MRI Simulation

There is a need for quantitative simulation of functional imaging experiments to: (1) validate existing analysis methods; (2) improve understanding of the interactions between acquisition and analysis; (3) provide forward models for artefact-reduction techniques. POSSUM (Physics-Oriented Simulated Scanner for Understanding MRI) is a simulation project designed to simulate the MR signal, starting from the fundamental physics. The inputs are in the form of general ``pulse sequence'' and ``motion'' files that specify gradients, RF pulses, sampling points and orientation as a function of time. Currently, the simulator uses the BrainWeb digital brain phantom [27] as the object model, but can use any sufficiently detailed voxel-based object model.

Our main research interest in the POSSUM simulator is in modelling the interaction of motion and acquisition in order to further understand motion artefacts in FMRI and develop methods for removing these artefacts. To do this the simulator has been designed so that it incorporates bulk motion directly at the Bloch equation level, allowing within-scan motion, spin-history effects and B0-motion interaction to be accurately modelled.

A consortium has recently been formed (with research groups at the Montreal Neurological Institute [27] and the University of Pittsburgh [36] who have complementary areas of expertise in instrumental and physiological aspects of FMRI modelling) to create a unified and comprehensive FMRI simulation environment named MIDAS (MR Imaging Data Acquisition Simulator: www.midas-online.org). Future work through this collaborative project will develop a simulator that incorporates the major sources of variation present in an FMRI acquisition: acquisition type (e.g., EPI, spiral-EPI, anatomical spin-echo), susceptibility artifacts, RF inhomogeneities, physiological noise, random noise, motion and activation. This simulator will be freely available to the FMRI community to aid researchers in validating their data processing streams and to provide insight into MRI physics.

Figure 12: Example of simulated functional MR images showing modelled artefacts: within-scan motion, ghosting, B0-inhomogeneities