Diffeomorphic Anatomical Registration Through Exponentiated Lie Algebra provides reduced effect of scanner for cortex volumetry with atlas-based method in healthy subjects

A minimalistic approach to classifying Alzheimer's disease using simple and extremely small convolutional neural networks

BACKGROUND

There is a broad interest in deploying deep learning-based classification algorithms to identify individuals with Alzheimer's disease (AD) from healthy controls (HC) based on neuroimaging data, such as T1-weighted Magnetic Resonance Imaging (MRI). The goal of the current study is to investigate whether modern, flexible architectures such as EfficientNet provide any performance boost over more standard architectures.

METHODS

MRI data was sourced from the Alzheimer's Disease Neuroimaging Initiative (ADNI) and processed with a minimal preprocessing pipeline. Among the various architectures tested, the minimal 3D convolutional neural network SFCN stood out, composed solely of 3x3x3 convolution, batch normalization, ReLU, and max-pooling. We also examined the influence of scale on performance, testing SFCN versions with trainable parameters ranging from 720 up to 2.9 million.

RESULTS

SFCN achieves a test ROC AUC of 96.0% while EfficientNet got an ROC AUC of 94.9 %. SFCN retained high performance down to 720 trainable parameters, achieving an ROC AUC of 91.4%.

COMPARISON WITH EXISTING METHODS

The SFCN is compared to DenseNet and EfficientNet as well as the results of other publications in the field.

CONCLUSIONS

The results indicate that using the minimal 3D convolutional neural network SFCN with a minimal preprocessing pipeline can achieve competitive performance in AD classification, challenging the necessity of employing more complex architectures with a larger number of parameters. This finding supports the efficiency of simpler deep learning models for neuroimaging-based AD diagnosis, potentially aiding in better understanding and diagnosing Alzheimer's disease.

Structural changes in eloquent cortex secondary to glioma in sensorimotor area

This study aims to investigate the structural reorganization in the sensorimotor area of the brain in patients with gliomas, distinguishing between those with impaired and unimpaired strength. Using voxel-based morphometry (VBM) and region of interest (ROI) analysis, gray matter volumes (GMV) were compared in the contralesional primary motor gyrus, primary sensory gyrus, premotor area, bilateral supplementary motor area, and medial Brodmann area 8 (BA8). The results revealed that in patients with right hemisphere gliomas, the right medial BA8 volume was significantly larger in the impaired group than in the unimpaired group, with both groups exceeding the volume in 16 healthy controls (HCs). In patients with left hemisphere gliomas, the right supplementary motor area (SMA) was more pronounced in the impaired group compared to the unimpaired group, and both groups were greater than HCs. Additionally, the volumes of the right medial BA8 in both the impaired group were greater than HCs. Contralateral expansions in the gray matter of hand- and trunk-related cortices of the premotor area, precentral gyrus, and postcentral gyrus were observed compared to HCs. Furthermore, a negative correlation was found between hand Medical Research Council (MRC) score and volumes of the contralateral SMA and bilateral medial BA8. Notably, our findings reveal consistent results across both analytical approaches in identifying significant structural reorganizations within the sensorimotor cortex. These consistent findings underscore the adaptive neuroplastic responses to glioma presence, highlighting potential areas of interest for further neurosurgical planning and rehabilitation strategies.

Discriminating nonfluent/agrammatic and logopenic PPA variants with automatically extracted morphosyntactic measures from connected speech

Morphosyntactic assessments are important for characterizing individuals with nonfluent/agrammatic variant primary progressive aphasia (nfvPPA). Yet, standard tests are subject to examiner bias and often fail to differentiate between nfvPPA and logopenic variant PPA (lvPPA). Moreover, relevant neural signatures remain underexplored. Here, we leverage natural language processing tools to automatically capture morphosyntactic disturbances and their neuroanatomical correlates in 35 individuals with nfvPPA relative to 10 healthy controls (HC) and 26 individuals with lvPPA. Participants described a picture, and ensuing transcripts were analyzed via part-of-speech tagging to extract sentence-related features (e.g., subordinating and coordinating conjunctions), verbal-related features (e.g., tense markers), and nominal-related features (e.g., subjective and possessive pronouns). Gradient boosting machines were used to classify between groups using all features. We identified the most discriminant morphosyntactic marker via a feature importance algorithm and examined its neural correlates via voxel-based morphometry. Individuals with nfvPPA produced fewer morphosyntactic elements than the other two groups. Such features robustly discriminated them from both individuals with lvPPA and HCs with an AUC of .95 and .82, respectively. The most discriminatory feature corresponded to subordinating conjunctions was correlated with cortical atrophy within the left posterior inferior frontal gyrus across groups (pFWE < .05). Automated morphosyntactic analysis can efficiently differentiate nfvPPA from lvPPA. Also, the most sensitive morphosyntactic markers correlate with a core atrophy region of nfvPPA. Our approach, thus, can contribute to a key challenge in PPA diagnosis.

Risk factors and cognitive correlates of white matter hyperintensities in ethnically diverse populations without dementia: The COSMIC consortium

INTRODUCTION

White matter hyperintensities (WMHs) are an important imaging marker for cerebral small vessel diseases, but their risk factors and cognitive associations have not been well documented in populations of different ethnicities and/or from different geographical regions.

METHODS

We investigated how WMHs were associated with vascular risk factors and cognition in both Whites and Asians, using data from five population-based cohorts of non-demented older individuals from Australia, Singapore, South Korea, and Sweden (N = 1946). WMH volumes (whole brain, periventricular, and deep) were quantified with UBO Detector and harmonized using the ComBat model. We also harmonized various vascular risk factors and scores for global cognition and individual cognitive domains.

RESULTS

Factors associated with larger whole brain WMH volumes included diabetes, hypertension, stroke, current smoking, body mass index, higher alcohol intake, and insufficient physical activity. Hypertension and stroke had stronger associations with WMH volumes in Whites than in Asians. No associations between WMH volumes and cognitive performance were found after correction for multiple testing.

CONCLUSION

The current study highlights ethnic differences in the contributions of vascular risk factors to WMHs.

Aberrant dynamic functional network connectivity in type 2 diabetes mellitus individuals

An increasing number of recent brain imaging studies are dedicated to understanding the neuro mechanism of cognitive impairment in type 2 diabetes mellitus (T2DM) individuals. In contrast to efforts to date that are limited to static functional connectivity, here we investigate abnormal connectivity in T2DM individuals by characterizing the time-varying properties of brain functional networks. Using group independent component analysis (GICA), sliding-window analysis, and k-means clustering, we extracted thirty-one intrinsic connectivity networks (ICNs) and estimated four recurring brain states. We observed significant group differences in fraction time (FT) and mean dwell time (MDT), and significant negative correlation between the Montreal Cognitive Assessment (MoCA) scores and FT/MDT. We found that in the T2DM group the inter- and intra-network connectivity decreases and increases respectively for the default mode network (DMN) and task-positive network (TPN). We also found alteration in the precuneus network (PCUN) and enhanced connectivity between the salience network (SN) and the TPN. Our study provides evidence of alterations of large-scale resting networks in T2DM individuals and shed light on the fundamental mechanisms of neurocognitive deficits in T2DM.

Accuracy of skull stripping in a single-contrast convolutional neural network model using eight-contrast magnetic resonance images

In automated analyses of brain morphometry, skull stripping or brain extraction is a critical first step because it provides accurate spatial registration and signal-intensity normalization. Therefore, it is imperative to develop an ideal skull-stripping method in the field of brain image analysis. Previous reports have shown that convolutional neural network (CNN) method is better at skull stripping than non-CNN methods. We aimed to evaluate the accuracy of skull stripping in a single-contrast CNN model using eight-contrast magnetic resonance (MR) images. A total of 12 healthy participants and 12 patients with a clinical diagnosis of unilateral Sturge-Weber syndrome were included in our study. A 3-T MR imaging system and QRAPMASTER were used for data acquisition. We obtained eight-contrast images produced by post-processing T1, T2, and proton density (PD) maps. To evaluate the accuracy of skull stripping in our CNN method, gold-standard intracranial volume (ICVG) masks were used to train the CNN model. The ICVG masks were defined by experts using manual tracing. The accuracy of the intracranial volume obtained from the single-contrast CNN model (ICVE) was evaluated using the Dice similarity coefficient [= 2(ICVE ⋂ ICVG)/(ICVE + ICVG)]. Our study showed significantly higher accuracy in the PD-weighted image (WI), phase-sensitive inversion recovery (PSIR), and PD-short tau inversion recovery (STIR) compared to the other three contrast images (T1-WI, T2-fluid-attenuated inversion recovery [FLAIR], and T1-FLAIR). In conclusion, PD-WI, PSIR, and PD-STIR should be used instead of T1-WI for skull stripping in the CNN models.

Risk factors and cognitive correlates of white matter hyperintensities in ethnically diverse populations without dementia: the COSMIC consortium

INTRODUCTION

White matter hyperintensities (WMH) are an important imaging marker for cerebral small vessel diseases, but their risk factors and cognitive associations have not been well-documented in populations of different ethnicities and/or from different geographical regions.

METHOD

Magnetic resonance imaging data of five population-based cohorts of non-demented older individuals from Australia, Singapore, South Korea, and Sweden (N = 1,946) were examined for WMH and their associations with vascular risk factors and cognition.

RESULT

Factors associated with larger whole brain WMH volumes included diabetes, hypertension, stroke, current smoking, body mass index, higher alcohol intake and insufficient physical activity. Participants with moderate or higher physical activity had less WMH than those who never exercised, but the former two groups did not differ. Hypertension and stroke had stronger associations with WMH volumes in the White, compared to Asian subsample.

DISCUSSION

The current study highlighted the ethnic differences in the contributions of vascular risk factors to WMH.

Altered Spontaneous Brain Activity and Its Predictive Role in Patients with Central Retinal Artery Occlusion Using fMRI and Machine Learning

Objective

To investigate spontaneous neuronal activity changes in patients with central retinal artery occlusion (CRAO) using the resting-state functional magnetic resonance imaging (fMRI) and detect whether these brain functional alterations can represent an objective biomarker of clinical response using a machine learning algorithm.

Methods

Eighteen patients with CRAO and eighteen healthy controls (HCs) were recruited. The regional homogeneity (ReHo) method of resting-state fMRI was conducted to evaluate the synchronous brain activity alterations between two groups. Differences of ReHo values between two groups were compared using the independent two-sample t-test. The support vector machine algorithm was to distinguish patients of CRAO from HCs based on the two groups' whole-brain ReHo patterns. The accuracy, sensitivity, and specificity for the classification were calculated. The classification performance was evaluated using the non-parametric permutation test.

Results

Compared to HCs, individuals with CRAO showed significantly lower ReHo in the right cerebellum and precuneus. Meanwhile, significant higher ReHo values were observed in the left superior temporal gyrus, postcentral gyrus, and precentral gyrus in the CRAO group compared to HCs. Furthermore, our results suggested that 77.78% individuals with CRAO could be successfully distinguished from HCs by the machine learning, with a sensitivity of 72.22% and a specificity of 83.33%, respectively. The area of receiver operating characteristic curve was calculated to be 0.85.

Conclusion

This study uncovered individuals with CRAO exhibited disturbed synchronous neuronal activities in multiple brain areas using neuroimaging techniques. The ReHo variability could distinguish individuals with CRAO from HCs with high accuracy.

Abnormal brain activity in lumbar disc herniation patients with chronic pain is associated with their clinical symptoms

Introduction

Lumbar disc herniation, a chronic degenerative disease, is one of the major contributors to chronic low back pain and disability. Although many studies have been conducted in the past on brain function in chronic low back pain, most of these studies did not classify chronic low back pain (cLBP) patients according to their etiology. The lack of etiologic classification may lead to inconsistencies between findings, and the correlation between differences in brain activation and clinical symptoms in patients with cLBP was less studied in the past.

Methods

In this study, 36 lumbar disc herniation patients with chronic low back pain (LDHCP) and 36 healthy controls (HCs) were included to study brain activity abnormalities in LDHCP. Visual analogue scale (VAS), oswestry disability index (ODI), self-rating anxiety scale (SAS), self-rating depression scale (SDS) were used to assess clinical symptoms.

Results

The results showed that LDHCP patients exhibited abnormally increased and diminished activation of brain regions compared to HCs. Correlation analysis showed that the amplitude of low frequency fluctuations (ALFF) in the left middle frontal gyrus is negatively correlated with SAS and VAS, while the right superior temporal gyrus is positively correlated with SAS and VAS, the dorsolateral left superior frontal gyrus and the right middle frontal gyrus are negatively correlated with VAS and SAS, respectively.

Conclusion

LDHCP patients have brain regions with abnormally increased and abnormally decreased activation compared to healthy controls. Furthermore, some of the abnormally activated brain regions were correlated with clinical pain or emotional symptoms.

Articulation-Function-Associated Cortical Developmental Changes in Patients with Cleft Lip and Palate

Cleft lip and palate (CLP) is one of the most common craniofacial malformations. Overall, 40–80% of CLP patients have varying degrees of articulation problems after palatoplasty. Previous studies revealed abnormal articulation-related brain function in CLP patients. However, the association between articulation disorders and cortical structure development in CLP patients remains unclear. Twenty-six CLP adolescents (aged 5–14 years; mean 8.88 years; female/male 8/18), twenty-three CLP adults (aged 18–35 years; mean 23.35 years; female/male 6/17), thirty-seven healthy adolescents (aged 5–16 years; mean 9.89 years; female/male 5/16), and twenty-two healthy adults (aged 19–37 years; mean 24.41 years; female/male 19/37) took part in the experiment. The current study aims to investigate developmental changes in cortical structures in CLP patients with articulation disorders using both structural and functional magnetic resonance imaging (MRI). Our results reveal the distinct distribution of abnormal cortical structures in adolescent and adult CLP patients. We also found that the developmental pattern of cortical structures in CLP patients differed from the pattern in healthy controls (delayed cortical development in the left lingual gyrus (t = 4.02, cluster-wise p < 0.05), inferior temporal cortex (z = −4.36, cluster-wise p < 0.05) and right precentral cortex (t = 4.19, cluster-wise p < 0.05)). Mediation analysis identified the cortical thickness of the left pericalcarine cortex as the mediator between age and articulation function (partial mediation effect (a*b = −0.48), 95% confident interval (−0.75, −0.26)). In conclusion, our results demonstrate an abnormal developmental pattern of cortical structures in CLP patients, which is directly related to their articulation disorders.

Demonstrating quality control procedures for fMRI in DPABI

Quality control (QC) is an important stage for functional magnetic resonance imaging (fMRI) studies. The methods for fMRI QC vary in different fMRI preprocessing pipelines. The inflating sample size and number of scanning sites for fMRI studies further add to the difficulty and working load of the QC procedure. Therefore, as a constituent part of the Demonstrating Quality Control Procedures in fMRI research topic in Frontiers, we preprocessed a well-organized open-available dataset using DPABI pipelines to illustrate the QC procedure in DPABI. Six categories of DPABI-derived reports were used to eliminate images without adequate quality. After the QC procedure, twelve participants (8.6%) were categorized as excluded and eight participants (5.8%) were categorized as uncertain. More automatic QC tools were needed in the big-data era while visually inspecting images was still indispensable now.

Latent feature representation learning for Alzheimer's disease classification

Early detection and treatment of Alzheimer's Disease (AD) are significant. Recently, multi-modality imaging data have promoted the development of the automatic diagnosis of AD. This paper proposes a method based on latent feature fusion to make full use of multi-modality image data information. Specifically, we learn a specific projection matrix for each modality by introducing a binary label matrix and local geometry constraints and then project the original features of each modality into a low-dimensional target space. In this space, we fuse latent feature representations of different modalities for AD classification. The experimental results on Alzheimer's Disease Neuroimaging Initiative database demonstrate the proposed methods effectiveness in classifying AD.

Abnormal topological parameters in the default mode network in patients with impaired cognition undergoing maintenance hemodialysis

Objective

The role of the default mode network (DMN) in the cognitive impairment experienced by patients with end-stage renal disease (ESRD) undergoing maintenance hemodialysis (MHD) remains unknown. This study tested the hypothesis that the topological architecture of the DMN plays a key role in ESRD-related cognitive impairment.

Methods

For this study, 43 ERSD patients receiving MHD and 41 healthy control (HC) volunteers matched for gender, age and education underwent resting-state functional magnetic resonance imaging examinations. DMN architecture was depicted by 20 selected DMN subregions. Graph theory approaches were applied to investigate multiple topological parameters within the DMN in resting state at the global, local and edge levels.

Results

Globally, the MHD group exhibited topological irregularities as indicated by reduced values for the clustering coeffcient (C_p), normalized C_p (γ), world-index (σ), and local effciency (E_loc) compared with the HC group. Locally, the MHD group showed greater nodal betweenness in the left retrosplenial cortex (RC) compared with the HC group. At the edge level, the MHD group exhibited disconnected resting-state functional connections (RSFCs) in the medial temporal lobe (MTL) subsystem including the ventral medial prefrontal cortex (VMPC)–left posterior inferior parietal lobule, VMPC–right parahippocampal cortex (PC), and right RC–left PC RSFCs. Additionally, the VMPC–right PC RSFC was positively correlated with the Digit Span Test score and E_loc, and the right RC–left PC RSFC was positively correlated with the Montreal Cognitive Assessment score and E_loc in the MHD group.

Conclusions

ESRD patients undergoing MHD showed local inefficiency, abnormal nodal centralities, and hypoconnectivity within the DMN, implying that the functional differentiation and local information transmission efficiency of the DMN are disturbed in ESRD. The disconnected RSFCs in the MTL subsystem likely facilitated topological reconfiguration in the DMN of ESRD patients, leading to impairments of multidomain neurocognition including memory and emotion regulation.

A new multimodality fusion classification approach to explore the uniqueness of schizophrenia and autism spectrum disorder

Schizophrenia (SZ) and autism spectrum disorder (ASD) sharing overlapping symptoms have a long history of diagnostic confusion. It is unclear what their differences at a brain level are. Here, we propose a multimodality fusion classification approach to investigate their divergence in brain function and structure. Using brain functional network connectivity (FNC) calculated from resting-state fMRI data and gray matter volume (GMV) estimated from sMRI data, we classify the two disorders using the main data (335 SZ and 380 ASD patients) via an unbiased 10-fold cross-validation pipeline, and also validate the classification generalization ability on an independent cohort (120 SZ and 349 ASD patients). The classification accuracy reached up to 83.08% for the testing data and 72.10% for the independent data, significantly better than the results from using the single-modality features. The discriminative FNCs that were automatically selected primarily involved the sub-cortical, default mode, and visual domains. Interestingly, all discriminative FNCs relating to the default mode network showed an intermediate strength in healthy controls (HCs) between SZ and ASD patients. Their GMV differences were mainly driven by the frontal gyrus, temporal gyrus, and insula. Regarding these regions, the mean GMV of HC fell intermediate between that of SZ and ASD, and ASD showed the highest GMV. The middle frontal gyrus was associated with both functional and structural differences. In summary, our work reveals the unique neuroimaging characteristics of SZ and ASD that can achieve high and generalizable classification accuracy, supporting their potential as disorder-specific neural substrates of the two entwined disorders.

The Effect of Long-Term Menstrual Pain on Large-Scale Brain Network in Primary Dysmenorrhea Patients

Purpose

Primary dysmenorrhea (PD) is a common gynecological disease, characterized by crampy and suprapubic pain occurring with menses. Growing evidences demonstrated that PD patients were associated with abnormalities in brain function and structure. However, little is known regarding whether the large-scale brain network changes in PD patients. The purpose of this study was to investigate the effect of long-term menstrual pain on large-scale brain network in PD patients using independent component analysis (ICA) method.

Methods

Twenty-eight PD patients (female, mean age, 24.25±1.00 years) and twenty-eight healthy controls (HCs) (mean age, 24.46±1.31 years), closely matched for age, sex, and education, underwent resting-state magnetic resonance imaging scans. ICA was applied to extract the resting-state networks (RSNs) in two groups. Then, two-sample t-tests were conducted to investigate different intranetwork FCs within RSNs and interactions among RSNs between two groups.

Results

Compared to the HC group, PD patients showed significant increased intra-network FCs within the auditory network (AN), sensorimotor network (SMN), right executive control network (RECN). However, PD patients showed significant decreased intra-network FCs within ventral default mode network (vDMN) and salience network (SN). Moreover, FNC analysis showed increased VN-AN and decreased VN-SMN functional connectivity between two groups.

Conclusion

Our study highlighted that PD patients had abnormal brain networks related to auditory, sensorimotor and higher cognitive network. Our results offer important insights into the altered large-scale brain network neural mechanisms of pain in PD patients.

Altered Default Mode Network Functional Connectivity in Parkinson’s Disease: A Resting-State Functional Magnetic Resonance Imaging Study

Purpose

Whether the intrinsic functional connectivity pattern of the default mode network (DMN) is involved in the progression of cognitive decline in Parkinson’s disease (PD) remains unclear. This study aimed to investigate the intrinsic functional connectivity (FC) pattern of the DMN anchored on the posterior cingulate cortex (PCC) in patients with PD by resting-state functional magnetic resonance imaging (fMRI).

Methods

Fifty patients with PD and 50 healthy controls (HCs) were included for resting-state fMRI scanning. A seed-based FC method was used to reveal FC patterns in the DMN with region of interest (ROI) in the PCC. Relationships between FC patterns and disease severity (UPDRS-III) were detected.

Results

Compared with the HCs, the patients with PD showed increased FC between the PCC and the right precuneus, left cuneus, and right angular gyrus. In the PD group, the increased FC values in the right precuneus were significantly and positively correlated with motor severity as assessed with UPDRS-III scores (rho = 0.337, p = 0.02).

Conclusion

Our result highlights that the patients with PD showed increased FC between the PCC and the right precuneus, left cuneus, and right angular gyrus in the DMN. The altered connectivity pattern in the DMN may play a crucial role in the neurophysiological mechanism of cognitive decline in patients with PD. These findings might provide new insights into neural mechanisms of cognitive decline in PD.

Comparing Medial Temporal Atrophy Between Early-Onset Semantic Dementia and Early-Onset Alzheimer's Disease Using Voxel-Based Morphometry: A Multicenter MRI Study

BACKGROUND

Early-onset Semantic dementia (EOSD) and early-onset Alzheimer's disease (EOAD) are often difficult to clinically differentiate in the early stages of the diseases because of the overlaps of clinical symptoms such as language symptoms. We compared the degree of atrophy in medial temporal structures between the two types of dementia using the voxel-based specific regional analysis system for Alzheimer's disease (VSRAD).

METHODS

The participants included 29 (age: 61.7±4.5 years) and 39 (age: 60.2±4.9 years) patients with EOSD and EOAD, respectively. The degree of atrophy in medial temporal structures was quantified using the VSRAD for magnetic resonance imaging data. Receiver operating characteristic (ROC) analysis was performed to distinguish patients with EOSD and EOAD using the mean Z score (Z-score) in bilateral medial temporal structures and the absolute value (laterality score) of the laterality of Z-score (| right-left |) for indicating the degree of asymmetrical atrophy in medial temporal structures.

RESULTS

The EOSD group had significantly higher Z and laterality scores than the EOAD group (Zscores: mean ± standard deviation: 3.74±1.05 vs. 1.56±0.81, respectively; P<0.001; laterality score: mean ± standard deviation: 2.35±1.23 vs. 0.68±0.51, respectively; P<0.001). In ROC analysis, the sensitivity and specificity to differentiate EOSD from EOAD by a Z-score of 2.29 were 97% and 85%, respectively and by the laterality score of 1.05 were 93% and 85%, respectively.

CONCLUSION

EOSD leads to more severe and asymmetrical atrophy in medial temporal structures than EOAD. The VSRAD may be useful to distinguish between these dementias that have several clinically similar symptoms.

Local-to-Remote Brain Functional Connectivity in Patients with Thyroid-Associated Ophthalmopathy and Assessment of Its Predictive Value Using Machine Learning

Purpose

To explore the alterations in both local and remote brain connectivity in patients with thyroid-associated ophthalmopathy (TAO) and to investigate whether the alterations of local neural function could be used to distinguish patients with TAO from healthy controls (HCs) using support vector machine (SVM) classifier.

Materials and Methods

In total, 21 patients with TAO and 21 well-matched HCs were enrolled in our study and underwent resting-state functional magnetic resonance imaging (rs-fMRI) scanning. We employed regional homogeneity (ReHo) algorithm to evaluate local neural function and selected significantly altered brain regions as seed areas for subsequent study of the remote functional connectivity (FC). Moreover, we chose the observed alterations in the ReHo analysis as classification features to differentiate patients with TAO from HCs through SVM classification method.

Results

Compared with the HCs, TAO patients showed significantly lower ReHo values in the right middle occipital gyrus (MOG) and right angular (ANG). In contrast, TAO patients displayed higher ReHo values in the left hippocampus (Hipp). We further found TAO patients exhibited decreased FC between the left and right Hipp, right MOG and left cerebellum (CER), right ANG and left rectus, right superior temporal pole gyrus (PSTG) (voxel-level p < 0.01, Gaussian random field correction, cluster-level p < 0.05). The alterations in local neural function exhibited an accuracy of 78.57% and area under curve of 0.81 for distinguishing the patients from HCs.

Conclusion

We mainly found the results that patients with TAO showed significantly dysfunctional local and remote brain functional connectivity in several brain regions associated with visual and cognitive functions. The ReHo variability has potential value in differentiating patients with TAO from HCs. These findings may provide novel insights into the neurological mechanisms underlying visual and cognitive disorders in patients with TAO.

Efficacy of Quantitative Susceptibility Mapping with Brain Surface Correction and Vein Removal for Detecting Increase Magnetic Susceptibility in Patients with Alzheimer's Disease

PURPOSE

Studies on quantitative susceptibility mapping (QSM) have reported an increase in magnetic susceptibilities in patients with Alzheimer's disease (AD). Despite the pathological importance of the brain surface areas, they are sometimes excluded in QSM analysis. This study aimed to reveal the efficacy of QSM analysis with brain surface correction (BSC) and/or vein removal (VR) procedures.

METHODS

Thirty-seven AD patients and 37 age- and sex-matched, cognitively normal (CN) subjects were included. A 3D-gradient echo sequence at 3T MRI was used to obtain QSM. QSM images were created with regularization enabled sophisticated harmonic artifact reduction for phase data (RESHARP) and constrained RESHARP with BSC and/or VR. We conducted ROI analysis between AD patients and CN subjects who did or did not undergo BSC and/or VR using a t-test, to compare the susceptibility values after gray matter weighting.

RESULTS

The susceptibility values in RESHARP without BSC were significantly larger in AD patients than in CN subjects in one region (precentral gyrus, 8.1 ± 2.9 vs. 6.5 ± 2.1 ppb) without VR and one region with VR (precentral gyrus, 7.5 ± 2.8 vs. 5.9 ± 2.0 ppb). Three regions in RESHARP with BSC had significantly larger susceptibilities without VR (precentral gyrus, 7.1 ± 2.0 vs. 5.9 ± 2.0 ppb; superior medial frontal gyrus, 5.7 ± 2.6 vs. 4.2 ± 3.1 ppb; putamen, 47,8 ± 16.5 vs. 40.0 ± 15.9 ppb). In contrast, six regions showed significantly larger susceptibilities with VR in AD patients than in CN subjects (precentral gyrus, 6.4 ± 1.9 vs. 4.9 ± 2.7 ppb; superior medial frontal gyrus, 5.3 ± 2.7 vs. 3.7 ± 3.3 ppb; orbitofrontal cortex, -2.1 ± 2.7 vs. -3.6 ± 3.2 ppb; parahippocampal gyrus, 0.1 ± 3.6 vs. -1.7 ± 3.7 ppb; putamen, 45.0 ± 14.9 vs. 37.6 ± 14.6 ppb; inferior temporal gyrus, -3.4 ± 1.5 vs. -4.4 ± 1.5 ppb).

CONCLUSION

RESHARP with BSC and VR showed more regions of increased susceptibility in AD patients than in CN subjects. This study highlights the efficacy of this method in facilitating the diagnosis of AD.

Altered Intra- and Inter-Network Functional Connectivity in Patients With Crohn’s Disease: An Independent Component Analysis-Based Resting-State Functional Magnetic Resonance Imaging Study

Background

Many studies have reported changes in the structure and function of several brain areas in patients with Crohn’s disease (CD). However, little is known about whether the possible functional connectivity of resting-state networks (RSNs) is altered in CD patients.

Purpose

Aim to investigate the intra- and inter-network alterations between related RSNs in patients with CD and the potential relationships between altered neuroimaging and CD clinical indices.

Materials and Methods

In this study, 20 CD patients and 22 age- and sex-matched healthy controls were included. All participants underwent functional magnetic resonance imaging examination. We used independent component analysis (ICA) to explore the changes in RSNs and evaluated functional connectivity between different RSNs using functional network connectivity (FNC) analysis, and Pearson correlation analysis was performed between altered intra- and inter-network functional connectivity and CD clinical index.

Results

Six CD-related RSNs were identified via ICA, namely the high visual, prime visual, language, dorsal default mode, posterior insula, and precuneus networks. Compared to healthy controls, patients with CD showed significant changes in prime visual and language networks. Additionally, the functional connectivity (FC) values of the left calcarine within the prime visual network were negatively correlated with CD duration. The inter-alterations showed that a significantly increased FNC existed between the language and dorsal default mode networks.

Conclusion

The results showed CD-related changes in brain functional networks. This evidence provides more insights into the pathophysiological mechanisms of brain plasticity in CD.

Advantages of Using Both Voxel- and Surface-based Morphometry in Cortical Morphology Analysis: A Review of Various Applications

Surface-based morphometry (SBM) is extremely useful for estimating the indices of cortical morphology, such as volume, thickness, area, and gyrification, whereas voxel-based morphometry (VBM) is a typical method of gray matter (GM) volumetry that includes cortex measurement. In cases where SBM is used to estimate cortical morphology, it remains controversial as to whether VBM should be used in addition to estimate GM volume. Therefore, this review has two main goals. First, we summarize the differences between the two methods regarding preprocessing, statistical analysis, and reliability. Second, we review studies that estimate cortical morphological changes using VBM and/or SBM and discuss whether using VBM in conjunction with SBM produces additional values. We found cases in which detection of morphological change in either VBM or SBM was superior, and others that showed equivalent performance between the two methods. Therefore, we concluded that using VBM and SBM together can help researchers and clinicians obtain a better understanding of normal neurobiological processes of the brain. Moreover, the use of both methods may improve the accuracy of the detection of morphological changes when comparing the data of patients and controls.

In addition, we introduce two other recent methods as future directions for estimating cortical morphological changes: a multi-modal parcellation method using structural and functional images, and a synthetic segmentation method using multi-contrast images (such as T1- and proton density-weighted images).

Measuring functional connectivity in patients with strabismus using stationary functional magnetic resonance imaging: a resting-state network study

BACKGROUND

Strabismus (STR) is a common eye disease characterized by abnormal eye movements and stereo vision. Neuroimaging studies have revealed that STR patients have impaired functional connectivity (FC) in the visual cortex and sensorimotor cortex.

PURPOSE

To investigate alterations in FC and connections within and between subnetworks of the visual network (VN), sensorimotor network (SMN), and default mode network (DMN) in patients with STR.

MATERIAL AND METHODS

A total of 32 patients with STR (24 men, 8 women) and 32 age- and sex-matched healthy controls (HCs) (24 men, 8 women) were recruited. Participants underwent resting-state functional magnetic resonance imaging scans. The resting-state network (RSN) was examined by independent component analysis, and differences in RSN FC between STR and HC groups were evaluated with the t test. Functional network connectivity (FNC) analysis was performed for the three RSNs.

RESULTS

Compared to the HC group, the STR group showed increased FC in the VN and SMN (voxel-level P < 0.01; two-tailed Gaussian random field correction; cluster-level P < 0.05). There were no significant alterations in DMN FC between the two groups. FNC analysis of connections in the RSN revealed that one of the three connections in the VN was reduced, but no connectivity changes were observed in the SMN or DMN. FNC analysis of the connection between two RSNs showed that two had increased and one had a decreased connection value.

CONCLUSION

The VN, SMN, and DMN are reorganized in patients with STR compared to HCs, providing novel insight into the neural substrates of STR.

Impaired Interhemispheric Synchrony in Bronchial Asthma

Purpose

Methods

Results

Conclusion

Machine Learning Analysis Reveals Abnormal Static and Dynamic Low-Frequency Oscillations Indicative of Long-Term Menstrual Pain in Primary Dysmenorrhea Patients

BACKGROUND

Previous neuroimaging studies demonstrated that patients with primary dysmenorrhea (PD) exhibited dysfunctional resting-state brain activity. However, alterations of dynamic brain activity in PD patients have not been fully characterized.

PURPOSE

Our study aimed to assess the effect of long-term menstrual pain on changes in static and dynamic neural activity in PD patients.

MATERIAL AND METHODS

Twenty-eight PD patients and 28 healthy controls (HCs) underwent resting-state magnetic resonance imaging scans. The amplitude of low-frequency fluctuations (ALFF) and dynamic ALFF was used as classification features in a machine learning approach involving a support vector machine (SVM) classifier.

RESULTS

Compared with the HC group, PD patients showed significantly increased ALFF values in the right cerebellum_crus2, right rectus, left supplementary motor area, right superior frontal gyrus, right supplementary motor area, and left superior frontal medial gyrus. Additionally, PD patients showed significantly decreased ALFF values in the right middle temporal gyrus and left thalamus. PD patients also showed significantly increased dALFF values in the right fusiform, Vermis_10, right middle temporal gyrus, right putamen, right insula, left thalamus, right precentral gyrus, and right postcentral gyrus. Based on ALFF and dALFF values, the SVM classifier achieved respective overall accuracies of 96.36% and 85.45% and respective areas under the curve of 1.0 and 0.95.

CONCLUSION

PD patients demonstrated abnormal static and dynamic brain activities that involved the default mode network, sensorimotor network, and pain-related subcortical nuclei. Moreover, ALFF and dALFF may offer sensitive biomarkers for distinguishing patients with PD from HCs.

Differential patterns of interhemispheric functional connectivity between AQP4-optic neuritis and MOG-optic neuritis: a resting-state functional MRI study

BACKGROUND

Several neuroimaging studies demonstrated that optic neuritis (ON) leads to functional and anatomical architecture changes in the brain. The alterations of interhemispheric functional connectivity (IFC) in patients with AQP4-ON and myelin oligodendrocyte glycoprotein (MOG)-ON are not well understood.

PURPOSE

To investigate the differential patterns of VMHC in patients with AQP4-ON and MOG-ON.

MATERIAL AND METHODS

Twenty-one patients with AQP4-ON, 11 patients with MOG-ON, and 34 healthy controls underwent resting-state MRI scans. One-way ANOVA was used to identify regions in which the zVMHC differed among the three groups. Post hoc two-sample t-tests were then conducted to compare zVMHC values between pairs of groups. Pearson correlation analysis was conducted to reveal relationships between mean zVMHC values and clinical variables in the AQP4-ON and MOG-ON groups.

RESULTS

The results revealed significant differences in zVMHC values in the PreCG among the three groups. Compared to the control group: the AQP4-ON group showed significantly lower VMHC values in the superior temporal gyrus, inferior frontal gyrus, and PreCG; and the MOG-ON group showed significantly higher zVMHC values in the PostCG. Compared to the AQP4-ON group, the MOG-ON group showed significantly lower zVMHC values in the PreCG/PostCG (voxel-level P<0.01, GRF correction, cluster-level P<0.05).

CONCLUSION

Patients with AQP4-ON and those with MOG-ON showed abnormal VMHC in the motor cortices, sensorimotor cortices, and frontal lobe, possibly indicating impaired sensorimotor function in patients with ON. Moreover, differential patterns of VMHC in patients with AQP4-ON, compared to patients with MOG-ON, might serve as a clinical indicator for classification of ON.

Altered Functional Connectivity of the Primary Visual Cortex in Patients With Iridocyclitis and Assessment of Its Predictive Value Using Machine Learning

Purpose

To explore the intrinsic functional connectivity (FC) alteration of the primary visual cortex (V1) between individuals with iridocyclitis and healthy controls (HCs) by the resting-state functional magnetic resonance imaging (fMRI) technique, and to investigate whether FC findings be used to differentiate patients with iridocyclitis from HCs.

Methods

Twenty-six patients with iridocyclitis and twenty-eight well-matched HCs were recruited in our study and underwent resting-state fMRI examinations. The fMRI data were analyzed by Statistical Parametric Mapping (SPM12), Data Processing and Analysis for Brain Imaging (DPABI), and Resting State fMRI Data Analysis Toolkit (REST) software. Differences in FC signal values of the V1 between the individuals with iridocyclitis and HCs were compared using independent two-sample t-tests. Significant differences in FC between two groups were chosen as classification features for distinguishing individuals with iridocyclitis from HCs using a support vector machine (SVM) classifier that involved machine learning. Classifier performance was evaluated using permutation test analysis.

Results

Compared with HCs, patients with iridocyclitis displayed significantly increased FC between the left V1 and left cerebellum crus1, left cerebellum 10, bilateral inferior temporal gyrus, right hippocampus, and left superior occipital gyrus. Moreover, patients with iridocyclitis displayed significantly lower FC between the left V1 and both the bilateral calcarine and bilateral postcentral gyrus. Patients with iridocyclitis also exhibited significantly higher FC values between the right V1 and left cerebellum crus1, bilateral thalamus, and left middle temporal gyrus; while they displayed significantly lower FC between the right V1 and both the bilateral calcarine and bilateral postcentral gyrus (voxel-level P<0.01, Gaussian random field correction, cluster-level P<0.05). Our results showed that 63.46% of the participants were correctly classified using the leave-one-out cross-validation technique with an SVM classifier based on the FC of the left V1; and 67.31% of the participants were correctly classified based on the FC of the right V1 (P<0.001, non-parametric permutation test).

Conclusion

Patients with iridocyclitis displayed significantly disturbed FC between the V1 and various brain regions, including vision-related, somatosensory, and cognition-related regions. The FC variability could distinguish patients with iridocyclitis from HCs with substantial accuracy. These findings may aid in identifying the potential neurological mechanisms of impaired visual function in individuals with iridocyclitis.

Changes in the topological organization of the default mode network in autism spectrum disorder

Neuroimaging studies have demonstrated that autism spectrum disorder (ASD) is accompanied by abnormal functional and structural features in specific brain regions of the default mode network (DMN). However, little is known about the alterations of the topological organization and the functional connectivity (FC) of the DMN in ASD patients. Thirty-seven ASD patients and 38 healthy control (HC) participants underwent a resting-state functional magnetic resonance imaging scan. Twenty DMN subregions were specifically selected to construct the DMN architecture. We applied graph theory approaches to the topological configuration and compare the FC patterns of the DMN. We then examined the relationships between the neuroimaging measures of the DMN and clinical characteristics in patients with ASD. The current study revealed that both the ASD and HC participants showed a small-world regimen in the DMN; however there were no significant differences in global network measures. Compared with the HC group, the ASD group exhibited significantly decreased nodal centralities in the bilateral anterior medial prefrontal cortex and increased nodal centralities in the right lateral temporal cortex and the right retrosplenial cortex. Patients with ASD displayed significantly reduced and increased FC within the DMN. Our findings demonstrated that ASD patients showed a pattern of disrupted FC metrics and nodal network metrics in the DMN, which could be a potential biomarker for objective ASD diagnoses and for the level of autism spectrum traits. HIGHLIGHTS: We used graph theoretical approaches and functional connectivity (FC) to investigate the topological configuration and FC patterns of the DMN in ASD. The current study revealed that both ASD and HC participants exhibited small-world regimes in the DMN, however there were no significant differences in global network measures. The ASD group showed abnormal nodal centralities in the bilateral aMPFC, the right LTC and the Rsp of the DMN, and ASD was characterized by altered FC patterns, including decreased and increased FC within the DMN.

Abnormal intrinsic functional network hubs in diabetic retinopathy patients

BACKGROUND

However, whether the whole-brain functional network hub changes occur in diabetic retinopathy patients remains unknown.

PURPOSE

The purpose of the study was to investigate the function network centrality and connectivity changes in diabetic retinopathy patients using the voxel-wise degree centrality method.

MATERIALS AND METHODS

Thirty-four diabetic retinopathy patients (18 male and 16 female) and 38 healthy controls (18 male and 20 female) closely matched in age, sex, and education were enrolled in the study. Graph theory-based network analysis was performed to investigate the degree centrality between two groups.

RESULTS

Compared with healthy controls, diabetic retinopathy patients had significantly higher degree centrality values in the pons and bilateral caudate and had significantly lower degree centrality values in the left lingual and right lingual, and right angular/middle occipital gyrus (MOG). Moreover, diabetic retinopathy patients exhibited increased functional connectivity between the bilateral lingual and right cerebellum lobe and right fusiform/bilateral caudate and increased functional connectivity between the right angular/MOG and bilateral anterior cingulum and right cuneus/bilateral precuneus and increased functional connectivity between the bilateral caudate and right lingual and right superior occipital gyrus. In contrast, diabetic retinopathy patients showed decreased functional connectivity between bilateral lingual and left lingual and right lingual and left superior occipital gyrus and decreased functional connectivity between the angular/MOG and right inferior occipital gyrus/right fusiform and left MOG/inferior occipital gyrus and decreased functional connectivity between the bilateral caudate and bilateral cerebellum crus1.

CONCLUSION

Our results highlight that reorganization of the hierarchy of the cortical connectivity network related to visual network.

Disrupted Neural Activity in Individuals With Iridocyclitis Using Regional Homogeneity: A Resting-State Functional Magnetic Resonance Imaging Study

Objective: This study used the regional homogeneity (ReHo) technique to explore whether spontaneous brain activity is altered in patients with iridocyclitis.

Methods: Twenty-six patients with iridocyclitis (14 men and 12 women) and 26 healthy volunteers (15 men and 11 women) matched for sex and age were enrolled in this study. The ReHo technique was used to comprehensively assess changes in whole-brain synchronous neuronal activity. The diagnostic ability of the ReHo method was evaluated by means of receive operating characteristic (ROC) curve analysis. Moreover, associations of average ReHo values in different brain areas and clinical characteristics were analyzed using correlation analysis.

Result: Compared with healthy volunteers, reduced ReHo values were observed in patients with iridocyclitis in the following brain regions: the right inferior occipital gyrus, bilateral calcarine, right middle temporal gyrus, right postcentral gyrus, left superior occipital gyrus, and left precuneus. In contrast, ReHo values were significantly enhanced in the right cerebellum, left putamen, left supplementary motor area, and left inferior frontal gyrus in patients with iridocyclitis, compared with healthy volunteers (false discovery rate correction, P < 0.05).

Conclusion: Patients with iridocyclitis exhibited disturbed synchronous neural activities in specific brain areas, including the visual, motor, and somatosensory regions, as well as the default mode network. These findings offer a novel image-guided research strategy that might aid in exploration of neuropathological or compensatory mechanisms in patients with iridocyclitis.

Dynamic Changes of Amplitude of Low-Frequency Fluctuations in Patients With Diabetic Retinopathy

Background: Growing evidence demonstrate that diabetic retinopathy (DR) patients have a high risk of cognitive decline and exhibit abnormal brain activity. However, neuroimaging studies thus far have focused on static cerebral activity changes in DR patients. The characteristics of dynamic cerebral activity in patients with DR are poorly understood.

Purpose: The purpose of the study was to investigate the dynamic cerebral activity changes in patients with DR using the dynamic amplitude of low-frequency fluctuation (dALFF) method.

Materials and methods: Thirty-four DR patients (18 men and 16 women) and 38 healthy controls (HCs) (18 males and 20 females) closely matched in age, sex, and education were enrolled in this study. The dALFF method was used to investigate dynamic intrinsic brain activity differences between the DR and HC groups.

Results: Compared with HCs, DR patients exhibited increased dALFF variability in the right brainstem, left cerebellum_8, left cerebellum_9, and left parahippocampal gyrus. In contrast, DR patients exhibited decreased dALFF variability in the left middle occipital gyrus and right middle occipital gyrus.

Conclusion: Our study highlighted that DR patients showed abnormal variability of dALFF in the visual cortices, cerebellum, and parahippocampal gyrus. These findings suggest impaired visual and motor and memory function in DR individuals. Thus, abnormal dynamic spontaneous brain activity might be involved in the pathophysiology of DR.

Three dimensional MRF obtains highly repeatable and reproducible multi-parametric estimations in the healthy human brain at 1.5T and 3T

Magnetic resonance fingerprinting (MRF) is highly promising as a quantitative MRI technique due to its accuracy, robustness, and efficiency. Previous studies have found high repeatability and reproducibility of 2D MRF acquisitions in the brain. Here, we have extended our investigations to 3D MRF acquisitions covering the whole brain using spiral projection k-space trajectories. Our travelling head study acquired test/retest data from the brains of 12 healthy volunteers and 8 MRI systems (3 systems at 3 T and 5 at 1.5 T, all from a single vendor), using a study design not requiring all subjects to be scanned at all sites. The pulse sequence and reconstruction algorithm were the same for all acquisitions. After registration of the MRF-derived PD T1 and T2 maps to an anatomical atlas, coefficients of variation (CVs) were computed to assess test/retest repeatability and inter-site reproducibility in each voxel, while a General Linear Model (GLM) was used to determine the voxel-wise variability between all confounders, which included test/retest, subject, field strength and site. Our analysis demonstrated a high repeatability (CVs 0.7-1.3% for T1, 2.0-7.8% for T2, 1.4-2.5% for normalized PD) and reproducibility (CVs of 2.0-5.8% for T1, 7.4-10.2% for T2, 5.2-9.2% for normalized PD) in gray and white matter. Both repeatability and reproducibility improved when compared to similar experiments using 2D acquisitions. Three-dimensional MRF obtains highly repeatable and reproducible estimations of T1 and T2, supporting the translation of MRF-based fast quantitative imaging into clinical applications.

A Comparative Study on the Predictive Value of Different Resting-State Functional Magnetic Resonance Imaging Parameters in Preclinical Alzheimer's Disease

Objective: Diverse resting-state functional magnetic resonance imaging (rs-fMRI) studies showed that rs-fMRI might be able to reflect the earliest detrimental effect of cerebral beta-amyloid (Aβ) pathology. However, no previous studies specifically compared the predictive value of different rs-fMRI parameters in preclinical AD. Methods: A total of 106 cognitively normal adults (Aβ+ group = 66 and Aβ- group = 40) were included. Three different rs-fMRI parameter maps including functional connectivity (FC), fractional amplitude of low-frequency fluctuations (fALFF), and regional homogeneity (ReHo) were calculated. Receiver operating characteristic (ROC) curve analyses were utilized to compare classification performance of the three rs-fMRI parameters. Results: FC maps showed the best classifying performance in ROC curve analysis (AUC, 0.915, p < 0.001). Good but weaker performance was achieved by using ReHo maps (AUC, 0.836, p < 0.001) and fALFF maps (AUC, 0.804, p < 0.001). The brain regions showing the greatest discriminative power included the left angular gyrus for FC, left anterior cingulate for ReHo, and left middle frontal gyrus for fALFF. However, among the three measurements, ROI-based FC was the only measure showing group difference in voxel-wise analysis. Conclusion: Our results strengthen the idea that rs-fMRI might be sensitive to earlier changes in spontaneous brain activity and FC in response to cerebral Aβ retention. However, further longitudinal studies with larger sample sizes are needed to confirm their utility in predicting the risk of AD.

Graph convolution network with similarity awareness and adaptive calibration for disease-induced deterioration prediction

Graph convolution networks (GCN) have been successfully applied in disease prediction tasks as they capture interactions (i.e., edges and edge weights on the graph) between individual elements. The interactions in existing works are constructed by fusing similarity between imaging information and distance between non-imaging information, whereas disregarding the disease status of those individuals in the training set. Besides, the similarity is being evaluated by computing the correlation distance between feature vectors, which limits prediction performance, especially for predicting significant memory concern (SMC) and mild cognitive impairment (MCI). In this paper, we propose three mechanisms to improve GCN, namely similarity-aware adaptive calibrated GCN (SAC-GCN), for predicting SMC and MCI. First, we design a similarity-aware graph using different receptive fields to consider disease status. The labelled subjects on the graph are only connected with those labelled subjects with the same status. Second, we propose an adaptive mechanism to evaluate similarity. Specifically, we construct initial GCN with evaluating similarity by using traditional correlation distance, then pre-train the initial GCN by using training samples and use it to score all subjects. Then, the difference between these scores replaces correlation distance to update similarity. Last, we devise a calibration mechanism to fuse functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI) information into edges. The proposed method is tested on the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset. Experimental results demonstrate that our proposed method is useful to predict disease-induced deterioration and superior to other related algorithms, with a mean classification accuracy of 86.83% in our prediction tasks.

Altered long- and short-range functional connectivity density associated with poor sleep quality in patients with chronic insomnia disorder: A resting-state fMRI study

INTRODUCTION

Previous neuroimaging studies have suggested that brain functional impairment and hyperarousal occur during the daytime among patients with chronic insomnia disorder (CID); however, alterations to the brain's intrinsic functional architecture and their association with sleep quality have not yet been documented.

METHODS

In this study, our aim was to investigate the insomnia-related alterations to the intrinsic connectome in patients with CID (n = 27) at resting state, with a data-driven approach based on graph theory assessment and functional connectivity density (FCD), which can be interpreted as short-range (intraregional) or long-range (interregional) mapping.

RESULTS

Compared with healthy controls with good sleep, CID patients showed significantly decreased long-range FCD in the dorsolateral prefrontal cortices and the putamen. These patients also showed decreased short-range FCD in their multimodal-processing regions, executive control network, and supplementary motor-related areas. Furthermore, several regions showed increased short-range FCD in patients with CID, implying hyper-homogeneity of local activity.

CONCLUSIONS

Together, these findings suggest that insufficient sleep during chronic insomnia widely affects cortical functional activities, including disrupted FCD and increased short-range FCD, which is associated with poor sleep quality.

Estimation of intracranial volume: A comparative study between synthetic MRI and FSL-brain extraction tool (BET)2

Brain extraction represents an important step in numerous neuroimaging analyses. The brain extraction tool (BET)2 is a widely used deformable model-based approach for extraction of intracranial volume (ICV). The aim of this study is to estimate the ICV extraction accuracy using synthetic MR(SyMRI) method and BET2 in healthy adult participants and patients with Sturge-Weber Syndrome (SWS), including infants. 'Quantification of relaxation times and proton density by multi-echo acquisition of saturation recovery with turbo-spin-echo readout' (QRAPMASTER) with a 3.0 T magnetic resonance image (MRI) system was used for data acquisition. Statistical evaluations were performed with linear regression analysis and the Jaccard similarity coefficient (J). ICV extraction accuracy with synthetic MR method is found to be higher than BET2, for both aged healthy participants and SWS.

Altered Temporal Dynamic Intrinsic Brain Activity in Late Blindness

Previous neuroimaging studies demonstrated that visual deprivation triggers significant crossmodal plasticity in the functional and structural architecture of the brain. However, prior neuroimaging studies focused on the static brain activity in blindness. It remains unknown whether alterations of dynamic intrinsic brain activity occur in late blindness (LB). This study investigated dynamic intrinsic brain activity changes in individuals with late blindness by assessing the dynamic amplitude of low-frequency fluctuations (dALFFs) using sliding-window analyses. Forty-one cases of late blindness (LB) (29 males and 12 females, mean age: 39.70 ± 12.66 years) and 48 sighted controls (SCs) (17 males and 31 females, mean age: 43.23 ± 13.40 years) closely matched in age, sex, and education level were enrolled in this study. The dALFF with sliding-window analyses was used to compare the difference in dynamic intrinsic brain activity between the two groups. Compared with SCs, individuals with LB exhibited significantly lower dALFF values in the bilateral lingual gyrus (LING)/calcarine (CAL) and left thalamus (THA). LB cases also showed considerably decreased dFC values between the bilateral LING/CAL and the left middle frontal gyrus (MFG) and between the left THA and the right LING/cerebelum_6 (CER) (two-tailed, voxel-level P < 0.01, Gaussian random field (GRF) correction, cluster-level P < 0.05). Our study demonstrated that LB individuals showed lower-temporal variability of dALFF in the visual cortices and thalamus, suggesting lower flexibility of visual thalamocortical activity, which might reflect impaired visual processing in LB individuals. These findings indicate that abnormal dynamic intrinsic brain activity might be involved in the neurophysiological mechanisms of LB.

Assessment of cerebral low-frequency oscillations in patients with retinal vein occlusion: a preliminary functional MRI study

BACKGROUND

There is increasing evidence that patients with retinal vein occlusion exhibit cerebral vascular changes and are at an increased risk of stroke. However, it remains unknown whether patients with retinal vein occlusion exhibit changes in intrinsic brain activity.

PURPOSE

This study investigated intrinsic brain activity changes in patients with retinal vein occlusion by assessing the amplitude of low-frequency fluctuations.

MATERIAL AND METHODS

Forty-five patients with retinal vein occlusion (22 men, 23 women, mean age 56.55 ± 6.97 years) and 43 healthy controls (13 men, 30 women; mean age 53.53 ± 8.19 years) closely matched in age, sex, and education level underwent resting-state MRI scans. The amplitude of low-frequency fluctuation method was used to compare intrinsic brain activity between the two groups.

RESULTS

Compared with healthy controls, patients with retinal vein occlusion exhibited significantly lower amplitude of low-frequency fluctuation values in the left middle occipital gyrus, right middle occipital gyrus, and right calcarine. However, patients with retinal vein occlusion showed significantly higher amplitude of low-frequency fluctuations in the bilateral cerebellum 6, right hippocampus, left insula, and left fusiform (voxel-level P < 0.01, Gaussian random field correction, cluster-level P < 0.05).

CONCLUSION

Our results demonstrated that patients with retinal vein occlusion showed abnormal spontaneous neural activities in the visual cortices, cerebellum, and Papez circuit, which might indicate impaired vision, cognition, and emotional function in patients with retinal vein occlusion. These findings offer important insights into the neural mechanism of retinal vein occlusion.

Influence of Patient-Specific Head Modeling on EEG Source Imaging

Electromagnetic source imaging (ESI) techniques have become one of the most common alternatives for understanding cognitive processes in the human brain and for guiding possible therapies for neurological diseases. However, ESI accuracy strongly depends on the forward model capabilities to accurately describe the subject's head anatomy from the available structural data. Attempting to improve the ESI performance, we enhance the brain structure model within the individual-defined forward problem formulation, combining the head geometry complexity of the modeled tissue compartments and the prior knowledge of the brain tissue morphology. We validate the proposed methodology using 25 subjects, from which a set of magnetic-resonance imaging scans is acquired, extracting the anatomical priors and an electroencephalography signal set needed for validating the ESI scenarios. Obtained results confirm that incorporating patient-specific head models enhances the performed accuracy and improves the localization of focal and deep sources.

Altered effective connectivity of primary visual cortex in primary angle closure glaucoma using Granger causality analysis

Background

Previous neuroimaging studies demonstrated that primary angle closure glaucoma patients were associated with abnormal intrinsic brain activity in primary visual cortex (V1).

Purpose

The purpose of this study was to investigate the effective connectivity patterns of V1 in patients with primary angle closure glaucoma.

Material and Methods

Thirty-seven patients with primary angle closure glaucoma (20 men, 17 women) and 36 healthy controls (20 men, 16 women) closely matched for age, sex, and education, underwent resting-state MRI scans. A voxel-wise Granger causality analysis method was performed to explore different effective connectivity pattern of V1 between the two groups.

Results

Compared with healthy controls, patients with primary angle closure glaucoma showed decreased effective connectivity from the left V1 to left cuneus and increased effective connectivity from the left V1 to left precentral gyrus and right supplementary motor area. Meanwhile, patients with primary angle closure glaucoma showed decreased effective connectivity from left precentral gyrus to left V1 and right frontal middle gyrus to left V1. In addition, patients with primary angle closure glaucoma showed a decreased effective connectivity from the right V1 to left cuneus/calcarine and increased effective connectivity from the right V1 to left inferior frontal gyrus and right caudate. Meanwhile, patients with primary angle closure glaucoma showed decreased effective connectivity from right middle frontal gyrus/precentral gyrus to right V1 and left precentral gyrus to right V1.

Conclusion

Our results highlighted that patients with primary angle closure glaucoma had abnormal effective connectivity between V1 and higher visual area, motor cortices, somatosensory cortices, and frontal lobe, which indicated that they might present with abnormal top-down modulations, visual imagery, vision-motor function, and vision-related higher cognition function.

Comparison of intrinsic brain activity in individuals with low/moderate myopia versus high myopia revealed by the amplitude of low-frequency fluctuations

Background

Previous neuroimaging studies demonstrated that individuals with high myopia are associated with abnormalities in anatomy of the brain.

Purpose

The purpose of this study was to explore alterations in the intrinsic brain activity by studying the amplitude of low-frequency fluctuations.

Material and Methods

A total of 64 myopia individuals (41 with high myopia with a refractive error <–600 diopter [D], 23 with low/moderate myopia with a refractive error between –100 and –600 D, and similarly 59 healthy controls with emmetropia closely matched for age) were recruited. The amplitude of low-frequency fluctuations method was conducted to investigate the difference of intrinsic brain activity across three groups.

Results

Compared with the healthy controls, individuals with low/moderate myopia showed significantly decreased amplitude of low-frequency fluctuation values in the bilateral rectal gyrus, right cerebellum anterior lobe/calcarine, and bilateral thalamus and showed significantly increased amplitude of low-frequency fluctuation values in left white matter (optic radiation), right prefrontal cortex, and left primary motor cortex (M1)/primary somatosensory cortex (S1). In addition, individuals with high myopia showed significantly decreased amplitude of low-frequency fluctuation values in the right cerebellum anterior lobe/calcarine/bilateral parahippocampal gyrus, bilateral posterior cingulate cortex, and bilateral middle cingulate cortex and significantly increased amplitude of low-frequency fluctuation values in left white matter (optic radiation), bilateral frontal parietal cortex, and left M1/S1. Moreover, we found that the amplitude of low-frequency fluctuation values of the different brain areas was closely related to the clinical features in the high myopia group.

Conclusion

Our results demonstrated that individuals with low/moderate myopia and high myopia had abnormal intrinsic brain activities in various brain regions related to the limbic system, default mode network, and thalamo-occipital pathway.

Frequency-specific oscillations synchronization in primary angle-closure glaucoma

Background

Previous neuroimaging studies demonstrated that patients with primary angle-closure glaucoma were accompanied by abnormal neuronal activity.

Purpose

To investigate frequency-dependent local oscillations synchronization in primary angle-closure glaucoma using the regional homogeneity method.

Material and Methods

In total, 37 individuals with primary angle-closure glaucoma (20 men, 17 women) and 37 normal-sighted controls (20 men, 17 women) closely matched in age, sex, and education underwent resting-state MRI scans. We compared the different regional homogeneity values in full band (0.01–0.08 Hz) and two different frequency bands (slow-4: 0.027–0.073 Hz and slow-5: 0.010–0.027 Hz) between two groups.

Results

Compared to the normal-sighted group, the primary angle-closure glaucoma group showed decreased regional homogeneity values in the left calcarine and left postcentral in full band. The primary angle-closure glaucoma group showed increased regional homogeneity values in the bilateral superior medial frontal lobe in the slow-4 band. The primary angle-closure glaucoma group exhibited decreased regional homogeneity values in the right calcarine in the slow-5 band. Specifically, we found that the regional homogeneity values in the right superior frontal lobe were greater in the slow-4 than in the slow-5 band, whereas regional homogeneity in the left calcarine, right pallidum, left inferior occipital gyrus, left superior occipital gyrus, left postcentral/angular gyrus, left paracentral lobule, left superior parietal gyrus, and right precuneus gyrus were greater in the slow-5 than in the slow-4 band.

Conclusion

Primary angle-closure glaucoma groups showed abnormal regional homogeneity in visual network (calcarine) and default mode network (superior medial frontal lobe) at two frequency bands. Moreover, the regional homogeneity signals in slow-5 band showed closely related to the severity of individuals with primary angle-closure glaucoma.

Impaired interhemispheric synchrony in late blindness

Background

Several neuroimaging studies demonstrated that visual deprivation led to significant cross-modal plasticity in the brain’s functional and anatomical architecture.

Purpose

To investigate the pattern of the interhemispheric functional connectivity in individuals with late blindness using the voxel-mirrored homotopic connectivity (VMHC) and seed-based functional connectivity (FC) methods.

Material and Methods

Forty-four individuals with late blindness (22 men, 22 women; mean age = 39.88 ± 12.84 years) and 55 sighted control individuals (35 men, 20 women; mean age = 43.13 ± 13.98 years)—closely matched for age, sex, and education—underwent resting-state magnetic resonance imaging scans. The VMHC and seed-based FC methods were applied to assess interhemispheric coordination in a voxel-wise manner.

Results

Compared with the sighted control groups, the late blindness groups showed decreased VMHC values in the bilateral cuneus/calcarine/lingual gyrus (CUN/CAL/LING) (BA 17/18/19) (voxel level: P < 0.001, Gaussian random field [GRF] correction, cluster level: P < 0.005). Meanwhile, for seed-based FC analysis, compared with the sighted control group, the late blindness group showed a decreased FC between the right lower VMHC regions and the bilateral CUN/LING/CAL/precuneus (PreCUN)/left middle occipital gyrus (MOG) (BA 18/19/30/31) and left precentral gyrus (PreCG) and postcentral gyrus (PostCG) (BA 2/3/4/6). The late blindness group showed a decreased FC between the left lower VMHC regions and the bilateral CUN/LING/CAL/PreCUN (BA 18/19/31) and left PreCG and PostCG (BA 2/3/4/6) relative to the sighted control group (voxel level: P < 0.001, GRF correction, cluster level: P < 0.005). Moreover, a negative correlation was observed between the duration of blindness and VMHC values in the bilateral CUN/CAL/LING (r = −0.393, P = 0.008) in individuals with late blindness.

Conclusion

Our results indicated that late blindness induced substantial impairment of interhemispheric coordination in the visual cortex. This might reflect impaired visual fusion, visual recognition function, and top-down modulations in individuals with late blindness.

Influence of Mild White Matter Lesions on Voxel-based Morphometry

Purpose:

The aim of this study was to investigate whether the detectability of brain volume change in voxel-based morphometry (VBM) with gray matter images is affected by mild white matter lesions (MWLs).

Methods:

Three-dimensional T₁-weighted images (3D-T₁WIs) of 11 healthy subjects were obtained using a 3T MR scanner. We initially created 3D-T₁WIs with focal cortical atrophy simulated cortical atrophy in left amygdala (type A) and the left medial frontal lobe (type B) from control 3D-T₁WIs. Next, the following three types of MWL images were created: type A + 1L and type B + 1L images, only one white matter lesion; type A + 4L and type B + 4L images, four white matter lesions at distant positions; and type A + 4L^* and type B + 4L^* images, four white matter lesions at clustered positions. Comparisons between the control group and the other groups were performed with VBM using segmented gray matter images.

Results:

The gray matter volume was significantly lower in the type A group than in the control group, and similar results were observed in the type A + 1L, type A + 4L, and type A + 4L^* groups. Additionally, the gray matter volume was significantly lower in the type B group than in the control group, and similar results were observed in the type B + 1L, type B + 4L, and type B + 4L^* groups, but the cluster size in type B + 4L^* was smaller than that in type B.

Conclusion:

Our study showed that the detectability of brain volume change in VBM with gray matter images was not decreased by MWLs as lacunar infarctions. Therefore, we think that group comparisons with VBM should be analyzed by groups including and excluding subjects with MWLs, respectively.

Large-Scale Neuronal Network Dysfunction in Diabetic Retinopathy

Diabetic retinopathy (DR) patients are at an increased risk of cognitive decline and dementia. There is accumulating evidence that specific functional and structural architecture changes in the brain are related to cognitive impairment in DR patients. However, little is known regarding whether the functional architecture of resting-state networks (RSNs) changes in DR patients. The purpose of this study was to investigate the intranetwork functional connectivity (FC) and functional network connectivity (FNC) of RSN changes in DR patients using independent component analysis (ICA). Thirty-four DR patients (18 men and 16 women; mean age, 53.53 ± 8.67 years) and 38 nondiabetic healthy controls (HCs) (15 men and 23 women; mean age, 48.63 ± 11.83 years), closely matched for age, sex, and education, underwent resting-state magnetic resonance imaging scans. ICA was applied to extract the nine RSNs. Then, two-sample t-tests were conducted to investigate different intranetwork FCs within nine RSNs between the two groups. The FNC toolbox was used to assess interactions among RSNs. Pearson correlation analysis was conducted to explore the relationship between intranetwork FCs and clinical variables in the DR group. A receiver operating characteristic (ROC) curve was conducted to assess the ability of the intranetwork FCs of RSNs in discriminating between the two groups. Compared to the HC group, DR patients showed significant decreased intranetwork FCs within the basal ganglia network (BGN), visual network (VN), ventral default mode network (vDMN), right executive control network (rECN), salience network (SN), left executive control network (lECN), auditory network (AN), and dorsal default mode network (dDMN). In addition, FNC analysis showed increased VN-BGN, VN-vDMN, VN-dDMN, vDMN-lECN, SN-BGN, lECN-dDMN, and AN-BGN FNCs in the DR group, relative to the HC group. Furthermore, altered intranetwork FCs of RSNs were significantly correlated with the glycosylated hemoglobin (HbA1c) level in DR patients. A ROC curve showed that these specific intranetwork FCs of RSNs discriminated between the two groups with a high degree of sensitivity and specificity. Our study highlighted that DR patients had widespread deficits in both low-level perceptual and higher-order cognitive networks. Our results offer important insights into the neural mechanisms of visual loss and cognitive decline in DR patients.

Abnormal Functional Connectivity Density in New-Onset Type 1 Diabetes Mellitus Children: A Resting-State Functional Magnetic Resonance Imaging Study

Type 1 diabetes mellitus (T1DM) causes cognitive changes in children, which may be due to deficits in brain functions. It is unclear whether T1DM children will have brain functional changes during the initial stage of the disease. We aimed to investigate the changes in the functional brain network topology in children with new-onset T1DM. In this study, 35 new-onset T1DM children and 33 age-, sex-matched healthy controls underwent resting-state fMRI. The whole brain functional connectivity density (FCD) analysis and seed-based functional connectivity (FC) analysis were performed to investigate the changes in functional brain networks in new-onset T1DM children when compared with the controls. Pearson correlational analysis was used to explore the correlation between FCD value of differential brain areas and clinical variables in T1DM children. Compared with the controls, children with new-onset T1DM exhibited significantly decreased FCDs of the right inferior temporal gyrus (ITG) and the right posterior cingulate cortex (PCC). In the subsequent FC analysis, decreased FC was found between right PCC and right cuneus and increased FC was found between right ITG and left orbital part of inferior frontal gyrus in children with new-onset T1DM compared to the controls. The FCD values of right ITG and PCC did not correlate with HbA1c, blood glucose level before imaging, and full-scale intelligence quotient (IQ) in T1DM children. These results revealed that T1DM affect the functional activity of the immature brain at the initial stage. These findings also indicate a decrease in regional brain function and abnormalities in temporal-frontal and limbic-occipital circuitry in children with new-onset T1DM, and highlight the effects of T1DM on children's brain networks involved in visual process and memory, which may contribute to the cognition impairments observed in children with T1DM.

Alterations of regional homogeneity in Parkinson's disease with mild cognitive impairment: a preliminary resting-state fMRI study

PURPOSE

Mild cognitive impairment (MCI) is commonly observed in Parkinson's disease (PD), even in the early stages. However, the neural substrates of cognitive impairment in PD remain unclear. The aim of the current study was to investigate the change of local brain function in PD patients with MCI.

METHODS

Fifty patients with PD, including 25 PD patients with MCI (PD-MCI) and 25 PD patients with normal cognition (PD-NC), and 25 age- and sex-matched healthy controls (HC) were enrolled. Conventional magnetic resonance imaging (MRI), 3D structural images, and resting state-functional MRI (rs-fMRI) were performed in all subjects. Regional homogeneity (ReHo) was measured based on the rs-fMRI images to investigate the altered local brain functions.

RESULTS

Brain regions with decreased ReHo were located in the left posterior cerebellar lobe in PD sub-groups compared to the HC group, and the brain regions with increased ReHo were located in the limbic lobe (right precuneus/bilateral middle cingulate cortex) in PD-MCI compared with HC group. PD-MCI presented with increased ReHo in the bilateral precuneus/left superior parietal lobe and decreased ReHo in the left insula compared to PD-NC. ReHo values for the left precuneus were negatively related to neuropsychological scores, and ReHo values for the left insula were positively related to neuropsychological scores in PD subjects.

CONCLUSION

The present study demonstrated abnormal spontaneous synchrony in the left insula and left precuneus in patients with PD-MCI compared to PD-NC, which might provide a novel insight into the diagnosis and clinical treatment of cognitive impairment in PD.

Correlations of quantitative MRI metrics with myelin basic protein (MBP) staining in a murine model of demyelination

Myelin imaging in the central nervous system is essential for monitoring pathologies involving white matter alterations. Various quantitative MRI protocols relying on the modeling of the interactions of water protons with myelinated tissues have shown sensitivities in case of myelin disruption. Some extracted model parameters are more sensitive to demyelination, such as the bound pool fraction (f) in quantitative magnetization transfer imaging (qMTI), the radial diffusivity in diffusion tensor imaging (DTI), and the myelin water fraction (MWF) in myelin water imaging (MWI). A 3D ultrashort echo time (UTE) sequence within an appropriate water suppression condition (Diff-UTE) is also considered for the direct visualization of the myelin semi-solid matrix (Diff-UTE normalized signal; rSPF). In this paper, we aimed at assessing the sensitivities and correlations of the parameters mentioned above to an immuno-histological study of the myelin basic protein (MBP) in a murine model of demyelination at 7 T. We demonstrated a high sensitivity of the MRI metrics to demyelination, and strong Spearman correlations in the corpus callosum between histology, macromolecular proton fraction (ρ>0.87) and Diff-UTE signal (ρ>0.76), but moderate ones with radial diffusivity and MWF (|ρ|<0.70).