Intensity normalization is an important preprocessing step in brain magnetic resonance image (MRI) analysis. During MR image acquisition, different scanners or parameters would be used for scanning different subjects or the same subject at a different time, which may result in large intensity variations. This intensity variation will greatly undermine the performance of subsequent MRI processing and population analysis, such as image registration, segmentation, and tissue volume measurement. In this work, we proposed a new histogram normalization method to reduce the intensity variation between MRIs obtained from different acquisitions. In our experiment, we scanned each subject twice on two different scanners using different imaging parameters. With noise estimation, the image with lower noise level was determined and treated as the high-quality reference image. Then the histogram of the low-quality image was normalized to the histogram of the high-quality image. The normalization algorithm includes two main steps: (1) intensity scaling (IS), where, for the high-quality reference image, the intensities of the image are first rescaled to a range between the low intensity region (LIR) value and the high intensity region (HIR) value; and (2) histogram normalization (HN),where the histogram of low-quality image as input image is stretched to match the histogram of the reference image, so that the intensity range in the normalized image will also lie between LIR and HIR. We performed three sets of experiments to evaluate the proposed method, i.e., image registration, segmentation, and tissue volume measurement, and compared this with the existing intensity normalization method. It is then possible to validate that our histogram normalization framework can achieve better results in all the experiments. It is also demonstrated that the brain template with normalization preprocessing is of higher quality than the template with no normalization processing. We have proposed a histogram-based MRI intensity normalization method. The method can normalize scans which were acquired on different MRI units. We have validated that the method can greatly improve the image analysis performance. Furthermore, it is demonstrated that with the help of our normalization method, we can create a higher quality Chinese brain template.

BACKGROUND AND PURPOSE: Anti-N-methyl-D-aspertate receptor encephalitis is an autoimmune-mediated disease without specific brain MRI features. Our aim was to investigate the brain MR imaging characteristics of anti-N-methyl-D-aspartate receptor encephalitis and their associations with clinical outcome at a 2-year follow-up. MATERIALS AND METHODS: We enrolled 53 patients with anti-N-methyl-D-aspartate receptor encephalitis and performed 2-year follow-up. Brain MRIs were acquired for all patients at the onset phase. The brain MR imaging manifestations were classified into 4 types: type 1: normal MR imaging findings; type 2: only hippocampal lesions; type 3: lesions not involving the hippocampus; and type 4: lesions in both the hippocampus and other brain areas. The modified Rankin Scale score at 2-year follow-up was assessed, and the association between the mRS and onset brain MR imaging characteristics was evaluated. RESULTS: Twenty-eight (28/53, 53%) patients had normal MR imaging findings (type 1), and the others (25/53, 47%) had abnormal MRI findings: type 2: 7 patients (13%); type 3: seven patients (13%); and type 4: eleven patients (21%). Normal brain MRI findings were more common in female patients (P = .02). Psychiatric and behavioral abnormalities were more common in adults (P = .015), and autonomic symptoms (P = .025) were more common in pediatric patients. The presence of hippocampal lesions (P = .008, OR = 9.584; 95% CI, 1.803–50.931) and relapse (P = .043, OR = 0.111; 95% CI, 0.013–0.930) was associated with poor outcome. CONCLUSIONS: Normal brain MRI findings were observed in half of the patients. Lesions in the hippocampus were the most common MR imaging abnormal finding. The presence of hippocampal lesions is the main MR imaging predictor for poor prognosis in patients with anti-N-methyl-D-aspartate receptor encephalitis.

We aim to clarify the mechanisms of acupuncture in treating mild cognitive impairment (MCI) and Alzheimer disease (AD) by using functional magnetic resonance imaging (fMRI). Thirty-six right-handed subjects (8 MCI patients, 14 AD patients, and 14 healthy elders) participated in this study. Clinical and neuropsychological examinations were performed on all the subjects. MRI data acquisition was performed on a SIEMENS verio 3-Tesla scanner. The fMRI study used a single block experimental design. We first acquired the baseline resting state data in the initial 3 minutes; we then acquired the fMRI data during the procession of acupuncture stimulation on the acupoints of Tai chong and Hegu for the following 3 minutes. Last, we acquired fMRI data for another 10 minutes after the needle was withdrawn. The preprocessing and data analysis were performed using the statistical parametric mapping (SPM8) software. Then the two-sample t-tests were performed between each two groups of different states. We found that during the resting state, brain activities in AD and MCI patients were different from those of control subjects. During the acupuncture and the second resting state after acupuncture, when comparing to resting state, there are several regions showing increased or decreased activities in MCI, AD subjects compared to normal subjects. Most of the regions were involved in the temporal lobe and the frontal lobe, which were closely related to the memory and cognition. In conclusion, we investigated the effect of acupuncture in AD and MCI patients by combing fMRI and traditional acupuncture. Our fMRI study confirmed that acupuncture at Tai chong (Liv3) and He gu (LI4) can activate certain cognitive-related regions in AD and MCI patients.

Neuroimaging studies have demonstrated that patients with Alzheimer’s disease presented disconnection syndrome. However, little is known about the alterations of interhemispheric functional interactions and underlying structural connectivity in the AD patients. In this study, we combined resting-state functional MRI and diffusion tensor imaging (DTI) to investigate interhemispheric functional and structural connectivity in 16 AD, 16 mild cognitive impairment (MCI), as well as 16 cognitive normal healthy subjects (CN). The pattern of the resting state interhemispheric functional connectivity was measured with a voxel-mirrored homotopic connectivity (VMHC) method. Decreased VMHC was observed in AD and MCI subjects in anterior brain regions including the prefrontal cortices and subcortical regions with a pattern of AD<MCI<CN. Increased VMHC was observed in MCI subjects in posterior brain regions with patterns of AD/CN < MCI (sensorimotor cortex) and AD < CN/MCI (occipital gyrus). DTI analysis showed the most significant difference among the three cohorts was the fractional anisotropy in the genu of corpus callosum, which was positively associated with the VMHC of prefrontal and subcortical regions. Across all the three cohorts, the diffusion parameters in the genu of corpus callosum and VMHC in the above brain regions had significant correlation with the cognitive performance. These results demonstrate that there are specific patterns of interhemispheric functional connectivity changes in the AD and MCI, which can be significantly correlated with the integrity changes in the midline white matter structures. These results suggest that VMHC can be used as a biomarker for the degeneration of the interhemispheric connectivity in AD.

Acupuncture has been used in the therapy of Alzheimer disease (AD); however, its neural mechanisms are still unclear. The aim of this study is to examine the effect of acupuncture on the functional connectivity in AD by using resting-state functional magnetic resonance imaging (rs-fMRI). Twenty-eight subjects (14 AD and 14 normal controls) participated in this study. The rs-fMRI data were acquired before and after acupuncture stimulation at the acupoints of Tai chong (Liv3) and Hegu (LI4). During the baseline resting state, by using the amplitude of low-frequency fluctuations (ALFF), we found a significantly decreased or increased ALFF in the AD patients relative to the controls. These regions were located in the right superior frontal gyrus (SFG), left postcentral gyrus, subgenual cingulate cortex (SCC), right middle cingulate cortex (MCC), right inferior frontal gyrus (IFG), right hippocampus and the right inferior temporal gyrus (ITG). Then, we selected these brain regions as seeds to investigate whether regional activity and functional connectivity could be modulated by acupuncture in the AD patients. When compared to the pre-acupuncture stage, several of the above regions showed an increased or decreased ALFF after acupuncture in the AD patients. In addition, the functional connectivity between the hippocampus and the precentral gyrus showed enhancement after acupuncture in the AD patients. Finally, there were close correlations between the functional activity, connectivity and clinical performance in the AD patients. The current study confirmed that acupuncture at Tai chong (Liv3) and He gu (LI4) can modulate functional activity and connectivity of specific cognition-related regions in AD patients.