COVID-19 research may be on the horizon with the help of Cerebriu

COVID-19 research may be on the horizon with the help of Cerebriu
© iStock/da-kuk

Cerebriu has entered a COVID-19 research deal with the aim to create a model for estimating the risk of newly diagnosed patients of needing intensive care and ventilator breathing support.

Hospitals are under unprecedented pressure to accurately monitor disease progression and predict which COVID-19 patients will need ICU support. Here, the University of Copenhagen, and Copenhagen University Hospital (Rigshospitalet), Denmark, have been awarded a grant by Novo Nordisk Foundation to develop an applied artificial intelligence prototype that can provide relevant stakeholders the severity of COVID-19 pneumonia based on clinical parameters and chest x-rays, thus contracting Cerebriu to provide chest x-ray AI and automated risk assessment scoring.

“Such models can be used by frontline staff”

Robert Lauritzen, Cerebriu’s CEO and Co-Founder stated: “No one knows how long this corona crisis will last, but Cerebriu has a world-class AI team within medical imaging, so if we can help improve workflow and save lives, that is our priority until we’re invited to implement our solutions again”.

Clinical COVID-19 diseases range from asymptomatic infection, to mild symptomatic disease, severe disease requiring hospitalisation and intensive care unit admission including respiratory support, and death. Hospitals need a risk stratification model based on laboratory findings, clinical findings and imaging findings associated with severe illness and mortality to support clinical decision making in critical, high stress scenarios, to ensure best quality care for patients and the best use of limited resources during this crisis.

Imaging has been used sparingly in relation to COVID-19. A mix of chest computer tomography (CT) and x-ray have been used as a second-line test due to long turnaround times of molecular testing RT-PCR. There have been mixed impacts in terms of the use of imaging, especially CT, due to long disinfection times of the machine necessary after each scan. In such circumstances, chest x-ray is preferred.

“The hope is that such models can be used by frontline staff when dealing with new COVID-19 patients as well as by planners in the health service,” says Mads Nielsen, Head of Department of Computer Science, University of Copenhagen.

Details of the project

Based on the latest knowledge about artificial intelligence (AI), analyses of patient records and courses of treatments, the project aims to create a model for estimating newly diagnosed COVID-19 patients’ risk of needing intensive care and ventilator breathing support based on the patient’s available health data.

The hope is that such models can be used by frontline staff when dealing with new COVID-19 patients as well as by planners in the health service. In addition, the project will seek to identify patterns in the patient data that may form the basis for new recommendations on how best to treat COVID-19 patients in the future.

The project team is centered around existing clinical and epidemiological research groups at Rigshospitalet and Bisbebjerg Hospital who have an interest in AI, with support from a team of AI experts from the Department of Computer Science at the University of Copenhagen.

Cerebriu applies expertise in time of need

At the dawn of the coronavirus, implementation of recently CE-marked software solution Cerebriu Apollo is postponed as hospitals postpone all R&D activities to focus on primary care.

“The chest x-ray risk assessment modelling of COVID-19 for monitoring and triage of patients is strategically aligned with our vision to provide fundamental technology to dramatically decrease rating time for radiologists, reducing burden on healthcare professionals and increasing overall quality of risk assessment,” Lauritzen continues.

Cerebriu’s vision is to expand from current CE-marked Cerebriu Apollo brain tumour and apoplexy clinical workflow support into other clinical workflows relying on diagnostic imaging.

Learn more about Cerebriu here: We Are CEREBRIU


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