The voxel-based morphometry (VBM) technique using brain magnetic resonance imaging (MRI) objectively maps gray matter loss on a voxel-by-voxel basis after anatomic standardization. In patients with Alzheimer's disease (AD), reductions of gray matter volume, mainly in the medial temporal structures, have been reported; however, inhomogeneity and geometric distortion of the field intensity hampers the reproducibility of MRI. In the present study, we developed a novel computed tomography (CT)-based VBM method and used this technique to detect volume loss in AD patients as compared with normal controls. The results were compared with MRI-based VBM using the same subjects. Pittsburgh Compound B ((11)C-PIB) positron emission tomography (PET)/CT was performed and two experts in neuro-nuclear medicine judged whether regional amyloid β load was consistent with a diagnosis of AD. Before the injection of (11)C-PIB, high-quality CT scans were obtained using the same PET/CT equipment. MRI was performed within a mean interval of 25.1 ± 8.2 days before the PET/CT scan. Using statistical parametric mapping 8 (SPM8), the extracted gray matter images from CT and MRI were spatially normalized using a gray matter template and smoothed using a Gaussian kernel. Group comparisons were performed using SPM8 between five (11)C-PIB-positive patients with probable AD and seven (11)C-PIB-negative age-matched controls with normal cognition. Gray matter volumes in the bilateral medial temporal areas were reduced in the AD group as compared with the cognitively normal group in both CT-based VBM (in the left; P < 0.0001, cluster size 2776 and in the right; P < 0.0001, cluster size 630) and MRI-based VBM (in the left; P < 0.0001, cluster size 381 and in the right, P < 0.0001, cluster size 421). This newly developed CT-based VBM technique can detect significant atrophy in the entorhinal cortex in probable AD patients as previously reported using MRI-based VBM. However, CT-VBM was more sensitive and revealed larger areas of significant atrophy than MR-VBM.
