Patterns of acute ischemic stroke and intracranial hemorrhage in patients with COVID-19 : Results of a retrospective multicenter neuroimaging-based study from three central European countries.

BACKGROUND: Coronavirus disease 2019 (COVID-19) is an infection which can affect the central nervous system. In this study, we sought to investigate associations between neuroimaging findings with clinical, demographic, blood and cerebrospinal fluid (CSF) parameters, pre-existing conditions and the severity of acute COVID-19. MATERIALS AND METHODS: Retrospective multicenter data retrieval from 10 university medical centers in Germany, Switzerland and Austria between February 2020 and September 2021. We included patients with COVID-19, acute neurological symptoms and cranial imaging. We collected demographics, neurological symptoms, COVID-19 severity, results of cranial imaging, blood and CSF parameters during the hospital stay. RESULTS: 442 patients could be included. COVID-19 severity was mild in 124 (28.1%) patients (moderate n = 134/30.3%, severe n = 43/9.7%, critical n = 141/31.9%). 220 patients (49.8%) presented with respiratory symptoms, 167 (37.8%) presented with neurological symptoms first. Acute ischemic stroke (AIS) was detected in 70 (15.8%), intracranial hemorrhage (IH) in 48 (10.9%) patients. Typical risk factors were associated with AIS; extracorporeal membrane oxygenation therapy and invasive ventilation with IH. No association was found between the severity of COVID-19 or blood/CSF parameters and the occurrence of AIS or IH. DISCUSSION: AIS was the most common finding on cranial imaging. IH was more prevalent than expected but a less common finding than AIS. Patients with IH had a distinct clinical profile compared to patients with AIS. There was no association between AIS or IH and the severity of COVID-19. A considerable proportion of patients presented with neurological symptoms first. Laboratory parameters have limited value as a screening tool.

CT-Based Risk Stratification for Intensive Care Need and Survival in COVID-19 Patients-A Simple Solution.

We evaluated a simple semi-quantitative (SSQ) method for determining pulmonary involvement in computed tomography (CT) scans of COVID-19 patients. The extent of lung involvement in the first available CT was assessed with the SSQ method and subjectively. We identified risk factors for the need of invasive ventilation, intensive care unit (ICU) admission and for time to death after infection. Additionally, the diagnostic performance of both methods was evaluated. With the SSQ method, a 10% increase in the affected lung area was found to significantly increase the risk for need of ICU treatment with an odds ratio (OR) of 1.68 and for invasive ventilation with an OR of 1.35. Male sex, age, and pre-existing chronic lung disease were also associated with higher risks. A larger affected lung area was associated with a higher instantaneous risk of dying (hazard ratio (HR) of 1.11) independently of other risk factors. SSQ measurement was slightly superior to the subjective approach with an AUC of 73.5% for need of ICU treatment and 72.7% for invasive ventilation. SSQ assessment of the affected lung in the first available CT scans of COVID-19 patients may support early identification of those with higher risks for need of ICU treatment, invasive ventilation, or death.

Decreased Medical Care During the COVID-19 Pandemic - A Comprehensive Analysis of Radiological Examinations.

OBJECTIVES: As a cross-section discipline within the hospital infrastructure, radiological departments might be able to provide important information regarding the impact of the COVID-19 pandemic on healthcare. The goal of this study was to quantify changes in medical care during the first wave of the pandemic using radiological examinations as a comprehensive surrogate marker and to determine potential future workload. METHODS: A retrospective analysis of all radiological examinations during the first wave of the pandemic was performed. The number of examinations was compared to time-matched control periods. Furthermore, an in-depth analysis of radiological examinations attributed to various medical specialties was conducted and postponed examinations were extrapolated to calculate additional workload in the near future. RESULTS: A total of 596,760 examinations were analyzed. Overall case volumes decreased by an average of 41 % during the shutdown compared to the control period. The most affected radiological modalities were sonography (-54 %), X-ray (-47 %) followed by MRI (-42 %). The most affected medical specialty was trauma and orthopedics (-60 % case volume) followed by general surgery (-49 %). Examination numbers increased during the post-shutdown period leading to a predicted additional workload of up to 22 %. CONCLUSION: This study shows a marked decrease in radiological examinations in total and among several core medical specialties, indicating a significant reduction in medical care during the first COVID-19 shutdown. KEY POINTS: · Number of radiological examinations decreased by 41 % during the first wave of the COVID-19 pandemic.. · Several core medical specialties were heavily affected with a reduction of case volumes up to 60 %.. · When extrapolating postponed examinations to the near future, the overall workload for radiological departments might increase up to 22 %.. CITATION FORMAT: · Fleckenstein FN, Maleitzke T, Böning G et al. Decreased Medical Care During the COVID-19 Pandemic - A Comprehensive Analysis of Radiological Examinations. Fortschr Röntgenstr 2021; 193: 937 - 946.

Neuroimaging Findings in Conjunction with Severe COVID-19.

PURPOSE: COVID-19 has a variable, but well-described course. However, some patients additionally present with neurological symptoms. Recent studies also show a broad range of neuroimaging features. The purpose of this study was to perform a snapshot analysis to approximate the frequency and types of neuroimaging findings on CT and MRI scans in a large cohort of SARS-CoV-2-positive patients in a level I COVID-19 center, both in general and in critically ill patients. MATERIALS AND METHODS: We retrospectively analyzed brain CT and MRI scans of 34 hospitalized COVID-19 patients at our level I COVID-19 center between March 15 and April 24 with regard to pathological neuroimaging findings. In addition, clinical parameters such as neurological symptoms, comorbidities, and type of ventilation therapy were also documented. A descriptive statistical analysis was performed. RESULTS: Pathological findings were detected in 38.2 % of patients in the study cohort. Based on the weekly institutional SARS-CoV-2 report of all positively tested patients in our clinic at the time of data collection, neuroimaging findings could be found in 6 % of all patients (34/565). The most common findings were microbleeds (20.6 %) and signs of hypoxic brain injury (11.8 %). Furthermore, cortical subarachnoid hemorrhage, typical and atypical cerebral hematomas, ischemic strokes, and generalized brain edema were documented. All neuroimaging findings occurred in patients who were either intubated or treated by ECMO. CONCLUSION: Based on the analysis of this large cohort of SARS-CoV-2-positive patients, pathological neuroimaging findings seem to be relatively rare in general but do occur in a substantial proportion of patients with severe COVID-19 disease needing intubation or ECMO. KEY POINTS: · Neuroimaging findings appear to be relatively rare in SARS-CoV-2 positive patients.. · Pathological findings occur mainly in critically ill COVID-19 patients.. · Frequent findings include hemorrhagic, ischemic and hypoxic changes.. · Critically ill COVID-19 patients should receive neuroimaging with a low threshold.. CITATION FORMAT: · Büttner L, Bauknecht HC, Fleckenstein FN et al. Neuroimaging Findings in Conjunction with Severe COVID-19. Fortschr Röntgenstr 2021; 193: 822 - 829.

Diagnostic Value of Initial Chest CT Findings for the Need of ICU Treatment/Intubation in Patients with COVID-19.

Computed tomography (CT) plays an important role in the diagnosis of COVID-19. The aim of this study was to evaluate a simple, semi-quantitative method that can be used for identifying patients in need of subsequent intensive care unit (ICU) treatment and intubation. We retrospectively analyzed the initial CT scans of 28 patients who tested positive for SARS-CoV-2 at our Level-I center. The extent of lung involvement on CT was classified both subjectively and with a simple semi-quantitative method measuring the affected area at three lung levels. Competing risks Cox regression was used to identify factors associated with the time to ICU admission and intubation. Their potential diagnostic ability was assessed with receiver operating characteristic (ROC)/area under the ROC curves (AUC) analysis. A 10% increase in the affected lung parenchyma area increased the instantaneous risk of intubation (hazard ratio (HR) = 2.00) and the instantaneous risk of ICU admission (HR 1.73). The semi-quantitative measurement outperformed the subjective assessment diagnostic ability (AUC = 85.6% for ICU treatment, 71.9% for intubation). This simple measurement of the involved lung area in initial CT scans of COVID-19 patients may allow early identification of patients in need of ICU treatment/intubation and thus help make optimal use of limited ICU/ventilation resources in hospitals.

Submillisievert chest CT in patients with COVID-19 - experiences of a German Level-I center.

PURPOSE: Computed tomography (CT) is used for initial diagnosis and therapy monitoring of patients with coronavirus disease 2019 (COVID-19). As patients of all ages are affected, radiation dose is a concern. While follow-up CT examinations lead to high cumulative radiation doses, the ALARA principle states that the applied dose should be as low as possible while maintaining adequate image quality. The aim of this study was to evaluate parameter settings for two commonly used CT scanners to ensure sufficient image quality/diagnostic confidence at a submillisievert dose. MATERIALS AND METHODS: We retrospectively analyzed 36 proven COVID-19 cases examined on two different scanners. Image quality was evaluated objectively as signal-to-noise ratio (SNR)/contrast-to-noise ratio (CNR) measurement and subjectively by two experienced, independent readers using 3-point Likert scales. CT dose index volume (CTDIvol) and dose-length product (DLP) were extracted from dose reports, and effective dose was calculated. RESULTS: With the tested parameter settings we achieved effective doses below 1 mSv (median 0.5 mSv, IQR: 0.2 mSv, range: 0.3-0.9 mSv) in all 36 patients. Thirty-four patients had typical COVID-19 findings. Both readers were confident regarding the typical COVID-19 CT-characteristics in all cases (3 ± 0). Objective image quality parameters were: SNRnormal lung: 17.0 ± 5.9, CNRGGO/normal lung: 7.5 ± 5.0, and CNRconsolidation/normal lung: 15.3 ± 6.1. CONCLUSION: With the tested parameters, we achieved applied doses in the submillisievert range, on two different CT scanners without sacrificing diagnostic confidence regarding COVID-19 findings.