Lipocalin-type prostaglandin D synthase: a glymphopathy marker in idiopathic hydrocephalus.

Idiopathic normal pressure hydrocephalus in elderly people is considered a form of glymphopathy caused by malfunction of the waste clearance pathway, called the glymphatic system. Tau is a representative waste material similar to amyloid-ß. During neurodegeneration, lipocalin-type prostaglandin D synthase (L-PGDS), a major cerebrospinal fluid (CSF) protein, is reported to act as a chaperone that prevents the neurotoxic aggregation of amyloid-ß. L-PGDS is also a CSF biomarker in idiopathic normal pressure hydrocephalus and significantly correlates with tau concentration, age, and age-related brain white matter changes detected by magnetic resonance imaging. To investigate this glymphopathy, we aimed to analyze white matter changes and contributing factors in vivo and their interactions ex vivo. Cerebrospinal tap tests were performed in 60 patients referred for symptomatic ventriculomegaly. Patients were evaluated using an idiopathic normal pressure hydrocephalus grading scale, mini-mental state examination, frontal assessment battery, and timed up-and-go test. The typical morphological features of high convexity tightness and ventriculomegaly were measured using the callosal angle and Evans index, and parenchymal white matter properties were evaluated with diffusion tensor imaging followed by tract-based spatial statistics. Levels of CSF biomarkers, including tau, amyloid-ß, and L-PGDS, were determined by ELISA, and their interaction, and localization were determined using immunoprecipitation and immunohistochemical analyses. Tract-based spatial statistics for fractional anisotropy revealed clusters that positively correlated with mini-mental state examination, frontal assessment battery, and callosal angle, and clusters that negatively correlated with age, disease duration, idiopathic normal pressure hydrocephalus grading scale, Evans index, and L-PGDS. Other parameters also indicated clusters that correlated with symptoms, microstructural white matter changes, and L-PGDS. Tau co-precipitated with L-PGDS, and colocalization was confirmed in postmortem specimens of neurodegenerative disease obtained from the human Brain Bank. Our study supports the diagnostic value of L-PGDS as a surrogate marker for white matter integrity in idiopathic normal pressure hydrocephalus. These results increase our understanding of the molecular players in the glymphatic system. Moreover, this study indicates the potential utility of enhancing endogenous protective factors to maintain brain homeostasis.

Traveling Subject-Informed Harmonization Increases Reliability of Brain Diffusion Tensor and Neurite Mapping.

Diffusion-weighted magnetic resonance imaging (dMRI) of brain has helped elucidate the microstructural changes of psychiatric and neurodegenerative disorders. Inconsistency between MRI models has hampered clinical application of dMRI-based metrics. Using harmonized dMRI data of 300 scans from 69 traveling subjects (TS) scanning the same individuals at multiple conditions with 13 MRI models and 2 protocols, the widely-used metrics such as diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI) were evaluated before and after harmonization with a combined association test (ComBat) or TS-based general linear model (TS-GLM). Results showed that both ComBat and TS-GLM significantly reduced the effects of the MRI site, model, and protocol for diffusion metrics while maintaining the intersubject biological effects. The harmonization power of TS-GLM based on TS data model is more powerful than that of ComBat. In conclusion, our research demonstrated that although ComBat and TS-GLM harmonization approaches were effective at reducing the scanner effects of the site, model, and protocol for DTI and NODDI metrics in WM, they exhibited high retainability of biological effects. Therefore, we suggest that, after harmonizing DTI and NODDI metrics, a multisite study with large cohorts can accurately detect small pathological changes by retaining pathological effects.

Deep Learning-Driven Transformation: A Novel Approach for Mitigating Batch Effects in Diffusion MRI Beyond Traditional Harmonization.

BACKGROUND: "Batch effect" in MR images, due to vendor-specific features, MR machine generations, and imaging parameters, challenges image quality and hinders deep learning (DL) model generalizability. PURPOSE: We aim to develop a DL model using contrast adjustment and super-resolution to reduce diffusion-weighted images (DWIs) diversity across magnetic field strengths and imaging parameters. STUDY TYPE: Retrospective. SUBJECTS: The DL model was built using an open dataset from one individual. The MR machine identification model was trained and validated on a dataset of 1134 adults (54% females, 46% males), with 1050 subjects showing no DWI abnormalities and 84 with conditions like stroke and tumors. The 21,000 images were divided into 80% for training, 20% for validation, and 3500 for testing. FIELD STRENGTH/SEQUENCE: Seven MR scanners from four manufacturers with 1.5 T and 3 T magnetic field strengths. DWIs were acquired using spin-echo sequences and high-resolution T2WIs using the T2-SPACE sequence. ASSESSMENT: An experienced, board-certified radiologist evaluated the effectiveness of restoring high-resolution T2WI and harmonizing diverse DWI with metrics such as PSNR and SSIM, and the texture and frequency attributes were further analyzed using gray-level co-occurrence matrix and 1-dimensional power spectral density. The model's impact on machine-specific characteristics was gauged through the performance metrics of a ResNet-50 model. Comprehensive statistical tests were employed for statistical robustness, including McNemar's test and the Dice index. RESULTS: Our DL protocol reduced DWI contrast and resolution variation. ResNet-50 model's accuracy decreased from 0.9443 to 0.5786, precision from 0.9442 to 0.6494, recall from 0.9443 to 0.5786, and F1 score from 0.9438 to 0.5587. The t-SNE visualization indicated more consistent image features across multiple MR devices. Autoencoder halved learning iterations; Dice coefficient >0.74 confirmed signal reproducibility in 84 lesions. CONCLUSION: This study presents a DL strategy to mitigate batch effects in diffusion MR images, improving their quality and generalizability. EVIDENCE LEVEL: 3 TECHNICAL EFFICACY: Stage 1.

Glymphatic system impairment in corticobasal syndrome: diffusion tensor image analysis along the perivascular space (DTI-ALPS).

PURPOSE: This study aimed to evaluate the along the perivascular space (ALPS) index based on the diffusion tensor image ALPS (DTI-ALPS) in corticobasal degeneration with corticobasal syndrome (CBD-CBS) and investigate its correlation with motor and cognitive functions. MATERIALS AND METHODS: The data of 21 patients with CBD-CBS and 17 healthy controls (HCs) were obtained from the 4-Repeat Tauopathy Neuroimaging Initiative and the Frontotemporal Lobar Degeneration Neuroimaging Initiative databases. Diffusion magnetic resonance imaging was performed using a 3-Tesla MRI scanner. The ALPS index based on DTI-ALPS was automatically calculated after preprocessing. The ALPS index was compared between the CBD-CBS and HC groups via a general linear model analysis, with covariates such as age, sex, years of education, and intracranial volume (ICV). Furthermore, to confirm the relation between the ALPS index and the motor and cognitive score in CBD-CBS, the partial Spearman's rank correlation coefficient was calculated with covariates such as age, sex, years of education, and ICV. A p value of < 0.05 was considered as statistically significant in all statistical analyses. RESULTS: The ALPS index of CBD-CBS was significantly lower than that of HC (Cohen's d = - 1.53, p < 0.005). Moreover, the ALPS index had a significant positive correlation with the mini mental state evaluation score (rs = 0.65, p < 0.005) and a significant negative correlation with the unified Parkinson's Disease Rating Scale III score (rs = - 0.75, p < 0.001). CONCLUSION: The ALPS index of patients with CBD-CBS, which is significantly lower than that of HCs, is significantly associated with motor and cognitive functions.

Glymphatic system impairment in sleep disruption: diffusion tensor image analysis along the perivascular space (DTI-ALPS).

PURPOSE: This study aimed to evaluate the relationship between sleep quality as assessed using the Pittsburgh Sleep Quality Index (PSQI) and the index of diffusivity along the perivascular space (ALPS index), a possible indirect indicator of glymphatic system activity. MATERIALS AND METHODS: This study included the diffusion magnetic resonance imaging (MRI) data of 317 people with sleep disruption and 515 healthy controls (HCs) from the Human Connectome Project (WU-MINN HCP 1200). The ALPS index was calculated automatically based on diffusion tensor image analysis (DTI)-ALPS of diffusion MRI. The ALPS index of the sleep disruption and HC groups was compared using general linear model (GLM) analysis with covariates, such as age, sex, level of education, and intracranial volume. In addition, to confirm the relationship between sleep quality and the ALPS index in the sleep disruption group as well as evaluate the effect of each PSQI component on the ALPS index, correlation analyses between the ALPS indices and PSQI scores of all the components and between the ALPS index and each PSQI component was performed using GLM analysis with the abovementioned covariates, respectively. RESULTS: The ALPS index was significantly lower in the sleep disruption group than in the HC group (p = 0.001). Moreover, the ALPS indices showed significant negative correlations with the PSQI scores of all the components (false discovery rate [FDR]-corrected p < 0.001). Two significant negative correlations were also found between the ALPS index and PSQI component 2 (sleep latency, FDR-corrected p < 0.001) and 6 (the use of sleep medication, FDR-corrected p < 0.001). CONCLUSION: Our findings suggest that glymphatic system impairment contributes to sleep disruption in young adults.

Reproducibility of automated calculation technique for diffusion tensor image analysis along the perivascular space.

PURPOSE: The method of diffusion tensor image analysis along the perivascular space (DTI-ALPS) was gathering attention to evaluate the brain's glymphatic function or interstitial fluid dynamics. However, to the best knowledge, no study was conducted on the reproducibility of these automated methods for ALPS index values. Therefore, the current study evaluated the ALPS index reproducibility based on DTI-ALPS using two major automated calculation techniques in scan and rescan of the same subject on the same day. MATERIALS AND METHODS: This study included 23 participants, including 2 with Alzheimer's disease, 15 with mild cognitive impairment, and 6 with cognitive normals. Scan and rescan data of diffusion magnetic resonance images were obtained, as well as automatically index for ALPS (ALPS index) and ALPS index maintaining tensor vector orientation information (vALPS index) with region of interest on the template fractional anisotropy map calculated by FSL software.These ALPS indices were compared in terms of scan and rescan reproducibility. RESULTS: The absolute difference in ALPS-index values between scan and rescan was larger in the ALPS index than in the vALPS index by approximately 0.6% as the relative difference. Cohen's d for the left and right ALPS indices between methods were 0.121 and 0.159, respectively. CONCLUSION: The vALPS index based on DTI-ALPS maintaining tensor vector orientation information has higher reproducibility than the ALPS index. This result encourages a multisite study on the ALPS index with a large sample size and helps detect a subtle pathological change in the ALPS index.

Review of Performance Improvement of a Noninvasive Brain-computer Interface in Communication and Motor Control for Clinical Applications.

Brain-computer interfaces (BCI) enable direct communication between the brain and a computer or other external devices. They can extend a person's degree of freedom by either strengthening or substituting the human peripheral working capacity. Moreover, their potential clinical applications in medical fields include rehabilitation, affective computing, communication, and control. Over the last decade, noninvasive BCI systems such as electroencephalogram (EEG) have progressed from simple statistical models to deep learning models, with performance improvement over time and enhanced computational power. However, numerous challenges pertaining to the clinical use of BCI systems remain, e.g., the lack of sufficient data to learn more possible features for robust and reliable classification. However, compared with fields such as computer vision and speech recognition, the training samples in the medical BCI field are limited as they target patients who face difficulty generating EEG data compared with healthy control. Because deep learning models incorporate several parameters, they require considerably more data than other conventional methods. Thus, deep learning models have not been thoroughly leveraged in medical BCI. This study summarizes the state-of-the-art progress of the BCI system over the last decade, highlighting critical challenges and solutions.

Association between white matter alterations on diffusion tensor imaging and incidence of frailty in older adults with cardiometabolic diseases.

Diffusion tensor imaging (DTI) can be used for the early detection of abnormal changes in the integrity of cerebral white matter tracts, and we have previously reported that these changes are associated with indices of early atherosclerotic lesions. Although these changes have been demonstrated to be associated with the incidence of frailty in older adults, no studies have investigated this relationship in patients at high risk for vascular disease. In this longitudinal study, we followed outpatients with cardiometabolic diseases for a maximum of 6 years (median, 3 years) and evaluated the association of baseline DTI data of seven white matter tracts with the incidence of frailty. The modified version of the Cardiovascular Health Study criteria and the Kihon Checklist were used as indices of frailty; fractional anisotropy (FA) and mean diffusivity (MD) were used as indices of white matter changes. Patients who developed frailty based on both indices had low FA and high MD in many of the tracts tested, with the most significant difference found in the MD of the anterior thalamic radiation (ATR). Cox proportional hazard model analysis revealed a significantly high risk of frailty defined by both indices in the groups with high MD values in the left ATR. Similar results were found in patients with diabetes mellitus but not in those without diabetes mellitus. Therefore, abnormalities in the integrity of the left ATR could be associated with the progression of frailty in older adults with cardiometabolic disease, particularly those with diabetes mellitus.

White matter fiber-specific degeneration in older adults with metabolic syndrome.

OBJECTIVE: Metabolic syndrome (MetS) is defined as a complex of interrelated risk factors for type 2 diabetes and cardiovascular disease, including glucose intolerance, abdominal obesity, hypertension, and dyslipidemia. Studies using diffusion tensor imaging (DTI) have reported white matter (WM) microstructural abnormalities in MetS. However, interpretation of DTI metrics is limited primarily due to the challenges of modeling complex WM structures. The present study used fixel-based analysis (FBA) to assess the effect of MetS on the fiber tract-specific WM microstructure in older adults and its relationship with MetS-related measurements and cognitive and locomotor functions to better understand the pathophysiology of MetS. METHODS: Fixel-based metrics, including microstructural fiber density (FD), macrostructural fiber-bundle cross-section (FC), and a combination of FD and FC (FDC), were evaluated in 16 healthy controls (no components of MetS; four men; mean age, 71.31 ± 5.06 years), 57 individuals with premetabolic syndrome (preMetS; one or two components of MetS; 29 men; mean age, 72.44 ± 5.82 years), and 46 individuals with MetS (three to five components of MetS; 27 men; mean age, 72.15 ± 4.97 years) using whole-brain exploratory FBA. Tract of interest (TOI) analysis was then performed using TractSeg across 14 selected WM tracts previously associated with MetS. The associations between fixel-based metrics and MetS-related measurements, neuropsychological, and locomotor function tests were also analyzed in individuals with preMetS and MetS combined. In addition, tensor-based metrics (i.e., fractional anisotropy [FA] and mean diffusivity [MD]) were compared among the groups using tract-based spatial statistics (TBSS) analysis. RESULTS: In whole-brain FBA, individuals with MetS showed significantly lower FD, FC, and FDC compared with healthy controls in WM areas, such as the splenium of the corpus callosum (CC), corticospinal tract (CST), middle cerebellar peduncle (MCP), and superior cerebellar peduncle (SCP). Meanwhile, in fixel-based TOI, significantly reduced FD was observed in individuals with preMetS and MetS in the anterior thalamic radiation, CST, SCP, and splenium of the CC compared with healthy controls, with relatively greater effect sizes observed in individuals with MetS. Compared with healthy controls, significantly reduced FC and FDC were only demonstrated in individuals with MetS, including regions with loss of FD, inferior cerebellar peduncle, inferior fronto-occipital fasciculus, MCP, and superior longitudinal fasciculus part I. Furthermore, negative correlations were observed between FD and Brinkman index of cigarette consumption cumulative amount and between FC or FDC and the Trail Making Test (parts B-A), which is a measure of executive function, waist circumference, or low-density lipoprotein cholesterol. Finally, TBSS analysis revealed that FA and MD were not significantly different among all groups. CONCLUSIONS: The FBA results demonstrate that substantial axonal loss and atrophy in individuals with MetS and early axonal loss without fiber-bundle morphological changes in those with preMetS within the WM tracts are crucial to cognitive and motor function. FBA also clarified the association between executive dysfunction, abdominal obesity, hyper-low-density lipoprotein cholesterolemia, smoking habit, and compromised WM neural tissue microstructure in MetS.

Comprehensive Volumetric Analysis of Mecp2-Null Mouse Model for Rett Syndrome by T2-Weighted 3D Magnetic Resonance Imaging.

Rett syndrome (RTT) is a severe progressive neurodevelopmental disorder characterized by various neurological symptoms. Almost all RTT cases are caused by mutations in the X-linked methyl-CpG-binding protein 2 (MeCP2) gene, and several mouse models have been established to understand the disease. However, the neuroanatomical abnormalities in each brain region of RTT mouse models have not been fully understood. Here, we investigated the global and local neuroanatomy of the Mecp2 gene-deleted RTT model (Mecp2-KO) mouse brain using T2-weighted 3D magnetic resonance imaging with different morphometry to clarify the brain structural abnormalities that are involved in the pathophysiology of RTT. We found a significant reduction in global and almost all local volumes in the brain of Mecp2-KO mice. In addition, a detailed comparative analysis identified specific volume reductions in several brain regions in the Mecp2-deficient brain. Our analysis also revealed that the Mecp2-deficient brain shows changes in hemispheric asymmetry in several brain regions. These findings suggest that MeCP2 affects not only the whole-brain volume but also the region-specific brain structure. Our study provides a framework for neuroanatomical studies of a mouse model of RTT.

Temporal Progression Patterns of Brain Atrophy in Corticobasal Syndrome and Progressive Supranuclear Palsy Revealed by Subtype and Stage Inference (SuStaIn).

Differentiating corticobasal degeneration presenting with corticobasal syndrome (CBD-CBS) from progressive supranuclear palsy with Richardson's syndrome (PSP-RS), particularly in early stages, is often challenging because the neurodegenerative conditions closely overlap in terms of clinical presentation and pathology. Although volumetry using brain magnetic resonance imaging (MRI) has been studied in patients with CBS and PSP-RS, studies assessing the progression of brain atrophy are limited. Therefore, we aimed to reveal the difference in the temporal progression patterns of brain atrophy between patients with CBS and those with PSP-RS purely based on cross-sectional data using Subtype and Stage Inference (SuStaIn)-a novel, unsupervised machine learning technique that integrates clustering and disease progression modeling. We applied SuStaIn to the cross-sectional regional brain volumes of 25 patients with CBS, 39 patients with typical PSP-RS, and 50 healthy controls to estimate the two disease subtypes and trajectories of CBS and PSP-RS, which have distinct atrophy patterns. The progression model and classification accuracy of CBS and PSP-RS were compared with those of previous studies to evaluate the performance of SuStaIn. SuStaIn identified distinct temporal progression patterns of brain atrophy for CBS and PSP-RS, which were largely consistent with previous evidence, with high reproducibility (99.7%) under cross-validation. We classified these diseases with high accuracy (0.875) and sensitivity (0.680 and 1.000, respectively) based on cross-sectional structural brain MRI data; the accuracy was higher than that reported in previous studies. Moreover, SuStaIn stage correctly reflected disease severity without the label of disease stage, such as disease duration. Furthermore, SuStaIn also showed the genialized performance of differentiation and reflection for CBS and PSP-RS. Thus, SuStaIn has potential for improving our understanding of disease mechanisms, accurately stratifying patients, and providing prognoses for patients with CBS and PSP-RS.

Comparison of Brain Volume Measurements Made with 0.3- and 3-T MR Imaging.

The volumes of intracranial tissues of 40 healthy volunteers acquired from 0.3- and 3-T scanners were compared using intraclass correlation coefficients, correlation analyses, and Bland-Altman analyses. We found high intraclass correlation coefficients, high Pearson's correlation coefficients, and low percentage biases in all tissues and most of the brain regions, although small differences were observed in some areas. These findings may support the validity of brain volumetry with low-field magnetic resonance imaging.

Subclinical Atherosclerosis, Vascular Risk Factors, and White Matter Alterations in Diffusion Tensor Imaging Findings of Older Adults With Cardiometabolic Diseases.

White matter abnormalities may reflect cerebral microvessel disease. Diffusion tensor imaging (DTI) can help detect early changes in white matter integrity in each tract. However, studies investigating the relationship between subclinical atherosclerosis markers and white matter alterations in DTI findings are limited. This study aimed to examine associations between cardiovascular risk factors and indices of subclinical atherosclerosis-ankle brachial index (ABI), brachial-ankle pulse wave velocity (baPWV), and carotid artery intima-media thickness (IMT)-and altered white matter integrity in older patients. A total of 224 patients (aged ≥65 years) with cardiometabolic disease who underwent magnetic resonance imaging (MRI) and either plethysmography or cervical ultrasound at the start of the 3-year observational study period were included in this study. We measured fractional anisotropy (FA) and mean diffusivity (MD), which are indices of white matter integrity in seven white matter tracts. In a univariate analysis, lower ABI and higher baPWV values were associated with FA or MD abnormalities in several tracts, whereas IMT was scarcely associated with such change. In addition, high blood pressure and glycoalbumin/glycohemoglobin ratio (GA/HbA1c) and low body mass index (BMI) and triglyceride (TG) levels were associated with FA or MD abnormalities. In a multivariate analysis adjusted for age, sex, BMI, diastolic blood pressure, TG, and GA/HbA1c, the associations between ABI and FA or MD remained in all of either side of the following tracts: anterior thalamic radiation, forceps minor, inferior frontooccipital fasciculus (p < 0.001 for all) and superior longitudinal fasciculus (SLF; p < 0.05), whereas most of those between baPWV and FA or MD disappeared except for SLF (p < 0.05). These results indicate that low ABI could be an indicator of white matter abnormalities.

Differences in the association between white matter hyperintensities and gait performance among older adults with and without cognitive impairment.

AIM: Gait impairment implies subtle cognitive impairment (CI) and is associated with severity of white matter hyperintensities (WMHs). However, cognitive differences in such an association are not yet fully understood. This study examined the association between WMHs and gait performance among three cognitively different older groups. METHODS: Gait performance and WMHs were assessed in 150 community-dwelling older adults, comprising 53 with CI (Mini-Mental State Examination [MMSE] score <24), 63 with mild CI (MMSE score ≥24 and Montreal Cognitive Assessment [MoCA] score <25), and 34 who were cognitively normal or preserved (MMSE ≥24 and MoCA score ≥25). Gait velocity and variability were assessed on a 5-m electronic walkway. Furthermore, WMH volume was derived by automated segmentation using 1.5 T magnetic resonance imaging. RESULTS: Adjusted multiple regression analyses showed that greater WMHs were associated with slower gait velocity and greater temporal (stride time) and spatial (stride and step lengths) variabilities among older adults with CI. In contrast, WMH was only associated with spatial variability in older adults with mild CI and in cognitively normal or preserved older adults. CONCLUSIONS: Our findings suggest that gait variability measures are more sensitive to subtle underlying neurological pathologies including WMHs in older adults. The cognitive-dependent differences found in the association between WMHs and gait performance suggests that the level of cognitive function interferes with the association between WMH and gait performance. Geriatr Gerontol Int 2021; ••: ••-••.

Associations between sarcopenia and white matter alterations in older adults with diabetes mellitus: A diffusion tensor imaging study.

AIMS/INTRODUCTION: Older adults with diabetes mellitus are susceptible to sarcopenia. Diffusion tensor imaging studies have also shown that patients with diabetes have altered white matter integrity. However, the relationship between these structural changes in white matter and sarcopenia remains poorly understood. MATERIALS AND METHODS: The study included 284 older patients (aged ≥65 years) who visited the Tokyo Metropolitan Geriatric Hospital Frailty Clinic. We used diffusion tensor imaging to measure fractional anisotropy (FA) and mean diffusivity (MD) to evaluate changes in white matter integrity. We investigated the associations between sarcopenia, or its diagnostic components, and FA or MD in seven white matter tracts considered to be associated with sarcopenia according to the patients' diabetes status. RESULTS: We found significantly low FA or high MD values in the bilateral anterior thalamic radiations (ATR) and right inferior fronto-occipital fasciculus (IFOF) of patients with Asian Working Group for Sarcopenia 2019-defined sarcopenia, in all patients and those with diabetes. Using binominal regression analyses, we associated low FA values in the left ATR and right IFOF with sarcopenia in all patients and those with diabetes, after adjusting for age, gender, HbA1c, blood pressure, cognitive function, physical activity, depression, nutritional status, and inflammation. CONCLUSIONS: White matter alterations in left ATR and right IFOF are associated with the prevalence of sarcopenia in patients with diabetes. Specific changes to the left ATR and right IFOF tracts could play critical roles in the occurrence of sarcopenia in patients with diabetes.

Corrigendum to "Predictors of Recovery from Traumatic Brain Injury-Induced Prolonged Consciousness Disorder".

[This corrects the article DOI: 10.1155/2017/9358092.].

Voxel-based morphometry focusing on medial temporal lobe structures has a limited capability to detect amyloid ß, an Alzheimer's disease pathology.

Voxel-based morphometry (VBM) analysis of nuclear Magnetic Resonance Imaging (MRI) data allows the identification of medial temporal lobe (MTL) atrophy and is widely used to assist the diagnosis of Alzheimer's disease (AD). However, its reliability in the clinical environment has not yet been confirmed. To determine the credibility of VBM, amyloid positron emission tomography (PET) and VBM studies were compared retrospectively. Patients who underwent Pittsburgh Compound B (PiB) PET were retrospectively recruited. Ninety-seven patients were found to be amyloid negative and 116 were amyloid positive. MTL atrophy in the PiB positive group, as quantified by thin sliced 3D MRI and VBM software, was significantly more severe (p =0.0039) than in the PiB negative group. However, data histogram showed a vast overlap between the two groups. The area under the ROC curve (AUC) was 0.646. MMSE scores of patients in the amyloid negative and positive groups were also significantly different (p = 0.0028), and the AUC was 0.672. Thus, MTL atrophy could not reliably differentiate between amyloid positive and negative patients in a clinical setting, possibly due to the wide array of dementia-type diseases that exist other than AD.

White matter changes in children and adolescents with reactive attachment disorder: A diffusion tensor imaging study.

Childhood maltreatment is associated with altered brain structure and function and is a major risk factor for psychopathology, including reactive attachment disorder (RAD). However, whether changes to white matter microstructural integrity are associated with RAD is unclear. We used diffusion tensor imaging (DTI) to assess group differences in fractional anisotropy (FA) in patients with RAD (n = 25; mean age = 13.2) to typically developing (TD) controls (n = 33; mean age = 13.0). To further interpret differences in FA, additional parameters such as mean diffusivity (MD), axial diffusivity (AD) and radial diffusivity (RD) were assessed. We found that FA values in the body of corpus callosum (CC) and in the projection and thalamic pathways, including the posterior limb of the internal capsule and corona radiata (anterior, posterior, and superior), were significantly higher in the RAD than in the TD group. Additionally, RAD group showed significantly lower RD values in the body of the CC and abovementioned pathways than TD group. Our findings indicate that RAD is associated with altered structure of the CC and projection and thalamic pathways, which may play a role in emotion regulation. The aberrant development of these tracts in RAD may reflect stress-related psychophysiological responses.

Severe Acute Pancreatitis in Autopsies Associated With Surgeries and Severe Inflammatory Diseases.

OBJECTIVE: We clarified clinicopathological characteristics of acute pancreatitis in terminal patients. METHODS: Pathological changes in the entire pancreas from serial autopsies (N = 183) classified lesions into the following 3 categories: focal neutrophil infiltration, focal necrotizing pancreatitis, and diffuse necrotizing pancreatitis. The former two are possible precursors of diffuse necrotizing pancreatitis. Immunohistochemical staining was performed to analyze pancreatic stellate cells and inflammatory cells. RESULTS: There were pathologically acute pancreatitis in 45 patients (24.6%), and no patients were diagnosed with it before autopsy. Focal neutrophil infiltration was present in 22 cases, focal necrotizing pancreatitis in 18 cases, and diffuse necrotizing pancreatitis in 5 cases. Severe inflammatory disease and surgery were associated with acute pancreatitis. Sepsis due to viral or bacterial infection was the most common cause of acute pancreatitis. Patients with diffuse necrotizing pancreatitis showed low white blood cell counts, while amylase levels were not increased. Increase in α-smooth muscle actin and nestin-positive stellate cell numbers in acute pancreatitis was correlated to increase in numbers of CD34-positive vascular endothelium, CD68- or CD163-positive macrophages, CD138-positive plasmacytes, CD3-positive T lymphocytes, and myeloperoxidase-positive leucocytes. CONCLUSIONS: Necrotizing pancreatitis without typical clinical signs was frequently detected in autopsy samples. Clinicians must be mindful of necrotizing pancreatitis in terminal patients.