The Radiology Landscape after COVID-19: Summary of the 2021 AUR Academic Radiology and Industry Leaders Roundtable.

The fifth Association of University Radiologists (AUR) Academic Radiology and Leaders Roundtable took place the day after the conclusion of the AUR annual meeting in May 2021 and involved leaders in academic radiology departments across the United States, and industry from companies who provide quintessential services to radiology departments. The open-ended discussion identified the key challenges facing the practice and business of radiology as we jointly move forward after the COVID-19 pandemic. Particular attention was paid to the identification of viable solutions that radiology departments should embrace to sustain clinical productivity, innovation, and well-being, and the ways that industry could contribute significantly to that endeavor.

Virtual Radiology Readouts After the Coronavirus Disease (COVID-19) Pandemic.

Social distancing concerns arising from the coronavirus disease (COVID-19) pandemic have led to the emergence of virtual readouts in radiology training programs. Given the myriad benefits of virtual readouts, radiology departments should continue using virtual readouts in at least a hybrid format, even after social distancing restrictions become relaxed. This article highlights the challenges and opportunities associated with virtual readouts and provides guidance and strategies for their long-term implementation by training programs.

The Effect of Virtual Interviews and Social Media on Applicant Decision-Making During The 2020-2021 Resident Match Cycle.

RATIONALE AND OBJECTIVES: The COVID-19 pandemic significantly altered the residency application and interview process. Due to social distancing concerns, residency programs have had to virtually showcase their program to applicants, many utilizing social media. Similarly, applicants have had to devise novel ways of assessing "goodness of fit", one of the top factor's applicants use when ranking programs (1). Whether or not these attempts made an impact on an applicant's decision-making process has yet to be determined. MATERIALS AND METHODS: Residency candidates interviewing for a diagnostic and/or interventional radiology residency position at our institution completed an online survey. The goal of the survey was to assess the potential influence of virtual interviews, social media, and virtual events on an applicant's decision to apply to, interview at, and rank residency programs. RESULTS: 78/156 (50%) candidates completed the survey. Thirty-five percent reported applying to more programs and 58% reported accepting more interviews than they would have if interviews were not virtual. Forty-two percent reported that social media played a vital role during the application season and 71% reported using social media to learn more about the program. Sixty-nine percent attended a virtual open house, 57% of whom reported that attending the open house influenced their decision to apply to a program. Sixty-three percent reported that attending a virtual reception influenced a program's ranking. CONCLUSION: Social media has had a growing role in the medical community, and the COVID-19 pandemic likely accelerated an inevitable shift in residency program "branding" and how applicants perceive overall "goodness of fit".

Radiology Education in the Time of COVID-19: A Novel Distance Learning Workstation Experience for Residents.

RATIONALE AND OBJECTIVES: The coronavirus disease of 2019 (COVID-19) pandemic has challenged the educational missions of academic radiology departments nationwide. We describe a novel cloud-based HIPAA compliant and accessible education platform which simulates a live radiology workstation for continued education of first year radiology (R1) residents, with an emphasis on call preparation and peer to peer resident learning. MATERIALS AND METHODS: Three tools were used in our education model: Pacsbin (Orion Medical Technologies, Baltimore, MD, pacsbin.com), Zoom (Zoom Video Communications, San Jose, CA, zoom.us), and Google Classroom (Google, Mountain View, CA, classroom.google.com). A senior radiology resident (R2-R4) (n = 7) driven workflow was established to provide scrollable Digital Imaging and Communications in Medicine (DICOM) based case collections to the R1 residents (n = 9) via Pacsbin. A centralized classroom was created using Google Classroom for assignments, reports, and discussion where attending radiologists could review content for accuracy. Daily case collections over an 8-week period from March to May were reviewed via Zoom video conference readout in small groups consisting of a R2-R4 teacher and R1 residents. Surveys were administered to R1 residents, R2-4 residents, and attending radiologist participants. RESULTS: Hundred percent of R1 residents felt this model improved their confidence and knowledge to take independent call. Seventy-eight percent of the R1 residents (n = 7/9) demonstrated strong interest in continuing the project after pandemic related restrictions are lifted. Based on a Likert "helpfulness" scale of 1-5 with 5 being most helpful, the project earned an overall average rating of 4.9. Two R2-R4 teachers demonstrated increased interest in pursuing academic radiology. CONCLUSION: In response to unique pandemic circumstances, our institution implemented a novel cloud-based distance learning solution to simulate the radiology workstation. This platform helped continue the program's educational mission, offered first year residents increased call preparation, and promoted peer to peer learning. This approach to case-based learning could be used at other institutions to educate residents.

Current Landscape of Imaging and the Potential Role for Artificial Intelligence in the Management of COVID-19.

The clinical management of COVID-19 is challenging. Medical imaging plays a critical role in the early detection, clinical monitoring and outcomes assessment of this disease. Chest x-ray radiography and computed tomography) are the standard imaging modalities used for the structural assessment of the disease status, while functional imaging (namely, positron emission tomography) has had limited application. Artificial intelligence can enhance the predictive power and utilization of these imaging approaches and new approaches focusing on detection, stratification and prognostication are showing encouraging results. We review the current landscape of these imaging modalities and artificial intelligence approaches as applied in COVID-19 management.