American Journal of Roentgenology

BACKGROUND. Neurologic sequelae of SARS-CoV-2 include potentially malignant cerebrovascular events arising from complex hemodynamic, hematologic, and inflammatory processes occurring in concert.

OBJECTIVE. This study concerns the hypothesis that despite angiographic reperfusion COVID-19 promotes continued consumption of at-risk tissue volumes after acute ischemic stroke (AIS), yielding critical insights into prognostication and monitoring paradigms in vaccine-naive patients experiencing AIS.

METHODS. This retrospective study compared 100 consecutive COVID-19 patients with AIS presenting between March 2020 and April 2021 with a contemporaneous cohort of 282 AIS patients without COVID-19. Reperfusion classes were dichotomized into positive (extended thrombolysis in cerebral ischemia [eTICI] score = 2c–3) and negative (eTICI score < 2c) groups. All patients underwent endovascular therapy after initial CT perfusion imaging (CTP) to document infarction core and total hypoperfusion volumes.

RESULTS. Ten COVID-positive (mean age ± SD, 67 ± 12 years; seven men, three women) and 144 COVID-negative patients (mean age, 71 ± 16 years; 76 men, 68 women) undergoing endovascular reperfusion, with antecedent CTP and follow-up imaging, comprised the final dataset. Initial infarction core and total hypoperfusion volumes (mean ± SD) were 1.5 ± 18 mL and 85 ± 100 mL in COVID-negative patients and 30.5 ± 34 mL and 117 ± 80.5 mL in COVID-positive patients, respectively. Final infarction volumes were significantly larger in patients with COVID-19, with median volumes of 77.8 mL versus 18.2 mL among control patients (p = .01), as were normalized measures of infarction growth relative to baseline infarction volume (p = .05). In adjusted logistic parametric regression models, COVID positivity emerged as a significant predictor for continued infarct growth (OR, 5.10 [95% CI, 1.00–25.95]; p = .05).

CONCLUSION. These findings support the potentially aggressive clinical course of cerebrovascular events in patients with COVID-19, suggesting greater infarction growth and ongoing consumption of at-risk tissues, even after angiographic reperfusion.

CLINICAL IMPACT. SARS-CoV-2 infection may promote continued infarction progression despite angiographic reperfusion in vaccine-naive patients with large-vessel occlusion AIS. The findings carry potential implications for prognostication, treatment selection, and surveillance for infarction growth among revascularized patients in future waves of infection by novel viral strains.

BACKGROUND. SARS-CoV-2 infection is associated with acute stroke, possibly caused by viral tropism to the vascular endothelium. Whether cerebrovascular endothelial dysfunction and inflammation persist after acute infection is poorly understood.

OBJECTIVE. The purposes of this study were to assess the association between prior SARS-CoV-2 infection and cerebrovascular reactivity (CVR) and vessel wall imaging (VWI) abnormalities and to explore the association between CVR impairment and post-COVID neurologic conditions.

METHODS. This prospective study included 15 participants with prior SARS-CoV-2 infection (11 women, four men; mean age, 43 years; mean time since infection, 238 days; three with prior critical illness, 12 with prior mild illness; seven with post-COVID neurologic conditions) and 10 control participants who had never had SARS-CoV-2 infection (two women, two men; mean age, 44 years) from July 1, 2021, to February 9, 2022. Participants underwent research MRI that included arterial spin labeling perfusion imaging with acetazolamide stimulus to measure cerebral blood flow (CBF) and calculate CVR. Examinations also included VWI, performed with a contrast-enhanced black-blood 3D T1-weighted sequence. An age- and sex-adjusted linear model was used to assess associations between CVR and prior infection. A t test was used to assess associations between CVR and post-COVID neurologic conditions in participants with previous infection. A difference of proportions test was used to assess associations between VWI abnormalities and infection status.

RESULTS. Mean whole-cortex CBF after acetazolamide administration was greater in participants without previous infection than in participants with previous infection (73.8 ± 13.2 [SD] vs 60.5 ± 15.8 mL/100 gm/min; p = .04). Whole-brain CVR was lower in participants with previous infection than those without previous infection (difference, −8.9 mL/100 g/min; p < .001); significantly lower CVR was also observed in participants with previous infection after exclusion of those with prior critical illness. Among participants with previous infection, CVR was lower in those with than those without post-COVID neurologic conditions, although this difference was not significant (16.9 vs 21.0 mL/100 g/min; p = .22). Six of 15 (40%) participants with previous infection versus 1 of 10 (10%) participants without previous infection had at least one VWI abnormality (p = .18). All VWI abnormalities were consistent with atherosclerosis.

CONCLUSION. SARS-CoV-2 infection is associated with chronic impairment of CVR. The mechanism is unknown from this study.

CLINICAL IMPACT. Future studies are needed to determine the clinical implications of SARS-CoV-2–associated CVR impairment.

Please see the Editorial Comment by Donna D'Alessio discussing this article.

BACKGROUND. Screening mammography facilities closed during the COVID-19 pandemic in spring 2020. Recovery of screening volumes has varied across patient subgroups and facilities.

OBJECTIVE. We compared screening mammography volumes and patient and facility characteristics between periods before COVID-19 and early and later postclosure recovery periods.

METHODS. This retrospective study included screening mammograms performed in the same 2-month period (May 26–July 26) in 2019 (pre–COVID-19), 2020 (early recovery), and 2021 (late recovery after targeted interventions to expand access) and across multiple facility types (urban, suburban, community health center). Suburban sites had highest proportion of White patients and the greatest scheduling flexibility and expanded appointments during initial reopening. Findings were compared across years.

RESULTS. For White patients, volumes decreased 36.6% from 6550 in 2019 (4384 in 2020) and then increased 61.0% to 6579 in 2021; for patients with races other than White, volumes decreased 53.9% from 1321 in 2019 (609 in 2020) and then increased 136.8% to 1442 in 2021. The percentage of mammograms in patients with races other than White was 16.8% in 2019, 12.2% in 2020, and 18.0% in 2021. The proportion performed at the urban center was 55.3% in 2019, 42.2% in 2020, and 45.9% in 2021; the proportion at suburban sites was 34.0% in 2019, 49.2% in 2020, and 43.5% in 2021. Pre–COVID-19 volumes were reached by the sixth week after reopening for suburban sites but were not reached during early recovery for the other sites. The proportion that were performed on Saturday for suburban sites was similar across periods, whereas the proportion performed on Saturday for the urban site was 7.6% in 2019, 5.3% in 2020, and 8.8% in 2021; the community health center did not offer Saturday appointments during recovery.

CONCLUSION. After reopening, screening shifted from urban to suburban settings, with a disproportionate screening decrease in patients with races other than White. Initial delayed access at facilities serving underserved populations exacerbated disparities. Interventions to expand access resulted in late recovery volumes exceeding prepandemic volumes in patients with races other than White.

CLINICAL IMPACT. Interventions to support equitable access across facilities serving diverse patient populations may mitigate potential widening disparities in breast cancer diagnosis during the pandemic.

Please see the Editorial Comment by Tessa S. Cook discussing this article.

Hundreds of imaging-based artificial intelligence (AI) models have been developed in response to the COVID-19 pandemic. AI systems that incorporate imaging have shown promise in primary detection, severity grading, and prognostication of outcomes in COVID-19, and have enabled integration of imaging with a broad range of additional clinical and epidemiologic data. However, systematic reviews of AI models applied to COVID-19 medical imaging have highlighted problems in the field, including methodologic issues and problems in real-world deployment. Clinical use of such models should be informed by both the promise and potential pitfalls of implementation. How does a practicing radiologist make sense of this complex topic, and what factors should be considered in the implementation of AI tools for imaging of COVID-19? This critical review aims to help the radiologist understand the nuances that impact the clinical deployment of AI for imaging of COVID-19. We review imaging use cases for AI models in COVID-19 (e.g., diagnosis, severity assessment, and prognostication) and explore considerations for AI model development and testing, deployment infrastructure, clinical user interfaces, quality control, and institutional review board and regulatory approvals, with a practical focus on what a radiologist should consider when implementing an AI tool for COVID-19.

This study evaluated the real-world diagnostic performance of Radiological Society of North America COVID-19 consensus reporting guidelines among 2618 chest CT reports from the author's health care network from April 2020 through March 2021; reverse-transcriptase polymerase chain reaction served as the reference. Typical findings exhibited sensitivity of 68% and specificity of 91%, similar to performance reported in research settings. PPV of 52% was lower than previously reported, attributed to low COVID-19 prevalence. Accuracy improved from 84% in April 2020 to 92% in March 2021 (p = .03).

An increasing incidence of rhinoorbitocerebral mucormycosis (ROCM) among patients with COVID-19 has recently been reported in India. We report the imaging findings for 25 patients with COVID-19 and invasive ROCM at a single hospital in India. Findings included sinus wall erosions (n = 20), air within bony sinus structures (n = 11), and focal mucosal nonenhancement (n = 8). Orbital, vascular, and intracranial complications were also observed. Radiologists should recognize the increasing incidence of ROCM among patients with COVID-19 to facilitate early diagnosis.

This article does not include an abstract.

Please see the accompanying Point by Sean L. Boone.

This article does not include an abstract.

Please see the accompanying Counterpoint by William C. Lavely.

Please see the Editorial Comment by Leif Jensen discussing this article.

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BACKGROUND. Previous studies compared CT findings of COVID-19 pneumonia with those of other infections; however, to our knowledge, no studies to date have included noninfectious organizing pneumonia (OP) for comparison.

OBJECTIVE. The objectives of this study were to compare chest CT features of COVID-19, influenza, and OP using a multireader design and to assess the performance of radiologists in distinguishing between these conditions.

METHODS. This retrospective study included 150 chest CT examinations in 150 patients (mean [± SD] age, 58 ± 16 years) with a diagnosis of COVID-19, influenza, or non-infectious OP (50 randomly selected abnormal CT examinations per diagnosis). Six thoracic radiologists independently assessed CT examinations for 14 individual CT findings and for Radiological Society of North America (RSNA) COVID-19 category and recorded a favored diagnosis. The CT characteristics of the three diagnoses were compared using random-effects models; the diagnostic performance of the readers was assessed.

RESULTS. COVID-19 pneumonia was significantly different (p < .05) from influenza pneumonia for seven of 14 chest CT findings, although it was different (p < .05) from OP for four of 14 findings (central or diffuse distribution was seen in 10% and 7% of COVID-19 cases, respectively, vs 20% and 21% of OP cases, respectively; unilateral distribution was seen in 1% of COVID-19 cases vs 7% of OP cases; non–tree-in-bud nodules was seen in 32% of COVID-19 cases vs 53% of OP cases; tree-in-bud nodules were seen in 6% of COVID-19 cases vs 14% of OP cases). A total of 70% of cases of COVID-19, 33% of influenza cases, and 47% of OP cases had typical findings according to RSNA COVID-19 category assessment (p < .001). The mean percentage of correct favored diagnoses compared with actual diagnoses was 44% for COVID-19, 29% for influenza, and 39% for OP. The mean diagnostic accuracy of favored diagnoses was 70% for COVID-19 pneumonia and 68% for both influenza and OP.

CONCLUSION. CT findings of COVID-19 substantially overlap with those of influenza and, to a greater extent, those of OP. The diagnostic accuracy of the radiologists was low in a study sample that contained equal proportions of these three types of pneumonia.

CLINICAL IMPACT. Recognized challenges in diagnosing COVID-19 by CT are furthered by the strong overlap observed between the appearances of COVID-19 and OP on CT. This challenge may be particularly evident in clinical settings in which there are substantial proportions of patients with potential causes of OP such as ongoing cancer therapy or autoimmune conditions.

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Among 2820 inpatients with coronavirus disease (COVID-19), 59 (2.1%) underwent brain MRI. Of them, six (10.2%) had MRI findings suspicious for COVID-19–related disseminated leukoencephalopathy (CRDL), which is characterized by extensive confluent or multifocal white matter lesions (with characteristics and locations atypical for other causes), microhemorrhages, diffusion restriction, and enhancement. CRDL is an uncommon but important differential consideration in patients with neurologic manifestations of COVID-19.

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.

Please see the Editorial Comment by Anil K. Dasyam discussing this article.

BACKGROUND. Coronavirus disease (COVID-19) is known to be associated with a distinct form of coagulopathy.

OBJECTIVE. The purpose of this study was to describe the imaging manifestations of COVID-19–associated coagulopathy across anatomic sites and modalities in hospitalized patients and to identify clinical variables associated with positive imaging findings.

METHODS. We conducted a retrospective review of consecutive adult patients with COVID-19 admitted to our hospital over a 3-week period. Data on patient demographics, hematologic values, cross-sectional imaging examinations, and clinical outcomes (death and intubation) were collected. Imaging was reviewed for manifestations of coagulopathy. Multivariable logistic regression analyses were performed to assess associations of patient demographics, hematologic markers, and outcomes with the need for imaging and imaging manifestations of coagulopathy.

RESULTS. Of 308 hospitalized patients with COVID-19, 142 (46%) underwent 332 cross-sectional imaging examinations. Of these, 37 (26%) had imaging results positive for coagulopathy. The most common imaging manifestations of coagulopathy were pulmonary embolus (n = 21) on contrast-enhanced CT or CTA, thrombus in the upper- or lower-extremity veins (n = 13) on Doppler ultrasound, end-organ infarction in the bowel (n = 4) and kidney (n = 4) on contrast-enhanced CT, and thrombus or parenchymal infarction in the brain (n = 2) on contrast-enhanced CTA or MRI with MRA. Among patients with imaging results positive for coagulopathy, eight (22%) had multisite involvement. Thrombi were multifocal in four of five patients with positive upper-extremity and three of eight patients with positive lower-extremity examination results and involved superficial veins, deep veins, or both. In multivariable analysis, intubation (p < .001) and prolonged prothrombin time (p = .04) were significantly associated with undergoing imaging. No patient variable was significantly associated with imaging results positive for coagulopathy (p > .05).

CONCLUSION. Imaging commonly shows manifestations of coagulopathy in hospitalized patients with COVID-19. Over one-fifth of patients with such manifestations show multisite involvement. Clinical variables poorly predict which patients have positive imaging results, indicating a complementary role of imaging in detecting COVID-19–associated coagulopathy.

CLINICAL IMPACT. In patients with COVID-19 with suspected systemic coagulopathy, pulmonary CTA, extremity Doppler ultrasound, contrast-enhanced abdominal CT, and contrast-enhanced brain MRI and MRA may all be appropriate in the absence of imaging contraindications.