Severity of Chest Imaging is Correlated with Risk of Acute Neuroimaging Findings among Patients with COVID-19.

BACKGROUND AND PURPOSE: Severe respiratory distress in patients with COVID-19 has been associated with higher rate of neurologic manifestations. Our aim was to investigate whether the severity of chest imaging findings among patients with coronavirus disease 2019 (COVID-19) correlates with the risk of acute neuroimaging findings. MATERIALS AND METHODS: This retrospective study included all patients with COVID-19 who received care at our hospital between March 3, 2020, and May 6, 2020, and underwent chest imaging within 10 days of neuroimaging. Chest radiographs were assessed using a previously validated automated neural network algorithm for COVID-19 (Pulmonary X-ray Severity score). Chest CTs were graded using a Chest CT Severity scoring system based on involvement of each lobe. Associations between chest imaging severity scores and acute neuroimaging findings were assessed using multivariable logistic regression. RESULTS: Twenty-four of 93 patients (26%) included in the study had positive acute neuroimaging findings, including intracranial hemorrhage (n = 7), infarction (n = 7), leukoencephalopathy (n = 6), or a combination of findings (n = 4). The average length of hospitalization, prevalence of intensive care unit admission, and proportion of patients requiring intubation were significantly greater in patients with acute neuroimaging findings than in patients without them (P < .05 for all). Compared with patients without acute neuroimaging findings, patients with acute neuroimaging findings had significantly higher mean Pulmonary X-ray Severity scores (5.0 [SD, 2.9] versus 9.2 [SD, 3.4], P < .001) and mean Chest CT Severity scores (9.0 [SD, 5.1] versus 12.1 [SD, 5.0], P = .041). The pulmonary x-ray severity score was a significant predictor of acute neuroimaging findings in patients with COVID-19. CONCLUSIONS: Patients with COVID-19 and acute neuroimaging findings had more severe findings on chest imaging on both radiographs and CT compared with patients with COVID-19 without acute neuroimaging findings. The severity of findings on chest radiography was a strong predictor of acute neuroimaging findings in patients with COVID-19.

Analysis of Stroke Detection during the COVID-19 Pandemic Using Natural Language Processing of Radiology Reports.

BACKGROUND AND PURPOSE: The coronavirus disease 2019 (COVID-19) pandemic has led to decreases in neuroimaging volume. Our aim was to quantify the change in acute or subacute ischemic strokes detected on CT or MR imaging during the pandemic using natural language processing of radiology reports. MATERIALS AND METHODS: We retrospectively analyzed 32,555 radiology reports from brain CTs and MRIs from a comprehensive stroke center, performed from March 1 to April 30 each year from 2017 to 2020, involving 20,414 unique patients. To detect acute or subacute ischemic stroke in free-text reports, we trained a random forest natural language processing classifier using 1987 randomly sampled radiology reports with manual annotation. Natural language processing classifier generalizability was evaluated using 1974 imaging reports from an external dataset. RESULTS: The natural language processing classifier achieved a 5-fold cross-validation classification accuracy of 0.97 and an F1 score of 0.74, with a slight underestimation (-5%) of actual numbers of acute or subacute ischemic strokes in cross-validation. Importantly, cross-validation performance stratified by year was similar. Applying the classifier to the complete study cohort, we found an estimated 24% decrease in patients with acute or subacute ischemic strokes reported on CT or MR imaging from March to April 2020 compared with the average from those months in 2017-2019. Among patients with stroke-related order indications, the estimated proportion who underwent neuroimaging with acute or subacute ischemic stroke detection significantly increased from 16% during 2017-2019 to 21% in 2020 (P = .01). The natural language processing classifier performed worse on external data. CONCLUSIONS: Acute or subacute ischemic stroke cases detected by neuroimaging decreased during the COVID-19 pandemic, though a higher proportion of studies ordered for stroke were positive for acute or subacute ischemic strokes. Natural language processing approaches can help automatically track acute or subacute ischemic stroke numbers for epidemiologic studies, though local classifier training is important due to radiologist reporting style differences.

Clinical and Neuroimaging Correlation in Patients with COVID-19.

BACKGROUND AND PURPOSE: Coronavirus disease 2019 (COVID-19) is increasingly being recognized for its multiorgan involvement, including various neurological manifestations. We examined the frequency of acute intracranial abnormalities seen on CT and/or MR imaging in patients with COVID-19 and investigated possible associations between these findings and clinical parameters, including length of hospital stay, requirement for intubation, and development of acute kidney injury. MATERIALS AND METHODS: This was a retrospective study performed at a large academic hospital in the United States. A total of 641 patients presented to our institution between March 3, 2020, and May 6, 2020, for treatment of coronavirus disease 2019, of whom, 150 underwent CT and/or MR imaging of the brain. CT and/or MR imaging examinations were evaluated for the presence of hemorrhage, infarction, and leukoencephalopathy. The frequency of these findings was correlated with clinical variables, including body mass index, length of hospital stay, requirement for intubation, and development of acute kidney injury as documented in the electronic medical record. RESULTS: Of the 150 patients, 26 (17%) had abnormal CT and/or MR imaging findings, with hemorrhage in 11 of the patients (42%), infarction in 13 of the patients (50%), and leukoencephalopathy in 7 of the patients (27%). Significant associations were seen between abnormal CT/MR imaging findings and intensive care unit admission (P = .039), intubation (P = .004), and acute kidney injury (P = .030). CONCLUSIONS: A spectrum of acute neuroimaging abnormalities was seen in our cohort of patients with coronavirus disease 2019, including hemorrhage, infarction, and leukoencephalopathy. Significant associations between abnormal neuroimaging studies and markers of disease severity (intensive care unit admission, intubation, and acute kidney injury) suggest that patients with severe forms of coronavirus disease 2019 may have higher rates of neuroimaging abnormalities.

Leukoencephalopathy Associated with Severe COVID-19 Infection: Sequela of Hypoxemia?

There is increasing evidence to suggest that complications of coronavirus disease 2019 (COVID-19) infection are not only limited to the pulmonary system but can also involve the central nervous system. Here, we report 6 critically ill patients with COVID-19 infection and neuroimaging findings of leukoencephalopathy. While these findings are nonspecific, we postulate that they may be a delayed response to the profound hypoxemia the patients experienced due to the infection. No abnormal enhancement, hemorrhage, or perfusion abnormalities were noted on MR imaging. In addition, Severe Acute Respiratory Syndrome coronavirus 2 was not detected in the CSF collected from the 2 patients who underwent lumbar puncture. Recognition of COVID-19-related leukoencephalopathy is important for appropriate clinical management, disposition, and prognosis.

Preserving Access: A Review of Stroke Thrombectomy during the COVID-19 Pandemic.

Thrombectomy for large-vessel-occlusion stroke is a highly impactful treatment. The spread of coronavirus 19 (COVID-19) across the United States and the globe impacts access to this crucial intervention through widespread societal and institutional changes. In this document, we review the implications of COVID-19 on the emergency care of large-vessel occlusion stroke, reviewing specific infection-control recommendations, available literature, existing resources, and expert consensus. As a population, patients with large-vessel occlusion stroke face unique challenges during pandemics. These are broad in scope. Responses to these challenges through adaptation of stroke systems of care and with imaging, thrombectomy, and postprocedural care are detailed. Preservation of access to thrombectomy must be prioritized for its public health impact. While the extent of required changes will vary by region, tiered planning for both escalation and de-escalation of measures must be a part of each practice. In addition, preparations described serve as templates in the event of future pandemics.