Prone Chest Radiographs: Distinguishing Features and Identification of Support Devices.

PURPOSE: Prone position is known to improve acute lung injury, and chest radiographs are often necessary to monitor disease and confirm support device placement. However, there is a paucity of literature regarding radiographs obtained in this position. We evaluated prone radiographs for distinguishing features and ability to identify support devices. METHODS: Pairs of prone and supine radiographs obtained during the COVID-19 pandemic were assessed retrospectively. IRB approval and waiver of informed consent were obtained. Radiographs were assessed for imaging adequacy, distinguishing features, and support device identification (endotracheal tube, enteric tube, or central line). Radiographs were reviewed by ≥ 2 cardiothoracic radiologists. RESULTS: Radiographs from 81 patients (63yo ± 13, 30% women) were reviewed. Prone and supine radiographs were comparable for imaging the lung bases (81% vs. 90%, p = 0.35) and apices (93% vs. 94%, p = 1); prone radiographs more frequently had significant rotation (36% vs. 19%, p = 0.021). To identify prone technique, scapula tip located beyond the rib border was 89% sensitive (95%CI 80-95%) and 85% specific (76-92%), and a fundal stomach bubble was 44% sensitive (33-56%) and 90% specific (81-96%). For women, displaced breast shadow was 46% sensitive (26-67%) and 92% specific (73-99%). Prone and supine radiographs each identified > 99% of support devices. Prone exams trended toward increased rate of malpositioned device (12% vs. 6%, p = 0.07). CONCLUSION: Scapula position reliably distinguishes prone from supine position; fundal stomach bubble or displaced breast shadow is specific for prone position. Prone radiographs reliably identify line and tube position, which is particularly important as prone patients appear at increased risk for malpositioned devices.

Mimickers of Hill-Sachs Lesions [Formula: see text].

The purpose of this article is to describe the imaging appearance, etiology, clinical features, and treatment of rare presentations of common bone and joint diseases known to mimic Hill-Sachs lesions. Knowledge of uncommonly encountered manifestations of ankylosing spondylitis, rheumatoid arthritis, septic joint, hyperparathyroidism, hydroxyapatite deposition disease, malignant bone tumors, and benign bone cysts which mimic traumatic Hill-Sachs lesions is important for radiologists to guide the clinical care of patients who present with shoulder symptoms.

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.

Determinants of Chest X-Ray Sensitivity for COVID- 19: A Multi-Institutional Study in the United States.

PURPOSE: To evaluate the sensitivity, specificity, and severity of chest x-rays (CXR) and chest CTs over time in confirmed COVID-19+ and COVID-19- patients and to evaluate determinants of false negatives. METHODS: In a retrospective multi-institutional study, 254 RT-PCR verified COVID-19+ patients with at least one CXR or chest CT were compared with 254 age- and gender-matched COVID-19- controls. CXR severity, sensitivity, and specificity were determined with respect to time after onset of symptoms; sensitivity and specificity for chest CTs without time stratification. Performance of serial CXRs against CTs was determined by comparing area under the receiver operating characteristic curves (AUC). A multivariable logistic regression analysis was performed to assess factors related to false negative CXR. RESULTS: COVID-19+ CXR severity and sensitivity increased with time (from sensitivity of 55% at ≤2 days to 79% at >11 days; p<0.001 for trends of both severity and sensitivity) whereas CXR specificity decreased over time (from 83% to 70%, p=0.02). Serial CXR demonstrated increase in AUC (first CXR AUC=0.79, second CXR=0.87, p=0.02), and second CXR approached the accuracy of CT (AUC=0.92, p=0.11). COVID-19 sensitivity of first CXR, second CXR, and CT was 73%, 83%, and 88%, whereas specificity was 80%, 73%, and 77%, respectively. Normal and mild severity CXR findings were the largest factor behind false-negative CXRs (40% normal and 87% combined normal/mild). Young age and African-American ethnicity increased false negative rates. CONCLUSION: CXR sensitivity in COVID-19 detection increases with time, and serial CXRs of COVID-19+ patients has accuracy approaching that of chest CT.