Radiology Residents Research Articles

Artificial intelligence improves resident detection of pediatric and young adult upper extremity fractures.

We wished to evaluate if an open-source artificial intelligence (AI) algorithm ( https://www.childfx.com ) could improve performance of (1) subspecialized musculoskeletal radiologists, (2) radiology residents, and (3) pediatric residents in detecting pediatric and young adult upper extremity fractures. A set of evaluation radiographs drawn from throughout the upper extremity (elbow, hand/finger, humerus/shoulder/clavicle, wrist/forearm, and clavicle) from 240 unique patients at a single hospital was constructed (mean age 11.3years, range 0-22years, 37.9% female). Two fellowship-trained musculoskeletal radiologists, three radiology residents, and two pediatric residents were recruited as readers. Each reader interpreted each case initially without and then subsequently 3-4weeks later with AI assistance and recorded if/where fracture was present. Access to AI significantly improved area under the receiver operator curve (AUC) of radiology residents (0.768 [0.730-0.806] without AI to 0.876 [0.845-0.908] with AI, P < 0.001) and pediatric residents (0.706 [0.659-0.753] without AI to 0.844 [0.805-0.883] with AI, P < 0.001) in identifying fracture, respectively. There was no evidence of improvement for subspecialized musculoskeletal radiology attendings in identifying fracture (AUC 0.867 [0.832-0.902] to 0.890 [0.856-0.924], P = 0.093). There was no evidence of difference between overall resident AUC with AI and subspecialist AUC without AI (resident with AI 0.863, attending without AI AUC 0.867, P = 0.856). Overall physician radiograph interpretation time was significantly lower with AI (38.9s with AI vs. 52.1s without AI, P = 0.030). An openly accessible AI model significantly improved radiology and pediatric resident accuracy in detecting pediatric upper extremity fractures.

Discrimination faced by radiology residents: an analysis of experiences and mitigation strategies

Rationale and objectivesLiterature shows that discrimination has been pervasive in the field of medicine. The aim of this study was to collect experiences related to discrimination among US radiology residents, including type and source, as well as the residents’ perception on lectures about discrimination and harassment. We also explored the barriers to reporting, and suggested strategies to overcome them. Material and methodsFollowing Institutional Review Board (IRB) approval, an online survey was sent to program directors and coordinators across the US, who were asked to forward the link to their radiology residents. A reminder email was sent over a period of 4 months. The participants were reassured the survey was confidential and anonymous. ResultsAmong the respondents, the most reported types of discrimination were based in gender, race and nationality, the majority of which not being reported. The most common perpetrators were attending radiologists, co-residents, technologists, and patients. The main barriers for reporting were fear of retaliation, confidentiality concerns, and skepticism about a positive outcome. ConclusionOur study examines some experiences of discrimination shared by residents during their training, with gender and race being the most common causes. This sheds light into a hidden and unspoken issue and highlights the need for more active discussions in radiology on microaggressions and implicit bias. Our data can guide future studies as well as residency programs to build effective strategies to address discrimination, aiming for sustainable changes.

Artificial intelligence for diagnosis and prognosis prediction of natural killer/T cell lymphoma using magnetic resonance imaging

Accurate diagnosis and prognosis prediction are conducive to early intervention and improvement of medical care for natural killer/T cell lymphoma (NKTCL). Artificial intelligence (AI)-based systems are developed based on nasopharynx magnetic resonance imaging. The diagnostic systems achieve areas under the curve of 0.905-0.960 in detecting malignant nasopharyngeal lesions and distinguishing NKTCL from nasopharyngeal carcinoma in independent validation datasets. In comparison to human radiologists, the diagnostic systems show higher accuracies than resident radiologists and comparable ones to senior radiologists. The prognostic system shows promising performance in predicting survival outcomes of NKTCL and outperforms several clinical models. For patients with early-stage NKTCL, only the high-risk group benefits from early radiotherapy (hazard ratio= 0.414 vs. late radiotherapy; 95% confidence interval, 0.190-0.900, p= 0.022), while progression-free survival does not differ in the low-risk group. In conclusion, AI-based systems show potential in assisting accurate diagnosis and prognosis prediction and may contribute to therapeutic optimization for NKTCL.

Analysis of National Resident Matching Program for Radiology Fellowships: Factors Affecting Program Fill Rates

PurposeThe National Resident Matching Program (NRMP) is used by an increasing number of diagnostic radiology (DR) residents applying to subspecialty fellowships. Data characterizing match outcomes on the basis of program characteristics are limited. The aim of this study was to determine if fellowship or residency size, location, or perceived reputation was related with a program filling its quota. MethodsUsing public NRMP data from 2004 to 2022, DR residency, breast imaging (BI), musculoskeletal imaging (MSK), interventional radiology (IR), and neuroradiology (NR) fellowship programs were characterized by geography, DR and fellowship quota, applicants per position (A/P), and reputation as determined by being an Aunt Minnie best DR program semifinalist, Doximity 2021-2022 top 25 program, or U.S. News & World Report top 20 hospital. The DR program’s reputation was substituted for fellowships at the same institution. A program was considered filled if it met its quota. ResultsThe 2022 A/P ratios were 1.02 for IR, 0.83 for BI, 0.75 for MSK, and 0.88 for NR. IR was excluded from additional analysis because its A/P was >1. The combined BI, MSK, and NR fellowships filled 78% of positions (529 of 679) and 56% of programs (132 of 234). Factors associated with higher program filling included Doximity top 25 program, Aunt Minnie semifinalist, and U.S. News & World Report top 20 hospital affiliation (P < .001 for all); DR residency quota greater than 9, and fellowship quota of three or more (P < .01). The Ohio Valley (Ohio, western Pennsylvania, West Virginia, and Kentucky) filled the lowest, at 39% of programs (P = .06). ConclusionsLarger fellowship programs with higher perceived reputations and larger underlying DR residency programs were significantly more likely to fill their NRMP quota.

Educating the next generation of radiologists: a comparative report of ChatGPT and e-learning resources

Rapid technological advances have transformed medical education, particularly in radiology, which depends on advanced imaging and visual data. Traditional electronic learning (e-learning) platforms have long served as a cornerstone in radiology education, offering rich visual content, interactive sessions, and peer-reviewed materials. They excel in teaching intricate concepts and techniques that necessitate visual aids, such as image interpretation and procedural demonstrations. However, Chat Generative Pre-Trained Transformer (ChatGPT), an artificial intelligence (AI)-powered language model, has made its mark in radiology education. It can generate learning assessments, create lesson plans, act as a round-the-clock virtual tutor, enhance critical thinking, translate materials for broader accessibility, summarize vast amounts of information, and provide real-time feedback for any subject, including radiology. Concerns have arisen regarding ChatGPT's data accuracy, currency, and potential biases, especially in specialized fields such as radiology. However, the quality, accessibility, and currency of e-learning content can also be imperfect. To enhance the educational journey for radiology residents, the integration of ChatGPT with expert-curated e-learning resources is imperative for ensuring accuracy and reliability and addressing ethical concerns. While AI is unlikely to entirely supplant traditional radiology study methods, the synergistic combination of AI with traditional e-learning can create a holistic educational experience.

Interrater Agreement of BT-RADS for Evaluation of Follow-up MRI in Patients with Treated Primary Brain Tumor.

The Brain Tumor Reporting and Data System (BT-RADS) is a structured radiology reporting algorithm that was introduced to provide uniformity in posttreatment primary brain tumor follow-up and reporting, but its interrater reliability (IRR) assessment has not been widely studied. Our goal is to evaluate the IRR among neuroradiologists and radiology residents in the use of BT-RADS. This retrospective study reviewed 103 consecutive MR studies in 98 adult patients previously diagnosed with and treated for primary brain tumor (January 2019 to February 2019). Six readers with varied experience (4 neuroradiologists and 2 radiology residents) independently evaluated each case and assigned a BT-RADS score. Readers were blinded to the original score reports and the reports from other readers. Cases in which at least 1 neuroradiologist scored differently were subjected to consensus scoring. After the study, a post hoc reference score was also assigned by 2 readers by using future imaging and clinical information previously unavailable to readers. The interrater reliabilities were assessed by using the Gwet AC2 index with ordinal weights and percent agreement. Of the 98 patients evaluated (median age, 53 years; interquartile range, 41-66 years), 53% were men. The most common tumor type was astrocytoma (77%) of which 56% were grade 4 glioblastoma. Gwet index for interrater reliability among all 6 readers was 0.83 (95% CI: 0.78-0.87). The Gwet index for the neuroradiologists' group (0.84 [95% CI: 0.79-0.89]) was not statistically different from that for the residents' group (0.79 [95% CI: 0.72-0.86]) (χ2 = 0.85; P = .36). All 4 neuroradiologists agreed on the same BT-RADS score in 57 of the 103 studies, 3 neuroradiologists agreed in 21 of the 103 studies, and 2 neuroradiologists agreed in 21 of the 103 studies. Percent agreement between neuroradiologist blinded scores and post hoc reference scores ranged from 41%-52%. A very good interrater agreement was found when tumor reports were interpreted by independent blinded readers by using BT-RADS criteria. Further study is needed to determine if this high overall agreement can translate into greater consistency in clinical care.

Radiologic Manifestations of Mycobacterium chimaera Infection After Open Heart Surgery.

The objective of this study is to identify and detail the radiologic manifestations of surgical site and disseminated Mycobacterium chimaera ( MC) infection. The aim is to facilitate early identification and diagnosis of MC, considering its indolent nature and the challenges involved in clinically and pathologically establishing the diagnosis. This was a retrospective cohort study reviewing computed tomography (CT), positron emission tomography (PET)/CT, and magnetic resonance imaging examinations in patients over the age of 18 years with a history of open heart surgery and a clinical or pathologic diagnosis of MC. Two radiology residents, a fellowship-trained nuclear medicine radiologist, and a fellowship-trained cardiothoracic radiologist performed consensus reads to determine the imaging findings seen in MC infection. Twenty-five patients were included. Localized, surgical site infection was more common than disseminated disease. Typical CT findings included peristernal soft tissue thickening, sinus tracts often extending to the cutaneous surface, slowly enlarging fluid collections, and sternal osteolysis. PET/CT findings demonstrated hypermetabolic activity in nearly all patients localized to sites of infection. Imaging findings for disseminated infection included hepatosplenomegaly, lymphadenopathy, involvement of the central nervous system, discitis/osteomyelitis, and distant abscesses. Imaging plays a vital role in suggesting possible surgical sites and disseminated MC infection acquired from open heart surgery. Radiologists must keep a high index of suspicion given the indolent nature and subtle imaging change over time. PET/CT is most useful in diagnosis and helps in differentiating between a sterile postoperative fluid collection or scarring and active MC infection and helps provide a target for debridement.

Comparing Accuracy of Night Radiology Interpretations for Pediatric Trauma: Radiology Residents Versus Attending Teleradiologists.

Background: Overnight radiology coverage for pediatric trauma patients (PTPs) is addressed with a combination of on-call radiology residents (RRs) and/or attending teleradiologists (ATs); however, the accuracy of these two groups has not been investigated for PTPs. We aimed to compare the accuracy of RRs vs AT interpretations of computed tomography (CT) scans for PTPs. Methods: Pediatric trauma patients (<18 years old) at a single level-I adult/level-II pediatric trauma center were studied in a retrospective analysis (3/2019-5/2020). Computed tomography scans interpreted by both RRs and ATs were included. Radiology residents were compared to ATs for time to interpretation (TTI) and accuracy compared to faculty attending radiologist interpretation, using the validated RADPEER scoring system. Additionally, RR and AT accuracies were compared to a previously studied adult cohort during the same time-period. Results: 42 PTPs (270 interpretations) and 1053 adults (8226 interpretations) were included. Radiology residents had similar rates of discrepancy (13.3% vs 13.3%), major discrepancy (4.4% vs 4.4%), missed findings (9.6% vs 12.6%), and overcalls (3.7% vs .7%) vs ATs (all P > .05). Mean TTI was shorter for RRs (55.9 vs 90.4minutes, P < .001). Radiology residents had a higher discrepancy rate for PTPs (13.3% vs 7.5%, P = .01) than adults. Attending teleradiologists had a similar discrepancy rate for PTPs and adults (13.3% vs 8.9%, P = .07). Discussion: When interpreting PTP CT imaging, RRs had similar discrepancy rates but faster TTI than ATs. Radiology residents had a higher discrepancy rate for PTP CTs than RR interpretation of adult patients, indicating both RRs and ATs need more focused training in the interpretation of PTP studies.

Attitudes toward communication skills with learner needs assessment within radiology residency programs in China: a cross-sectional survey

BackgroundCommunication skills (CS) represent a core competency in radiology residency training. However, no structured curriculum exists to train radiology residents in CS in China. The aim of this study was to evaluate the status and prevalence of doctor–patient communication training among radiology residents in nine Chinese accredited radiology residency training programs and to determine whether there is a perceived need for a formalized curriculum in this field.MethodsWe administered a cross-sectional online survey to radiology residents involved in CS training at nine standard residency training programs in China. The questionnaire developed for this study included CS training status, residents’ demographics, attitudes toward CS training, communication needs, and barriers. Residents’ attitudes toward CS training were measured with the Communication Skills Attitude Scale (CSAS) and its subscales, a positive attitude scale (PAS) and negative attitude scale (NAS).ResultsA total of 133 (48.36%) residents participated in the survey. The mean total scores on the two dimensions of the CSAS were 47.61 ± 9.35 in the PAS and 36.34 ± 7.75 in the NAS. Factors found to be significantly associated with the PAS included receiving previous training in CS, medical ethics, or humanities and the doctor’s attire. We found that first-year residents and poor personal CS were the most influential factors on the NAS. Only 58.65% of participants reported having previously received CS training during medical school, and 72.93% of respondents reported failure in at least one difficult communication during their residency rotation. Most of those surveyed agreed that CS can be learned through courses and were interested in CS training. Some of the most common barriers to implementing formal CS training were a lack of time, no standardized curriculum, and a lack of materials and faculty expertise.ConclusionsMost residents had a very positive attitude toward CS training and would value further training, despite the limited formal CS training for radiology residents in China. Future efforts should be made to establish and promote a standard and targeted CS curriculum for Chinese radiology residents.

Women in leadership matters: Achieving diversity in radiology residency recruitment

Rationale and objectivesTo assess whether academic radiology departments and residency programs with efforts toward supporting and augmenting Diversity, Equity, and Inclusion (DEI) are associated with a higher proportion of residents from diverse backgrounds. Materials and methodsProgram Directors within the Radiology Residency Education Research Alliance were surveyed to gather information about program characteristics, incorporation of diversity in resident recruitment, the sponsoring department's commitment to efforts at expanding diversity, and a summary of their current and past residents, staff and faculty members (academic years 2020 and 2023) with respect to a list of diversity characteristics. ResultsSurvey response rate was 51 %. Sixty-three percent (15/24) of participating programs have departmental committees dedicated to DEI work; 46 % (11/24) of programs' departments have a Vice Chair for DEI. Sixty percent (15/24) of programs use their social media accounts to advertise their DEI programming efforts. Ninety-six percent (23/24) of programs participating in the survey use diversity factors to select candidates for their program. Women Leadership was associated with above-median diversity of residents and faculty. ConclusionThis study of radiology residency programs encourages a more prominent role for women in leadership positions within academic radiology departments to drive diversity and inclusion efforts.

Should Breastfeeding Be Interrupted after Radiological Imaging Examinations? Evidence and Clinical Applications.

Purpose: Breastfeeding provides optimal growth and development for infants. Lactating mothers may have challenges maintaining breastfeeding, and one of those challenges is being falsely advised to interrupt breastfeeding following radiologic studies. The aim of this study was to evaluate the knowledge, attitudes and experiences of healthcare professionals regarding breastfeeding after radiological imaging studies on lactating mothers. Method: In this cross-sectional study, an online survey consisting of 29 semi-structured questions was delivered to radiology technicians and physicians in radiology and pediatrics via social media. Mixed methods were used to analyze responses descriptively. Results: Of the 404 participants, 39% (n = 158) were radiology technicians, 31% (n = 125) were pediatricians, 11% (n = 46) were radiologists, 10% (n = 41) were pediatric residents and 8% (n = 34) were radiology residents. Of all healthcare professionals, 91% reported that breastfeeding does not need to be interrupted after ultrasound, 75% X-ray, 56% mammography, 62% non-contrast CT, 18% contrast-enhanced CT, 93% non-contrast MRI and 23% contrast-enhanced MRI. Interruption of breastfeeding was recommended more frequently after contrast-enhanced imaging studies (p < 0.01). After contrast-enhanced CT, 54% of participants recommended pumping and dumping for <24 h and 25% for 24-48 h; after contrast-enhanced MRI, these rates were found to be 57% and 20%, respectively. Of the healthcare professionals, 63% reported that their knowledge about management of breastfeeding after radiological studies was not sufficient. Conclusions: Situations requiring the interruption of breastfeeding after radiological studies are rare. However, recommendations in clinical practice vary in our country. Increasing the awareness and knowledge of healthcare professionals will prevent breastfeeding from being negatively affected.

Knowledge, Attitude, and Practice of Diagnostic Radiology Among Clinical Year Medical Students.

Background Nowadays, radiology is considered one of the most important disciplines of medicine as it guides physicians to reach the proper diagnosis by using many types of medical imaging modalities, such as x-ray radiography, computed tomography (CT), ultrasonography (US), and magnetic resonance imaging (MRI). These modalities are used to create dynamic images of different parts of the human body, which are being used to accurately diagnose and follow up on a variety of medical conditions.Moreover, in recent decades, radiology has experienced substantial growth and transformation, establishing itself not just in diagnostics but also in the domain of medical interventions, which includes the increasingly recognized discipline of interventional radiology. Methodology A descriptive cross-sectional study was conducted at Umm Al-Qura University (UQU) in Makkah from October 2022 to April 2023. The population size of medical students from the fourth to sixth year at Umm Al-Qura University is about 820 students. Results The total number of participants was 359, but two did not fill out properly. Hence, data was analyzed for (n=357), whereas more than half of them were female, 195 (54.6%). About 133 (37%) of the students were in their sixth year, while 106 (29%) were in their fourth year. Regarding their grade point average (GPA), 209 (58%) had >3.5, and 119 (33%) had 3.0-3.5. The maximum number of females 77 (57.9%) students were in the sixth year. Regarding knowledge, 291 (81.5%) had heard about interventional radiology before, while 66 (18.5%) had never heard about interventional radiology before. Moreover, 270 (75.6%) believe that the years in radiology residency are the same as other specialties. Regarding perceived knowledge about radiology, 183 (51.3%) said it is adequate. Conclusion This study showed that medical students at Umm Al-Qura University have a positive attitude towards radiology. However, the majority of the students do not have adequate knowledge regarding radiology as well as radiation hazards. We can improve this by increasing radiology experience in our institutions. Also, courses should be designed and incorporated into the curriculum to increase the knowledge of medical students about ionizing radiation.

ChatGPT: Evaluating answers on contrast media related questions and finetuning by providing the model with the ESUR guideline on contrast agents

ObjectiveThis study aimed to assess the feasibility of GPT-4 for answering questions related to contrast media with and without the context of the European Society of Urogenital Radiology (ESUR) guideline on contrast agents. The overarching goal was to determine whether contextual enrichment by providing guideline information improves answers of GPT-4 for clinical decision-making in radiology. MethodsA set of 64 questions, based on the ESUR guideline on contrast agents mirroring pertinent sections, was developed and posed to GPT-4 both directly and after providing the guideline using a plugin. Responses were graded by experienced radiologists for quality of information and accuracy in pinpointing information from the guideline as well as by radiology residents for utility, using Likert-scales. ResultsGPT-4′s performance improved significantly with the guideline. Without the guideline, average quality rating was 3.98, which increased to 4.33 with the guideline (p = 0036). In terms of accuracy, 82.3% of answers matched the information from the guideline. Utility scores also reflected a significant improvement with the guideline, with average scores of 4.1 (without) and 4.4 (with) (p = 0.008) with a Fleiss´ Kappa of 0.44. ConclusionGPT-4, when contextually enriched with a guideline, demonstrates enhanced capability in providing guideline-backed recommendations. This approach holds promise for real-time clinical decision-support, making guidelines more actionable. However, further refinements are necessary to maximize the potential of large language models (LLMs). Inherent limitations need to be addressed.

The application of computer-aided diagnosis in Breast Imaging Reporting and Data System ultrasound training for residents-a randomized controlled study.

The consistency of Breast Imaging Reporting and Data System (BI-RADS) classification among experienced radiologists is different, which is difficult for inexperienced radiologists to master. This study aims to explore the value of computer-aided diagnosis (CAD) (AI-SONIC breast automatic detection system) in the BI-RADS training for residents. A total of 12 residents who participated in the first year and the second year of standardized resident training in Ningbo No. 2 Hospital from May 2020 to May 2021 were randomly divided into 3 groups (Group 1, Group 2, Group 3) for BI-RADS training. They were asked to complete 2 tests and questionnaires at the beginning and end of the training. After the first test, the educational materials were given to the residents and reviewed during the breast imaging training month. Group 1 studied independently, Group 2 studied with CAD, and Group 3 was taught face-to-face by experts. The test scores and ultrasonographic descriptors of the residents were evaluated and compared with those of the radiology specialists. The trainees' confidence and recognition degree of CAD were investigated by questionnaire. There was no statistical significance in the scores of residents in the first test among the 3 groups (P=0.637). After training and learning, the scores of all 3 groups of residents were improved in the second test (P=0.006). Group 2 (52±7.30) and Group 3 (54±5.16) scored significantly higher than Group 1 (38±3.65). The consistency of ultrasonographic descriptors and final assessments between the residents and senior radiologists were improved (κ3 > κ2 > κ1), with κ2 and κ3 >0.4 (moderately consistent with experts), and κ1 =0.225 (fairly agreed with experts). The results of the questionnaire showed that the trainees had increased confidence in BI-RADS classification, especially Group 2 (1.5 to 3.5) and Group 3 (1.25 to 3.75). All trainees agreed that CAD was helpful for BI-RADS learning (Likert scale score: 4.75 out of 5) and were willing to use CAD as an aid (4.5, max. 5). The AI-SONIC breast automatic detection system can help residents to quickly master BI-RADS, improve the consistency between residents and experts, and help to improve the confidence of residents in the classification of BI-RADS, which may have potential value in the BI-RADS training for radiology residents. Chinese Clinical Trial Registry (ChiCTR2400081672).

How young radiologists use contrast media and manage adverse reactions: an international survey

ObjectivesTo collect real-world data about the knowledge and self-perception of young radiologists concerning the use of contrast media (CM) and the management of adverse drug reactions (ADR).MethodsA survey (29 questions) was distributed to residents and board-certified radiologists younger than 40 years to investigate the current international situation in young radiology community regarding CM and ADRs. Descriptive statistics analysis was performed.ResultsOut of 454 respondents from 48 countries (mean age: 31.7 ± 4 years, range 25–39), 271 (59.7%) were radiology residents and 183 (40.3%) were board-certified radiologists. The majority (349, 76.5%) felt they were adequately informed regarding the use of CM. However, only 141 (31.1%) received specific training on the use of CM and 82 (18.1%) about management ADR during their residency. Although 266 (58.6%) knew safety protocols for handling ADR, 69.6% (316) lacked confidence in their ability to manage CM-induced ADRs and 95.8% (435) expressed a desire to enhance their understanding of CM use and handling of CM-induced ADRs. Nearly 300 respondents (297; 65.4%) were aware of the benefits of contrast-enhanced ultrasound, but 249 (54.8%) of participants did not perform it. The preferred CM injection strategy in CT parenchymal examination and CT angiography examination was based on patient’s lean body weight in 318 (70.0%) and 160 (35.2%), a predeterminate fixed amount in 79 (17.4%) and 116 (25.6%), iodine delivery rate in 26 (5.7%) and 122 (26.9%), and scan time in 31 (6.8%) and 56 (12.3%), respectively.ConclusionTraining in CM use and management ADR should be implemented in the training of radiology residents.Critical relevance statementWe highlight the need for improvement in the education of young radiologists regarding contrast media; more attention from residency programs and scientific societies should be focused on training about contrast media use and the management of adverse drug reactions.Key points• This survey investigated training of young radiologists about use of contrast media and management adverse reactions.• Most young radiologists claimed they did not receive dedicated training.• An extreme heterogeneity of responses was observed about contrast media indications/contraindications and injection strategy.Graphical

The efficacy of pediatric elbow radiographic guidance in diagnosis of lateral humeral condyle fracture.

Although lateral humeral condyle fracture is common, the incidence of missed diagnosis is very high. Delayed and missed diagnosis led to significant morbidities and loss of functions. We designed a pediatric elbow radiographic guidance aiming to improve the accuracy of diagnosis. This study was aimed to evaluate the efficacy of the radiographic guidance for the diagnosis of lateral condyle fracture. A cross-sectional study was conducted after defining the essential parameters as a guidance for assessing the pediatric elbow radiographs. We included medical students, emergency medicine, orthopedic, and radiology residents and fellows into this study. A questionnaire was used to evaluate the efficacy of the guidance. All participants underwent a pretest evaluation, followed by studying the guidance, and then finished a posttest evaluation. Baseline characteristics, diagnostic scores, and parameter evaluation scores were collected. The pretest and posttest scores were analyzed using paired t-test. Association between baseline characteristics and diagnostic scores were analyzed using multiple regression analysis. We included 177 participants. Average diagnostic score was significantly increased after using the guidance, from 12.2 ± 1.9 to 13.0 ± 1.7 (p < 0.0001). Medical students showed the most improvement, from 11.9 ± 1.9 to 13.1 ± 1.3 (p <0.001). All means of essential parameter evaluation scores were significantly improved in overall participants.The pediatric elbow radiographic guidance is useful for evaluation and diagnosis of lateral condyle fracture, especially for young physicians and trainees. Therefore, this should be recommended in routine medical education and general practice.

The Inter-Observer Agreement Between Resident and Consultant Radiologists in Reporting Emergency Head CT Scans

Objectives: To determine the inter-observer agreement between resident and consultant radiologists in reporting emergency head CT scans. Materials and Methods: This descriptive cross-sectional retrospective study was performed in a tertiary care hospital Karachi from 1st October 2021 to 31st march 2022. Total of 111 number of patients of 18-70 years of age of either gender who underwent emergency Head CT scans were included. Patients who came for follow-up CT scans were excluded. CT findings were interpreted by the radiology resident on duty. Subsequently, these CT images were interpreted by a consultant radiologist, and the decision of both resident and faculty member CT was correlated for inter-observer agreement. Results: The mean age was 47.47 ± 14.20 years. The majority of the patients 46 (41.44%) were between 56 to 70 years of age. Out of these 111 patients, 72 (64.86%) were male and 39 (35.14%) were female with a ratio of 1.9:1. Discrepancy between resident and consultant radiologists in reporting emergency head CT scans is seen in 6 (5.41%) patients. Inter-observer agreement between resident and consultant radiologists in reporting emergency head CT scans was found to be 94.59% with a kappa “κ” value of 0.885 which showed a very strong agreement. Conclusion: This study concluded that little discrepancy was found in inter-observer agreement between the radiology residents and the faculty members for interpretation of CT images of Head.

AI-Assisted X-ray Fracture Detection in Residency Training: Evaluation in Pediatric and Adult Trauma Patients.

Background: This study aimed to evaluate the impact of an AI-assisted fracture detection program on radiology residents' performance in pediatric and adult trauma patients and assess its implications for residency training. Methods: This study, conducted retrospectively, included 200 radiographs from participants aged 1 to 95 years (mean age: 40.7 ± 24.5 years), encompassing various body regions. Among these, 50% (100/200) displayed at least one fracture, totaling one hundred thirty-five fractures, assessed by four radiology residents with different experience levels. A machine learning algorithm was employed for fracture detection, and the ground truth was established by consensus among two experienced senior radiologists. Fracture detection accuracy, reporting time, and confidence were evaluated with and without AI support. Results: Radiology residents' sensitivity for fracture detection improved significantly with AI support (58% without AI vs. 77% with AI, p < 0.001), while specificity showed minor improvements (77% without AI vs. 79% with AI, p = 0.0653). AI stand-alone performance achieved a sensitivity of 93% with a specificity of 77%. AI support for fracture detection significantly reduced interpretation time for radiology residents by an average of approximately 2.6 s (p = 0.0156) and increased resident confidence in the findings (p = 0.0013). Conclusion: AI support significantly enhanced fracture detection sensitivity among radiology residents, particularly benefiting less experienced radiologists. It does not compromise specificity and reduces interpretation time, contributing to improved efficiency. This study underscores AI's potential in radiology, emphasizing its role in training and interpretation improvement.

Digital eye strain and its associated factors among radiology physicians in Pakistan: a cross-sectional survey using logistic regression analysis.

Increased use of digital devices in the modern era has led to the development of digital eye strain (DES) or computer vision syndrome in their users. This can result in the development of various ocular and visual symptoms among them. In this study, the authors aimed to view the prevalence of digital eye strain among radiology physicians in Pakistan and their associated risk factors. A cross-sectional study was conducted to evaluate occupational DES among radiology physicians in Pakistan. The data collection was done using the convenience sampling technique, and the data were analyzed using IBM SPSS for Windows, Version 25.0. Out of the 247 respondents, 33.6% were males and 66.4% were females. 41.7% of them were between 30 and 40 years of age and 51.8% of them were radiology residents. 52.2% of the participants had a refractive error and were using a corrective lens. The majority of the radiologists in our study (84.2%) preferred picture archiving and communication system (PACS) over films and 82.2% of them reported having breaks of less than 15 min. Major symptoms reported by the participants were tired or heavy eyes (69.6%) and headache (69.3%). The proportion of developing DES was higher in females [P=0.001, adjusted odds ratio (aOR)=2.94], radiology residents (P=0.031, aOR=3.29), and working hours of more than 4 h per day (P<0.001, aOR=0.04). With recent advances in the field of radiology in Pakistan, the frequency of developing DES among radiologists is increasing. Being a female, having long working hours, and having noticeable flickers on the digital screens were among the significant factors in developing DES among radiologists.

Workflow interruptions in an era of instant messaging: A detailed analysis

IntroductionThe complex practice environment and responsibilities incumbent on diagnostic radiologists creates a workflow susceptible to disruption. While interruptions have been shown to contribute to medical errors in the healthcare delivery environment, the exact impact on highly subspecialized services such as diagnostic radiology is less certain. One potential source of workflow disruption is the use of a departmental instant messaging system (Webex), to facilitate communications between radiology faculty, residents, fellows, and technologists. A retrospective review was conducted to quantify the frequency of interruption experienced by our neuroradiology fellows. Materials and methodsData logs were gathered comprising all instant messages sent and received within the designated group chats from July 5–December 31, 2021, during weekday shifts staffed by neuroradiology fellows. Interruptions per shift were calculated based on month, week, and day of the week. Results14,424 messages were sent across 289 total shifts. The 6 fellows assigned to the main neuroradiology reading room sent 3258 messages and received 10,260 messages from technologists and other staff. There was an average of 50 interruptions per shift when examined by month (range 48–53), and 52 interruptions per shift when examined by day of the week (range 40–60). ConclusionNeuroradiology fellows experience frequent interruptions from the departmental instant messaging system. These disruptions, when considered in conjunction with other non-interpretative tasks, may have negative implications for workflow efficiency, requiring iterative process improvements when incorporating new technology into the practice environment of diagnostic radiology.