A biophysical simulation framework for magnetic resonance microstructure imaging

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This project develops a simulation system for the MR signal in biological tissue and its dependence on molecular dynamics as influenced by tissue microarchitecture and composition. The system is an essential tool in the development of next-generation non-invasive imaging techniques. Specifically, it underpins the development and translation of the emerging paradigm of microstructure imaging. The paradigm uses mathematical models, which relate the MR signal to underlying tissue properties, to estimate and map those properties by fitting the models voxel-by-voxel to combinations of appropriately sensitised image data. The approach provides much greater biological specificity than standard MRI, thus enhancing diagnosis and treatment planning.The current generation of microstructure-imaging techniques is now starting to find widespread application in clinical studies. Prominent examples include NODDI for neuroimaging and VERDICT for cancer imaging, both developed by the investigators on this project. Those techniques are based entirely on diffusion MRI and their extension and refinement within that single contrast mechanism continues rapidly. However, a new generation of microstructure-imaging technique is just beginning to emerge that draws on multiple sources of MR contrast, for example combining diffusion MRI with relaxometry, susceptibility, etc. Such techniques offer great promise in the decades to come for the realisation of 'virtual histology' avoiding invasive procedures, such as biopsy, across a wide range of medical applications.EPSRC grant EP/E064280/1, which finished in 2011, developed the current state-of-the-art simulation system within the Camino toolkit. That system underpinned the early development of the microstructure-imaging paradigm, which led to current techniques like NODDI and VERDICT. However, the current system is insufficient to evaluate even current microstructure imaging techniques, because it excludes key effects that influence the diffusion MR signal. Moreover, its implementation limits the simulation to molecular diffusion as the only source of MR contrast, which fundamentally prevents its extension for validation of next-generation techniques. The new simulation system will use more sophisticated underlying models of tissue geometry and MR signal generation enabling it to support both modern diffusion-based microstructure-imaging applications and future multi-modal techniques. It provides a unique and invaluable validation tool allowing us to realise the full potential of quantitative non-invasive imaging in medicine and beyond. Within the project we demonstrate the new system by evaluating the performance of NODDI and VERDICT under a wide range of conditions. We also test two early examples of multi-modal microstructure imaging techniques paving the way for their robust development and eventual clinical translation.