Cheshire and Merseyside has become the first regional data hub for the newly launched national Covid-19 chest imaging database.
The consortium has integrated data across 13 trusts, providing researchers with access to 15 years of imaging data across 2.5 million people in the region.
Working with tech supplier Philips to deploy its SMART box solution, the region was able to consolidate the data into one hub. The interface was commissioned in January 2021 and has since been used for cross-site image retrieval for the National Covid-19 chest imaging database (NCCID).
Introducing this solution makes Cheshire and Merseyside better placed to lead the way in setting standards in multi-trust collaboration with regional partners. It is the only regional hub connected to NCCID.
Prof Mark-Halling Brown, head of scientific computing at Royal Surrey NHS Foundation Trust, said: “One of the findings coming out of the end of this project will definitely be to focus on regional hubs that will be able to coordinate and better centralise the data, a hub just like Cheshire and Merseyside.
“It can take many months or even years to set up SMART boxes at individual trusts, so doing it regionally is the only way to scale up nationally.”
The NCCID was established by NHSX in January 2021 to provide hospitals and universities with access to thousands of Covid-19 images and scans in a bid to develop artificial intelligence (AI) solutions to tackle the virus.
NHSX has collected more than 40,000 CT scans, MRIs and X-rays from more than 10,000 patients across 18 NHS trusts over the course of the pandemic.
It is hoped the database will speed up diagnosis of coronavirus, ultimately leading to quicker treatment and less pressure on the NHS by predicting things like the need for additional ICU capacity.
The British Society of Thoratic Imaging, Royal Surrey NHS Foundation Trust and AI company Faculty are working with NHSX on the database as part of the NHS AI Lab.
Clinicians at Addenbrooke’s Hospital in Cambridge are currently using the NCCID to develop an algorithm to inform a more accurate diagnosis of patients when they present with potential Covid-19.
Using visual signatures of the virus, as they appear in chest scans, they are able to compare the patterns in the patient’s imaging with those seen previously in the NCCID to get a more accurate diagnosis and prognosis.
It’s hoped in the future it could be used to develop AI solutions to address a number of other conditions such as heart disease and cancers.