The impact of the Covid-19 pandemic on adult diagnostic neuroradiology in Europe

Purpose The purpose of this survey was to understand the impact the Covid-19 pandemic has or has had on the work, training, and wellbeing of professionals in the field of diagnostic neuroradiology. Methods A survey was emailed to all ESNR members and associates as well as distributed via professional social media channels. The survey was held in the summer of 2020 when the first wave had subsided in most of Europe, while the second wave was not yet widespread. The questionnaire featured a total of 46 questions on general demographics, the various phases of the healthcare crisis, and the numbers of Covid-19 patients. Results One hundred sixty-seven responses were received from 48 countries mostly from neuroradiologists (72%). Most commonly taken measures during the crisis phase were reduction of outpatient exams (87%), reduction of number of staff present in the department (83%), reporting from home (62%), and shift work (54%). In the exit phase, these measures were less frequently applied, but reporting from home was still frequent (33%). However, only 22% had access to a fully equipped work station at home. While 81% felt safe at work during the crisis, fewer than 50% had sufficient personal protection equipment for the duration of the entire crisis. Mental wellbeing is an area of concern, with 61% feeling (much) worse than usual. Many followed online courses/congresses and considered these a viable alternative for the future. Conclusion The Covid-19 pandemic substantially affected the professional life as well as personal wellbeing of neuroradiologists.

Diagnostic Neuroradiology Subspecialty Training: 1 Versus 2 Years; the Canadian Perspective

Background: Canada began a national reform of its post-graduate medical education training programs to a Competence By Design (CBD) model. Trends from accredited neuroradiology programs from the past 10 years were investigated to inform educators and stakeholders for this process. Methods: A 13-question electronic survey was sent to program directors of all 8 accredited neuroradiology training programs in Canada. Data was requested for each year on the 2008-2019 graduating classes. Questions pertained to program enrolment; program completion; post-training employment; and the sufficiency of 1-year training programs. Results: Response rate was 100%. Over the timeframe studied, the 2-year programs increased in size ( P = 0.007), while the 1-year programs remained steady ( P = 0.27). 12.2% of trainees enrolled in the 2-year program dropped out after 1 year, and were considered 1-year trainees thereafter. A higher proportion of 2-year trainees obtain positions within academic institutions (89.5 vs 67.2%, P = 0.0007), whereas a higher proportion of 1-year trainees obtain positions within non-academic institutions (29.3 vs 8.1%, P = 0.0007). A higher proportion of those with Canadian board certification in diagnostic radiology who completed a 2-year program obtained a position within a Canadian academic institution compared to non-certified 2-year trainees ( P < 0.001). 71.4% of program directors agreed that a 1-year program was sufficient for non-academic staff positions. Conclusion: The length of the training program has significant impact on employment in academic vs non-academic institutions. This information can be used to guide the upcoming CBD initiative for neuroradiology programs.

Analysis of MRI Data in Diagnostic Neuroradiology

Magnetic resonance imaging (MRI) is a noninvasive imaging tool for neuroradiological diagnosis. Numerous concepts of automated MRI analysis and the use of machine learning have been proposed to assist diagnosis and prognosis. While these academic innovations have proven effective in principle within controlled environments, their application to clinical practice has faced unmet requirements, such as the ability to perform reliably across a heterogeneous population, to work robustly in the presence of comorbidities, and to be invariant to scanner hardware and image quality. The lack of realistic confidence bounds and the inability to handle missing data have also reduced the application of most of these methods outside of academic studies. Mastering the complex challenges in the diagnostic process may help researchers discover novel biological constructs in multimodal data and improve stratification for clinical trials, paving the way for precision medicine. This review presents the state of the art of computerized brain MRI analysis for diagnostic purposes. We critically evaluate the current clinical usefulness of the methods and highlight challenges and future perspectives of the field.