A framework for efficient synergistic spatiotemporal reconstruction of PET-MR dynamic data

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Magnetic resonance (MR) and radionuclide imaging using positron emission tomography (PET) are now essential in many areas of medical diagnosis, clinical research and drug development. The complementary information provided by PET and MR has recently lead to a new generation of dual-modality systems. Clinical applications of these devices are emerging in many priority areas for human health, including dementia, cardiology, and oncology. The previously established Collaborative Computational Project (CCP) for synergistic PET-MR reconstruction connects researchers working on sophisticated algorithms to estimate stacks of slices through the patient from the measured data. In this flagship project, we extend this work towards imaging of dynamic processes. Measuring the redistribution over time of contrasts agents or labelled molecules while taking organ movement into account provides considerable information on the biology, allowing extraction of parameters such as blood flow, receptor density and tissue elasticity.By exploiting correlations between these parameters in both space and time, we can probe fast dynamic processes at higher accuracy than achievable in single modality imaging. This flagship will provide freely available software and methods to the community to accelerate research and development in this area.