Health and Bioscience IDEAS - Imaging, Data structures, gEnetics and Analytical Strategies

We will develop a training program for researchers at universities, hospitals, and businesses that helps them better use data from medical images in their research. These images are generated from many different machines, such as microscopes, magnetic resonance imaging (MRI) scanners, and computer tomography (CT) scanners. These technologies not only can produce maps of the human body's structure (from single cells to large organs), but they can also tell you how the body is functioning, such as how blood is being delivered to different parts of the body or where abnormal proteins that could cause Alzheimer's disease are present. These images have played a major part in many recent scientific discoveries across a range of medical fields. As a result, imaging data is being used more often in research and the amount of imaging data available for researchers to work with and ask new scientific questions is also growing rapidly. This means that researchers from a diverse set of backgrounds now have the opportunity to work with imaging data and bring their own expertise and perspective to answering new questions about various diseases. However, this imaging data is often complex and difficult to work with, specialist training is required to understand how to handle, process, and obtain accurate and reliable information from these images. This training is often not a part of most scientists' standard curriculum, so it can be an entry barrier for many scientists in terms of getting started with research involving imaging.

We are proposing a series of short courses that will cover many different aspects of working with medical imaging data. Most importantly, as security of the sensitive personal data contained in imaging becomes a greater concern, we will focus on teaching attendees about best practices in terms of data management and protection. Some of these courses will be given as intensive face-to-face workshops, while others will be online courses where the users will set their own pace. The courses will cover a wide range of backgrounds, from newcomers who are just getting started working with imaging data to those who wish to do more advanced, complex analysis. We will also develop some courses that will allow a smaller set of individuals be able to train staff at their own institutions about how to work with this imaging data. We have experts in all of these aspects who will develop the lectures and exercise for the courses, and we will hire a course leader who will combine this content into a cohesive set of courses about medical imaging. Feedback will be sought from those attending the courses, as to assess their effectiveness, tailor them to the needs of the community, and improve them. By the end of the two years, we will make this project self-sufficient after the 2 years; the resulting courses will continue to be delivered to new researchers, with a charge that is both fair and good value to attendees throughout the UK, while also being sustainable financially from the university's perspective. During the project we will create and nurture a network that starts with fostering interaction between attendees during and after the course, creating a community of these "imaging literate" researchers throughout the UK. We hope this will lead to a range of collaborations and critical-mass for exiting and large projects.

Imaging and genetic analysis have dramatically transformed medicine and bioscience in a short period of time. This transformation has been so fast that a substantial knowledge gap has developed between most scientists/clinicians and the computational experts. While open-source methods for data structuring and analysis can provide an equilibrating force, the expertise to apply these responsibly and effectively is lacking. Researchers must also balance open science mandates with data protection law, creating complex challenges surrounding collecting, managing, analysing and sharing imaging data, particularly when integrating with genetic data. Our consortium will produce a series of face-to-face and virtual workshops, as well as self-directed online courses and tools to close the knowledge gap for clinical and imaging science researchers in the UK and beyond. This content will cover handling imaging and genetic data, data protection, data sharing, and code sharing; with hands-on activities (such as hackathons) to help attendees develop skills while addressing their research. We will generate a core curriculum that will subsequently be tailored to fit the skill levels and research domain of the attendees. We will target this training at researchers who are based at universities, hospitals, and the burgeoning UK biotech industry. A large majority of these researchers will be clinicians, basic scientists, epidemiologists, and medical physicists, among others. At the completion of this grant, we will have established a course that will produce good results for the researchers and thus good feedback and reputation, and we will continue to offer this content at a price that represents good value for potential attendees while maintaining financial stability and support from the university.