Stroke Scans Could Reveal COVID-19 Infection
|
By HospiMedica International staff writers Posted on 18 Sep 2020 |

Illustration
New research has found that COVID-19 may be diagnosed on the same emergency scans intended to diagnose stroke. The findings have important implications in the management of patients presenting with suspected stroke through early identification of COVID-19.
Researcher from the School of Biomedical Engineering & Imaging Sciences at King’s College London (London, UK) have found that the emergency scans captured images of the top of the lungs where a fluffiness known as ‘ground glass opacification’ allowed COVID-19 to be diagnosed. The findings allow earlier selection of the appropriate level of personal protective equipment (PPE) and attendant staff numbers, triage to appropriate inpatient ward settings, self-isolation and contact tracing.
For their study, the team examined 225 patients from three London Hyper-Acute Stroke Units. The emergency stroke scan consisted of a computed tomography (CT) of the head and neck blood vessels. The results showed that when the team saw these changes in the top of the lungs during the emergency scan, they were able to reliably and accurately diagnose COVID-19 and the changes also predicted increased mortality.
“This is particularly relevant given the limitations of currently available Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) reverse transcriptase-polymerase chain reaction (RT-PCR) testing as it takes time to complete the test and sometimes it is inaccurate,” said Dr. Thomas Booth, study lead, senior lecturer in neuroimaging and consultant radiologist at King’s College Hospital.
“Additionally, our data have prognostic information given the increased mortality in those with lung changes shown in our cohort,” added Dr. Booth. “These are useful results because the changes are simple for radiologists and other doctors to see. This is “free information” from a scan intended for another purpose yet extremely valuable.”
Related Links:
King’s College London
Researcher from the School of Biomedical Engineering & Imaging Sciences at King’s College London (London, UK) have found that the emergency scans captured images of the top of the lungs where a fluffiness known as ‘ground glass opacification’ allowed COVID-19 to be diagnosed. The findings allow earlier selection of the appropriate level of personal protective equipment (PPE) and attendant staff numbers, triage to appropriate inpatient ward settings, self-isolation and contact tracing.
For their study, the team examined 225 patients from three London Hyper-Acute Stroke Units. The emergency stroke scan consisted of a computed tomography (CT) of the head and neck blood vessels. The results showed that when the team saw these changes in the top of the lungs during the emergency scan, they were able to reliably and accurately diagnose COVID-19 and the changes also predicted increased mortality.
“This is particularly relevant given the limitations of currently available Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) reverse transcriptase-polymerase chain reaction (RT-PCR) testing as it takes time to complete the test and sometimes it is inaccurate,” said Dr. Thomas Booth, study lead, senior lecturer in neuroimaging and consultant radiologist at King’s College Hospital.
“Additionally, our data have prognostic information given the increased mortality in those with lung changes shown in our cohort,” added Dr. Booth. “These are useful results because the changes are simple for radiologists and other doctors to see. This is “free information” from a scan intended for another purpose yet extremely valuable.”
Related Links:
King’s College London
Latest COVID-19 News
- Low-Cost System Detects SARS-CoV-2 Virus in Hospital Air Using High-Tech Bubbles
- World's First Inhalable COVID-19 Vaccine Approved in China
- COVID-19 Vaccine Patch Fights SARS-CoV-2 Variants Better than Needles
- Blood Viscosity Testing Can Predict Risk of Death in Hospitalized COVID-19 Patients
- ‘Covid Computer’ Uses AI to Detect COVID-19 from Chest CT Scans
- MRI Lung-Imaging Technique Shows Cause of Long-COVID Symptoms
- Chest CT Scans of COVID-19 Patients Could Help Distinguish Between SARS-CoV-2 Variants
- Specialized MRI Detects Lung Abnormalities in Non-Hospitalized Long COVID Patients
- AI Algorithm Identifies Hospitalized Patients at Highest Risk of Dying From COVID-19
- Sweat Sensor Detects Key Biomarkers That Provide Early Warning of COVID-19 and Flu
- Study Assesses Impact of COVID-19 on Ventilation/Perfusion Scintigraphy
- CT Imaging Study Finds Vaccination Reduces Risk of COVID-19 Associated Pulmonary Embolism
- Third Day in Hospital a ‘Tipping Point’ in Severity of COVID-19 Pneumonia
- Longer Interval Between COVID-19 Vaccines Generates Up to Nine Times as Many Antibodies
- AI Model for Monitoring COVID-19 Predicts Mortality Within First 30 Days of Admission
- AI Predicts COVID Prognosis at Near-Expert Level Based Off CT Scans
Channels
Artificial Intelligence
view channel
Machine Learning Approach Enhances Liver Cancer Risk Stratification
Hepatocellular carcinoma, the most common form of primary liver cancer, is often detected late despite targeted surveillance programs. Current screening guidelines emphasize patients with known cirrhosis,... Read more
New AI Approach Monitors Brain Health Using Passive Wearable Data
Brain health spans cognitive and emotional functions and can fluctuate even in adults without diagnosed disease. Detecting early changes remains difficult in routine care and burdens specialty services... Read moreCritical Care
view channel
Automated IV Labeling Solution Improves Infusion Safety and Efficiency
Medication administration in high-acuity settings is often complicated by multiple concurrent infusions, making accurate line identification essential. In a 10-hospital intensive care unit study, 60% of... Read more
First-Of-Its-Kind AI Tool Detects Pulmonary Hypertension from Standard ECGs
Pulmonary hypertension is a progressive, life‑threatening disease that is frequently missed early because symptoms such as dyspnea are nonspecific and diagnostic delays can exceed two years.... Read moreSurgical Techniques
view channel
Continuous Monitoring with Wearables Enhances Postoperative Patient Safety
Postoperative hypoxemia on general surgical wards is common and often missed by intermittent vital sign checks. Undetected low oxygen levels can delay recovery and raise the risk of complications that... Read more
New Approach Enables Customized Muscle Tissue Without Biomaterial Scaffolds
Volumetric muscle loss is a traumatic loss of skeletal muscle that often leads to permanent functional impairment and limited reconstructive options. Current experimental strategies struggle to deliver... Read morePatient Care
view channel
Wearable Sleep Data Predict Adherence to Pulmonary Rehabilitation
Chronic obstructive pulmonary disease (COPD) is a long-term lung disorder that makes breathing difficult and often disturbs sleep, reducing energy for daily activities. Limited engagement in pulmonary... Read more
Revolutionary Automatic IV-Line Flushing Device to Enhance Infusion Care
More than 80% of in-hospital patients receive intravenous (IV) therapy. Every dose of IV medicine delivered in a small volume (<250 mL) infusion bag should be followed by subsequent flushing to ensure... Read moreHealth IT
view channel
EMR-Based Tool Predicts Graft Failure After Kidney Transplant
Kidney transplantation offers patients with end-stage kidney disease longer survival and better quality of life than dialysis, yet graft failure remains a major challenge. Although a successful transplant... Read more
Printable Molecule-Selective Nanoparticles Enable Mass Production of Wearable Biosensors
The future of medicine is likely to focus on the personalization of healthcare—understanding exactly what an individual requires and delivering the appropriate combination of nutrients, metabolites, and... Read moreBusiness
view channel








