Search

The objectives of this study were to investigate how the extra-neurite conductivity (EC) and intra-neurite conductivity (IC) were reflected in Alzheimer's disease (AD) patients compared with old cognitively normal (CN) people and patients with amnestic mild cognitive impairment (MCI) and to evaluate the association between those conductivity values and cognitive decline. To do this, high-frequency conductivity (HFC) at the Larmor frequency was obtained using MRI-based electrical property tomography (MREPT) and was decomposed into EC and IC using information of multi-shell multi-gradient direction diffusion tensor images. This prospective single-center study included 20 patients with mild or moderate AD, 25 patients with amnestic MCI, and 21 old CN participants. After decomposing EC and IC from HFC for all participants, we performed voxel-based and regions-of-interest analyses to compare conductivity between the three participant groups and to evaluate the association with either age or the Mini-Mental State Examination (MMSE) scores. We found increased EC in AD compared to CN and MCI. EC was significantly negatively associated with MMSE scores in the insula, and middle temporal gyrus. EC might be used as an imaging biomarker for helping to monitor cognitive function., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier B.V. All rights reserved.)

Background: Apolipoprotein E (ApoE) ε4 carriers have a higher risk of developing Alzheimer's disease (AD) and show brain atrophy and cognitive decline even before diagnosis., Objective: To predict ApoE ε4 status using gray matter volume (GMV) obtained from magnetic resonance imaging images and demographic data with machine learning (ML) methods., Methods: We recruited 74 participants (25 probable AD, 24 amnestic mild cognitive impairment, and 25 cognitively normal older people) with known ApoE genotype (22 ApoE ε4 carriers and 52 noncarriers) and scanned them with three-dimensional (3D) T1-weighted (T1W) and 3D double inversion recovery (DIR) sequences. We extracted GMV from regions of interest related to AD pathology and used them as features along with age and mini-mental state examination (MMSE) scores to train different ML models. We performed both receiver operating characteristic curve analysis and the prediction analysis of the ApoE ε4 carrier with different ML models., Results: The best model of ML analyses was a cubic support vector machine (SVM3) that used age, the MMSE score, and DIR GMVs at the amygdala, hippocampus, and precuneus as features (AUC = .88). This model outperformed models using T1W GMV or demographic data alone., Conclusion: Our results suggest that brain atrophy with DIR GMV and cognitive decline with aging can be useful biomarkers for predicting ApoE ε4 status and identifying individuals at risk of AD progression., (© 2024 The Authors. Brain and Behavior published by Wiley Periodicals LLC.)

The oligomeric amyloid-β (oAβ) is a reliable feature for an early diagnosis of Alzheimer's disease (AD). Therefore, the objective of this study was to demonstrate imaging of oAβ deposits using our developed DNA aptamer called ob5 conjugated with gadolinium (Gd)-dodecane tetraacetic acid (DOTA) as a contrast agent for early diagnosis of AD using MRI. An oAβ-specific aptamer was developed by amide bond formation and conjugated to Gd-DOTA MRI contrast agent and/or cyanine5 (cy5). We verified the performance of our new contrast agent with an AD mouse model using in vivo and ex vivo fluorescent imaging and animal MRI experiments. The presence of soluble Aβ in 3xTg AD mice was detected using GdDOTA-ob5-cy5 probe ex vivo. Fluorescence intensities of the GdDOTA-ob5-cy5 contrast agent were high in the brains of 3xTg-AD mice, but relatively low in the brains of control mice. The GdDOTA-ob5 contrast agent had higher relaxivity than a clinically available contrast agent. T1-weighted MRI signals in 5-month-old 3xTg AD mice increased at 5 min, were prolonged until 10 min, then decreased 15 min after injecting the GdDOTA-ob5 contrast agent. Our targeted DNA aptamer GdDOTA-ob5 contrast agent could be potentially useful for validating the efficacy of a novel diagnostic contrast agent for selectively targeting neurotoxic oAβ. It could ultimately be used for early diagnosis of AD., (© 2022 John Wiley & Sons Ltd.)

Background: Amnestic mild cognitive impairment (aMCI) is often considered a precursor to Alzheimer's disease (AD) and represents a key therapeutic target for early intervention of AD. However, no treatments have been approved for MCI at present. Our previous pilot study has shown that Kami Guibi-tang (KGT), a traditional herbal prescription widely used in Korean medicine for treating amnesia, might be beneficial for improving general cognitive function of aMCI patients. We will conduct a larger-scale clinical trial to validate the findings of our pilot study and further examine the efficacy and safety of KGT in aMCI., Methods: This trial is designed as a randomized, double-blind, placebo-controlled clinical trial. A total of 84 aMCI patients will be recruited and randomized into the treatment and control groups. Participants will be administered either KGT or placebo granules for 24 weeks, with a follow-up period of 12 weeks after the last treatment. Primary outcomes will include changes in cognitive performance assessed using a neuropsychological test battery, called the Seoul Neuropsychological Screening Battery, between the baseline, post-intervention visit, and follow-up visit (24th and 36th week, respectively). Secondary outcomes will involve the rate of progression to AD, changes in neuroimaging signals assessed using structural magnetic resonance imaging (MRI), resting-state functional MRI (rs-fMRI), and task-based fMRI, and changes in blood biomarkers measured by the ratio of plasma amyloid-β 42/40 levels (Aβ42/Aβ40) between the baseline and post-intervention visit (24th week). For safety assessments, blood chemistry tests and electrocardiograms (ECG) will also be performed., Discussion: This study aims to provide confirmatory evidence of the effect of the Korean herbal medicine, KGT, on improving cognitive function in patients with aMCI. We will identify the possible mechanisms underlying the effects of KGT using neuroimaging signals and blood biomarkers., Trial Registration: Korean Clinical Trial Registry ( https://cris.nih.go.kr/cris/search/detailSearch.do/16918; Registration number: KCT0007039; Date of registration: February 24, 2022)., (© 2022. The Author(s).)

Progressive aggregation and protein misfolding are the initial fundamental indicators of neurodegenerative disorders such as Alzheimer's disease (AD). In this study, a highly sensitive and novel method to detect amyloid beta (Aβ) biomarkers, which are a hallmark of AD, using an immunoassay platform-based interdigitated capacitive biosensor, has been explored. For several decades, aptamers have classified as a novel class of molecular recognition probes comprising single-stranded complementary DNA sequences that bind to their identified targets with high specificity and affinity by an in vitro technique called SELEX (systematic evolution of exponential and enrichment). Aptamers, often referred to as "chemical antibodies", possess several highly obvious features for clinical use. The proposed sensing bio-device was fabricated and glazed with oligomeric Aβ (oAβ) aptamer and anti-oAβ antibody, functionalized onto a Pt/Ti-featured SiO 2 substrate. Subsequently, analytical studies were conducted to confirm that the specificity, sensitivity, and selective detection of the oAβ-based bioengineered surfaces facilitate a label-free approach. The bionic capacitive sensor achieved real-time detection within 5 s (faster response than ELISA) under the femto-molar range concentrations of oAβ peptide in plasma using anti-oAβ antibody and oAβ aptamer with ultra-high affinity. Furthermore, the prepared capacitive biochip was selective against plasma-borne antigens and standby for 100 days at 4 °C. The developed biosensor is suitable for point-of-care (POC) diagnostic applications owing to its portability and scalability. Furthermore, the superior efficacy of oAβ in identifying AD has huge potential for biomedical applications., (Copyright © 2022. Published by Elsevier B.V.)

Background: Longitudinal changes of brain metabolites during a functional stimulation are unknown in amnestic mild cognitive impairment (aMCI) and Alzheimer's disease (AD) subjects., Objective: This study was to evaluate the longitudinal changes of brain metabolites using proton magnetic resonance spectroscopy (1H MRS) in response to treatment during a memory task in the subjects of cognitive normal (CN), aMCI, and AD., Methods: We acquired functional magnetic resonance spectroscopy (fMRS) data from 28 CN elderly, 16 aMCI and 12 AD subjects during a face-name association task. We measured fMRS metabolite ratios over 24 months in the 8-month apart, determined the temporal changes of the metabolites, and evaluated the differences among the three groups under the three different conditions (base, novel, repeat)., Results: The results of comparisons for the three subject groups and the three-time points showed that tNAA/tCho and tCr/tCho were statistically significant among the three subject groups in any of the three conditions. The dynamic temporal change measurements for the metabolites for each condition showed that Glx/tCho and Glu/tCho levels at the third visit increased significantly compared with in the first visit in the novel condition in the AD group., Conclusion: We found declines in tNAA/tCho and tCr/tCho in the aMCI and AD subjects with increasing disease severity, being highest in CN and lowest in AD. The Glx/tCho level increased temporally in the AD subjects after they took an acetylcholine esterase inhibitor. Therefore, Glx may be suitable to demonstrate functional recovery after treatment., (Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.)

Background and Purpose: Limited evidence has suggested that a deep learning automatic brain segmentation and classification method, based on T1-weighted brain MR images, can predict Alzheimer disease. Our aim was to develop and validate a deep learning-based automatic brain segmentation and classification algorithm for the diagnosis of Alzheimer disease using 3D T1-weighted brain MR images., Materials and Methods: A deep learning-based algorithm was developed using a dataset of T1-weighted brain MR images in consecutive patients with Alzheimer disease and mild cognitive impairment. We developed a 2-step algorithm using a convolutional neural network to perform brain parcellation followed by 3 classifier techniques including XGBoost for disease prediction. All classification experiments were performed using 5-fold cross-validation. The diagnostic performance of the XGBoost method was compared with logistic regression and a linear Support Vector Machine by calculating their areas under the curve for differentiating Alzheimer disease from mild cognitive impairment and mild cognitive impairment from healthy controls., Results: In a total of 4 datasets, 1099, 212, 711, and 705 eligible patients were included. Compared with the linear Support Vector Machine and logistic regression, XGBoost significantly improved the prediction of Alzheimer disease ( P  < .001). In terms of differentiating Alzheimer disease from mild cognitive impairment, the 3 algorithms resulted in areas under the curve of 0.758-0.825. XGBoost had a sensitivity of 68% and a specificity of 70%. In terms of differentiating mild cognitive impairment from the healthy control group, the 3 algorithms resulted in areas under the curve of 0.668-0.870. XGBoost had a sensitivity of 79% and a specificity of 80%., Conclusions: The deep learning-based automatic brain segmentation and classification algorithm allowed an accurate diagnosis of Alzheimer disease using T1-weighted brain MR images. The widespread availability of T1-weighted brain MR imaging suggests that this algorithm is a promising and widely applicable method for predicting Alzheimer disease., (© 2020 by American Journal of Neuroradiology.)

Alzheimer's disease (AD) is the most common type of dementia. AD involves major pathologies such as amyloid-β (Aβ) plaques and neurofibrillary tangles in the brain. During the progression of AD, microglia can be polarized from anti-inflammatory M2 to pro-inflammatory M1 phenotype. The activation of triggering receptor expressed on myeloid cells 2 (TREM2) may result in microglia phenotype switching from M1 to M2, which finally attenuated Aβ deposition and memory loss in AD. Low-dose ionizing radiation (LDIR) is known to ameliorate Aβ pathology and cognitive deficits in AD; however, the therapeutic mechanisms of LDIR against AD-related pathology have been little studied. First, we reconfirm that LDIR (two Gy per fraction for five times)-treated six-month 5XFAD mice exhibited (1) the reduction of Aβ deposition, as reflected by thioflavins S staining, and (2) the improvement of cognitive deficits, as revealed by Morris water maze test, compared to sham-exposed 5XFAD mice. To elucidate the mechanisms of LDIR-induced inhibition of Aβ accumulation and memory loss in AD, we examined whether LDIR regulates the microglial phenotype through the examination of levels of M1 and M2 cytokines in 5XFAD mice. In addition, we investigated the direct effects of LDIR on lipopolysaccharide (LPS)-induced production and secretion of M1/M2 cytokines in the BV-2 microglial cells. In the LPS- and LDIR-treated BV-2 cells, the M2 phenotypic marker CD206 was significantly increased, compared with LPS- and sham-treated BV-2 cells. Finally, the effect of LDIR on M2 polarization was confirmed by detection of increased expression of TREM2 in LPS-induced BV2 cells. These results suggest that LDIR directly induced phenotype switching from M1 to M2 in the brain with AD. Taken together, our results indicated that LDIR modulates LPS- and Aβ-induced neuroinflammation by promoting M2 polarization via TREM2 expression, and has beneficial effects in the AD-related pathology such as Aβ deposition and memory loss.

Background: Because Alzheimer's Disease (AD) has very complicated pattern changes, it is difficult to evaluate it with a specific factor. Recently, novel machine learning methods have been applied to solve limitations., Objective: The objective of this study was to investigate the approach of classification and prediction methods using the Machine Learning (ML)-based Optimized Combination-Feature (OCF) set on Gray Matter Volume (GMV) and Quantitative Susceptibility Mapping (QSM) in the subjects of Cognitive Normal (CN) elderly, Amnestic Mild Cognitive Impairment (aMCI), and mild and moderate AD., Materials and Methods: 57 subjects were included: 19 CN, 19 aMCI, and 19 AD with GMV and QSM. Regions-of-Interest (ROIs) were defined at the well-known regions for rich iron contents and amyloid accumulation areas in the AD brain. To differentiate the three subject groups, the Support Vector Machine (SVM) with the three different kernels and with the OCF set was conducted with GMV and QSM values. To predict the aMCI stage, regression-based ML models were performed with the OCF set. The result of prediction was compared with the accuracy of clinical data., Results: In the group classification between CN and aMCI, the highest accuracy was shown using the combination of GMVs (hippocampus and entorhinal cortex) and QSMs (hippocampus and pulvinar) data using the 2nd SVM classifier (AUC = 0.94). In the group classification between aMCI and AD, the highest accuracy was shown using the combination of GMVs (amygdala, entorhinal cortex, and posterior cingulate cortex) and QSMs (hippocampus and pulvinar) data using the 2nd SVM classifier (AUC = 0.93). In the group classification between CN and AD, the highest accuracy was shown using the combination of GMVs (amygdala, entorhinal cortex, and posterior cingulate cortex) and QSMs (hippocampus and pulvinar) data using the 2nd SVM classifier (AUC = 0.99). To predict aMCI from CN, the exponential Gaussian process regression model with the OCF set using GMV and QSM data was shown the most similar result (RMSE = 0.371) to clinical data (RMSE = 0.319)., Conclusion: The proposed OCF based ML approach with GMV and QSM was shown the effective performance of the subject group classification and prediction for aMCI stage. Therefore, it can be used as personalized analysis or diagnostic aid program for diagnosis., (Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.)

Objective: The study aimed to investigate exchangeable proton signals of Aβ proteins of the brains of Alzheimer's disease (AD) model mice by using a chemical exchange-sensitive spin-lock (CESL) MR imaging technique., Method: Eight non-transgenic (Tg) mice (5 young and 3 old) and twelve Tg-APPswe/PSdE9 mice (5 young and 7 old) were used in this study. CESL Z-spectra were obtained by using two saturation powers, which were ω1 = 25 Hz with TSL = 3.0 s and ω1 = 500 Hz with TSL = 150 ms, at 71 offsets with uneven intervals between the offset frequencies at Ω = ±7.0 ppm at a 9.4-T animal MRI system. For Zspectrum analyses, regions of interest (ROIs) were drawn in the cortex, hippocampus, and thalamus of both hemispheres. Magnetization transfer ratio asymmetry (MTRasym) curves were obtained from the Zspectra. The Mann-Whitney test was used to compare the MTRasym values between the Tg and non-Tg mice for each offset frequency and for each ROI., Results: The water saturation width of the full Z-spectrum was narrow with the 25-Hz saturation power, but relatively broad with the 500-Hz saturation power. With the 25-Hz CESL saturation power, most of the MTRasym values were negative for 3.5-, 3.0-, 2.0-, and 0.9-ppm offset frequencies and the MTRasym values were significantly different between the control and Tg groups only in the left thalamus region at 3.5 ppm offset (p=0.0487). The MTRasym values were -6% to -7% for both 3.5 and 3.0 ppm, but less than -2% for both 2.0 and 0.9 ppm. With 500-Hz CESL saturation power, all the MTRasym values were positive for the 3.5-, 3.0-, 2.0-, and 0.9-ppm offset frequencies and the MTRasym values were not significantly different between the control and Tg groups at all ROIs and at all offset frequencies. However, a trend towards a significant difference was observed between the control and Tg groups in the right cortex at 3.5 ppm (p=0.0578). The MTRasym values were 6% to 9% for 3.5, 3.0, and 2.0 ppm, but less than 2% for 0.9 ppm., Conclusion: In an in-vivo AD model experiment, MTRasym values increased with the high saturation power than with the low saturation power. The MTRasym values were not significantly different, except in the left thalamus region at 3.5 ppm offset. The CESL technique should be further developed to enable its application in the brain of patients with neurodegenerative diseases., (Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.)

The objective of this study was to evaluate susceptibility changes caused by iron accumulation in cognitive normal (CN) elderly, those with amnestic mild cognitive impairment (aMCI), and those with early state AD, and to compare the findings with gray matter volume (GMV) changes caused by neuronal loss. The participants included 19 elderly CN, 19 aMCI, and 19 AD subjects. The voxel-based quantitative susceptibility map (QSM) and GMV in the brain were calculated and the differences of those insides were compared among the three groups. The differences of the QSM data and GMVs among the three groups were investigated by voxel-based and region of interest (ROI)-based comparisons using a one-way analysis of covariance (ANCOVA) test with the gender and age as covariates. Finally, a receiver-operating-characteristic (ROC) curve analysis was performed. The voxel-based results showed that QSM demonstrated more areas with significant difference between the CN and AD groups compared to GMV. GMVs were decreased, but QSM values were increased in aMCI and AD groups compared with the CN group. QSM better differentiated aMCI from CN than GMV in the precuneus and allocortex regions. In the accumulation regions of iron and amyloid β, QSM can be used to differentiate between CN and aMCI groups, indicating a useful an auxiliary imaging for early diagnosis of AD.

Our goal was to investigate whether three-dimensional (3D) double inversion recovery (DIR) images can show alterations of gray matter volume (GMV) between Alzheimer's disease (AD) patients and nondemented controls and to compare alterations of GMV between groups using DIR images and those using 3D T1-weighted (T1W) images. We included 25 subjects with mild or probable AD, 25 subjects with amnestic mild cognitive impairment (MCI), and 25 elderly cognitively normal (CN) subjects. Group differences in GMV among CN, MCI, and AD patients were tested by voxel-wise, one-way ANOVA. Additional region-of-interest-based comparisons of GMV differences among the three groups for DIR and T1WI were performed using ANCOVA. Finally, ROC curve analysis was performed. In the AD group compared with the CN and MCI groups, GMV was decreased in both DIR and T1W images. However, the areas showing GMV loss were larger in DIR images compared to those in T1W images. Amygdala had the highest area under curve value for both DIR and T1W images. DIR images were sensitive for identifying GMV loss in patients with AD compared with MCI and CN subjects and areas showing GMV loss identified with DIR were extended to more brain areas than those identified with T1W. With DIR, amygdala GMV is the most sensitive in differentiating between subject groups.

Purpose: Although a number of studies have focused on finding anatomical regions in which iron concentrations are high, no study has been conducted to examine the overall variations in susceptibility maps of Alzheimer's disease (AD). The objective of this study, therefore, was to differentiate AD from cognitive normal (CN) and mild cognitive impairment (MCI) using a texture analysis of quantitative susceptibility maps (QSMs)., Methods: The study was approved by the local institutional review board, and informed consent was obtained from all subjects. In each participant group-CN, MCI, and AD-18 elderly subjects were enrolled. A fully first-order flow-compensated 3D gradient-echo sequence was run to obtain axial magnitudes and phase images and to produce QSM data. Sagittal structural 3D T1-weighted (3DT1W) images were also obtained with the magnetization-prepared rapid acquisition of gradient-echo sequence to obtain brain tissue images. The first- and second-order texture parameters of the QSMs and 3DT1W images were obtained to evaluate group differences using a one-way analysis of covariance., Results: For the first-order QSM analysis, mean, standard deviation, and covariance of signal intensity separated the subject groups (F = 5.191, p = 0.009). For the second-order analysis, angular second moment, contrast, and correlation separated the subject groups (F = 6.896, p = 0.002). Finally, a receiver operating characteristic curve analysis differentiated MCI from CN in white matter on the QSMs (z = 3.092, p = 0.0020)., Conclusions: This was the first study to evaluate the textures of QSM in AD, which overcame the limitations of voxel-based analyses. The QSM texture analysis successfully distinguished both AD and MCI from CN and outperformed the voxel-based analysis using 3DT1-weighed images in separating MCI from CN. The first-order textures were more efficient in differentiating MCI from CN than did the second-order.

Background: The metabolite response during a memory task in Alzheimer's disease (AD) patients is unknown., Objective: To investigate the metabolite changes in subjects with AD, amnestic mild cognitive impairment (aMCI), and cognitively normal (CN) elderly during a memory task using functional magnetic resonance spectroscopy (fMRS)., Methods: This study involved 23 young normal controls (YC), 24 CN elderly, 24 aMCI, and 24 mild and probable AD individuals. fMRS data were acquired at the precuneus and posterior cingulate brain regions during a face-name association task. Statistical analyses of quantified metabolites were performed to evaluate differences of the metabolite values between the stimulation conditions and among the four subject groups. Receiver operating curve analysis was performed to evaluate whether the metabolic changes after functional activations can differentiate the subject groups., Result: Glutamine and glutamate complex (Glx) was statistically significantly different between the fixation and repeat conditions in aMCI (p = 0.0492) as well as between the fixation and the novel conditions in the AD (p = 0.0412) group. The total N-acetylaspartate (tNAA) was statistically significantly different among the four subject groups in the fixation condition (DF = 3, F = 7.673, p <  0.001), the novel condition (DF = 3, F = 6.945, p <  0.001), and the repeat condition (DF = 3, F = 7.127, p <  0.001). tNAA, tCr, and mIns could be used to differentiate CN from aMCI. Furthermore, tNAA, tCr, Glx, and Glu could also differentiate CN from AD, and aMCI from AD., Conclusion: Glx was altered during a stimulation that may be used to evaluate neuronal dysfunction in a demented patient. tNAA and tCr were reduced in patients with AD.

Introduction: The objective of this study was to evaluate the effect of apolipoprotein E (APOE) epsilon 4 allele on regional cerebral perfusion (rCBF) changes using arterial spin labeling (ASL) magnetic resonance imaging (MRI) in subjects who are carriers or noncarriers of this risk factor for Alzheimer disease (AD)., Methods: Twenty-five subjects with AD, 25 with amnestic mild cognitive impairment (MCI) and 25 cognitively normal (CN) subjects underwent isotropic volumetric T1-weighted imaging and pulsed ASL MRI. All subjects were divided into carrier or noncarriers of the epsilon4 allele. Voxel-based statistical analyses were performed among groups on rCBF by ANOVA tests. In each subject group, we also evaluated the rCBF change between carrier and noncarrier groups., Results: rCBF was significantly reduced in AD subjects compared to other subjects. In CN and AD subjects, rCBF in the carrier group was significantly reduced in several areas of the brain compared with that of the noncarrier group. In the carrier group, rCBF was significantly increased in the right parahippocampal gyrus, the bilateral cingulate gyri and the right posterior cingulate on the MCI group in addition to the right superior frontal gyrus in the AD group., Conclusion: rCBF in the CN and AD groups were significantly reduced in the subjects with the carriers of the epsilon4 allele, which is a risk factor for Alzheimer's disease. In addition, rCBF in the MCI group was significantly increased in subjects who were carriers. Therefore, rCBF can be used as a biomarker to show disease progression in areas of the brain of MCI subjects.

Purpose: Mapping of the distribution of local susceptibility strength could be very important in understanding the mechanisms of progression in neurodegenerative diseases, due to depositions of iron and iron-containing plaques. The goal of this study is to map the voxelwise distribution of local cross-term b-value (b(c)) effect caused by interactions between the external and internal gradients, in subjects with Alzheimer's disease (AD), mild cognitive impairment (MCI), and cognitively normal (CN) elderly, using a diffusion tensor (DT) MRI., Methods: Two DT-MRI experiments were conducted with opposite polarities of the external diffusion-sensitizing gradients, and the authors modeled the 3 × 3 tensor matrix of b(c) maps and drove a rotationally independent mean b(c) (i.e., MB(c)) maps. To test whether AD has higher cross-term gradients than MCI and∕or CN, 15 AD patients, 18 MCI patients, and 16 CN controls were acquired from DT-MRI data, with six diffusion encoding directions, five b-values (0, 160, 360, 640, and 1000 s∕mm(2)), and positively and negatively alternating polarities of the external diffusion-sensitizing gradients. The b(c) and MB(c) maps were calculated and were spatially normalized into a study specific template for all subjects. The differences of MB(c) maps across the three subject groups were investigated with voxelwise one-way ANOVA tests for each b-value. The differences of MB(c) maps, among the four b-values, were also investigated with a voxelwise one-way within-subject ANOVA test for each group., Results: The authors successfully mapped the local cross-term strength, using a DT-MRI data in the three groups. The MB(c) differences between the groups were increased with increasing b-values. Compared with the CN group and the MCI group, MB(c) values in the AD group were significantly increased. However, compared with the CN group, MB(c) values in the MCI group were not significantly different for all the b-values., Conclusions: In order to map the b-matrix cross-term effect, the authors developed a rotationally invariant index of MB(c), and the index was applied in AD, MCI, and CN subjects. In the AD group, compared with the MCI and CN groups, MB(c) values were increased. AD patients may have much more local intrinsic gradients in the brain than those MCI or CN subjects. MB(c) maps may be used to detect the intrinsically susceptible materials in the human brain, such as iron-containing plaques in the brain with AD.

Recent studies with positron emission tomography (PET) using the Pittsburgh compound B (PIB) found widespread amyloid plaque depositions in patients with Alzheimer's disease (AD) and mild cognitive impairment (MCI) and even in cognitively normal (CN) subjects. The aim of this study was to investigate whether the local susceptibility gradients in brain tissue alter regional diffusion measurements using MRI in patients with AD and MCI. Two diffusion tensor (DT)-MRI data sets were acquired with alternating polarities of the external diffusion-sensitizing gradients. Three subject groups were included: 15 patients with AD, 18 patients with MCI and 16 CN. Maps of mean diffusivity (MD) and fractional anisotropy (FA) were computed separately for positive (p) and negative (n) polarities (pMD and nMD, pFA and nFA). Voxel-wise paired t-tests were performed between pMD versus nMD or between pFA versus nFA maps, separately for each subject group. We also investigated regions-of-interest (ROIs) in the brain. Based on the pair-wise comparisons, we found significant differences between pMD and nMD in all three groups. Results of ROI-based analyses showed that the non-linear behaviors of the ROI data sets were shown for all three groups. In conclusion, significant differences of MD maps between the two polarities of diffusion-sensitizing gradients were found, suggesting that the intrinsic background gradients may alter MD signals in specific regions. It can be important to take into account the effects of local gradient alterations during diffusion measurements in patients with AD, MCI and elderly controls.

Introduction: The objective of the study was to explore the impact of the background gradients on diffusion tensor (DT) magnetic resonance imaging (DT-MRI) in patients with Alzheimer's disease (AD), mild cognitive impairment (MCI), or cognitively normal (CN) aging., Methods: Two DT-MRI sets with positive and negative polarities of the diffusion-sensitizing gradients were obtained in 15 AD patients, 18 MCI patients, and 16 CN control subjects. The maps of mean diffusivity (MD) and fractional anisotropy (FA) were computed separately for positive (p: pMD and pFA) and negative (n: nMD and nFA) polarities, and we computed the geometric mean (gm) of the DT-MRI to obtain the gmFA and gmMD with reducing the background gradient effects. Regional variations were assessed across the groups using one-way analysis of variance., Results: Increased regional gmMD values in the AD subjects, as compared to the regional gmMD values in the MCI and CN subjects, were found primarily in the frontal, limbic, and temporal lobe regions. We also found increased nMD and pMD values in the AD subjects compared to those values in the MCI and CN subjects, including in the temporal lobe and the left limbic parahippocampal gyrus white matter. Results of comparisons among the three methods showed that the left limbic parahippocampal gyrus and right temporal gyrus were the increased MD in the AD patients for all three methods., Conclusion: Background gradients affect the DT-MRI measurements in AD patients. Geometric average diffusion measures can be useful to minimize the intrinsic local magnetic susceptibility variations in brain tissue.

Accumulated amyloid-β (Aβ) is a well-known cause of neuronal apoptosis in Alzheimer disease and functions in part by generating oxidative stress. Our previous work suggested that cyclophilin B (CypB) protects against endoplasmic reticulum (ER) stress. Therefore, in this study we examined the ability of CypB to protect against Aβ toxicity. CypB is present in the neurons of rat and mouse brains, and treating neural cells with Aβ(25-35) mediates apoptotic cell death. Aβ(25-35)-induced neuronal toxicity was inhibited by the overexpression of CypB as measured by cell viability, apoptotic morphology, sub-G1 cell population, intracellular reactive oxygen species accumulation, activated caspase-3, PARP cleavage, Bcl-2 proteins, mitogen-activated protein kinase (MAPK) activation, and phosphoinositide 3-kinase (PI-3-K) activation. CypB/R95A PPIase mutants did not reduce Aβ(25-35) toxicity. We showed that Aβ(25-35)-induced apoptosis is more severe in a CypB knockdown model, confirming that CypB protects against Aβ(25-35)-induced toxicity. Consequently, these findings suggest that CypB may protect against Aβ toxicity by its antioxidant properties, by regulating MAPK and PI-3-K signaling, and through the ER stress pathway., (Copyright © 2011 Elsevier Inc. All rights reserved.)

Background: Neuroimaging in mild cognitive impairment (MCI) and Alzheimer disease (AD) generally shows medial temporal lobe atrophy and diminished glucose metabolism and cerebral blood flow in the posterior cingulate gyrus. However, it is unclear whether these abnormalities also impact the cingulum fibers, which connect the medial temporal lobe and the posterior cingulate regions., Objective: To use diffusion tensor imaging (DTI), by measuring fractional anisotropy (FA), to test 1) if MCI and AD are associated with DTI abnormalities in the parahippocampal and posterior cingulate regions of the cingulum fibers; 2) if white matter abnormalities extend to the neocortical fiber connections in the corpus callosum (CC); 3) if DTI improves accuracy to separate AD and MCI from healthy aging vs structural MRI., Methods: DTI and structural MRI were preformed on 17 patients with AD, 17 with MCI, and 18 cognitively normal (CN) subjects., Results: FA of the cingulum fibers was significantly reduced in MCI, and even more in AD. FA was also significantly reduced in the splenium of the CC in AD, but not in MCI. Adding DTI to hippocampal volume significantly improved the accuracy to separate MCI and AD from CN., Conclusion: Assessment of the cingulum fibers using diffusion tensor imaging may aid early diagnosis of Alzheimer disease.

Objectives: To test if arterial spin labeling (ASL) MRI could detect a pattern of hypoperfusion in frontotemporal dementia (FTD) vs cognitively normal (CN) control subjects; to determine the regional difference of perfusion between FTD and Alzheimer disease (AD); and to determine whether hypoperfusion in FTD correlates with cognitive impairment., Methods: We included 21 patients with FTD, 24 patients with AD, and 25 CN subjects in this cross-sectional MRI study. All subjects had MRI scans including T1-weighted structural images and ASL-MR images., Results: ASL-MRI detected a pattern of hypoperfusion in right frontal regions in patients with FTD vs CN subjects, similar to PET and SPECT. FTD had higher perfusion than AD in the parietal regions and posterior cingulate. Frontal hypoperfusion in FTD correlated with deficits in judgment and problem solving. Adding frontal perfusion to gray matter (GM) atrophy significantly improved the classification of FTD from normal aging to 74%, and adding parietal perfusion to GM atrophy significantly improved the classification of FTD from AD to 75%. Combining frontal and parietal lobe perfusion further improved the classification of FTD from AD to 87%., Conclusion: Frontotemporal dementia and Alzheimer disease display different spatial distributions of hypoperfusion on arterial spin labeling MRI. With further development and evaluation, arterial spin labeling MRI could contribute to the differential diagnosis between frontotemporal dementia and Alzheimer disease.

In Alzheimer's disease (AD), atrophy negatively impacts cognition while in healthy adults, inverse relationships between brain volume and cognition may occur. We investigated correlations between gray matter volume and cognition in elderly controls, AD and mild cognitive impairment (MCI) patients with memory and executive deficits. AD demonstrated substantial loss in temporal, parietal and frontal regions while MCI exhibited moderate volume loss in temporal and frontal regions. In controls, memory and executive function were negatively correlated with frontal regions, while in AD, memory was positively correlated with temporal and frontal gyri, and executive function with frontal regions. The combination of the two patterns may explain the lack of correlations in MCI. Developmental versus pathological contributions to these relationships are discussed.

We developed a new flexible approach for a co-analysis of multi-modal brain imaging data using a non-parametric framework. In this approach, results from separate analyses on different modalities are combined using a combining function and assessed with a permutation test. This approach identifies several cross-modality relationships, such as concordance and dissociation, without explicitly modeling the correlation between modalities. We applied our approach to structural and perfusion MRI data from an Alzheimer's disease (AD) study. Our approach identified areas of concordance, where both gray matter (GM) density and perfusion decreased together, and areas of dissociation, where GM density and perfusion did not decrease together. In conclusion, these results demonstrate the utility of this new non-parametric method to quantitatively assess the relationships between multiple modalities.

Purpose: To prospectively determine if pulsed arterial spin-labeling perfusion magnetic resonance (MR) imaging depicts regional cerebral hypoperfusion in subjects with Alzheimer disease (AD) and mild cognitive impairment (MCI), compared with perfusion in cognitively normal (CN) subjects, that is consistent with results of fluorodeoxyglucose (FDG) positron emission tomography (PET) and hexamethylpropyleneamine oxime (HMPAO) single photon emission computed tomography (SPECT) studies of similar populations., Materials and Methods: Institutional review board approval and informed consent were obtained. Twenty subjects with AD (13 men, seven women; mean age, 72.9 years), 18 with MCI (nine men, nine women; mean age, 73.3 years), and 23 CN subjects (10 men, 13 women; mean age, 72.9 years) underwent arterial spin-labeling and volumetric T1-weighted structural MR imaging. Perfusion images were coregistered to structural images, corrected for partial volume effects (PVEs) with information from the structural image to determine tissue content of perfusion voxels, and normalized to a study-specific template. Analyses of perfusion differences between groups, with and without corrections for PVEs, were performed on a voxel-by-voxel basis with a one-tailed fixed-effects analysis of covariance model adjusted for age. In addition, tests were performed with and without accounting for global perfusion., Results: The AD group showed significant regional hypoperfusion, compared with the CN group, in the right inferior parietal cortex extending into the bilateral posterior cingulate gyri (P <.001), bilateral superior and middle frontal gyri (P <.001), and left inferior parietal lobe (P=.007). When PVEs from underlying cortical gray matter atrophy were accounted for, the AD group still showed hypoperfusion in the right inferior parietal lobe extending into the bilateral posterior cingulate gyri (P <.001) and left (P=.003) and right (P=.012) middle frontal gyri. With a more liberal voxel-level threshold of P <.01, the MCI group showed significant regional hypoperfusion relative to the CN group in the inferior right parietal lobe (P=.046), similar to the region of greatest significance in the AD group., Conclusion: Arterial spin-labeling MR imaging showed regional hypoperfusion with AD, in brain regions similar to those seen in FDG PET and HMPAO SPECT studies of similar populations; this hypoperfusion persists after accounting for underlying cortical gray matter atrophy.

A new method, based on a deformable shape-intensity model (DSM), was developed to improve the signal-to-noise ratio (SNR) of multidimensional magnetic resonance spectroscopic imaging (MRSI) data sets without affecting spectral lineshapes and linewidths. Improvements with DSM, compared to digital filters using conventional signal apodization, were demonstrated on both simulated and experimental in vivo (1)H MRS images from 22 cognitively normal (CN) elderly subjects and 25 patients with Alzheimer's disease (AD). Simulated MRSI data showed that DSM achieved superior noise suppression compared to a matched apodization filter. Experimental MRSI data showed that SNR could be increased 2.1-fold with DSM without distorting spectral resolution, thus maintaining all spectral features of the raw, unfiltered data. In conclusion, DSM should be used to achieve high SNR in reconstructing MRSI data., (Copyright 2003 Wiley-Liss, Inc.)