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Abstract
Objective: A procedure for acquisition, automated registration, and fusion of functional and anatomical magnetic resonance images is presented. Its accuracy is quantitatively assessed using a publicly available gold standard. A patient case is used to illustrate the technique's clinical usefulness in image-guided neurosurgery.
Materials and Methods: Before and after functional MRI (fMRI) acquisition, additional anatomical images were acquired at spatial locations identical to those of the functional images (5–10 slices) for the purpose of voxel-based image registration. Registration accuracy of the anatomical volumes and high-resolution 3D MRI volumes (MP-RAGE imaging) was quantified using adapted data (8 patients) originating from the Vanderbilt Retrospective Registration Evaluation Project (NIH project 1 R01 NS33926–02). Selecting three subsets of slices from that data (5 slices/6 mm slice distance, 10 slices/3 mm distance, and 10 slices/6 mm distance), the small number of images available from fMRI acquisition was taken into account. Accuracies in registering these sparse data sets were then compared to the accuracy achieved using complete data. For clinical patient data (16 patients), fMRI images were fused with MP-RAGE images, thereby integrating anatomical images with information about the locations of functional areas. The resulting images were used for planning and navigation during tumor resections using an operating microscope (MKM, Zeiss).
Results: Quantitative analysis showed no loss of registration accuracy due to a reduced number of slices, regardless of whether 5 or 10 slices were used. For small-volume coverage in the anatomical images (thickness 24 mm), registration of one patient failed, and this could easily be identified by visual inspection. No failures were experienced when 54 mm was covered. In the clinical environment, all 16 interventions using fused fMRI and MRI data were successful.