Case competition sessions: a global education and academic engagement tool.

BACKGROUND: Radiology virtual teaching sessions utilize live video conferencing to promote collaborative learning and engagement by discussing radiology cases. Because of its convenience and flexibility, this mode of education has gained popularity, particularly after the corona virus disease 2019 pandemic. OBJECTIVE: We describe our experience in organizing a series of "Global Health Imaging Case Competitions" for trainees in low- and middle-income countries (LMICs). These competitions provide the trainees with an opportunity to present unique radiology cases, network with radiologists, learn about various radiology topics, win prizes and potentially publish their case reports in a peer-reviewed journal. MATERIALS AND METHODS: Planning and execution of the competition involves several steps. First, trainees are invited to participate and submit abstracts discussing unique cases. The organizing committee grades these abstracts; the authors of the 20 abstracts with the highest scores are asked to submit a video presentation of their cases to be presented during the live webinar. During this webinar, presentations are displayed and graded to select winners. Additionally, the audience votes to choose a participant as the people's favorite. We have completed four cycles (Africa, Latin America and the Caribbean, Africa and the Middle East and Asia) and will continue in the same order of rotation. RESULTS: Attendance totalled 2,510 participants from 50 countries. Pediatric cases represented the majority of cases among finalists. Feedback was positive; 26 out of 29  (90%) participants surveyed indicated that the webinar was "very good" to "excellent" with well-organized and challenging cases. Diversity of participating countries was noted. Limitations included technology barriers such as internet connectivity. CONCLUSION: This innovative approach emphasizing audience participation engaged trainees from LMICs and fostered locoregional collegiality and mentoring.

MRI scarcity in low- and middle-income countries.

Since the introduction of MRI as a sustainable diagnostic modality, global accessibility to its services has revealed a wide discrepancy between populations-leaving most of the population in LMICs without access to this important imaging modality. Several factors lead to the scarcity of MRI in LMICs; for example, inadequate infrastructure and the absence of a dedicated workforce are key factors in the scarcity observed. RAD-AID has contributed to the advancement of radiology globally by collaborating with our partners to make radiology more accessible for medically underserved communities. However, progress is slow and further investment is needed to ensure improved global access to MRI.

Reduction in Radiologist Interpretation Time of Serial CT and MR Imaging Findings with Deep Learning Identification of Relevant Priors, Series and Finding Locations.

RATIONALE AND OBJECTIVES: Finding comparison to relevant prior studies is a requisite component of the radiology workflow. The purpose of this study was to evaluate the impact of a deep learning tool simplifying this time-consuming task by automatically identifying and displaying the finding in relevant prior studies. MATERIALS AND METHODS: The algorithm pipeline used in this retrospective study, TimeLens (TL), is based on natural language processing and descriptor-based image-matching algorithms. The dataset used for testing comprised 3872 series of 246 radiology examinations from 75 patients (189 CTs, 95 MRIs). To ensure a comprehensive testing, five finding types frequently encountered in radiology practice were included: aortic aneurysm, intracranial aneurysm, kidney lesion, meningioma, and pulmonary nodule. After a standardized training session, nine radiologists from three university hospitals performed two reading sessions on a cloud-based evaluation platform resembling a standard RIS/PACS. The task was to measure the diameter of the finding-of-interest on two or more exams (a most recent and at least one prior exam): first without use of TL, and a second session at an interval of at least 21 days with the use of TL. All user actions were logged for each round, including time needed to measure the finding at all timepoints, number of mouse clicks, and mouse distance traveled. The effect of TL was evaluated in total, per finding type, per reader, per experience (resident vs. board-certified radiologist), and per modality. Mouse movement patterns were analyzed with heatmaps. To assess the effect of habituation to the cases, a third round of readings was performed without TL. RESULTS: Across scenarios, TL reduced the average time needed to assess a finding at all timepoints by 40.1% (107 vs. 65 seconds; p < 0.001). Largest accelerations were demonstrated for assessment of pulmonary nodules (-47.0%; p < 0.001). Less mouse clicks (-17.2%) were needed for finding evaluation with TL, and mouse distance traveled was reduced by 38.0%. Time needed to assess the findings increased from round 2 to round 3 (+27.6%; p < 0.001). Readers were able to measure a given finding in 94.4% of cases on the series initially proposed by TL as most relevant series for comparison. The heatmaps showed consistently simplified mouse movement patterns with TL. CONCLUSION: A deep learning tool significantly reduced both the amount of user interactions with the radiology image viewer and the time needed to assess findings of interest on cross-sectional imaging with relevant prior exams.

Radiology for Thoracic Conditions in Low- and Middle-Income Countries.

With a disproportionately high burden of global morbidity and mortality caused by chronic respiratory diseases (CRDs) in low and middle-income countries (LMICs), access to radiological services is of critical importance for screening, diagnosis, and treatment guidance.

Balancing Patient Autonomy, Surrogate Decision Making, and Physician Non-Maleficence When Considering Do-Not-Resuscitate Orders: An Ethics Case Analysis.

[Full article available at http://rimed.org/rimedicaljournal-2017-10.asp].

Cerebral Epidural Abscess Secondary to Blastomyces Masquerading as an Epidermoid Tumor.

There have been infrequent reports of isolated central nervous system blastomycosis. We report a case of intracranial epidural abscess secondary to Blastomyces dermatitidis in a patient residing in Rhode Island with a history of remote travel to an endemic area. The clinical, radiographic, and pathologic features of this unique case are reviewed.