PET++: Improving Localisation, Diagnosis and Quantification in Clinical and Medical PET Imaging with Randomised Optimisation

Award Number
Research Grant
Status / Stage
31 August 2019 -
30 August 2023
Duration (calculated)
03 years 11 months
Funding Amount
Funder/Grant study page
Contracted Centre
University of Cambridge
Principal Investigator
Carola-Bibiane Schönlieb
PI Contact
WHO Catergories
Development of clinical assessment of cognition and function
Disease Type
Dementia (Unspecified)

CPEC Review Info
Reference ID662
ResearcherReside Team


Award NumberEP/S026045/1
Status / StageActive
Start Date20190831
End Date20230830
Duration (calculated) 03 years 11 months
Funder/Grant study pageEPSRC
Contracted CentreUniversity of Cambridge
Funding Amount£821,421.00


Positron Emission Tomography (PET) is a pillar of modern diagnostic imaging, allowing non-invasive, sensitive and specific detection of functional changes in several disease types. In endocrinology, the precise localisation of small functioning tumours of the pituitary or adrenal glands is crucial for planning curative surgery or radiotherapy. While PET imaging shows good promise for this task, initial studies suggest significant room for improvement, with improved PET imaging and subsequent more accurate localisation opening up the possibility for more adapted therapies. In dementia, the accurate quantification of PET images is key for the early detection of disease. Improved PET imaging may allow for earlier detection of dementia while asymptomatic and increased sensitivity to assess and monitor treatment once appropriate drugs have been found.

In this project mathematicians team up with researchers and clinicians from Addenbrooke’s Hospital Cambridge, Dementias Platform UK (DPUK), GE Healthcare and University College London (UCL) for improved diagnosis and localization for tumours in endocrinology and earlier diagnosis of dementia with improved PET imaging. In particular, we investigate modern PET reconstruction approaches based on advanced mathematical methods to increase the PET image resolution and contrast, while keeping computational complexity low, thereby directly benefiting clinical workflow.

Planned Impact
Beneficiaries: This project lives at the interface between applied mathematics, imaging technologies, medical research and clinical practice. As such, it will impact each of these areas.
– Applied Mathematicians: Interdisciplinary research like that, that links mathematical innovation closely with the application, is often desired but not often successfully achieved. This project is one of the few pioneers in this respect. Showcasing, therefore, both interesting mathematical innovation and success in the application domain at the same time, will impact how mathematicians think about research, potentially encouraging them to pursue similar approaches for different problems and as such accelerate impact that mathematics has on other disciplines, society, healthcare and more.
– Imaging Technologies: The mathematical optimisation methods and image reconstruction algorithms developed in this project for PET have several generic elements who are applicable to other imaging problems, e.g. MRI, CT, PAT, etc., and which can benefit those in turn.
– Medical Research and clinical practice: Qualitatively and quantitatively improved PET images can potentially impact the analysis and further understanding of a wide range of diseases, their analysis, diagnosis and treatment.

National Importance: Our proposal fits perfectly within the EPSRC’s portfolio and funding strategy, and also connects to other parts of UKRI. It was recognized by a panel of international experts [1] that more focus should be laid on connecting numerical analysis to computation which is a cornerstone of this proposal. With Healthcare Technologies it falls into the EPSRC Optimising Treatment Healthcare Challenge. Dementia is one of the greatest challenges of our time. In 2015 an estimated 850k people in the UK were living with dementia, a number which may rise to 2m by 2050 unless ways to cure or prevent dementia are found [2]. It also accounted for 11.6% of all deaths registered in England and Wales in 2015 making it the leading cause of death [3]. The economic cost of caring to the UK is estimated at more than 23bn in 2014 [4]. To counterfeit this development, it has been noted that “the vast majority of cutting edge biology/health sciences results … have only been made possible by preceding advances in physics, chemistry, computing, mathematics, materials or engineering” [5]. Moreover, in March 2018 the UK government announced an investment of 40m into the UK Dementia Research Institute [6] which is built to create a new hub of interdisciplinary research for developing new treatments for dementia. An important pillar in our fight again dementia is PET imaging where the UK is world-leading in research and development and several members of UKRI made large infrastructural investments. Most recently, seven PET-MR scanners were purchased as part of the nation wide alliance DPUK “aiming to make the UK leaders in the field of this relatively new technology” [7]. Our aim to improve PET imaging to fight dementia aligns with the MRC priority challenge [8] and helps to “provide solutions to major challenges facing society, in the UK and globally” [8]. As such, this proposal contributes directly to the EPSRC’s prosperity outcome Health Nation [8]. Next to EPSRC’s vision, this proposal also aligns with STFC’s vision as connecting mathematical imaging to its applications helps “to maximise the impact of our knowledge, skills, facilities and resources for the benefit of the United Kingdom and its people” [8].

[1] M. Wright et al., International Review of Mathematical Sciences 2010
[2] Alzheimer’s Society UK, 2018
[3] Office of National Statistics, Deaths Registered in England and Wales 2016
[4] F. Lewis et al., Report for Alzheimer’s Research UK by OHE Consulting 2014
[5] EPSRC, Maxwell Review 2014
[7] MRC Review of PET within The Medical Imaging Research Landscape 2017
[8] RCUK, Spending Plan 2016