></div>","PeriodicalId":49044,"journal":{"name":"Journal of the American College of Radiology","volume":"22 1","pages":"Pages 44-55"},"PeriodicalIF":4.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142336722","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-01DOI: 10.1016/j.jacr.2024.11.020
Kaelan Yao MS , Jeffers Nguyen MD , Mahan Mathur MD
In today’s medical landscape, rapidly learning vast amounts of information requires innovative learning methods. Spaced repetition tools (like Anki) aid efficient knowledge absorption and retention among medical trainees. Yet, adoption of these tools in radiology medical student education lags despite proven effectiveness. This article highlights spaced repetition as a learning tool alongside other evidence-based educational practices, aiming to revolutionize radiology education among medical students. We (1) describe the educational theory and current application of spaced repetition in the setting of other learning techniques often found in undergraduate medical education; (2) underscore the underutilization of tools such as Anki in radiology education; and (3) offer practical guidance for educators interested in integrating spaced repetition into their teaching methodologies.
{"title":"Spaced Repetition Learning in Radiology Education: Exploring Its Potential and Practical Application","authors":"Kaelan Yao MS , Jeffers Nguyen MD , Mahan Mathur MD","doi":"10.1016/j.jacr.2024.11.020","DOIUrl":"10.1016/j.jacr.2024.11.020","url":null,"abstract":"<div><div>In today’s medical landscape, rapidly learning vast amounts of information requires innovative learning methods. Spaced repetition tools (like Anki) aid efficient knowledge absorption and retention among medical trainees. Yet, adoption of these tools in radiology medical student education lags despite proven effectiveness. This article highlights spaced repetition as a learning tool alongside other evidence-based educational practices, aiming to revolutionize radiology education among medical students. We (1) describe the educational theory and current application of spaced repetition in the setting of other learning techniques often found in undergraduate medical education; (2) underscore the underutilization of tools such as Anki in radiology education; and (3) offer practical guidance for educators interested in integrating spaced repetition into their teaching methodologies.</div></div>","PeriodicalId":49044,"journal":{"name":"Journal of the American College of Radiology","volume":"22 1","pages":"Pages 15-21"},"PeriodicalIF":4.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142755791","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-01DOI: 10.1016/j.jacr.2024.11.001
{"title":"JACR Annual Awards 2024","authors":"","doi":"10.1016/j.jacr.2024.11.001","DOIUrl":"10.1016/j.jacr.2024.11.001","url":null,"abstract":"","PeriodicalId":49044,"journal":{"name":"Journal of the American College of Radiology","volume":"22 1","pages":"Pages 1-2"},"PeriodicalIF":4.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143153100","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-01DOI: 10.1016/j.jacr.2024.08.009
Dhairya A. Lakhani MD , Mahla Radmard MD , Armin Tafazolimoghadam MD , Sahil Patel MD , Arun Murugesan MD , Hammad Malik MD , Jeffery P. Hogg MD , Ziling Shen ScM , David M. Yousem MD, MBA , Francis Deng MD
Objective
Two-tiered preference signaling has been implemented in the radiology residency application system to reduce congestion in the setting of high-volume applications. Signals are an indicator of strong interest that an applicant can transmit to a limited number of programs. This study assessed the impact of program signaling on interview invitations, how applicants strategically used signals based on their application’s competitiveness, and applicants’ attitudes toward the current signaling system.
Methods
A survey was sent to radiology residency applicants registered with TheRadRoom during the 2024 application cycle. We queried the applicants’ background, applications, signal distribution, and interview outcome depending on the type of signal sent. We also asked whether respondents received an interview invitation from a hypothetical “comparator nonsignaled program” if they had one additional signal to use. Group differences were assessed using nonparametric Wilcoxon signed rank test.
Results
A total of 202 applicants completed the survey (28% response rate). Most applied to diagnostic radiology (81%). Nearly all respondents used all six gold (98%) and six silver (96.5%) signals. Interview invitation rates were significantly higher for signaled programs (59.8% ± 27.4%) than nonsignaled (8.5% ± 8.5%); the invitation rate at the comparator nonsignaled programs was 37%. Gold-signaled programs had significantly higher interview rates (67.8% ± 29.3) than silver (51.8% ± 31.3%). Respondents used 49.2% (±21.7%) of their signals for “likely to match” programs, 33.1% (±20.9%) for “aspirational” programs, and 17.6% (±15.8%) for “safety” programs. Most respondents (146; 76%) supported continuing the signaling system for future cycles.
Conclusion
Signaling programs significantly enhanced interview invitation rates, with gold signals being more effective than silver. The applicants used about six total signals for “likely-to-match” programs, two for “aspirational” programs, and about four for “safety” programs.
{"title":"Preference Signaling in the Radiology Residency Match: National Survey of Applicants","authors":"Dhairya A. Lakhani MD , Mahla Radmard MD , Armin Tafazolimoghadam MD , Sahil Patel MD , Arun Murugesan MD , Hammad Malik MD , Jeffery P. Hogg MD , Ziling Shen ScM , David M. Yousem MD, MBA , Francis Deng MD","doi":"10.1016/j.jacr.2024.08.009","DOIUrl":"10.1016/j.jacr.2024.08.009","url":null,"abstract":"<div><h3>Objective</h3><div>Two-tiered preference signaling has been implemented in the radiology residency application system to reduce congestion in the setting of high-volume applications. Signals are an indicator of strong interest that an applicant can transmit to a limited number of programs. This study assessed the impact of program signaling on interview invitations, how applicants strategically used signals based on their application’s competitiveness, and applicants’ attitudes toward the current signaling system.</div></div><div><h3>Methods</h3><div>A survey was sent to radiology residency applicants registered with TheRadRoom during the 2024 application cycle. We queried the applicants’ background, applications, signal distribution, and interview outcome depending on the type of signal sent. We also asked whether respondents received an interview invitation from a hypothetical “comparator nonsignaled program” if they had one additional signal to use. Group differences were assessed using nonparametric Wilcoxon signed rank test.</div></div><div><h3>Results</h3><div>A total of 202 applicants completed the survey (28% response rate). Most applied to diagnostic radiology (81%). Nearly all respondents used all six gold (98%) and six silver (96.5%) signals. Interview invitation rates were significantly higher for signaled programs (59.8% ± 27.4%) than nonsignaled (8.5% ± 8.5%); the invitation rate at the comparator nonsignaled programs was 37%. Gold-signaled programs had significantly higher interview rates (67.8% ± 29.3) than silver (51.8% ± 31.3%). Respondents used 49.2% (±21.7%) of their signals for “likely to match” programs, 33.1% (±20.9%) for “aspirational” programs, and 17.6% (±15.8%) for “safety” programs. Most respondents (146; 76%) supported continuing the signaling system for future cycles.</div></div><div><h3>Conclusion</h3><div>Signaling programs significantly enhanced interview invitation rates, with gold signals being more effective than silver. The applicants used about six total signals for “likely-to-match” programs, two for “aspirational” programs, and about four for “safety” programs.</div></div>","PeriodicalId":49044,"journal":{"name":"Journal of the American College of Radiology","volume":"22 1","pages":"Pages 116-124"},"PeriodicalIF":4.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142115723","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-01DOI: 10.1016/j.jacr.2024.09.004
Ann Seliger MA , Mahadevappa Mahesh MS, PhD , Lydia Gregg MA, CMI
{"title":"Examining the Effects of a Narrative-Based Educational Animation for Radiology Technologists About Discontinuing Gonadal Shielding","authors":"Ann Seliger MA , Mahadevappa Mahesh MS, PhD , Lydia Gregg MA, CMI","doi":"10.1016/j.jacr.2024.09.004","DOIUrl":"10.1016/j.jacr.2024.09.004","url":null,"abstract":"","PeriodicalId":49044,"journal":{"name":"Journal of the American College of Radiology","volume":"22 1","pages":"Pages 125-128"},"PeriodicalIF":4.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142302710","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-01DOI: 10.1016/j.jacr.2024.09.012
Elizabeth M. McGuire , Samantha L. Heller PhD, MD
{"title":"Patient-Friendly Summary of the ACR Appropriateness Criteria®: Imaging After Breast Surgery","authors":"Elizabeth M. McGuire , Samantha L. Heller PhD, MD","doi":"10.1016/j.jacr.2024.09.012","DOIUrl":"10.1016/j.jacr.2024.09.012","url":null,"abstract":"","PeriodicalId":49044,"journal":{"name":"Journal of the American College of Radiology","volume":"22 1","pages":"Page 145"},"PeriodicalIF":4.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142482488","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-01DOI: 10.1016/j.jacr.2024.10.006
Dustin A. Gress MS , Ehsan Samei PhD , Donald P. Frush MD , Casey E. Pelzl MPH , Joel G. Fletcher MD , Mahadevappa Mahesh MS, PhD , David B. Larson MD, MBA , Mythreyi Bhargavan-Chatfield PhD
Objective
This study sought to determine consensus opinions from subspecialty radiologists and imaging physicists on the relative importance of image quality features in CT.
Methods
A prospective survey of subspecialty radiologists and medical physicists was conducted to collect consensus opinions on the relative importance of 10 image quality features: axial sharpness, blooming, contrast, longitudinal sharpness, low-contrast axial sharpness, metal artifact, motion, noise magnitude, noise texture, and streaking. The survey was first sent to subspecialty radiologists in volunteer leadership roles in the ACR and RSNA, thereafter relying on snowball sampling. Surveyed subspecialties were abdominal, cardiac, emergency, musculoskeletal, neuroradiology, pediatric, and thoracic radiology and medical physics. Individual respondents’ ratings were normalized for calculation of mean normalized ratings and priority rankings for each feature within subspecialties. Also calculated were intraclass correlation coefficients across image quality features within subspecialties and analysis of variance across subspecialties within each feature.
Results
Most subspecialties had moderate to excellent intraclass agreement. For every radiology subspecialty except musculoskeletal, motion was the most important image quality feature. There was agreement across subspecialties that axial sharpness and contrast are only moderately important. There was disagreement across subspecialties on the relative importance of noise magnitude. Blooming was highly important to cardiac radiologists, and noise texture was highly important to musculoskeletal radiologists.
Conclusion
Image quality preferences differ based on clinical tasks and challenges in each anatomical radiology subspecialty. CT image analysis and development of quantitative measures of quality and protocol optimization—and related policy initiatives—should be specific to radiology subspecialty.
{"title":"Ranking the Relative Importance of Image Quality Features in CT by Consensus Survey","authors":"Dustin A. Gress MS , Ehsan Samei PhD , Donald P. Frush MD , Casey E. Pelzl MPH , Joel G. Fletcher MD , Mahadevappa Mahesh MS, PhD , David B. Larson MD, MBA , Mythreyi Bhargavan-Chatfield PhD","doi":"10.1016/j.jacr.2024.10.006","DOIUrl":"10.1016/j.jacr.2024.10.006","url":null,"abstract":"<div><h3>Objective</h3><div>This study sought to determine consensus opinions from subspecialty radiologists and imaging physicists on the relative importance of image quality features in CT.</div></div><div><h3>Methods</h3><div>A prospective survey of subspecialty radiologists and medical physicists was conducted to collect consensus opinions on the relative importance of 10 image quality features: axial sharpness, blooming, contrast, longitudinal sharpness, low-contrast axial sharpness, metal artifact, motion, noise magnitude, noise texture, and streaking. The survey was first sent to subspecialty radiologists in volunteer leadership roles in the ACR and RSNA, thereafter relying on snowball sampling. Surveyed subspecialties were abdominal, cardiac, emergency, musculoskeletal, neuroradiology, pediatric, and thoracic radiology and medical physics. Individual respondents’ ratings were normalized for calculation of mean normalized ratings and priority rankings for each feature within subspecialties. Also calculated were intraclass correlation coefficients across image quality features within subspecialties and analysis of variance across subspecialties within each feature.</div></div><div><h3>Results</h3><div>Most subspecialties had moderate to excellent intraclass agreement. For every radiology subspecialty except musculoskeletal, motion was the most important image quality feature. There was agreement across subspecialties that axial sharpness and contrast are only moderately important. There was disagreement across subspecialties on the relative importance of noise magnitude. Blooming was highly important to cardiac radiologists, and noise texture was highly important to musculoskeletal radiologists.</div></div><div><h3>Conclusion</h3><div>Image quality preferences differ based on clinical tasks and challenges in each anatomical radiology subspecialty. CT image analysis and development of quantitative measures of quality and protocol optimization—and related policy initiatives—should be specific to radiology subspecialty.</div></div>","PeriodicalId":49044,"journal":{"name":"Journal of the American College of Radiology","volume":"22 1","pages":"Pages 66-75"},"PeriodicalIF":4.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142482493","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-01-01DOI: 10.1016/j.jacr.2024.10.016
Taha Lodhi BS , Francis Deng MD
Purpose
Ranking preferences by residency programs in the Match could shape the diversity of selective specialties. We investigated demographic characteristics of applicants and matched residents in radiology and other specialties to identify changes in representation.
Methods
Survey data from the National Resident Matching Program were obtained for applicants to radiology (diagnostic radiology, interventional radiology, and combined diagnostic radiology and nuclear medicine) and nonradiology programs in the 2022 to 2024 Main Residency Matches. Demographics among applicants preferring a specialty and matched residents were compared using χ2 tests.
Results
Radiology had a 73.9% match rate (3,486 of 4,718 applicants). Women represented 29.0% of radiology applicants compared with 52.0% in other specialties. In radiology, only US citizenship had higher representation among matched residents compared with applicants (+4.0%, 95% confidence interval [CI], 2.8%-5.3%) (P = .001). Other demographics were not significantly different between applicants and matched residents in radiology overall. A higher representation of women was observed in matched residents compared with applicants in diagnostic radiology (+2.4%, 95% CI, 0.2%-4.6%) (P = .031) but not interventional radiology (+0.2%, 95% CI, −5.1% to 5.5%) (P = .944). In nonradiology specialties, female sex, nonheterosexual orientation, White race, US citizenship, first-generation medical graduate, and nonurban childhood were associated with higher match rates.
Conclusion
US citizenship but not other demographic variables was associated with higher rates of matching into radiology. Women are underrepresented among radiology applicants and have slightly higher match rates in diagnostic radiology but not interventional radiology.
{"title":"Demographic Differences in the Radiology Residency Match, 2022 to 2024","authors":"Taha Lodhi BS , Francis Deng MD","doi":"10.1016/j.jacr.2024.10.016","DOIUrl":"10.1016/j.jacr.2024.10.016","url":null,"abstract":"<div><h3>Purpose</h3><div>Ranking preferences by residency programs in the Match could shape the diversity of selective specialties. We investigated demographic characteristics of applicants and matched residents in radiology and other specialties to identify changes in representation.</div></div><div><h3>Methods</h3><div>Survey data from the National Resident Matching Program were obtained for applicants to radiology (diagnostic radiology, interventional radiology, and combined diagnostic radiology and nuclear medicine) and nonradiology programs in the 2022 to 2024 Main Residency Matches. Demographics among applicants preferring a specialty and matched residents were compared using χ<sup>2</sup> tests.</div></div><div><h3>Results</h3><div>Radiology had a 73.9% match rate (3,486 of 4,718 applicants). Women represented 29.0% of radiology applicants compared with 52.0% in other specialties. In radiology, only US citizenship had higher representation among matched residents compared with applicants (+4.0%, 95% confidence interval [CI], 2.8%-5.3%) (<em>P</em> = .001). Other demographics were not significantly different between applicants and matched residents in radiology overall. A higher representation of women was observed in matched residents compared with applicants in diagnostic radiology (+2.4%, 95% CI, 0.2%-4.6%) (<em>P</em> = .031) but not interventional radiology (+0.2%, 95% CI, −5.1% to 5.5%) (<em>P</em> = .944). In nonradiology specialties, female sex, nonheterosexual orientation, White race, US citizenship, first-generation medical graduate, and nonurban childhood were associated with higher match rates.</div></div><div><h3>Conclusion</h3><div>US citizenship but not other demographic variables was associated with higher rates of matching into radiology. Women are underrepresented among radiology applicants and have slightly higher match rates in diagnostic radiology but not interventional radiology.</div></div>","PeriodicalId":49044,"journal":{"name":"Journal of the American College of Radiology","volume":"22 1","pages":"Pages 25-32"},"PeriodicalIF":4.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142549388","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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