Paris classification of colonic polyps using CT colonography: prospective cohort study of interobserver variation.

BACKGROUND: The Paris classification categorises colorectal polyp morphology. Interobserver agreement for Paris classification has been assessed at optical colonoscopy (OC) but not CT colonography (CTC). We aimed to determine the following: (1) interobserver agreement for the Paris classification using CTC between radiologists; (2) if radiologist experience influenced classification, gross polyp morphology, or polyp size; and (3) the extent to which radiologist classifications agreed with (a) colonoscopy and (b) a combined reference standard. METHODS: Following ethical approval for this non-randomised prospective cohort study, seven radiologists from three hospitals classified 52 colonic polyps using the Paris system. We calculated interobserver agreement using Fleiss kappa and mean pairwise agreement (MPA). Absolute agreement was calculated between radiologists; between CTC and OC; and between CTC and a combined reference standard using all available imaging, colonoscopic, and histopathological data. RESULTS: Overall interobserver agreement between the seven readers was fair (Fleiss kappa 0.33; 95% CI 0.30-0.37; MPA 49.7%). Readers with < 1500 CTC experience had higher interobserver agreement (0.42 (95% CI 0.35-0.48) vs. 0.33 (95% CI 0.25-0.42)) and MPA (69.2% vs 50.6%) than readers with ≥ 1500 experience. There was substantial overall agreement for flat vs protuberant polyps (0.62 (95% CI 0.56-0.68)) with a MPA of 87.9%. Agreement between CTC and OC classifications was only 44%, and CTC agreement with the combined reference standard was 56%. CONCLUSION: Radiologist agreement when using the Paris classification at CT colonography is low, and radiologist classification agrees poorly with colonoscopy. Using the full Paris classification in routine CTC reporting is of questionable value. CLINICAL RELEVANCE STATEMENT: Interobserver agreement for radiologists using the Paris classification to categorise colorectal polyp morphology is only fair; routine use of the full Paris classification at CT colonography is questionable. KEY POINTS: • Overall interobserver agreement for the Paris classification at CT colonography (CTC) was only fair, and lower than for colonoscopy. • Agreement was higher for radiologists with < 1500 CTC experience and for larger polyps. There was substantial agreement when classifying polyps as protuberant vs flat. • Agreement between CTC and colonoscopic polyp classification was low (44%).

Society of Radiologists in Ultrasound Consensus Conference Recommendations for Incidental Gallbladder Polyp Management: Interreader Agreement Among 10 Radiologists.

BACKGROUND. The 2022 Society of Radiologists in Ultrasound (SRU) consensus conference recommendations for small gallbladder polyps support management that is less aggressive than earlier approaches and may help standardize evaluation of polyps by radiologists. OBJECTIVE. The purpose of the present study was to assess the interreader agreement of radiologists in applying SRU recommendations for management of incidental gallbladder polyps on ultrasound. METHODS. This retrospective study included 105 patients (75 women and 30 men; median age, 51 years) with a gallbladder polyp on ultrasound (without features highly suspicious for invasive or malignant tumor) who underwent cholecystectomy between January 1, 2003, and January 1, 2021. Ten abdominal radiologists independently reviewed ultrasound examinations and, using the SRU recommendations, assessed one polyp per patient to assign risk category (extremely low risk, low risk, or indeterminate risk) and make a possible recommendation for surgical consultation. Five radiologists were considered less experienced (< 5 years of experience), and five were considered more experienced (≥ 5 years of experience). Interreader agreement was evaluated. Polyps were classified pathologically as nonneoplastic or neoplastic. RESULTS. For risk category assignments, interreader agreement was substantial among all readers (k = 0.710), less-experienced readers (k = 0.705), and more-experienced readers (k = 0.692). For surgical consultation recommendations, inter-reader agreement was substantial among all readers (k = 0.795) and more-experienced readers (k = 0.740) and was almost perfect among less-experienced readers (k = 0.811). Of 10 readers, a median of 5.0 (IQR, 2.0-8.0), 4.0 (IQR, 2.0-7.0), and 0.0 (IQR, 0.0-0.0) readers classified polyps as extremely low risk, low risk, and indeterminate risk, respectively. Across readers, the percentage of polyps classified as extremely low risk ranged from 32% to 72%; as low risk, from 24% to 65%; and as indeterminate risk, from 0% to 8%. Of 10 readers, a median of zero change to 0 (IQR, 0.0-1.0) readers recommended surgical consultation; the percentage of polyps receiving a recommendation for surgical consultation ranged from 4% to 22%. Of a total of 105 polyps, 102 were nonneo-plastic and three were neoplastic (all benign). Based on readers' most common assessments for nonneoplastic polyps, the risk category was extremely low risk for 53 polyps, low risk for 48 polyps, and indeterminate risk for one polyp; surgical consultation was recommended for 16 polyps. CONCLUSION. Ten abdominal radiologists showed substantial agreement for polyp risk categorizations and surgical consultation recommendations, although areas of reader variability were identified. CLINICAL IMPACT. The findings support the overall reproducibility of the SRU recommendations, while indicating opportunity for improvement.

Imaging approach to ingested foreign bodies in the neck.

Foreign body ingestion is a common clinical occurrence worldwide, with high morbidity in the pediatric population and in adult patients with intentional attempts. Coins and button battery ingestions are more common among children. Bone impaction and swallowed dentures are usually seen in older adults. While most ingested foreign bodies pass through the gastrointestinal tract spontaneously with no complications, some require endoscopic and/or surgical intervention. Complications such as pharyngoesophageal ulceration, perforation, stricture, and deep neck infection can develop without timely diagnosis and management. The purpose of this article is to familiarize radiologists with the imaging approach to assess for characteristics and impacted locations of ingested foreign bodies in the neck.

Mounier-Kuhn syndrome in poorly controlled asthma.

INTRODUCTION: Mounier-Kuhn syndrome or tracheobronchomegaly, is a rare condition that consists of abnormal dilation of the trachea and main bronchi due to a pathological arrangement of smooth muscle fibers in this area. CASE REPORT: We present the case of a 46-year-old woman with poorly controlled asthma and recurrent infections, who was diagnosed with Mounier-Kuhn syndrome through a computed tomography scan revealing an unusual enlargement of the trachea with associated bronchiectasis. RESULTS: The diagnosis of Mounier-Kuhn syndrome is radiological, involving measurement of the trachea where a diameter >25 mm in men and >21 mm in women is observed. While diagnosis is sometimes incidental, there is an association with respiratory diseases such as asthma or COPD, hence clinical suspicion is important in patients with poorly controlled underlying conditions who present with recurrent infections, inadequate secretion management, or even hemoptysis. CONCLUSIONS: Despite its rarity, this syndrome significantly impacts patients' quality of life. Diagnosis and management involve comprehensive evaluations including computed tomography, with a multidisciplinary approach including pulmonologists and radiologists. Exploring its clinical features, associations with other respiratory diseases and treatment options is crucial in managing this rare respiratory condition.

Current status of pediatric radiology in India: a perspective.

This review is a bird's eye view of the practice of pediatric radiology in India. The key focus of this article is training, certification and employment opportunities for radiologists aspiring to specialise in pediatric radiology. Further, we have traced the growth in academic and research opportunities over the past two decades, as well as given a peep into the future trajectory of this speciality. An understanding of these concepts is key to the expansion of pediatric radiologists not just within India, but across the globe.

System-based strategies for mitigating burnout in radiology.

BACKGROUND: Burnout is a chronic problem prevalent in radiology, with a significant burden on individuals and healthcare systems. DISCUSSION: A substantial portion of the literature on managing burnout has focused on individual-based remedies. We posit that burnout is a systemic problem and present an overview of some system-based strategies that could be employed to mitigate burnout in radiology. These include managing workload, optimizing work shifts, maximizing autonomy, limiting work-life conflicts, creating opportunities for professional fulfillment, utilizing user-friendly electronic medical records (EMR), deploying efficient picture archiving and communication systems (PACS), building system redundancy, leadership transparency, and fostering a healthy work environment.  CONCLUSION: System-based strategies can help mitigate burnout.

Algorithmic transparency and interpretability measures improve radiologists' performance in BI-RADS 4 classification.

OBJECTIVE: To evaluate the perception of different types of AI-based assistance and the interaction of radiologists with the algorithm's predictions and certainty measures. METHODS: In this retrospective observer study, four radiologists were asked to classify Breast Imaging-Reporting and Data System 4 (BI-RADS4) lesions (n = 101 benign, n = 99 malignant). The effect of different types of AI-based assistance (occlusion-based interpretability map, classification, and certainty) on the radiologists' performance (sensitivity, specificity, questionnaire) were measured. The influence of the Big Five personality traits was analyzed using the Pearson correlation. RESULTS: Diagnostic accuracy was significantly improved by AI-based assistance (an increase of 2.8% ± 2.3%, 95 %-CI 1.5 to 4.0 %, p = 0.045) and trust in the algorithm was generated primarily by the certainty of the prediction (100% of participants). Different human-AI interactions were observed ranging from nearly no interaction to humanization of the algorithm. High scores in neuroticism were correlated with higher persuasibility (Pearson's r = 0.98, p = 0.02), while higher consciousness and change of accuracy showed an inverse correlation (Pearson's r = -0.96, p = 0.04). CONCLUSION: Trust in the algorithm's performance was mostly dependent on the certainty of the predictions in combination with a plausible heatmap. Human-AI interaction varied widely and was influenced by personality traits. KEY POINTS: • AI-based assistance significantly improved the diagnostic accuracy of radiologists in classifying BI-RADS 4 mammography lesions. • Trust in the algorithm's performance was mostly dependent on the certainty of the prediction in combination with a reasonable heatmap. • Personality traits seem to influence human-AI collaboration. Radiologists with specific personality traits were more likely to change their classification according to the algorithm's prediction than others.

Primary bone tumor detection and classification in full-field bone radiographs via YOLO deep learning model.

OBJECTIVES: Automatic bone lesions detection and classifications present a critical challenge and are essential to support radiologists in making an accurate diagnosis of bone lesions. In this paper, we aimed to develop a novel deep learning model called You Only Look Once (YOLO) to handle detecting and classifying bone lesions on full-field radiographs with limited manual intervention. METHODS: In this retrospective study, we used 1085 bone tumor radiographs and 345 normal bone radiographs from two centers between January 2009 and December 2020 to train and test our YOLO deep learning (DL) model. The trained model detected bone lesions and then classified these radiographs into normal, benign, intermediate, or malignant types. The intersection over union (IoU) was used to assess the model's performance in the detection task. Confusion matrices and Cohen's kappa scores were used for evaluating classification performance. Two radiologists compared diagnostic performance with the trained model using the external validation set. RESULTS: In the detection task, the model achieved accuracies of 86.36% and 85.37% in the internal and external validation sets, respectively. In the DL model, radiologist 1 and radiologist 2 achieved Cohen's kappa scores of 0.8187, 0.7927, and 0.9077 for four-way classification in the external validation set, respectively. The YOLO DL model illustrated a significantly higher accuracy for intermediate bone tumor classification than radiologist 1 (95.73% vs 88.08%, p = 0.004). CONCLUSIONS: The developed YOLO DL model could be used to assist radiologists at all stages of bone lesion detection and classification in full-field bone radiographs. KEY POINTS: • YOLO DL model can automatically detect bone neoplasms from full-field radiographs in one shot and then simultaneously classify radiographs into normal, benign, intermediate, or malignant. • The dataset used in this retrospective study includes normal bone radiographs. • YOLO can detect even some challenging cases with small volumes.

A survey by the European Society of Breast Imaging on radiologists' preferences regarding quality assurance measures of image interpretation in screening and diagnostic mammography.

OBJECTIVES: Quality assurance (QA) of image interpretation plays a key role in screening and diagnostic mammography, maintaining minimum standards and supporting continuous improvement in interpreting images. However, the QA structure across Europe shows considerable variation. The European Society of Breast Imaging (EUSOBI) conducted a survey among the members to collect information on radiologists' preferences regarding QA measures in mammography. MATERIALS AND METHODS: An anonymous online survey consisting of 25 questions was distributed to all EUSOBI members and national breast radiology bodies in Europe. The questions were designed to collect demographic characteristics, information on responders' mammography workload and data about QA measures currently used in their country. Data was analysed using descriptive statistical analysis, the χ2 test, linear regression, and Durbin-Watson statistic test. RESULTS: In total, 251 breast radiologists from 34 countries completed the survey. Most respondents were providing both screening and symptomatic services (137/251, 54.6%), working in an academic hospital (85/251, 33.9%) and reading 1000-4999 cases per year (109/251, 43.4%). More than half of them (133/251, 53%) had established QA measures in their workplace. Although less than one-third (71/251, 28.3%) had to participate in regular performance testing, the vast majority (190/251, 75.7%) agreed that a mandatory test would be helpful to improve their skills. CONCLUSION: QA measures were in place for more than half of the respondents working in screening and diagnostic mammography to evaluate their breast imaging performance. Although there were substantial differences between countries, the importance of having QA in the workplace and implemented was widely acknowledged by radiologists. CLINICAL RELEVANCE STATEMENT: Although several quality assurance (QA) measures of image interpretation are recommended by European bodies or national organisations, the QA in mammography is quite heterogenous between countries and reporting settings, and not always actively implemented across Europe. KEY POINTS: The first survey that presents radiologists' preferences regarding QA measures of image interpretation in mammography. Quality assurance measures in the workplace are better-established for breast screening compared to diagnostic mammography. Radiologists consider that performance tests would help to improve their mammography interpretation skills.

AI support for accurate and fast radiological diagnosis of COVID-19: an international multicenter, multivendor CT study.

OBJECTIVES: Differentiation between COVID-19 and community-acquired pneumonia (CAP) in computed tomography (CT) is a task that can be performed by human radiologists and artificial intelligence (AI). The present study aims to (1) develop an AI algorithm for differentiating COVID-19 from CAP and (2) evaluate its performance. (3) Evaluate the benefit of using the AI result as assistance for radiological diagnosis and the impact on relevant parameters such as accuracy of the diagnosis, diagnostic time, and confidence. METHODS: We included n = 1591 multicenter, multivendor chest CT scans and divided them into AI training and validation datasets to develop an AI algorithm (n = 991 CT scans; n = 462 COVID-19, and n = 529 CAP) from three centers in China. An independent Chinese and German test dataset of n = 600 CT scans from six centers (COVID-19 / CAP; n = 300 each) was used to test the performance of eight blinded radiologists and the AI algorithm. A subtest dataset (180 CT scans; n = 90 each) was used to evaluate the radiologists' performance without and with AI assistance to quantify changes in diagnostic accuracy, reporting time, and diagnostic confidence. RESULTS: The diagnostic accuracy of the AI algorithm in the Chinese-German test dataset was 76.5%. Without AI assistance, the eight radiologists' diagnostic accuracy was 79.1% and increased with AI assistance to 81.5%, going along with significantly shorter decision times and higher confidence scores. CONCLUSION: This large multicenter study demonstrates that AI assistance in CT-based differentiation of COVID-19 and CAP increases radiological performance with higher accuracy and specificity, faster diagnostic time, and improved diagnostic confidence. KEY POINTS: • AI can help radiologists to get higher diagnostic accuracy, make faster decisions, and improve diagnostic confidence. • The China-German multicenter study demonstrates the advantages of a human-machine interaction using AI in clinical radiology for diagnostic differentiation between COVID-19 and CAP in CT scans.

Work expectations, their fulfillment, and exhaustion among radiologists of all career levels: what can be learned from the example of Germany.

OBJECTIVES: To evaluate work expectations of radiologists at different career levels, their fulfillment, prevalence of exhaustion, and exhaustion-associated factors. METHODS: A standardized digital questionnaire was distributed internationally to radiologists of all career levels in the hospital and in ambulatory care via radiological societies and sent manually to 4500 radiologists of the largest German hospitals between December 2020 and April 2021. Statistics were based on age- and gender-adjusted regression analyses of respondents working in Germany (510 out of 594 total respondents). RESULTS: The most frequent expectations were "joy at work" (97%) and a "good working atmosphere" (97%), which were considered fulfilled by at least 78%. The expectation of a "structured residency within the regular time interval" (79%) was more frequently judged fulfilled by senior physicians (83%, odds ratio (OR) 4.31 [95% confidence interval (95% CI) 1.95-9.52]), chief physicians (85%, 6.81 [95% CI 1.91-24.29]), and radiologists outside the hospital (88%, 7.59 [95% CI 2.40-24.03]) than by residents (68%). Exhaustion was most common among residents (physical exhaustion: 38%; emotional exhaustion: 36%), in-hospital specialists (29%; 38%), and senior physicians (30%; 29%). In contrast to paid extra hours, unpaid extra hours were associated with physical exhaustion (5-10 extra hours: OR 2.54 [95% CI 1.54-4.19]). Fewer opportunities to shape the work environment were related to a higher probability of physical (2.03 [95% CI 1.32-3.13]) and emotional (2.15 [95% CI 1.39-3.33]) exhaustion. CONCLUSIONS: While most radiologists enjoy their work, residents wish for more training structure. Ensuring payment of extra hours and employee empowerment may help preventing burnout in high-risk groups. KEY POINTS: • Most important work expectations of radiologists who work in Germany are "joy at work," a "good working atmosphere," "support for further qualification," and a "structured residency within the regular time interval," with the latter containing potential for improvement according to residents. • Physical and emotional exhaustion are common at all career levels except for chief physicians and for radiologists who work outside the hospital in ambulatory care. • Exhaustion as a major burnout criterion is associated with unpaid extra hours and reduced opportunities to shape the work environment.

The uncovered biases and errors in clinical determination of bone age by using deep learning models.

OBJECTIVES: To evaluate AI biases and errors in estimating bone age (BA) by comparing AI and radiologists' clinical determinations of BA. METHODS: We established three deep learning models from a Chinese private dataset (CHNm), an American public dataset (USAm), and a joint dataset combining the above two datasets (JOIm). The test data CHNt (n = 1246) were labeled by ten senior pediatric radiologists. The effects of data site differences, interpretation bias, and interobserver variability on BA assessment were evaluated. The differences between the AI models' and radiologists' clinical determinations of BA (normal, advanced, and delayed BA groups by using the Brush data) were evaluated by the chi-square test and Kappa values. The heatmaps of CHNm-CHNt were generated by using Grad-CAM. RESULTS: We obtained an MAD value of 0.42 years on CHNm-CHNt; this result indicated an appropriate accuracy for the whole group but did not indicate an accurate estimation of individual BA because with a kappa value of 0.714, the agreement between AI and human clinical determinations of BA was significantly different. The features of the heatmaps were not fully consistent with the human vision on the X-ray films. Variable performance in BA estimation by different AI models and the disagreement between AI and radiologists' clinical determinations of BA may be caused by data biases, including patients' sex and age, institutions, and radiologists. CONCLUSIONS: The deep learning models outperform external validation in predicting BA on both internal and joint datasets. However, the biases and errors in the models' clinical determinations of child development should be carefully considered. KEY POINTS: • With a kappa value of 0.714, clinical determinations of bone age by using AI did not accord well with clinical determinations by radiologists. • Several biases, including patients' sex and age, institutions, and radiologists, may cause variable performance by AI bone age models and disagreement between AI and radiologists' clinical determinations of bone age. • AI heatmaps of bone age were not fully consistent with human vision on X-ray films.

Attitudes and perceptions of radiologists towards online (virtual) oncologic multidisciplinary team meetings during the COVID-19 pandemic-a survey of the European Society of Oncologic Imaging (ESOI).

OBJECTIVES: To explore radiologists' opinions regarding the shift from in-person oncologic multidisciplinary team meetings (MDTMs) to online MDTMs. To assess the perceived impact of online MDTMs, and to evaluate clinical and technical aspects of online meetings. METHODS: An online questionnaire including 24 questions was e-mailed to all European Society of Oncologic Imaging (ESOI) members. Questions targeted the structure and efficacy of online MDTMs, including benefits and limitations. RESULTS: A total of 204 radiologists responded to the survey. Responses were evaluated using descriptive statistical analysis. The majority (157/204; 77%) reported a shift to online MDTMs at the start of the pandemic. For the most part, this transition had a positive effect on maintaining and improving attendance. The majority of participants reported that online MDTMs provide the same clinical standard as in-person meetings, and that interdisciplinary discussion and review of imaging data were not hindered. Seventy three of 204 (35.8%) participants favour reverting to in-person MDTs, once safe to do so, while 7/204 (3.4%) prefer a continuation of online MDTMs. The majority (124/204, 60.8%) prefer a combination of physical and online MDTMs. CONCLUSIONS: Online MDTMs are a viable alternative to in-person meetings enabling continued timely high-quality provision of care with maintained coordination between specialties. They were accepted by the majority of surveyed radiologists who also favoured their continuation after the pandemic, preferably in combination with in-person meetings. An awareness of communication issues particular to online meetings is important. Training, improved software, and availability of support are essential to overcome technical and IT difficulties reported by participants. KEY POINTS: • Majority of surveyed radiologists reported shift from in-person to online oncologic MDT meetings during the COVID-19 pandemic. • The shift to online MDTMs was feasible and generally accepted by the radiologists surveyed with the majority reporting that online MDTMs provide the same clinical standard as in-person meetings. • Most would favour the return to in-person MDTMs but would also accept the continued use of online MDTMs following the end of the current pandemic.

Improving personal growth and sustaining mental and physical health of radiologists: essential quotients to embrace.

This special report provides a viewpoint on attaining knowledge of essential traits also known as quotients (Q) that can improve the mental, physical, and spiritual satisfaction and health of radiologists. While intelligence Q is generally above-average for most doctors and radiologists, other Qs needed for wholesome personal growth include emotional Q, spiritual Q, cultural Q, and more importantly, the meaning Q. Self-reflection and embracing such elements can aid in personal development, enhanced mental peace, and improved systems-based practice in the context of integrated healthcare organizations. KEY POINT: • Emotional, spiritual, cultural, and meaning quotients can be embraced by radiologists for better self-development and improved systems-based practice in the context of integrated healthcare organizations.

Abbreviated Versus Full-Protocol MRI for Breast Cancer Neoadjuvant Chemotherapy Response Assessment: Diagnostic Performance by General and Breast Radiologists.

BACKGROUND. Abbreviated protocols could allow wider adoption of MRI in patients undergoing breast cancer neoadjuvant chemotherapy (NAC). However, abbreviated MRI has been explored primarily in screening settings. OBJECTIVE. The purpose of this article was to compare diagnostic performance of abbreviated MRI and full-protocol MRI for evaluation of breast cancer NAC response, stratifying by radiologists' breast imaging expertise. METHODS. This retrospective study included 203 patients with breast cancer (mean age, 52.1 ± 11.2 [SD] years) from two hospitals who underwent MRI before NAC initiation and after NAC completion before surgical resection from March 2017 to April 2021. Abbreviated MRI was extracted from full-protocol MRI and included the axial T2-weighted sequence and precontrast and single early postcontrast T1-weighted sequences. Three general radiologists and three breast radiologists independently interpreted abbreviated and full-protocol MRI in separate sessions, identifying enhancing lesions to indicate residual tumor and measuring lesion size. The reference standard was presence and size of residual tumor on pathologic assessment of post-NAC surgical specimens. RESULTS. A total of 50 of 203 patients had pathologic complete response (pCR). Intraobserver and interobserver agreement for abbreviated and full-protocol MRI for general and breast radiologists ranged from substantial to nearly perfect (κ = 0.70-0.81). Abbreviated MRI compared with full-protocol MRI showed no significant difference for general radiologists in sensitivity (54.7% vs 57.3%, p > .99), specificity (92.8% vs 95.6%, p = .29), or accuracy (83.4% vs 86.2%, p = .30), nor for breast radiologists in sensitivity (60.0% vs 61.3%, p > .99), specificity (94.6% vs 97.4%, p = .22), or accuracy (86.0% vs 88.5%, p = .30). Sensitivity, specificity, and accuracy were not significantly different between protocols for any reader individually (p > .05). Mean difference in residual tumor size on MRI relative to pathology for abbreviated protocol ranged for general radiologists from -0.19 to 0.03 mm and for breast radiologists from -0.15 to -0.05 mm, and for full protocol ranged for general radiologists from 0.57 to 0.65 mm and for breast radiologists from 0.66 to 0.79 mm. CONCLUSION. Abbreviated compared with full-protocol MRI showed similar intraobserver and interobserver agreement and no significant difference in diagnostic performance. Full-protocol MRI but not abbreviated MRI slightly overestimated pathologic tumor sizes. CLINICAL IMPACT. Abbreviated protocols may facilitate use of MRI for post-NAC response assessment by general and breast radiologists.

Work-related musculoskeletal symptoms among Saudi radiologists: a cross-sectional multi-centre study.

BACKGROUND: Musculoskeletal disorders are common health problems worldwide. Several factors cause these symptoms, including ergonomics and other individual considerations. Computer users are prone to repetitive strain injuries that increase the risk of developing musculoskeletal symptoms (MSS). Radiologists are susceptible to developing MSS because they work long hours analysing medical images on computers in an increasingly digitalised field. This study aimed to identify the prevalence of MSS among Saudi radiologists and the associated risk factors. METHODS: This study was a cross-sectional, non-interventional, self-administered online survey. The study was conducted on 814 Saudi radiologists from various regions in Saudi Arabia. The study's outcome was the presence of MSS in any body region that limited participation in routine activities over the previous 12 months. The results were descriptively examined using binary logistic regression analysis to estimate the odds ratio (OR) of participants who had disabling MSS in the previous 12 months. All university, public, and private radiologists received an online survey containing questions about work surroundings, workload (e.g., spent at a computer workstation), and demographic characteristics. RESULTS: The prevalence of MSS among the radiologists was 87.7%. Most of the participants (82%) were younger than 40 years of age. Radiography and computed tomography were the most common imaging modalities that caused MSS (53.4% and 26.8%, respectively). The most common symptoms were neck pain (59.3%) and lower back pain (57.1%). After adjustment, age, years of experience, and part-time employment were significantly associated with increased MSS (OR = .219, 95% CI = .057-.836; OR = .235, 95% CI = 087-.634; and OR = 2.673, 95% CI = 1.434-4.981, respectively). Women were more likely to report MSS than males (OR = 2.12, 95% CI = 1.327-3.377). CONCLUSIONS: MSS are common among Saudi radiologists, with neck pain and lower back pain being the most frequently reported symptoms. Gender, age, years of experience, type of imaging modality, and employment status were the most common associated risk factors for developing MSS. These findings are vital for the development of interventional plans to reduce the prevalence of musculoskeletal complaints in clinical radiologists.

Professional practice and awareness of child abuse among radiologists and radiologic technologists: results from Saudi Arabia.

BACKGROUND: The knowledge, awareness and professionalism of health care providers in the field of child protection are crucial in identifying and reporting suspected child abuse. Radiologic technologists and radiologists play a vital role in the diagnosis of suspected physical child abuse. OBJECTIVE: To assess current practice, knowledge and awareness of child abuse among radiologic technologists and radiologists in Saudi Arabia. MATERIALS AND METHODS: We distributed an internet-based questionnaire to radiologic technologists and radiologists working in Saudi Arabia via national radiology societies and social media channels over a 6-week period (27 October to 8 December 2021). Survey questions covered knowledge regarding child abuse, professional practice in radiology departments in Saudi Arabia in cases of suspected physical abuse (SPA), and knowledge of the national legislation and reporting and acting procedures in child abuse. RESULTS: A total of 315 respondents (224 radiologic technologists and 91 radiologists) participated in this study. The median score for knowledge of abuse was higher amongst radiologists (4.8) than radiologic technologists (4.0); P < 0.001. In total, 210 (93.8%) radiologic technologists and 61 (67.0%) radiologists reported that there was no protocol (i.e. skeletal survey) at their hospital for imaging children with SPA. Most radiologic technologists had no training in paediatric radiology (165/224, 73.7%) and most radiologists had received no training in evaluating imaging performed for SPA (73/91, 80.2%). More than half of respondents - 131 (58.5%) radiologic technologists and 44 (48.4%) radiologists - were not familiar with the reporting and acting procedures at their hospitals in cases of child abuse. CONCLUSION: Although radiologic technologists and radiologists in Saudi Arabia have good knowledge and awareness of child abuse in general, they lack specific knowledge of the reporting and acting procedures at their hospitals in cases of suspected child abuse. National imaging guidelines and training courses are needed to develop appropriate skills in the recognition, imaging and reporting of SPA in infants and young children in Saudi Arabia.

Neonatal neurosonography practices: a survey of active Society for Pediatric Radiology members.

BACKGROUND: While neonatal brain US is emerging as an imaging modality with greater portability, widespread availability and relative lower cost compared to MRI, it is unknown whether US is being maximized in infants to increase sensitivity in detecting intracranial pathology related to common indications such as hemorrhage, ischemia and ventriculomegaly. OBJECTIVE: To survey active members of the Society for Pediatric Radiology (SPR) regarding their utilization of various cranial US techniques and reporting practices in neonates. MATERIALS AND METHODS: We distributed an online 10-question survey to SPR members to assess practice patterns of neonatal cranial US including protocol details, use of additional sonographic views, perceived utility of spectral Doppler evaluation, and germinal matrix hemorrhage and ventricular size reporting preferences. RESULTS: Of the 107 institutions represented, 90% of respondents were split evenly between free-standing children's hospitals and pediatric departments attached to a general hospital. We found that most used template reporting (72/107, 67%). The anterior fontanelle approach was standard practice (107/107, 100%). We found that posterior fontanelle views (72% sometimes, rarely or never) and high-frequency linear probes to evaluate far-field structures (52% sometimes, rarely or never) were seldom used. Results revealed a range of ways to report germinal matrix hemorrhage and measure ventricular indices to assess ventricular dilatation. There was substantial intra-institutional protocol and reporting variability as well. CONCLUSION: Our results demonstrate high variability in neurosonography practice and reporting among active SPR members, aside from the anterior fontanelle views, template reporting and linear high-resolution near-field evaluation. Standardization of reporting germinal matrix hemorrhage and ventricular size would help ensure a more consistent application of neonatal US in research and clinical practice.

Efficient Collaboration Between Radiologists Using the PACS-Integrated Refer Function to Reduce Communication Times.

The purpose of this study was to assess the utility of a picture archiving and communication systems (PACS)-integrated refer function for improving collaboration between radiologists and radiographers during daily reading sessions. Retrospective analysis was conducted on refers sent by radiologists using a PACS-integrated refer system from March 2020 to December 2021. Refers were categorized according to receiver: radiologists in the same division (intra-division), radiologists in a different division (inter-division), and radiographers. The proportions of answered refers, content of refers, and timing of refer posts were evaluated. Additionally, time intervals in minutes from initial refer post to refer response were assessed to assess the efficiency of the refer system and compared according to receivers using the Mann-Whitney U test. Among a total of 691 refers posted by radiologists, 579 (83.8%) were answered directly using the refer function in PACS. Of the answered refers, 346 refers (59.8%) were made between radiologists, and 173 (50%) were intra-division refers. About the content of refers, about 82.6% of radiologists' refers were about imaging interpretation consultation, and about 98.9% of refers from radiologists to radiographers were for image quality control. The median time interval until refer response was 9 min, and this response time did not differ between intra-division and inter-division refers (p = 0.998). Of the refers that got responses, 74.3% (257/346) were sent among radiologists before official reports were made, and the median time until refer response was 9-10 min. The proportion of refers answered by radiographers was 85.7% (233/272). The median time interval until refer response by radiographers was 87 min for all refers, and 63% were made within 6 h. Therefore, the PACS-integrated refer function can facilitate communication between radiologists for image interpretation and quality control.

Are the Pilots Onboard? Equipping Radiologists for Clinical Implementation of AI.

The incorporation of artificial intelligence into radiological clinical workflow is on the verge of being realized. To ensure that these tools are effective, measures must be taken to educate radiologists on tool performance and failure modes. Additionally, radiology systems should be designed to avoid automation bias and the potential decline in radiologist performance. Designed solutions should cater to every level of expertise so that patient care can be enhanced and risks reduced. Ultimately, the radiology community must provide education so that radiologists can learn about algorithms, their inputs and outputs, and potential ways they may fail. This manuscript will present suggestions on how to train radiologists to use these new digital systems, how to detect AI errors, and how to maintain underlying diagnostic competency when the algorithm fails.