Journal of the American College of Radiology : JACR最新文献

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.

Purpose: Routine imaging of soft tissue infection is not recommended and represents a potential area of CT overuse. The utility of CT in patients with superficial soft tissue infection of the extremities is unknown. The purpose of this study is to evaluate the utilization and clinical impact of CT ordered in the setting of extremity cellulitis.

Methods: We retrospectively analyzed patients with extremity cellulitis examined with CT between 2012 and 2021 at a single center. We collected patient history, diagnostic imaging characteristics, and subsequent surgery decision. We hypothesized that yield of CT for deep infection was significantly lower than 10% and that yield was decreasing over time. These hypotheses were evaluated with Rao-Scott χ² tests and repeated measures logistic regression.

Results: There were 496 eligible encounters among 463 patients. Yield of positive CT among lower extremity patients was 5.5% (95% confidence interval 3.33-7.75), significantly less than our hypothesis of 10% (P = .003). In 71.8% of encounters, patients underwent diagnostic imaging studies in addition to CT. Utilization rose from 0.08% per hospital visit in 2012 to 2013 to 0.14% in 2020 to 2021, with differences in yield between time periods not reaching statistical significance (P = .059). Among 496 encounters, 62 received surgery (12.1%), with 21 of these cases preceded by a positive CT for deep infection.

Conclusions: Our 10-year single-center analysis of CT use for extremity cellulitis demonstrated a low yield of positive CT findings for deep infection and limited impact of CT on surgical management. A high incidence of patients undergoing multiple radiologic examinations suggests uncertainty in selecting appropriate imaging modalities in this clinical scenario.

Summary: This single-center retrospective analysis found that CT examination of patients with clinically diagnosed cellulitis of the extremities has significantly low yield for deep infection in the lower extremities.

Purpose: Increasing volumes and productivity expectations, along with practice type consolidation, may be impacting trainees' roles in the work effort of radiologists involved in education. We assessed temporal shifts in trainee participation in radiologists' workload nationally.

Methods: All US radiologists interpreting noninvasive diagnostic imaging for Medicare fee-for-service beneficiaries were identified from annual 5% Research Identifiable Files from 2008 to 2020 (n = 35,595). Teaching radiologists were defined as those billing services using Medicare's GC modifier, indicating trainee supervision. Billed work relative value units were used to determine the percentage of teaching radiologists' total workload with trainee participation. Mean trainee participation in workload was calculated for teaching radiologists overall and stratified by radiologist and practice characteristics determined using National Downloadable Files.

Results: The percentage of radiologists involved in teaching increased from 13.6% (2008) to 20.4% (2020). Among teaching radiologists, mean total workload increased 7% from 2008 to 2019 and decreased in 2020 to 2% below 2008's level; mean teaching workload decreased 19% from 2008 to 2019 and decreased in 2020 to 31% below 2008's level. Mean trainee participation in teaching radiologists' total workload decreased from 35.3% (2008) to 26.3% (2019) and 24.5% (2020). Teaching radiologists showed decreased mean trainee participation when stratified by gender, experience, subspecialty, geography, practice type, and practice size.

Conclusions: The percentage of US radiologists involved in resident teaching has increased, likely reflecting academic practice expansion and academic-community practice consolidation. However, a declining percentage of teaching radiologists' total workload involves trainees; this dispersion effect could have implications for education quality.

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 ten 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 American College of Radiology and Radiological Society of North America, thereafter relying on snowball sampling. Surveyed subspecialties were abdominal, cardiac, emergency, musculoskeletal, neuro, 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.

Purpose: Best practices exist for communicating medical information to patients, but there is less emphasis on methods to communicate risks, especially in medical imaging. The authors conducted a scoping review of patient decision aids in medical imaging and characterized the presentation methods of imaging risks.

Methods: Embase, MEDLINE, CINAHL, and PsychINFO were searched to identify studies involving patient decision aids used in diagnostic imaging that communicated the risks. Study characteristics included the number and types of risks included, as well as the presentation type and how the probability of risks were communicated.

Results: The final study included 46 articles encompassing 27 distinct patient decision aids. Mammography was the most common imaging scenario (22 of 46), followed by lung cancer screening (18 of 46), traumatic brain injury (5 of 46), and urolithiasis (1 of 46). All patient decision aids included risks associated with imaging, but the number of risk types varied from two to nine (mean, 4 ± 2). Twelve risks were identified across the 27 decision aids, but no single study included all risks. Overall, most risks (65%) were communicated with text, and the presentation mode varied by type of risk. False-positive risks were most commonly communicated using a visual format, whereas radiation risk was most commonly communicated using text format.

Conclusions: There was no consistent manner of communicating risk to patients, and visual methods such as icon arrays were not consistently used. The variability of both included risks and the risk presentation modes in the patient decision aids may affect decision making, especially among patients and caregivers with lower health literacy and numeracy.