NPIC: National Pathology Imaging Co-Operative

Lead Participant: University of Leeds

Abstract

"Pathologists are the **doctors who diagnose disease**. To do this, we examine samples (""biopsies"") using a microscope, to decide if a sample shows cancer, and what type of cancer it is.

New scanners allow us to create digital images of microscope slides, so we can look at them on computers, and share them between hospitals more easily. This is called **digital pathology** - it will be a revolution in how we diagnose cancer.

But digital images allow us to go one step further - to use computers to help us look at the images. ""**Artificial intelligence**"" (AI) is a computer technology which allows computers to do pattern recognition.

AI can be trained to recognise the patterns of disease - for example searching for small areas of cancer in a large sample. So pathologists will be able to use AI to diagnose cancer faster, better and at lower cost.

To work, AI needs to ""learn"" the patterns by looking at large numbers of images and learn from them, like a human would. But there are no large collections of digital images that can be used for this.

In this project, the **Northern Pathology Imaging Co-operative (NPIC)**, we are bringing together the NHS, industry and scientists to solve this problem.

We will put scanners in 12 Northern NHS hospitals to gather digital pathology images training AI systems. This will generate a lot of data - about 760,000 images per year by the end of the project, which is about 1.2 Petabytes.

We will then work with industry and scientists to make new AI systems to analyse our images and make better diagnoses. This is a big opportunity for the UK to lead in this new area.

Because it is a **co-operative with a shared goal, led by doctors**, this project will ensure that AI systems are safe, and that doctors and the NHS are in control of how they are used.

Just as important, we need to ensure the public understand what we are doing and trust that we are using NHS data properly and securely - this will be an important part of our project.

We hope that by the end of our project, we have used the funding to create something that is world leading. We want to develop the best systems for gathering and using data to make AI systems, bringing value for the NHS and patients."

Lead Participant

Project Cost

Grant Offer

University of Leeds, United Kingdom £1,822,560 £ 1,822,560
 

Participant

Royal Surrey County Hospital NHS Foundation Trust, Guildford £30,348 £ 30,348
Bradford Teaching Hospitals NHS Foundation Trust £387,378 £ 387,378
Harrogate and District NHS Foundation Trust £174,975 £ 174,975
Mtuitive UK Limited, Doncaster £766,818 £ 230,045
Ffei Limited, HEMEL HEMPSTEAD £57,047 £ 34,228
Clinisys Group Limited, Chertsey £316,601 £ 50,656
University of Liverpool, United Kingdom £81,877 £ 81,877
Newcastle University, Newcastle Upon Tyne £53,714 £ 53,714
HeteroGenius Limited £128,288 £ 89,802
University of Sheffield, United Kingdom £235,459 £ 235,459
The Royal Liverpool and Broadgreen University Hospitals NHS Trust £304,687 £ 304,687
The Newcastle upon Tyne Hospitals NHS Foundation Trust, Newcastle Upon Tyne £231,715 £ 231,715
X - Lab Limited, LEEDS £182,308 £ 127,616
Leeds Teaching Hospitals NHS Trust, United Kingdom £6,174,586 £ 6,174,586
University of Nottingham £292,175 £ 292,175
University of Oxford, United Kingdom £400,840 £ 400,840
Leica Biosystems Newcastle Limited, Sheffield £3,746,178
The Victoria University of Manchester £372,159 £ 372,159
Futamura Chemical UK Limited, Wigton £139,389 £ 45,998
Airedale NHS Foundation Trust £247,305 £ 247,305
Microsoft Limited, READING
The Mid Yorkshire Hospitals NHS Trust, Wakefield £273,000 £ 273,000
Calderdale and Huddersfield NHS Foundation Trust £237,186 £ 237,186
Sectra Limited, London Stansted £1,629,859 £ 653,963
Roche Diagnostics Limited, WEST SUSSEX £1,540,000

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