Industry Payments to Radiologists During the Last 5 Years and Impact of COVID-19 Pandemic.

OBJECTIVE: The aim of this study is to assess the trends in industry payments to radiologists and the impact of the COVID-19 pandemic, including trends in different categories of payments. METHODS: The Open Payments Database from CMS was accessed and analyzed for the period from January 1, 2016, to December 31, 2021. Payments were grouped into six categories: consulting fees, education, gifts, research, speaker fees, and royalties or ownership. The total number, value, and types of industry payments to radiologists were subsequently determined and compared pre- and postpandemic from 2016 to 2021. RESULTS: The total number of industry payments and the number of radiologists receiving these payments dropped by 50% and 32%, respectively, between 2019 and 2020, with only partial recovery in 2021. However, the mean payment value and total payment value increased by 177% and 37%, respectively, between 2019 and 2020. Gifts and speaker fees experienced the largest decreases between 2019 and 2020 (54% and 63%, respectively). Research and education grants were also disrupted, with the number of payments decreasing by 37% and 36% and payment value decreasing by 37% and 25%, respectively. However, royalty or ownership increased during the first year of the pandemic (8% for number of payments and 345% for value of payments). CONCLUSIONS: There was significant decline in overall industry payments coinciding with the COVID-19 pandemic, with biggest declines in gifts and speaker fees. The impact on the different categories of payments and recovery in the last 2 years has been heterogeneous.

Machine Learning Models for Classifying High- and Low-Grade Gliomas: A Systematic Review and Quality of Reporting Analysis.

Objectives: To systematically review, assess the reporting quality of, and discuss improvement opportunities for studies describing machine learning (ML) models for glioma grade prediction. Methods: This study followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses of Diagnostic Test Accuracy (PRISMA-DTA) statement. A systematic search was performed in September 2020, and repeated in January 2021, on four databases: Embase, Medline, CENTRAL, and Web of Science Core Collection. Publications were screened in Covidence, and reporting quality was measured against the Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) Statement. Descriptive statistics were calculated using GraphPad Prism 9. Results: The search identified 11,727 candidate articles with 1,135 articles undergoing full text review and 85 included in analysis. 67 (79%) articles were published between 2018-2021. The mean prediction accuracy of the best performing model in each study was 0.89 ± 0.09. The most common algorithm for conventional machine learning studies was Support Vector Machine (mean accuracy: 0.90 ± 0.07) and for deep learning studies was Convolutional Neural Network (mean accuracy: 0.91 ± 0.10). Only one study used both a large training dataset (n>200) and external validation (accuracy: 0.72) for their model. The mean adherence rate to TRIPOD was 44.5% ± 11.1%, with poor reporting adherence for model performance (0%), abstracts (0%), and titles (0%). Conclusions: The application of ML to glioma grade prediction has grown substantially, with ML model studies reporting high predictive accuracies but lacking essential metrics and characteristics for assessing model performance. Several domains, including generalizability and reproducibility, warrant further attention to enable translation into clinical practice. Systematic Review Registration: PROSPERO, identifier CRD42020209938.

Initial Impact of COVID-19 on Radiology Practices: An ACR/RBMA Survey.

PURPOSE: The coronavirus disease 2019 (COVID-19) pandemic affected radiology practices in many ways. The aim of this survey was to estimate declines in imaging volumes and financial impact across different practice settings during April 2020. METHODS: The survey, comprising 48 questions, was conducted among members of the ACR and the Radiology Business Management Association during May 2020. Survey questions focused on practice demographics, volumes, financials, personnel and staff adjustments, and anticipation of recovery. RESULTS: During April 2020, nearly all radiology practices reported substantial (56.4%-63.7%) declines in imaging volumes, with outpatient imaging volumes most severely affected. Mean gross charges declined by 50.1% to 54.8% and collections declined by 46.4% to 53.9%. Percentage reductions did not correlate with practice size. The majority of respondents believed that volumes would recover but not entirely (62%-88%) and anticipated a short-term recovery, with a surge likely in the short term due to postponement of elective imaging (52%-64%). About 16% of respondents reported that radiologists in their practices tested positive for COVID-19. More than half (52.3%) reported that availability of personal protective equipment had become an issue or was inadequate. A majority (62.3%) reported that their practices had existing remote reading or teleradiology capabilities in place before the pandemic, and 22.3% developed such capabilities in response to the pandemic. CONCLUSIONS: Radiology practices across different settings experienced substantial declines in imaging volumes and collections during the initial wave of the COVID-19 pandemic in April 2020. Most are actively engaged in both short- and long-term operational adjustments.

Multisystem Imaging Manifestations of COVID-19, Part 2: From Cardiac Complications to Pediatric Manifestations.

Infection with severe acute respiratory syndrome coronavirus 2 results in coronavirus disease 2019 (COVID-19), which was declared an official pandemic by the World Health Organization on March 11, 2020. COVID-19 has been reported in most countries, and as of August 15, 2020, there have been over 21 million cases of COVID-19 reported worldwide, with over 800 000 COVID-19-associated deaths. Although COVID-19 predominantly affects the respiratory system, it has become apparent that many other organ systems can also be involved. Imaging plays an essential role in the diagnosis of all manifestations of the disease and its related complications, and proper utilization and interpretation of imaging examinations is crucial. A comprehensive understanding of the diagnostic imaging hallmarks, imaging features, multisystem involvement, and evolution of imaging findings is essential for effective patient management and treatment. In part 1 of this article, the authors described the viral pathogenesis, diagnostic imaging hallmarks, and manifestations of the pulmonary and peripheral and central vascular systems of COVID-19. In part 2 of this article, the authors focus on the key imaging features of the varied pathologic manifestations of COVID-19, involving the cardiac, neurologic, abdominal, dermatologic and ocular, and musculoskeletal systems, as well as the pediatric and pregnancy-related manifestations of the virus. Online supplemental material is available for this article. ©RSNA, 2020.

Multisystem Imaging Manifestations of COVID-19, Part 1: Viral Pathogenesis and Pulmonary and Vascular System Complications.

Infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) results in coronavirus disease 2019 (COVID-19), which was declared an official pandemic by the World Health Organization on March 11, 2020. The infection has been reported in most countries around the world. As of August 2020, there have been over 21 million cases of COVID-19 reported worldwide, with over 800 000 COVID-19-associated deaths. It has become apparent that although COVID-19 predominantly affects the respiratory system, many other organ systems can also be involved. Imaging plays an essential role in the diagnosis of all manifestations of the disease, as well as its related complications, and proper utilization and interpretation of imaging examinations is crucial. With the growing global COVID-19 outbreak, a comprehensive understanding of the diagnostic imaging hallmarks, imaging features, multisystemic involvement, and evolution of imaging findings is essential for effective patient management and treatment. To date, only a few articles have been published that comprehensively describe the multisystemic imaging manifestations of COVID-19. The authors provide an inclusive system-by-system image-based review of this life-threatening and rapidly spreading infection. In part 1 of this article, the authors discuss general aspects of the disease, with an emphasis on virology, the pathophysiology of the virus, and clinical presentation of the disease. The key imaging features of the varied pathologic manifestations of this infection that involve the pulmonary and peripheral and central vascular systems are also described. Part 2 will focus on key imaging features of COVID-19 that involve the cardiac, neurologic, abdominal, dermatologic and ocular, and musculoskeletal systems, as well as pediatric and pregnancy-related manifestations of the virus. Vascular complications pertinent to each system will be also be discussed in part 2. Online supplemental material is available for this article. ©RSNA, 2020.