Key Results: Three Chinese radiologists had a sensitivity of 72%, 72% and 94% and specificity of 94%, 88% and 24% in differentiating 219 COVID-19 from 205 non-COVID-19 pneumonia.  Four United States radiologists had a sensitivity of 93%, 83%, 73% and 73% and specificity of 100%, 93%, 93% and 100%.  The most discriminating features for COVID-19 pneumonia included a peripheral distribution (80% vs. 57%, p<0.001), ground-glass opacity (91% vs. 68%, p<0.001) and vascular thickening (58% vs. 22%, p<0.001). Manuscript type: original researchThe total number of words of the manuscript, including entire text from title page to tables and references: 4364 This copy is for personal use only. To order printed copies, contact reprints@rsna.org I n P r e s s Performance of radiologists in differentiating COVID-19 from viral pneumonia on chest CT Summary: Radiologists had high specificity but moderate sensitivity in differentiating COVID-19 from viral pneumonia on chest CT. Key Results:  Three Chinese radiologists had sensitivities of 72%, 72% and 94% and specificities of 94%, 88% and 24% in differentiating 219 COVID-19 from 205 non-COVID-19 pneumonia.  Four United States radiologists had sensitivities of 93%, 83%, 73% and 73% and specificities of 100%, 93%, 93% and 100%.  The most discriminating features for COVID-19 pneumonia included a peripheral distribution (80% vs. 57%, p<0.001), ground-glass opacity (91% vs. 68%, p<0.001) and vascular thickening (58% vs. 22%, p<0.001). Abstract Background: Despite its high sensitivity in diagnosing COVID-19 in a screening population, chest CT appearances of COVID 19 pneumonia are thought to be non-specific. Purpose: To assess the performance of United States (U.S.) and Chinese radiologists in differentiating COVID-19 from viral pneumonia on chest CT. Methods: A total of 219 patients with both positive COVID-19 by RT-PCR and abnormal chest CT findings were retrospectively identified from 7 Chinese hospitals in Hunan Providence, China from January 6 to February 20, 2020. A total of 205 patients with positive Respiratory Pathogen Panel for viral pneumonia and CT findings consistent with or highly suspicious for pneumonia by original radiology interpretation within 7 days of each other were identified from Rhode Island Hospital in Providence, RI. Three Chinese radiologists blindly reviewed all chest CTs (n=424) to differentiate COVID-19 from viral pneumonia. A sample of 58 age-matched cases was randomly selected and evaluated by 4 U.S. radiologists in a similar fashion. Different CT features were recorded and compared between the two groups. Results: For all chest CTs, three Chinese radiologists correctly differentiated COVID-19 from non-COVID-19 pneumonia 83% (350/424), 80% (338/424), and 60% (255/424) of the time, respectively. The seven radiologists had sensitivities of 80%, 67%, 97%, 93%, 83%, 73% and 70% and specificities of 100%, 93%, 7%, 100%, 93%, 93%, 100%. Compared to non-COVID-19 pneumonia, COVID-19 pneumonia was more likely to have a peripheral distribution (80% vs. 57%, p...

AI assistance improved radiologists' performance in distinguishing COVID-19 from pneumonia of other etiology on chest CT. Key Results: An AI model had higher test accuracy (96% vs 85%, p<0.001), sensitivity (95% vs 79%, p<0.001), and specificity (96% vs 88%, p=0.002) than radiologists. In an independent test set, our AI model achieved an accuracy of 87%, sensitivity of 89% and specificity of 86%. With AI assistance, the radiologists achieved a higher average accuracy (90% vs 85%, p<0.001), sensitivity (88% vs 79%, p<0.001) and specificity (91% vs 88%, p=0.001). AbstractBackground: COVID-19 and pneumonia of other etiology share similar CT characteristics, contributing to the challenges in differentiating them with high accuracy.Purpose: To establish and evaluate an artificial intelligence (AI) system in differentiating COVID-19 and other pneumonia on chest CT and assess radiologist performance without and with AI assistance.Methods: 521 patients with positive RT-PCR for COVID-19 and abnormal chest CT findings were retrospectively identified from ten hospitals from January 2020 to April 2020. 665 patients with non-COVID-19 pneumonia and definite evidence of pneumonia on chest CT were retrospectively selected from three hospitals between 2017 and 2019. To classify COVID-19 versus other pneumonia for each patient, abnormal CT slices were input into the EfficientNet B4 deep neural network architecture after lung segmentation, followed by two-layer fully-connected neural network to pool slices together.Our final cohort of 1,186 patients (132,583 CT slices) was divided into training, validation and test sets in a 7:2:1 and equal ratio. Independent testing was performed by evaluating model performance on separate hospitals. Studies were blindly reviewed by six radiologists without and then with AI assistance.Results: Our final model achieved a test accuracy of 96% (95% CI: 90-98%), sensitivity 95% (95% CI: 83-100%) and specificity of 96% (95% CI: 88-99%) with Receiver Operating Characteristic (ROC) AUC of 0.95 and Precision-Recall (PR) AUC of 0.90. On independent testing, our model achieved an accuracy of 87% (95% CI: 82-90%), sensitivity of 89% (95% CI: 81-94%) and specificity of 86% (95% CI: 80-90%) with ROC AUC of 0.90 and PR AUC of 0.87. Assisted by the models' probabilities, the radiologists achieved a higher average test accuracy (90% vs. 85%, ∆=5, p<0.001), sensitivity (88% vs. 79%, ∆=9, p<0.001) and specificity (91% vs. 88%, ∆=3, p=0.001).

Cardiac MRI studies often show susceptibility artifacts along the inferoapical myocardial margin in both human and in vivo animal experiments at field strengths of 1.5T and greater. This study was designed to determine the cause of these artifacts in porcine myocardium at 3T. Gradient echo images were obtained under various anatomic and physiologic conditions to systematically study potential sources of local susceptibility gradients. Lung resection in the open‐chested, euthanized swine was the only intervention that eliminated the artifact. The data suggest that in the porcine model, the heart‐lung interface is the primary cause of these artifacts. Magn Reson Med 45:341–345, 2001. © 2001 Wiley‐Liss, Inc.

An MR line scan protocol has been used to measure relaxation parameters (T1 and T2) in isolated, blood perfused rabbit hearts at various blood oxygenations. Hearts were retrogradely perfused at 37 degrees C with a cardioplegic solution (modified St. Thomas' solution) containing sheep red blood cells and adenosine (1 mM) to maximally vasodilate the coronary vascular bed. Arresting the hearts eliminated motion complications and minimized arteriovenous oxygenation differences. The authors have found that under conditions of stable flow, there is a strong correlation between T2 in myocardial septa and hemoglobin (Hb) saturation, while tissue T1 is virtually independent of blood oxygenation. These effects are believed to be due to the paramagnetic agent deoxyhemoglobin.

Interpretation of first-pass myocardial perfusion studies employing bolus administration of T1 magnetic resonance (MR) contrast agents requires an understanding of the relationship between contrast concentration and image pixel intensity. The potential effects of myocardial water exchange rates among the intravascular, interstitial, and cellular compartments on this relationship are controversial. We directly studied these issues in isolated, nonbeating canine interventricular septa. Myocardial T1 was measured three times/s during bolus transit of intravascular (albumin-Gd-DTPA and polylysine-Gd-DTPA) and extracellular (gadoteridol) contrast agents. For polylysine-Gd-DTPA, the peak changes in myocardial 1/T1 (delta R1) scaled nonlinearly with perfusate contrast concentration whereas a linear relationship would be expected for fast water exchange among the vascular, interstitial, and cellular compartments. For all agents, the peak delta R1 were much smaller than the values expected on the basis of fast myocardial water exchange. The data demonstrate that in isolated myocardial tissue, myocardial T1 enhancement during bolus administration of contrast can be strongly affected by myocardial water exchange for both intravascular and extracellular MR contrast agents.

NCFs are commonly encountered on cardiac MRI studies, many of which are clinically relevant. Proper recognition of NCFs is critical to the comprehensive management of patients referred for cardiac MRI.

Direct and noninvasive determination of regional Hb saturation with susceptibility-dependent MR imaging may provide information regarding regional myocardial O2 content.

Very few malignancies were diagnosed with repeat FNA following nondiagnostic FNA results (two of 336, 0.6%); therefore, clinical and US follow-up may be more appropriate than repeat FNA following nondiagnostic biopsy results.