Subspecialty Of Radiology Research Articles

Gender Distribution of Faculty Is Strongly Correlated With Resident Gender at Canadian Radiology Residency Programs

Objective: Women are underrepresented in radiology overall, in radiology subspecialties, and in radiology leadership and academic positions. It is unclear why this disparity persists despite greater gender diversification in medicine. We sought to determine if a correlation exists between the proportion of female faculty at an institution, and the proportion of female residents in the associated residency program across Canada. Methods: Faculty gender for each Canadian Diagnostic Imaging Residency Program was obtained through publicly available sources (departmental websites and provincial physician registries) in the fall of 2020. Resident gender data was obtained through a survey emailed to programs following the April 2021 CaRMS match. Data was analyzed using Pearson's correlation coefficient. Research ethics approval was obtained. Results: Faculty information was available for 15 of the 16 Canadian radiology residency programs (94%) and resident information was obtained for 16 programs (100% response rate). Overall, women accounted for 31.4% of radiologist faculty and 31.9% of radiology residents, with a wide range between institutions (19.5-47.8% for faculty and 13.3%-47.1% for residents). There was a strong positive correlation between the proportion of female faculty and the proportion of female residents within individual programs (r=0.73; R2=0.54; p=0.002). Conclusion: Approximately one third of faculty and residents at Canadian Diagnostic Radiology residency programs were female but there was a wide range across the country with a strong correlation between faculty and resident gender distribution. Further exploration is warranted to determine causes of this correlation including the possible influence of role modeling, mentoring, female-friendly culture, and bias.

Retrospective Analysis of Gender Disparity in Radiology Subspecialty Training: A Decade of Little Progress

Retrospective Analysis of Gender Disparity in Radiology Subspecialty Training: A Decade of Little Progress

Performance of an algorithm for diagnosing acute cholecystitis using clinical and sonographic parameters.

Identify an algorithm using clinical and ultrasound (US) parameters with high diagnostic performance for acute cholecystitis. Consecutive emergency department (ED) patients from 4/1/2019 to 12/31/2019 were retrospectively reviewed to record non-US parameters and make US observations. Outcomes were categorized as either: (1) acute cholecystitis; or (2) negative acute cholecystitis. Pivot tables identified parameter combinations either not found with acute cholecystitis or with predictive value for acute cholecystitis to establish the algorithm. US Division radiologists finalized an US report prior to ED disposition without use of the algorithm. Radiologist impression and algorithm prediction for acute cholecystitis were categorized as either (1) acute cholecystitis; (2) negative acute cholecystitis; or (3) inconclusive. Three hundred and sixty-six studies on 357 patients (mean age, 51 yrs ± 20 yrs; 215 women) met the inclusion criteria. 10.9% (40/366) of US studies had acute cholecystitis, 12.6% (46/366) had pathologically identified chronic cholecystitis without acute cholecystitis, and 76.5% (280/366) were negative acute cholecystitis. Algorithm compared to radiologist diagnostic performance was as follows: (1) sensitivity: 90.0% vs. 55.0%, p < 0.001; (2) augmented sensitivity (defined as when inconclusive categorization is considered consistent with acute cholecystitis): 100% vs. 85.0%, p < 0.001; (3) specificity: 93.6% vs. 94.8%, p = 0.50; (4) diagnostic rate (opposite of inconclusive rate): 96.4% vs. 93.2%, p = 0.04; (5) adverse outcome rate: 0.0% vs. 1.6%, p undefined. For acute cholecystitis, an algorithm using non-binary ultrasound and clinical assessments had higher sensitivity, higher diagnostic rate, and fewer adverse outcomes, than subspecialty radiologist impressions.

Biomodeling and 3D printing: A novel radiology subspecialty

3D biomodels are a new kind of medical image that enables easier interpretation of medical imaging findings, virtual surgical planning and 3D printing of anatomical biomodels and personalized surgical tools. New applications emerge every week in all surgical specialties for diagnostic, treatment and educational purposes. High performance software is available for biomodeling but it still requires human supervision to ensure biomodel fidelity with patient anatomy. Radiology technologists, bioengineers or other health care providers may have sufficient training to provide accurate segmentation in most cases. However, radiologists should be involved to add their expertise in medicine and medical imaging since there is a great deal of medical professional responsibility involved in the biomodeling and virtual planning process. The aim of this work is to review the key role of radiologists in the usual workflow of patients that require 3D technologies for diagnostic and treatment purposes in ensuring safe practices. Imaging requirements and a short description of the biomodeling process necessary to achieve high quality 3D biomodels is presented. General applications and the main difficulties for implementation of 3D technologies are reviewed.

One Hundred Years of the Pathology Medical Student Fellowship.

The Pathology Medical Student Fellowship (PSF) is a unique, year-long immersive educational experience. Review of institutional archives describes a medical student "Fellowship in Pathology" founded in 1919. To characterize the impacts of this 100-year-old program. We determined the subsequent medical specialty of each PSF graduate in our department and surveyed those with available contact information. Of 145 pathology student fellows graduating between 1924 and 2020, a total of 50 (34.4%) matched into pathology; medical, surgical, and radiology subspecialties were also well-represented career choices. Between 2001 and 2020, of 36 students who matched into pathology from our institution, 19 (52.8%) had completed the fellowship. Survey respondents (n = 42) indicated that before the PSF, 11 of 42 students (26.2 %) were undecided in their specialty, with only 6 (14.3%) identifying pathology as their primary field of interest. Of survey respondents who had completed training, 26 (61.9%) practice in academic settings. Nonpathology physicians reported frequent utilization of skills gained during the PSF year, with 5 of 23 (21.7%) responding "daily," and 9 (39.1%) responding "weekly." The most useful skills included knowledge of pathophysiology of disease and anatomy, improved communication with multidisciplinary teams, and/or interpretation of pathology results (each selected by 17 to 20 students, 73.9%-87.0%). Free-text responses on impacts of the PSF described enhanced knowledge of disease pathobiology and diagnostic complexity and increased confidence and autonomy. We describe the program structure, educational benefits, graduate specialty choices, and career impacts of 100 years of the PSF at our institution. Although undecided before pathology exposure, many PSF graduates subsequently enter pathology careers. Regardless of specialty choice, PSF graduates have a high rate of subsequently pursuing academic medical careers.

Use of a PACS Embedded System for Communicating Radiologist to Technologist Learning Opportunities and Patient Callbacks

ObjectiveThis study aimed to determine effect of modality, care setting, and radiology subspecialty on frequency of diagnostic image quality issues identified by radiologists during image interpretation. MethodsThis Institutional Review Board-exempt retrospective study was performed 10/1/18-6/30/20 at an academic radiology practice performing 700,000+ examinations annually. A closed-loop communication tool integrated in PACS workflow enabled radiologists to alert technologists to image quality issues. Radiologists categorized communications as requiring patient callback, or as technologist learning opportunities if image quality was adequate to generate a diagnostic report. Fisher's exact test assessed impact of imaging modality, radiology subspecialty, and care setting on radiologist-identified image quality issues. Results976,915 imaging examinations were performed during the study period. Radiologists generated 1,935 technologist learning opportunities (0.20%) and 208 callbacks (0.02%). Learning opportunity rates were highest for MRI (0.60%) when compared to CT (0.26%) and radiography (0.08%) (p<0.0001). The same was true for patient callbacks (MRI 0.13%, CT 0.02%, radiography 0.0006%; p<0.0001). Outpatient examinations generated more learning opportunities (1479/637,092; 0.23%) vs. inpatient (305/200,206; 0.15%) and Emergency Department (151/139,617; 0.11%) (p<0.0001). Abdominal subspecialists were most likely to generate learning opportunities when compared to other subspecialists and cardiovascular imagers were most likely to call a patient back. ConclusionsImage quality issues identified by radiologists during the interpretation process were rare and 10 times more commonly categorized as learning opportunities not interfering with a clinically adequate report than as requiring patient callback. Further work is necessary to determine if creating learning opportunities leads to fewer patients requiring repeat examinations.

The development of musculoskeletal radiology for 100 years as presented in the pages of Acta Radiologica.

During the last 100 years, musculoskeletal radiology has developed from bone-only radiography performed by everyone to a dedicated subspecialty, still secure in its origins in radiography but having expanded into all modalities of imaging. Like other subspecialties in radiology, it has become heavily dependent on cross-sectional and functional imaging, and musculoskeletal interventions play an important role in tumor diagnosis and treatment and in joint diseases. All these developments are reflected in the pages in Acta Radiologica, as shown in this review.

Diagnostic performance of US for suspected appendicitis: Does multi-categorical reporting provide better estimates of disease in adults, and what factors are associated with false or indeterminate results?

PurposeTo identify factors associated with false or indeterminate US result for suspected appendicitis, and assess whether multi-categorical reporting of US yields more precise estimates regarding the probability of appendicitis. Methods562 US examinations for suspected appendicitis between May 2013-April 2015 were categorized as true (77/562 true positives or true negatives) or false/indeterminate (485/562 false negatives, false positives or indeterminates) based on results from a prior study. Of 541 examinations with images available retrospectively, a category of A–E was assigned as follows: non-visualized appendix with secondary findings (A) absent or (B) present; appendix visualized and considered (C) negative, (D) equivocal, or (E) positive for appendicitis. The following factors were recorded: age; sex; scan time (daytime vs. off-hours); resident/fellow involvement; abdominal subspecialty radiologist; radiologist experience (>5 years or not); and tenderness on interrogation. Associations between factors and US result were assessed (t-tests, Fisher’s exact test and multivariate logistic regression). ResultsThe true group had proportionally more males (18/77 (23.4%) vs. 66/485 (13.6%), p = 0.04) and patients with sonographic tenderness (43/77 (55.8%) vs. 132/353 (27.3%), p < 0.0001). There was no significant difference or association with other factors. On multivariate logistic regression, false/indeterminate results were 1.9 times (95% CIs 1.0–3.5) more likely among females and 3.8 times more likely in the absence of tenderness (95% CIs 2.3–6.4). The proportion of patients with appendicitis in categories A-E was 34/410 (8.3%), 24/44 (54.5%), 0/18 (0%), 0/3 (0%) and 61/66 (92.4%), respectively. ConclusionsFemales and absence of tenderness were associated with a false/indeterminate US. Categorical reporting provides more granular estimates of the post-test probability of appendicitis.

Value of second opinion subspecialty radiology consultation in suspected abdominal medium vessel vasculitis

To perform a descriptive analysis of individuals with suspected Polyarteritis nodosa (PAN) referred for second opinion imaging consultation. A retrospective observational cohort study was performed at a single institution. A consecutive sample was performed of individuals who underwent a second opinion CT or MR angiography subspecialty radiologist consultation between January 2008 and September 2019 for suspected abdominal medium vessel vasculitis. Demographic, clinical, and imaging data were collected. Clinical and imaging findings were reported for PAN, small vessel vasculitis, and "non-vasculitis" groups. Agreement and diagnostic accuracy between final clinical and second opinion imaging diagnoses for PAN were determined. Two-tailed t-tests with a significant p-value < 0.05 were utilized. Of the 58 participants, 9 were clinically diagnosed with PAN, 11 with small vessel vasculitis (including lupus, IgA, and ANCA-associated vasculitis), and 38 with non-vasculitis diagnoses. The non-vasculitis group included 15 SAM, 3 FMD, and 1 SAM-FMD spectrum diagnoses. Higher C-reactive protein level (51 vs 17, p = 0.04) and superior mesenteric artery involvement (56% vs 21%, p = 0.04) were more common in PAN than non-vasculitis diagnoses, while arterial dissection (40% vs 0%, p = 0.02) and celiac vasculature involvement (53% vs 0%, p = 0.003) were more common in the non-vasculitis group. There was 88% agreement (51/58; Cohen's kappa 0.56); sensitivity was 67% [95%-confidence interval (CI) 30-93%] and specificity was 92% (95%-CI 80-98%). Isolated celiac artery involvement and arterial dissection were more common in non-inflammatory vasculopathies than PAN. Our findings highlight the need for multidisciplinary collaboration and awareness of the diverse findings of abdominal vasculopathies.

Past, present, and future of abdominal radiology fellowship recruitment.

The authors provide a commentary on the current status of the Abdominal Radiology Fellowship recruitment process, which is not presently governed by a formal Match. Abdominal Radiology is the largest radiology subspecialty fellowship that remains outside of the Match. The Society of Abdominal Radiology convened a task force in 2019 to assess stakeholder viewpoints on a Match and found that the community was divided. Radiology departments and Abdominal Radiology fellowship program directors have voluntarily complied with a series of guidelines laid out by the Society of Chairs in Academic Radiology Departments during the two most recent recruiting cycles, but challenges in the process persist. Stakeholders report improved organization and fairness as a result of these procedural changes, and the authors suggest that Abdominal Radiology may continue to consider a formal fellowship Match in coming years.

Quantitative dual-energy CT techniques in the abdomen.

Advances in dual-energy CT (DECT) technology and spectral techniques are catalyzing the widespread implementation of this technology across multiple radiology subspecialties. The inclusion of energy- and material-specific datasets has ushered overall improvements in CT image contrast and noise as well as artifacts reduction, leading to considerable progress in radiologists' ability to detect and characterize pathologies in the abdomen. The scope of this article is to provide an overview of various quantitative clinical DECT applications in the abdomen and pelvis. Several of the reviewed applications have not reached mainstream clinical use and are considered investigational. Nonetheless awareness of such applications is critical to having a fully comprehensive knowledge base to DECT and fostering future clinical implementation.

Standardized Classification of Lumbar Spine Degeneration on Magnetic Resonance Imaging Reduces Intra- and Inter-subspecialty Variability

Background and PurposeTo determine the efficacy of standardized definitions of degenerative change in reducing variability in interpretation of lumbar spine magnetic resonance imaging within and between groups of subspecialty-trained neuroradiologists (NR) and musculoskeletal radiologists (MSK). Materials and MethodsSix radiologists, three from both NR and MSK groups were trained on a standardized classification system of degenerative change. After an 11-month washout period, they independently re-interpreted fifty exams at the L4-L5 and L5-S1 levels. Responses were converted to a six-point ordinal scale for the assessment of neural foraminal stenosis and spinal canal stenosis (SCS), three-point scale for lateral recess stenosis, and four-point scale for facet osteoarthritis (FO). Intra-subspecialty and inter-subspecialty analysis was performed using the weighted Cohen's kappa with a binary matrix of all reader pairs. ResultsInter-subspecialty agreement improved from k=0.527 (moderate) to k=0.602 (substantial) for neural foraminal stenosis, from k=0.540 (moderate) to k=0.652 (substantial) for SCS, from k=0.0818 (slight) to k=0.337 (fair) for lateral recess stenosis, and from k=0.176 (slight) to k=0.495 (moderate) for FO. The NR group demonstrated improved intra-subspecialty agreement for the assessment of SCS, from k=0.368 (fair) to k=0.638 (substantial). The MSK group demonstrated improved intra-subspecialty agreement for the assessment of FO, from k=0.134 (slight) to k=0.413 (moderate). Intra-subspecialty agreement was similar for other parameters before and after training. ConclusionsAs result of the standardized definitions training, the NR and MSK groups each improved in one of the four parameters, while inter-subspecialty variability improved in all four parameters. These definitions may be useful in clinical practice across radiology subspecialties.

Sarcopenia is a predictor of chemotherapy response score at the time of interval debulking surgery in advanced epithelial ovarian carcinoma

<h3>Objectives:</h3> To examine the relationship between sarcopenia as measured by skeletal muscle index (SMI) on CT and chemotherapy outcomes and pathologic response after neoadjuvant chemotherapy (NACT) in patients with advanced epithelial ovarian carcinoma (EOC). <h3>Methods:</h3> Our institutional database was retrospectively queried for all women with advanced EOC who underwent NACT between 2007-2020. Demographic and clinical variables including number of NACT cycles, dose reductions, and dose delays were collected. Treatment response by 3-tier pathologic chemotherapy response score (CRS) and residual disease at time of interval cytoreductive surgery were recorded. Pre-treatment and post-treatment contrast enhanced CT scans were reviewed by two subspecialty radiologists to determine baseline and post-treatment SMI. SMI was calculated by dividing total psoas muscle and paraspinal muscle area (m²) (measured at the level of L4 vertebrae by height (cm²) squared. Patients were stratified to account for change in SMI after NACT and grouped into patients with >2% decrease in SMI (group 1) and increase or ≤2% decrease in SMI (group 2). SMI was also analyzed as a continuous variable for association with demographic and clinical factors by Kruskal-Wallis test/Spearman's correlation (results summarized as median [25th, 75th percentiles]). <h3>Results:</h3> Among 77 patients who met inclusion criteria, there were no significant differences between stage at diagnosis, baseline performance status, frailty scores, number of NACT cycles, histology, or tumor grade between the two groups. However, pretreatment Ca125 was higher in patients in group 2 (p=0.031). When SMI was analyzed as a continuous variable, age at diagnosis was negatively associated with higher SMI (-0.47, (-0.63, -0.28, p=<0.001). Number of completed NACT cycles was negatively associated with higher SMI -0.23 (-0.43, -0.0, p=0.048). Lower CRS, indicating no/minimal chemotherapy response at the time of interval cytoreduction was associated with lower SMI (0.45, (0.01, 0.75), p=0.043) despite no difference in residual disease. <h3>Conclusions:</h3> Sarcopenia as measured by SMI is associated with older age and increased number of NACT cycles in our patient population. Additionally, sarcopenia was predictive of lower chemotherapy response at the time of interval cytoreduction. Data collection is ongoing to further delineate the relationship between sarcopenia and response to NACT.

Sarcopenia is associated with higher surgical complexity in patients undergoing interval cytoreduction for advanced epithelial ovarian carcinoma

Objectives: Loss of skeletal muscle mass (sarcopenia) has been correlated with adverse postoperative outcomes after primary cytoreduction in patients with epithelial ovarian carcinoma (EOC). We investigated the association between sarcopenia as measured by skeletal muscle index (SMI) prior to and after neoadjuvant chemotherapy (NACT) and post-operative outcomes following interval cytoreduction for EOC. Methods: Patients undergoing NACT for EOC between 2007-2020 were identified through our institutional database. A retrospective review was performed to identify cancer-specific, preoperative, surgical, and post-operative variables. Pretreatment and post-treatment contrast-enhanced CT scans were reviewed by two subspecialty radiologists to determine skeletal muscle index (SMI). SMI was calculated by dividing total psoas and paraspinal muscle area (m2) (measured at the level of L4 vertebrae) by height squared (cm2). Patients were grouped based on SMI into Group 1) patients with >2% decrease in SMI, and Group 2) patients with an increase or less than or equal to 2% decrease in SMI after NACT. SMI was also analyzed as a continuous variable for association with demographic and clinical factors by Kruskal-Wallis test/Spearman's correlation (results summarized as median [25th, 75th percentiles]). Results: A total of 77 patients met the inclusion criteria. Baseline demographic characteristics were consistent between group 1 and 2 patients. Baseline CA125 was significantly higher in group 2 patients (increase or less than or equal to 2% decrease in SMI) (p=0.031). However, change in SMI was not significantly associated with surgical or postoperative outcomes. When analyzed as a continuous variable, SMI was correlated with higher surgical complexity score (SCS); patients with low SCS had a median SMI of 20.7 m2/cm2 vs 23.6 and 23.8 m2/cm2 for intermediate and high SCS, respectively (p=0.01). Length of surgery was also positively correlated with SMI (0.29, (0.05, 0.51), p=0.021) (Table 1). There was no association between SMI and readmission rates, length of hospital stay, postoperative complications, or non-home discharge. Download : Download high-res image (135KB) Download : Download full-size image Conclusions: Higher SMI is predictive of longer operative time and higher SCS in patients undergoing interval debulking, but was not predictive of postoperative outcomes, complications, length of stay, or non-home discharge in this study. These data suggest that SMI may be a surrogate for extent of interval surgical debulking. A larger population of NACT patients is being evaluated to determine more robust correlations in postoperative outcomes.

Role of 3D Printing and Modeling to Aid in Neuroradiology Education for Medical Trainees.

Applications of 3-dimensional (3D) printing in medical imaging and health care are expanding. Currently, primary uses involve presurgical planning and patient and medical trainee education. Neuroradiology is a complex subdiscipline of radiology that requires further training beyond radiology residency. This review seeks to explore the clinical value of 3D printing and modeling specifically in enhancing neuroradiology education for radiology physician residents and medical trainees. A brief review summarizing the key steps from radiologic image to 3D printed model is provided, including storage of computed tomography and magnetic resonance imaging data as digital imaging and communications in medicine files; conversion to standard tessellation language (STL) format; manipulation of STL files in interactive medical image control system software (Materialise) to create 3D models; and 3D printing using various resins via a Formlabs 2 printer. For the purposes of demonstration and proof of concept, neuroanatomy models deemed crucial in early radiology education were created via open-source hardware designs under free or open licenses. 3D-printed objects included a sphenoid bone, cerebellum, skull base, middle ear labyrinth and ossicles, mandible, circle of Willis, carotid aneurysm, and lumbar spine using a combination of clear, white, and elastic resins. Based on this single-institution experience, 3D-printed complex neuroanatomical structures seem feasible and may enhance resident education and patient safety. These same steps and principles may be applied to other subspecialties of radiology. Artificial intelligence also has the potential to advance the 3D process.

The current and future roles of artificial intelligence in pediatric radiology.

Artificial intelligence (AI) is a broad and complicated concept that has begun to affect many areas of medicine, perhaps none so much as radiology. While pediatric radiology has been less affected than other radiology subspecialties, there are some well-developed and some nascent applications within the field. This review focuses on the use of AI within pediatric radiology for image interpretation, with descriptive summaries of the literature to date. We highlight common features that enable successful application of the technology, along with some of the limitations that can inhibit the development of this field. We present some ideas for further research in this area and challenges that must be overcome, with an understanding that technology often advances in unpredictable ways.

Do oncologists prefer subspecialty radiology reports? A quality care study

BackgroundThe main objective was to assess whether CT reports of radiologists subspecialized in oncologic imaging respond better to oncological referrals than reports from general radiologists. The secondary objective was to assess differences in ratings between a senior and junior oncologist. Two hundred radiological reports pertaining to oncological patients were retrospectively selected of which 100 each were written by subspecialized radiologists and general radiologists, respectively. The senior and junior oncologists each rated all CT reports using a Likert scale from 1 to 5 (1 = very poor, 5 = excellent) for the following information: anatomical details; interpretation of findings; need for further explanations; appropriateness of conclusions; overall satisfaction. Comparisons between ratings assigned to reports from generalist radiologists and subspecialty radiologists were performed using the Mann–Whitney U test. Agreement between both oncologists was assessed through Gwet's coefficient.ResultsFor all but two of the five items obtained from the senior oncologist, oncologists' ratings were significantly higher for subspecialty radiologists' reports (p < 0.01); mean values from both oncologists were generally higher for subspecialty reports (p < 0.001). Agreement between the senior and junior oncologist in the rating of reports from general and subspecialty radiologists was either moderate to substantial (0.5986–0.6788) or substantial to almost perfect (0.6958–0.8358).ConclusionsAccording to a senior and junior oncologist, CT reports performed by subspecialized radiologists in oncologic imaging are clearer, more accurate, and more appropriate in the interpretation and conclusions compared to reports written by general radiologists. Likewise, the overall satisfaction of the oncologist from a subspecialized radiologist report is higher.

Utilization of 3-T fetal magnetic resonance imaging in clinical practice: a single-institution experience.

As the safety and efficacy of fetal magnetic resonance imaging (MRI) at 3 tesla (T) continues to evolve, understanding its potential benefits and limitations is becoming increasingly important. We aim to compare the image quality of fetal MRI between 1.5T and 3T in routine clinical practice. Fetal MRIs performed at 3T between Jan. 1, 2019, and Dec. 31, 2019, at our institution were retrospectively reviewed by four fellowship-trained subspecialty radiologists. Imaging quality by system, sequence and artifacts were compared with matched controls at 1.5T and rated using a modified Likert scale. Thirty-three fetal MRIs at 3T were reviewed, and a control group of studies for the same clinical indication and equivalent gestational age were selected for comparison. Two of the four radiologists preferred 3-T image quality of the brain with slight agreement among the four reviewers (k=0.19, P=0.01). Three of the four radiologists had no preference for 1.5T vs. 3T in the majority of cases in evaluating the chest and abdomen. In the overall assessment, 3T was preferred in less than half of cases by all four radiologists (k=0.07, P=0.26). In the evaluation of standing wave, moire fringe and magnetic susceptibility artifacts, 3T was not preferred in the majority of studies by all four radiologists. Total exam time was significantly longer in the 3-T fetal MRIs (75.0±15.1min) compared to the 1.5-T fetal MRIs (55.5±13.3min, P<0.001). While 3T is a feasible alternative to 1.5T for fetal MRI, the increased artifacts and longer exam times observed at 3T without clear improvement in overall image quality make 1.5T preferable for fetal MRI in routine clinical practice.

Canadian Association of Radiologists Recommendations for the Safe Use of MRI During Pregnancy

The use of magnetic resonance imaging (MRI) during pregnancy is associated with concerns among patients and health professionals with regards to fetal safety. In this work, the Canadian Association of Radiologists (CAR) Working Group on MRI in Pregnancy presents recommendations for the use of MRI in pregnancy, derived from literature review as well as expert panel opinions and discussions. The working group, which consists of academic subspecialty radiologists and obstetrician-gynaecologists, aimed to provide updated, evidence-based recommendations addressing safety domains related to energy deposition, acoustic noise, and gadolinium-based contrast agent use based on magnetic field strength (1.5T and 3T) and trimester scanned, in addition to the effects of sedative use and occupational exposure.

An international survey on AI in radiology in 1041 radiologists and radiology residents part 2: expectations, hurdles to implementation, and education

ObjectivesCurrently, hurdles to implementation of artificial intelligence (AI) in radiology are a much-debated topic but have not been investigated in the community at large. Also, controversy exists if and to what extent AI should be incorporated into radiology residency programs.MethodsBetween April and July 2019, an international survey took place on AI regarding its impact on the profession and training. The survey was accessible for radiologists and residents and distributed through several radiological societies. Relationships of independent variables with opinions, hurdles, and education were assessed using multivariable logistic regression.ResultsThe survey was completed by 1041 respondents from 54 countries. A majority (n = 855, 82%) expects that AI will cause a change to the radiology field within 10 years. Most frequently, expected roles of AI in clinical practice were second reader (n = 829, 78%) and work-flow optimization (n = 802, 77%). Ethical and legal issues (n = 630, 62%) and lack of knowledge (n = 584, 57%) were mentioned most often as hurdles to implementation. Expert respondents added lack of labelled images and generalizability issues. A majority (n = 819, 79%) indicated that AI should be incorporated in residency programs, while less support for imaging informatics and AI as a subspecialty was found (n = 241, 23%).ConclusionsBroad community demand exists for incorporation of AI into residency programs. Based on the results of the current study, integration of AI education seems advisable for radiology residents, including issues related to data management, ethics, and legislation.Key Points• There is broad demand from the radiological community to incorporate AI into residency programs, but there is less support to recognize imaging informatics as a radiological subspecialty.• Ethical and legal issues and lack of knowledge are recognized as major bottlenecks for AI implementation by the radiological community, while the shortage in labeled data and IT-infrastructure issues are less often recognized as hurdles.• Integrating AI education in radiology curricula including technical aspects of data management, risk of bias, and ethical and legal issues may aid successful integration of AI into diagnostic radiology.