Association between Gray and White Matter Lesions and Its Involvement in Clinical Symptoms of Alzheimer's-Type Dementia.

BACKGROUND: Not only gray matter lesions (GMLs) but also white matter lesions (WMLs) can play important roles in the pathology of Alzheimer's disease (AD). The progression of cognitive impairment (CI) and behavioral and psychological symptoms of dementia (BPSD) might be caused by a concerted effect of both GML and WML. OBJECTIVE: This study aimed to investigate the association between GML and WML and how they are involved in the symptoms of CI and BPSD in dementia patients by means of imaging technology. METHODS: Patients in our memory clinic, who were diagnosed with AD-type dementia or amnestic mild cognitive impairment (aMCI) and had undergone both single-photon emission computed tomography (SPECT) and brain MRI, were consecutively enrolled (n = 156; 61 males and 95 females; 79.8 ± 7.4 years old). Symptoms of CI and BPSD were obtained from patients' medical records. For the analysis of GMLs and WMLs, SPECT data and MRI T1-weighted images were used, respectively. This study followed the Declaration of Helsinki, and all procedures were approved by the institutional ethics committee. RESULTS: According to a multivariate analysis, disorientation and disturbed attention demonstrated a relationship between the precuneus and WMLs in both hemispheres. Hyperactivity in BPSD showed multiple correlations between GMLs on both sides of the frontal cortex and WMLs. Patients with aMCI presented more multiple correlations between GMLs and WMLs compared with those with AD-type dementia regarding dementia symptoms including BPSD. CONCLUSION: The interaction between GMLs and WMLs may vary depending on the symptoms of CI and BPSD. Hyperactivity in BPSD may be affected by the functional relationship between GMLs and WMLs in the left and right hemispheres. The correlation between GMLs and WMLs may be changing in AD-type dementia and aMCI.

Impact of hs-CRP concentration on brain structure alterations and cognitive trajectory in Alzheimer's disease.

Introduction: Present study was to investigate hs-CRP concentration, brain structural alterations, and cognitive function in the context of AD [Subjective cognitive decline (SCD), mild cognitive impairment (MCI), and AD]. Methods: We retrospectively included 313 patients (Mean age = 76.40 years, 59 SCD, 101 MCI, 153 AD) in a cross-sectional analysis and 91 patients (Mean age = 75.83 years, 12 SCD, 43 MCI, 36 AD) in a longitudinal analysis. Multivariable linear regression was conducted to investigate the relationship between hs-CRP concentration and brain structural alterations, and cognitive function, respectively. Results: Hs-CRP was positively associated with gray matter volume in the left fusiform (ß = 0.16, pFDR = 0.023) and the left parahippocampal gyrus (ß = 0.16, pFDR = 0.029). Post hoc analysis revealed that these associations were mainly driven by patients with MCI and AD. The interaction of diagnosis and CRP was significantly associated with annual cognitive changes (ß = 0.43, p = 0.008). Among these patients with AD, lower baseline CRP was correlated with greater future cognitive decline (r = -0.41, p = 0.013). Conclusion: Our study suggests that increased hs-CRP level may exert protective effect on brain structure alterations and future cognitive changes among patients already with cognitive impairment.

Tohoku Medical Megabank Brain Magnetic Resonance Imaging Study: Rationale, Design, and Background.

The Tohoku Medical Megabank Brain Magnetic Resonance Imaging Study (TMM Brain MRI Study) was established to collect multimodal information through neuroimaging and neuropsychological assessments to evaluate the cognitive function and mental health of residents who experienced the Great East Japan Earthquake (GEJE) and associated tsunami. The study also aimed to promote advances in personalized healthcare and medicine related to mental health and cognitive function among the general population. We recruited participants for the first (baseline) survey starting in July 2014, enrolling individuals who were participating in either the TMM Community-Based Cohort Study (TMM CommCohort Study) or the TMM Birth and Three-Generation Cohort Study (TMM BirThree Cohort Study). We collected multiple magnetic resonance imaging (MRI) sequences, including 3D T1-weighted sequences, magnetic resonance angiography (MRA), diffusion tensor imaging (DTI), pseudo-continuous arterial spin labeling (pCASL), and three-dimensional fluid-attenuated inversion recovery (FLAIR) sequences. To assess neuropsychological status, we used both questionnaire- and interview-based rating scales. The former assessments included the Tri-axial Coping Scale, Impact of Event Scale in Japanese, Profile of Mood States, and 15-item Depression, Anxiety, and Stress Scale, whereas the latter assessments included the Mini-Mental State Examination, Japanese version. A total of 12,164 individuals were recruited for the first (baseline) survey, including those unable to complete all assessments. In parallel, we returned the MRI results to the participants and subsequently shared the MRI data through the TMM Biobank. At present, the second (first follow-up) survey of the study started in October 2019 is underway. In this study, we established a large and comprehensive database that included robust neuroimaging data as well as psychological and cognitive assessment data. In combination with genomic and omics data already contained in the TMM Biobank database, these data could provide new insights into the relationships of pathological processes with neuropsychological disorders, including age-related cognitive impairment.

Impact of atrial fibrillation on the cognitive decline in Alzheimer's disease.

BACKGROUND: Atrial fibrillation (AF) is a strong risk factor for Alzheimer's disease (AD) independent of ischemic stroke. However, the clinicopathological impact of AF on the severity of AD has not been well elucidated. We aimed to investigate the clinical differences between dementia patients with AF and those without AF by means of imaging data. METHODS: Following approval from the institutional ethics committee, patients with newly diagnosed AD or amnestic mild cognitive impairment (aMCI) were retrospectively screened (n = 170, 79.5 ± 7.4 years old). Cognitive function was assessed using the Mini-Mental State Examination (MMSE). Based on the MRI data, the cerebral volume, cerebral microbleeds (CMBs), periventricular white matter lesions (WMLs), and deep WMLs were evaluated. The regional cerebral blood flow (rCBF) was measured using 123I-IMP SPECT. RESULTS: Of the patients, 14 (8.2%) and 156 (91.8%) had AF (AF group) and sinus rhythm (SR group), respectively. The AF group had significantly lower MMSE scores than the SR group (average [standard deviation (SD)]: 19.4 [4.4] and 22.0 [4.4], respectively; p = 0.0347). Cerebral volume and CMBs did not differ between the two groups. The periventricular WMLs, but not the deep WMLs, were significantly larger in the AF group than in the SR group (mean [SD] mL: 6.85 [3.78] and 4.37 [3.21], respectively; p = 0.0070). However, there was no significant difference in rCBF in the areas related to AD pathology between the two groups. CONCLUSION: AD and aMCI patients with AF showed worse cognitive decline along with larger periventricular WMLs compared to those with SR, although the reduction of rCBF was not different between patients with AF and SR. The white matter lesions may be a more important pathology than the impairment of cerebral blood flow in dementia patients with AF. A larger study is needed to confirm our findings in the future.

Impact of constipation on progression of Alzheimer's disease: A retrospective study.

BACKGROUND AND PURPOSE: In terms of the gut-brain axis, constipation has been considered to be an important factor of neurodegenerative diseases, although the exact mechanism is still controversial. Herein, we aimed to investigate the contribution of constipation to the progression of dementia in a retrospective study. METHODS: Patients of Alzheimer's disease(AD) and amnestic mild cognitive impairment were consecutively screened between January 2015 and December 2020, and those of whom brain MRI and neuropsychological tests were performed twice were enrolled in this study. Participants were classified into with constipation (Cons[+], n = 20) and without constipation (Cons[-], n = 64) groups. Laboratory data at the first visit were used. Regression analysis was performed in MMSE, ADAS-Cog, and the volumes of hippocampus on MRI-MPRAGE images and deep white matter lesions (DWMLs) on MRI-FLAIR images obtained at two different time points. RESULTS: The main finding was that the Cons[+] group showed 2.7 times faster decline in cognitive impairment compared with the Cons[-] group, that is, the liner coefficients of ADAS-Cog were 2.3544 points/year in the Cons[+] and 0.8592 points/year in the Cons[-] groups. Ancillary, changes of DWMLs showed significant correlation with the time span (p < 0.01), and the liner coefficients of DWMLs were 24.48 ml/year in the Cons[+] and 14.83 ml/year in the Cons[-] group, although annual rate of hippocampal atrophy was not different between the two groups. Moreover, serum homocysteine level at baseline was significantly higher in the Cons[+] group than Cons[-] group (14.6 ± 6.4 and 11.5 ± 4.2 nmol/ml, respectively: p = 0.03). CONCLUSION: There is a significant correlation between constipation and faster progression of AD symptoms along with expansion of DWMLs.

Association of the prefrailty with global brain atrophy and white matter lesions among cognitively unimpaired older adults: the Nakajima study.

Physical frailty has been associated with adverse outcomes such as dementia. However, the underlying structural brain abnormalities of physical frailty are unclear. We investigated the relationship between physical frailty and structural brain abnormalities in 670 cognitively unimpaired individuals (mean age 70.1 years). Total brain volume (TBV), hippocampal volume (HV), total white matter hypointensities volume (WMHV), and estimated total intracranial volume (eTIV) on the 3D T1-weighted images were automatically computed using FreeSurfer software. Participants were divided into two states of physical frailty (robust vs. prefrail) based on the revised Japanese version of the Cardiovascular Health Study criteria. The multivariable-adjusted mean values of the TBV-to-eTIV ratio was significantly decreased, whereas that of the WMHV-to-eTIV ratio was significantly increased in the prefrail group compared with the robust group. Slowness, one of the components of physical frailty, was significantly associated with reduced TBV-to-eTIV and HV-to-eTIV ratios, and slowness and weakness were significantly associated with an increased WMHV-to-eTIV ratio. Our results suggest that the prefrail state is significantly associated with global brain atrophy and white matter hypointensities. Furthermore, slowness was significantly associated with hippocampal atrophy.

Impact of Catheter Ablation on Brain Microstructure and Blood Flow Alterations for Cognitive Improvements in Patients with Atrial Fibrillation: A Pilot Longitudinal Study.

Atrial fibrillation (AF) predisposes patients to develop cognitive decline and dementia. Clinical and epidemiological data propose that catheter ablation may provide further benefit to improve neurocognitive function in patients with AF, but the underlying mechanism is poorly available. Here, we conducted a pilot prospective study to investigate whether AF ablation can alter regional cerebral blood flow (rCBF) and brain microstructures, using multimodal magnetic resonance imaging (MRI) technique. Eight patients (63 ± 7 years) with persistent AF underwent arterial-spin labeling (ASL) perfusion, 3D T1-structural images and cognitive test batteries before and 6 months after intervention. ASL and structural MR images were spatially normalized, and the rCBF and cortical thickness of different brain areas were compared between pre- and 6-month post-treatment. Cognitive-psychological function was improved, and rCBF was significantly increased in the left posterior cingulate cortex (PCC) (p = 0.013), whereas decreased cortical thickness was found in the left posterior insular cortex (p = 0.023). Given that the PCC is a strategic site in the limbic system, while the insular cortex is known to play an important part in the central autonomic nervous system, our findings extend the hypothesis that autonomic system alterations are an important mechanism explaining the positive effect of AF ablation on cognitive function.

Higher-resolution quantification of white matter hypointensities by large-scale transfer learning from 2D images on the JPSC-AD cohort.

White matter lesions (WML) commonly occur in older brains and are quantifiable on MRI, often used as a biomarker in Aging research. Although algorithms are regularly proposed that identify these lesions from T2-fluid-attenuated inversion recovery (FLAIR) sequences, none so far can estimate lesions directly from T1-weighted images with acceptable accuracy. Since 3D T1 is a polyvalent and higher-resolution sequence, it could be beneficial to obtain the distribution of WML directly from it. However a serious difficulty, both for algorithms and human, can be found in the ambiguities of brain signal intensity in T1 images. This manuscript shows that a cross-domain ConvNet (Convolutional Neural Network) approach can help solve this problem. Still, this is non-trivial, as it would appear to require a large and varied dataset (for robustness) labelled at the same high resolution (for spatial accuracy). Instead, our model was taught from two-dimensional FLAIR images with a loss function designed to handle the super-resolution need. And crucially, we leveraged a very large training set for this task, the recently assembled, multi-sites Japan Prospective Studies Collaboration for Aging and Dementia (JPSC-AD) cohort. We describe the two-step procedure that we followed to handle such a large number of imperfectly labeled samples. A large-scale accuracy evaluation conducted against FreeSurfer 7, and a further visual expert rating revealed that WML segmentation from our ConvNet was consistently better. Finally, we made a directly usable software program based on that trained ConvNet model, available at https://github.com/bthyreau/deep-T1-WMH.

Altruistic Social Activity, Depressive Symptoms, and Brain Regional Gray Matter Volume: Voxel-Based Morphometry Analysis From 8,695 Old Adults.

Altruistic social activity, such as giving support to others, has shown protective benefits on dementia risk and cognitive decline. However, the pathological mechanism is unclear. In the present study, we investigated the association between altruistic social activity and brain regional gray matter. Furthermore, to explore the psychological interplay in altruistic social activity, we tested mediating effect of depressive symptoms on brain regional gray matter. We performed a cross-sectional voxel-based morphology (VBM) analysis including 8 695 old adults (72.9 ± 6.1 years) from Japan Prospective Studies Collaboration for Aging and Dementia (JPSC-AD) Cohort. We measured altruistic social activities by self-report questionnaires, depressive symptoms by Geriatric Depression Scale (GDS)-short version. We employed the whole-brain VBM method to detect relevant structural properties related to altruistic social activity. We then performed multiple regression models to detect the mediating effect of depressive symptoms on particular brain regional gray matter volume while adjusting possible physical and social lifestyle covariables. We found that altruistic social activity is associated with larger gray matter volume in posterior insula, middle cingulate gyrus, hippocampus, thalamus, superior temporal gyrus, anterior orbital gyrus, and middle occipital gyrus. Depressive symptoms mediated over 10% on altruistic social activity and hippocampus volume, over 20% on altruistic social activity and cingulate gyrus volume. Our results indicated that altruistic social activity might preserve brain regional gray matter which are sensitive to aging and cognitive decline. Meanwhile, this association may be explained by indirect effect on depressive symptoms, suggesting that altruistic social activity may mitigate the neuropathology of dementia.

Impact of medium-chain triglycerides on gait performance and brain metabolic network in healthy older adults: a double-blind, randomized controlled study.

Nutritional supplementation with medium-chain triglycerides (MCTs) has the potential to increase memory function in elderly patients with frailty and dementia. Our aim was to investigate the effects of MCT on cognitive and gait functions and their relationships with focal brain metabolism and functional connectivity even in healthy older adults. Participants were blindly randomized and allocated to two groups: 18 g/day of MCT oil and matching placebo formula (control) administered as a jelly stick (6 g/pack, ingested three times a day). Gait analysis during the 6-m walk test, cognition, brain focal glucose metabolism quantified by 18F-fluorodeocyglucose positron emission tomography, and magnetic resonance imaging-based functional connectivity were assessed before and after a 3-month intervention. Sixty-three healthy, normal adults (females and males) were included. Compared with the control group, the MCT group showed better balance ability, as represented by the lower Lissajous index (23.1 ± 14.4 vs. 31.3 ± 18.9; P < 0.01), although no time × group interaction was observed in cognitive and other gait parameters. Moreover, MCT led to suppressed glucose metabolism in the right sensorimotor cortex compared with the control (P < 0.001), which was related to improved balance (r = 0.37; P = 0.04) along with increased functional connectivity from the ipsilateral cerebellar hemisphere. In conclusion, a 3-month MCT supplementation improves walking balance by suppressing glucose metabolism, which suggests the involvement of the cerebro-cerebellar network. This may reflect, at least in part, the inverse reaction of the ketogenic switch as a beneficial effect of long-term MCT dietary treatment.

Voxel-Based Morphometry Reveals a Correlation Between Bone Mineral Density Loss and Reduced Cortical Gray Matter Volume in Alzheimer's Disease.

Background: Decreased bone mineral density (BMD) was associated with poorer cognitive function and increased risk of Alzheimer's disease (AD). However, objective evidence for the relationship between osteoporosis and AD in humans has not been extensively described. Objectives: We aimed to evaluate the relationships between BMD and the cortical volumes of brain regions vulnerable to AD; hippocampus, parahippocampal gyrus, precuneus, posterior cingulate, and angular gyrus, using voxel-based morphometry (VBM), to investigate the association between bone loss and AD. Methods: A cohort of 149 consecutive elderly participants who complained of memory disturbance underwent high-resolution structural brain magnetic resonance imaging (MRI) and dual-energy X-ray absorptiometry (DXA). We used SPM12 software to conduct a voxel-based multiple regression analysis to examine the association between femoral neck BMD values and regional gray matter volume (rGMV) on structural T1-weighted MRI. Results: After adjusting for subject age, gender, total brain volume (TBV), and mini-mental state examination (MMSE) scores, the multiple regression analysis showed significant correlations between BMD loss and rGMV decline in the left precuneus, which is an important neural network hub vulnerable to AD. Conclusion: These data suggest that the bone and brain communicate with each other, as in "bone-brain crosstalk," and that control of BMD factors could contribute to cognitive function and help prevent AD.

Learning a cortical parcellation of the brain robust to the MRI segmentation with convolutional neural networks.

The parcellation of the human cortex into meaningful anatomical units is a common step of various neuroimaging studies. There have been multiple successful efforts to process magnetic resonance (MR) brain images automatically and identify specific anatomical regions, following atlases defined from cortical landmarks. Those definitions usually rely first on a high-quality brain surface reconstruction. On the other hand, when high accuracy is not a requirement, simpler methods based on warping a probabilistic atlas have been widely adopted. Here, we develop a cortical parcellation method for MR brain images based on Convolutional Neural Networks (ConvNets), a machine-learning method, with the goal of automatically transferring the knowledge obtained from surface analyses onto something directly applicable on simpler volume data. We train a ConvNet on a large (thousand) set of cortical ribbons of multiple MRI cohorts, to reproduce parcellations obtained from a surface method, in this case FreeSurfer. Further, to make the model applicable in a broader context, we force the model to generalize to unseen segmentations. The model is evaluated on unseen data of unseen cohorts. We characterize the behavior of the model during learning, and quantify its reliance on the dataset itself, which tends to give support for the necessity of large training sets, augmentation, and multiple contrasts. Overall, ConvNets can provide an efficient way to parcel MRI images, following the guidance established within more complex methods, quickly and accurately. The trained model is embedded within a open-source parcellation tool available at https://github.com/bthyreau/parcelcortex.

Morphological prediction of glaucoma by quantitative analyses of ocular shape and volume using 3-dimensional T2-weighted MR images.

Elongated axial length of the eye increases the morbidity of glaucoma. Myopia also associates with elongated axial length, and such ellipsoid shape of the eyeball strongly contributes its pathogenesis. Morphological features of the eyeballs, which could be important factors for developing glaucoma, have not been well described. The aim of this study was to investigate the three-dimensional (3D) topographic features of glaucomatous eyeballs with/without myopia to evaluate the potential of those features for predicting glaucoma. Using a 3.0-tesla MRI, volume-isotropic turbo-spin-echo acquisition T2-weighted images were obtained from 55 patients with glaucoma and 22 controls to delineate the eyeballs. Eyeball volumes, axial lengths and transverse lengths were semi-automatically calculated and compared between four groups: normal, myopia, glaucoma, and glaucoma with myopia. Both glaucoma and myopia increased the eyeball volume compared to the normal eyes. An increased anisotropy ratio (axial/transversus length) was observed in myopic eyes compared to normal, whereas in the glaucomatous eyes, with or without myopia, no increase in anisotropy ratio was observed. Increasing volume of eyes can be caused by myopia and glaucoma. Myopic eyes were ellipsoid in shape, but there was less anisotropy and a near-spherical shape in glaucomatous eyes, even in glaucomatous myopic eyes.

Comparing fully automated state-of-the-art cerebellum parcellation from magnetic resonance images.

The human cerebellum plays an essential role in motor control, is involved in cognitive function (i.e., attention, working memory, and language), and helps to regulate emotional responses. Quantitative in-vivo assessment of the cerebellum is important in the study of several neurological diseases including cerebellar ataxia, autism, and schizophrenia. Different structural subdivisions of the cerebellum have been shown to correlate with differing pathologies. To further understand these pathologies, it is helpful to automatically parcellate the cerebellum at the highest fidelity possible. In this paper, we coordinated with colleagues around the world to evaluate automated cerebellum parcellation algorithms on two clinical cohorts showing that the cerebellum can be parcellated to a high accuracy by newer methods. We characterize these various methods at four hierarchical levels: coarse (i.e., whole cerebellum and gross structures), lobe, subdivisions of the vermis, and the lobules. Due to the number of labels, the hierarchy of labels, the number of algorithms, and the two cohorts, we have restricted our analyses to the Dice measure of overlap. Under these conditions, machine learning based methods provide a collection of strategies that are efficient and deliver parcellations of a high standard across both cohorts, surpassing previous work in the area. In conjunction with the rank-sum computation, we identified an overall winning method.

Segmentation of the hippocampus by transferring algorithmic knowledge for large cohort processing.

The hippocampus is a particularly interesting target for neuroscience research studies due to its essential role within the human brain. In large human cohort studies, bilateral hippocampal structures are frequently identified and measured to gain insight into human behaviour or genomic variability in neuropsychiatric disorders of interest. Automatic segmentation is performed using various algorithms, with FreeSurfer being a popular option. In this manuscript, we present a method to segment the bilateral hippocampus using a deep-learned appearance model. Deep convolutional neural networks (ConvNets) have shown great success in recent years, due to their ability to learn meaningful features from a mass of training data. Our method relies on the following key novelties: (i) we use a wide and variable training set coming from multiple cohorts (ii) our training labels come in part from the output of the FreeSurfer algorithm, and (iii) we include synthetic data and use a powerful data augmentation scheme. Our method proves to be robust, and it has fast inference (<30s total per subject), with trained model available online (https://github.com/bthyreau/hippodeep). We depict illustrative results and show extensive qualitative and quantitative cohort-wide comparisons with FreeSurfer. Our work demonstrates that deep neural-network methods can easily encode, and even improve, existing anatomical knowledge, even when this knowledge exists in algorithmic form.

Phase Difference-Enhanced Magnetic Resonance (MR) Imaging (PADRE) Technique for the Detection of Age-Related Microstructural Changes in Optic Radiation: Comparison with Diffusion Tensor Imaging (DTI).

BACKGROUND The optic radiation (OR) is a white-matter bundle connecting the lateral geniculate body and the visual cortex. Phase difference-enhanced imaging (PADRE) is a new MRI technique that is able to achieve precise delineation of the OR. The aim of this study was to investigate the effect of age on the volume and signal intensity of the OR using PADRE, and to establish a volumetric reference of the OR from a healthy population, compared with diffusion tensor imaging (DTI). MATERIAL AND METHODS Thirty-nine healthy volunteers underwent MR imaging with PADRE and DTI sequences on a 3.0-T scanner. For the volumetric analysis with PADRE, the OR corresponding to the external sagittal stratum was manually traced, while an automated thresholding method was used for the DTI-based volumetric analysis of the OR. RESULTS The mean right and left OR volumes measured from the PADRE images were 1469.0±242.4 mm³ and 1372.6±310.2 mm³, respectively. Although OR volume showed no significant correlation with age, the normalized OR signal intensity showed a linear correlation with increasing age (r²=0.50-0.53; P<0.01). The OR signal intensity on PADRE and DTI-related quantitative parameters for the OR showed significant correlations (r²=0.46-0.49; P<0.01). CONCLUSIONS The PADRE technique revealed exceptional preservation of OR volume, even in later life. Moreover, PADRE was able to detect age-related changes in signal intensity of the OR and may contribute to future analyses of pathological neurodegeneration in patients with glaucoma and multiple sclerosis.

The neural basis of the imitation drive.

Spontaneous imitation is assumed to underlie the acquisition of important skills by infants, including language and social interaction. In this study, functional magnetic resonance imaging (fMRI) was used to examine the neural basis of 'spontaneously' driven imitation, which has not yet been fully investigated. Healthy participants were presented with movie clips of meaningless bimanual actions and instructed to observe and imitate them during an fMRI scan. The participants were subsequently shown the movie clips again and asked to evaluate the strength of their 'urge to imitate' (Urge) for each action. We searched for cortical areas where the degree of activation positively correlated with Urge scores; significant positive correlations were observed in the right supplementary motor area (SMA) and bilateral midcingulate cortex (MCC) under the imitation condition. These areas were not explained by explicit reasons for imitation or the kinematic characteristics of the actions. Previous studies performed in monkeys and humans have implicated the SMA and MCC/caudal cingulate zone in voluntary actions. This study also confirmed the functional connectivity between Urge and imitation performance using a psychophysiological interaction analysis. Thus, our findings reveal the critical neural components that underlie spontaneous imitation and provide possible reasons why infants imitate spontaneously.

Regional reliability of quantitative signal targeting with alternating radiofrequency (STAR) labeling of arterial regions (QUASAR).

BACKGROUND AND PURPOSE: Quantitative signal targeting with alternating radiofrequency labeling of arterial regions (QUASAR) is a recent spin labeling technique that could improve the reliability of brain perfusion measurements. Although it is considered reliable for measuring gray matter as a whole, it has never been evaluated regionally. Here we assessed this regional reliability. METHODS: Using a 3-Tesla Philips Achieva whole-body system, we scanned four times 10 healthy volunteers, in two sessions 2 weeks apart, to obtain QUASAR images. We computed perfusion images and ran a voxel-based analysis within all brain structures. We also calculated mean regional cerebral blood flow (rCBF) within regions of interest configured for each arterial territory distribution. RESULTS: The mean CBF over whole gray matter was 37.74 with intraclass correlation coefficient (ICC) of .70. In white matter, it was 13.94 with an ICC of .30. Voxel-wise ICC and coefficient-of-variation maps showed relatively lower reliability in watershed areas and white matter especially in deeper white matter. The absolute mean rCBF values were consistent with the ones reported from PET, as was the relatively low variability in different feeding arteries. CONCLUSIONS: Thus, QUASAR reliability for regional perfusion is high within gray matter, but uncertain within white matter.

Correlations between brain structures and study time at home in healthy children: a longitudinal analysis.

INTRODUCTION: Like sleeping and eating habits, the study habits adopted by children when they are at home are important contributors to lifestyle and they affect cognitive ability. It has recently been reported that sleeping and eating habits change the brain structure of children. However, no research on the effect of study habits at home on the brain structure of children has been conducted thus far. We investigated the effects of study habits at home on the brain structures of healthy children by examining correlations between study time at home and changes in brain structure over the course of 3 years. METHODS: We used the brain magnetic resonance images of 229 healthy children aged 5.6-18.4 years and computed the changes (time 2-time 1) in regional gray matter and white matter volume (rWMV) using voxel-based morphometry. Whole-brain multiple regression analysis revealed a significant positive correlation between study time at home and changes in rWMV in the right superior frontal gyrus (SFG). Behaviorally, we found a significant positive correlation between study time at home and change in the verbal comprehension index (VCI), one of the subscales of the Wechsler Intelligence Scale for Children-third edition (WISC-III). RESULTS AND CONCLUSIONS: Given that the SFG is involved in memory control and that the VCI measures abilities related to vocabulary, our results indicate that greater SFG involvement in the memorization component of longer study times may result in greater increases in the number of axons and more axon branching and myelination, causing plastic changes in the neural network involved in memory processes.

Spinal fMRI of interoceptive attention/awareness in experts and novices.

Many disciplines/traditions that promote interoceptive (inner sensation of body parts) attention/awareness (IAA) train practitioners to both attend to and be aware of interoceptive sensory experiences in body parts. The effect of such practices has been investigated in previous imaging studies but limited to cerebral neural activity. Here, for the first time, we studied the impact of these practices on the spinal neural activity of experts and novices. We also attempted to clarify the effect of constant and deep breathing, a paradigm utilized in concentration practices to avoid mind wandering, on IAA-related spinal neural activity. Subjects performed IAA tasks with and without a deep and constant breathing pattern in two sessions. Results showed that neural activity in the spinal segment innervating the attended-to body area increased in experts (P = 0.04) when they performed IAA and that this increase was significantly larger for experts versus novices in each of the sessions (P = 0.024). The significant effects of IAA and expertise on spinal neural activity are consistent with and elaborate on previous reports showing similar effects on cerebral neural activity. As the spinal cord directly innervates body parts, the results might indicate that IAA has an instantaneous (possibly beneficial) effect on the physical body after extended training.