Using language of entrustable professional activities to define learning objectives of radiology clerkship: A modified Delphi study.

Background: A standard undergraduate radiology education is essential to prepare graduates for multidisciplinary clinical practice yet the literature lacks clear guidelines or consensus about the learning objectives of an optimal radiology clerkship.Aim: To define a competency-based framework for undergraduate radiology education by using language of Entrustable Professional Activities (EPAs).Methods: A modified Delphi method with three iterative rounds was used as an expert consensus approach. An online questionnaire with Likert scale was formulated incorporating EPAs and their components (competencies, assessment strategies, and supervision level) and distributed to 45 consultant radiologists following pilot study. Items reaching consensus were accepted and rest were resent in round 2. In round 3, a dichotomous scale was used for final approval and to see response stability.Results: A final set of six EPAs with 87 competencies and respective assessment strategies, all aiming for 'level 3a' of supervision was identified. These include recommending cost effective appropriate imaging tests for common pathologies, obtaining informed consent for diagnostic contrast studies, basic interpretation and communication of common pathologies/emergencies on radiographs (chest, abdominal, and skeletal) and on CT brain.Conclusion: This EPA framework for radiology clerkship is a first step towards a competency-based approach to undergraduate radiology training and assessment.

Chest CT Severity Score as an Auxiliary Grading Tool to COVID-19 Pneumonia Imaging Classification: A Tertiary Care Experience in Pakistan.

OBJECTIVE:   To identify utility of chest computed tomography severity score (CT-SS) as an additional tool to COVID-19 pneumonia imaging classification in assessing severity of COVID-19. STUDY DESIGN: Descriptive analytical study Place and Duration of Study: Armed Forces Institute of Radiology and Imaging, (AFIRI) Rawalpindi, from April 2020 to June 2020. METHODOLOGY: Five hundred suspected COVID-19 cases referred for high resolution computed tomography - chest were included in the study. Cases were categorised by radiological findings using COVID-19 pneumonia imaging classification, proposed in the radiological society of North America expert consensus statement on reporting chest CT findings related to COVID-19. CT-SS was calculated for all scans. Patients were clinically classified according to disease severity as per 'Diagnosis And Treatment Program of Pneumonia of New Coronavirus Infection' recommended by China's National Health Commission. The relationships between radiological findings, CT-SS, and clinical severity were explored. RESULTS: Based on the radiological findings, 298 cases were graded as typical, 34 as indeterminate, 15 as atypical, and 153 as negative for pneumonia. The apical and posterior basal segments of lower lobes were most commonly involved. The CT-SS showed higher values in patients of severe group as compared to those in moderate group (p < 0.05). CT-SS threshold for recognising severe COVID-19 was 18.5 (area under curve, 0.960), with 84.3% sensitivity and 92.5% specificity. CONCLUSION: In coherence with COVID-19 pneumonia imaging classification, CT-SS may provide a comprehensive and objective assessment of COVID-19 severity. Key Words: COVID-19, COVID-19 pneumonia, CT-SS, High resolution computed tomography.