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Evaluation of sub-voxel registration accuracy between MRI and 3D MR spectroscopy of the brain

The implementation of Magnetic Resonance Spectroscopic Imaging (MRSI) for diagnostic imaging benefits from close integration of the lower-spatial resolution MRSI information with information from high-resolution structural MRI. Since patients can commonly move between acquisitions, it is necessary to account for possible mis-registration between the datasets arising from differences in patient positioning. In this paper we evaluate the use of 4 common multi-modality registration criteria to recover alignment between high resolution structural MRI and 3D MRSI data of the brain with sub-voxel accuracy. We explore the use of alternative MRSI water reference images to provide different types of structural information for the alignment process. The alignment accuracy was evaluated using both synthetically created MRSI and MRI data and a set of carefully collected subject image data with known ground truth spatial transformation between image volumes. The final accuracy and precision of estimates were assessed using multiple random starts of the registration algorithm. Sub voxel accuracy was found by all four similarity criteria with normalized mutual information providing the lowest target registration error for the 7 subject images. This effort supports the ongoing development of a database of brain metabolite distributions in normal subjects, which will be used in the evaluation of metabolic changes in neurological diseases.