Scotland’s national imaging database holds roughly 23 million clinical scans—X-rays, CTs, MRIs, ultrasounds, and nuclear medicine images—but researchers cannot currently search or retrieve them in bulk for large-scale studies. The problem is threefold: patient confidentiality must be guaranteed, the datasets are enormous, and the NHS software that manages the images is designed to pull up a single patient’s scan, not to answer research queries like “return all CT chest scans of smokers aged 55–65 who received contrast.” This five-year programme will build secure, open-source software to query an anonymised copy of that database, hosted at the University of Edinburgh, and extract hundreds of thousands of images for research. Two exemplar projects will test the system: one uses hundreds of thousands of CT chest scans to detect lung nodules and coronary artery calcification, then predicts risk of lung cancer and cardiovascular disease—working with industry partner Aidence to validate the method directly on NHS clinical workstations. The other uses MRI brain scans, genetic data, and medical records to predict dementia risk in people with diabetes. If successful, the infrastructure will turn millions of routinely collected, otherwise-ignored clinical images into a resource for earlier diagnosis and treatment, improving patient outcomes and reducing NHS costs.
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Clinical imaging including X-rays, CT, MRI, ultrasound and nuclear medicine scans are core diagnostic technologies. These images can support many important areas of research to improve any or all of diagnosis, monitoring of disease progression and response to treatment. Currently most research using images is based on those collected specifically for a particular research project. The images are of "research" quality. That means that they are captured at high resolution using standardised procedures to reduce the variability of images. Research data collection is expensive so studies tend to be small, and the people who take part in research studies are different to those seen in normal clinical care. It is therefore often uncertain whether research findings can be translated to "real world" images or patients. Each year millions of clinical images are generated in Scotland through routine examinations at hospitals and stored in a huge database. The Scottish national imaging database currently has ~23 million different images collected since 2010. Access to these "real world" images would be extremely valuable for research, but there are a number of big challenges. Firstly, it is very important that all data is kept confidential. Secondly, imaging datasets are very large which it technically challenging. Thirdly, the software which manages these images is optimised for retrieval of images by NHS staff specifically for an individual patient's clinical care (e.g. return Mrs Jones' scan taken on the 28th of May 2016) rather than for research (e.g. return all the CT chest scans of smokers between age 55 and 65 where a contrast agent has been used). What will be delivered? This 5 year programme will enable secure access to routinely collected imaging data for research. Using the foundation blocks already in place from previous research grants, PICTURES will extend, scale and enhance innovative open source software to query a research copy of the Scottish National imaging database securely hosted by the University of Edinburgh and provide anonymised extracts of hundreds of thousands of images for research. PICTURES will also develop this software to query imaging data linked to genomic data securely hosted by the University of Dundee. There are 3 main areas of research required within the core programme: (1) Data science research for complex cohort building from real-world, messy data. (2) Engineering required for scaling and handling big data within a Safe Haven environment. (3) Cybersecurity research needed to ensure that the patient data is securely held and de-identified appropriately for research. PICTURES will support 2 major exemplar research projects to guide and shape the underpinning resources. Exemplar one will develop a method to detect lung nodules and coronary artery calcification using hundreds of thousands of CT chest scans provided by the core programme. It will also predict the risk of getting lung cancer based upon the presence of lung nodules and the risk of cardiovascular disease based upon the presence of coronary artery calcification. This exemplar will work in partnership with an industrial partner, Aidence, to validate and test the method directly in NHS clinical workstations within the course of the programme. Exemplar 2 will predict individual risk of dementia in people with diabetes using MRI brain scans, genetic data and medical records. The most important variables will be found. The predictive tool will be validated on the large image dataset provided by the core programme. Both of our exemplars will determine new information from routinely collected data that would otherwise have been ignored. Predicting and therefore treating diseases at an early stage improves patient outcomes and reduces the cost to the NHS. PICTURES is truly interdisciplinary requiring expertise in Radiomics, AI, Cybersecurity, Software Engineering, Data Science, Data Governance and Medicine.
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