The University of Oxford-led National Consortium of Intelligent Medical Imaging (NCIMI) in the UK is collaborating with GE Healthcare to develop and test algorithms to aid in the diagnosis and management of COVID-19 pneumonia.
The programme will focus on developing, enhancing and testing potential algorithms to help diagnose COVID-19 pneumonia, predict which patients will develop severe respiratory distress - a key cause of mortality in patients who develop COVID-19 pneumonia - and which patients might develop longer-term lung function problems, even when they recover from respiratory distress.
At present, clinicians cannot easily predict which patients who test positive for COVID-19 will deteriorate and require hospital admission for oxygen and possible ventilation. Nor is it clear which patients will suffer long-term consequences from the lung damage from COVID-19 pneumonia.
The teams aim to develop algorithms incorporating data from thousands of patients medical imaging, laboratory and clinical observations to provide both a quicker diagnosis and a prediction of how a patient may progress and recover.
Currently, some patients admitted to hospital do not see a worsening of their symptoms, whereas others who appear stable can deteriorate rapidly. Identification of those patients at highest risk of deterioration and long-term lung function problems may help physicians to accelerate intensive support. It may also allow those with lower risk to be monitored in a suitably safe environment, potentially including the patient’s home.
The researchers aim to develop tools to help in the management of these COVID-19 patients from triage to acute monitoring, interventions, and discharge and those requiring follow-up after recovery.
The development of robust algorithms and models requires large data sets comprising thousands of patients. The Oxford and NCIMI teams will have access to data from NCIMI NHS partner hospitals as well as the National COVID-19 Chest Imaging Database.
