The coronavirus disease 2019 (COVID-19) pandemic is a global health care emergency. Although reverse-transcription polymerase chain reaction testing is the reference standard method to identify patients with COVID-19 infection, chest radiography and CT play a vital role in the detection and management of these patients. Prediction models for COVID-19 imaging are rapidly being developed to support medical decision making. However, inadequate availability of a diverse annotated data set has limited the performance and generalizability of existing models. To address this unmet need, the RSNA and Society of Thoracic Radiology collaborated to develop the RSNA International COVID-19 Open Radiology Database (RICORD). This database is the first multi-institutional, multinational, expert-annotated COVID-19 imaging data set. It is made freely available to the machine learning community as a research and educational resource for COVID-19 chest imaging. Pixel-level volumetric segmentation with clinical annotations was performed by thoracic radiology subspecialists for all COVID-19–positive thoracic CT scans. The labeling schema was coordinated with other international consensus panels and COVID-19 data annotation efforts, the European Society of Medical Imaging Informatics, the American College of Radiology, and the American Association of Physicists in Medicine. Study-level COVID-19 classification labels for chest radiographs were annotated by three radiologists, with majority vote adjudication by board-certified radiologists. RICORD consists of 240 thoracic CT scans and 1000 chest radiographs contributed from four international sites. It is anticipated that RICORD will ideally lead to prediction models that can demonstrate sustained performance across populations and health care systems. © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Bai and Thomasian in this issue.

Objective to investigate the relationships between self-reported cognitive abilities, psychological symptoms and neuropsychological outcomes in PSS. Methods PSS patients and healthy controls completed a comprehensive neuropsychometric battery and questionnaires: the Centers for Epidemiological Scale-Depression, the Profile of Fatigue- mental domain (Prof-M) for cognitive symptoms, Fatigue Severity Scale and the Short-Form McGill Pain Questionnaire. Results Female PSS patients (N=39) were similar to controls (N=17) in estimated pre-morbid intellectual function, age and education. Depression (p=.002), cognitive symptoms (p=.001), fatigue (p=.000003) and pain (p=.024) scores were greater in the patient group. PSS patients demonstrated inferior performance relative to controls in psychomotor processing (p=.027) and verbal reasoning (p=.007). PSS patients with and without depression had similar performance on multiple tests, but depressed patients had significantly lower scores for executive function (p=.041). Cognitive symptoms correlated with verbal memory (p=.048), whereas pain correlated with executive function measures (Stroop, p=.017) and working memory (Trails B, p=.036). In the regression model, depression and verbal memory were independent predictors that accounted for 61 % of the variance in cognitive symptoms. Conclusion The Prof-M is a simple self-report measure which could be useful in screening PSS subjects who may benefit from detailed psychometric evaluation. Our results are consistent with the hypothesis that depression and verbal memory impairment are overlapping but independent aspects of neural involvement in PSS. While pain and depression are significant confounders of cognitive function in PSS, this study suggests that impaired verbal reasoning ability in PSS is not attributable to pain or depression.

Objectives To compare clinical characteristics and patient-reported outcomes in seropositive versus seronegative primary Sjogren’s syndrome patients (pSS) and to investigate the effect of serological status on the prevalence of chronic pain, comorbidity and health quality. Methods Pain severity and neuropathic pain symptoms, comorbidity and health status were assessed in 108 pSS patients. Differences between patient groups were assessed by t-test and chi-square tests and adjusted pain-affect associations. The effect of predictor variables on pain severity was examined with multivariate regression. Results Pain severity was greater (p=.003) and physical function (p=.023) reduced in the seronegative patients. Prevalence of neuropathic pain, depression, anxiety and disability were similar between groups. Chronic pain, defined as daily pain for greater than 3 months, was reported by 65% of seropositive (N=65) and 75% of seronegative patients (N=40). After adjustment for age, sleep quality and psychological distress, the difference in pain severity between seropositive and seronegative patients remained significant. Conclusion Chronic pain is pervasive in both seropositive and seronegative pSS patients, while pain severity and functional impairment is greater in seronegative patients. Neuropathic pain is equally prevalent and is the predominant pain phenotype in patients with moderate to severe pain. Accurate assessment of pain phenotypes is needed for more effective management of chronic pain in pSS. The focus of future research should be to standardize assessment of pain and to identify the factors contributing to more severe pain in seronegative patients.

In this exploratory study, frontal region WM microstructure alterations accompanied cognitive symptoms and were associated with mild cognitive impairment in PSS. While additional study is warranted to assess the specificity and stability of these results, DTI could provide novel insight into the pathological processes accompanying the subtle cognitive dysfunction commonly experienced by PSS patients.