Diffusion Tensor Imaging Scans Research Articles

Differential diagnosis of neurodegenerative diseases using an innovative deep learning approach

AbstractBackgroundNeurodegenerative diseases lead to memory disorders and cognitive impairments with major impacts on day‐to‐day function. Early detection of patients is essential for an efficient care approach, and differential diagnosis is essential for determining prognosis and tailoring management. Most research studies compare patients by pairwise comparison methods, but this does not correspond to daily clinical practice, in which clinicians need to distinguish many different possible types of dementia concomitantly. It has been shown that magnetic resonance imaging (MRI) can mark with good accuracy the different types of dementia, such as: Alzheimer’s disease (AD), Frontotemporal dementia (FTD), Parkinson’s disease (PD), dementia with Lewy bodies (DLB). Recently, Deep Learning approaches have started being used although differential diagnosis is still almost ignored. The aim of this study was to develop a Convolution Neural Network (CNN) to classify probable AD, FTD, DLB, PD and healthy elderly control (CN) subjects starting from Diffusion Tensor Imaging (DTI).MethodThe cohort used in this study came from six different initiatives: ADNI1, NIFD2, NACC3, PDBP4, PPMI5 and Newcastle University6,7,8,9. We analysed a total of 108 CN, 110 AD, 135 FTD, 150 DLB, 132 PD. Demographic and neuropsychological characterization is shown in Table 1. The DTI scans were pre‐processed using the FMRIB software library (FSL) with eddy current correction, skull‐stripping and diffusion tensor calculation. We post‐processed the Fractional Anisotropy (FA) map using 3D CNN. The proposed CNN structure consisted of an image input layer, convolutional filters, several batch normalization with max‐pooling layers and, finally, the classification layer. A data augmentation approach was adopted that ultimately resulted in a dataset of 26’450 brain scans. A hold‐out validation (70% training set 30% test set) was performed.ResultWe found excellent performance of the 3D CNN in discriminating the different neurodegenerative diseases. Figure 1 shows the confusion matrix with the following values for the area under the ROC curve in each class: 0.92 for CN, 0.90 for AD, 0.97 for DLB, 0.96 for FTD, 0.99 for PD.ConclusionThese results prove that Deep Learning and the 3D CCN method are suitable for clinical practice and provide additional clues that can help clinicians in diagnosis making.

Evidence of lateralised white matter plasticity: A longitudinal study of balance performance in nonexpert healthy adults.

Training-induced plasticity by practicing expert skills has been of particular interest; however, little is known about white matter plasticity for improving a fundamental element of body function, such as balance or postural control. This study explored white matter plasticity in nonexpert healthy adults, based on stepwise balance training. Seventeen participants were included and performed a home-based balance training program for 4weeks (30 min/day, 3days/week). Before commencing training, they underwent a baseline diffusion tensor imaging scan. A second scan was acquired at the end of the 4-week training. Lateralised balance load was applied on the right leg to contrast any lateralised effect on the white matter tracts. The balance function was assessed using the Community Balance & Mobility Scale. We examined changes in the fractional anisotropy values of the tracts of interest between pre- and post-training. After the 4-week training, the fractional anisotropy values were enhanced in the right superior cerebellar peduncle, transverse pontine fibre, body of the corpus callosum, left fornix and left uncinate fasciculus. The Community Balance & Mobility Scalescore improved after 4-week training, but an association with changes in fractional anisotropy values cannot be evaluated due to the ceiling effect of the balance assessment tools. Balance training can strengthen the cerebro-cerebellar and interhemispheric structural connections and induce microstructural changes in the limbic structures, including the fornix and uncinate fasciculus. The effect of a lateralised balance load could be projected to the specific white matter tracts in a lateralised manner.

The Effect of Dehydroepiandrosterone Administration during Rehabilitation on White Matter Integrity Among Individuals With Polysubstance Use Disorder.

Individuals with polysubstance use disorder (pSUD) exhibit vulnerability to relapse even after prolonged abstinence, with rehabilitation efforts achieving limited success. Previous studies highlighted dehydroepiandrosterone (DHEA) as a putative therapeutic agent that may aid rehabilitation, potentially by impacting white matter (WM) properties. The current study tested, for the first time, the effect of DHEA administration during rehabilitation on WM integrity among pSUD individuals, while assessing its putative association with long-term relapse rates. Immediately after admission to rehabilitation, 30 pSUD individuals were assigned to receive either placebo or DHEA (100 mg) daily for 3 months, via a randomized double-blind counterbalanced design. Participants also provided blood samples to assess circulating DHEA levels at treatment initiation and completed a diffusion tensor imaging (DTI) scan approximately 1 month after treatment initiation. Clinical status was evaluated 16 months after treatment initiation. Thirty matched healthy controls also underwent a DTI scan without any intervention. DHEA administration was not associated with reduced relapse rates compared with placebo. Nevertheless, exploratory analysis revealed that DHEA was associated with successful rehabilitation among pSUD individuals with low circulating DHEA levels at treatment initiation. White matter integrity in the splenium corpus callosum (CC) was reduced in pSUD individuals compared with healthy controls, yet pSUD individuals receiving DHEA exhibited recovery of splenium CC WM integrity. DHEA administration during rehabilitation may restore WM integrity in the CC among pSUD individuals. Although DHEA was not associated with reduced relapse rates in here, its therapeutic efficacy may depend on circulating DHEA levels at treatment initiation.

Neural fingerprints of gambling disorder using diffusion tensor imaging

Gambling disorder (GD) is a behavioral addiction associated with personal, social and occupational consequences. Thus, examining GD's clinical relationship with its neural substrates is critical. We compared neural fingerprints using diffusion tensor imaging (DTI) in GD subjects undergoing treatment relative to healthy volunteers (HV). Fifty-three (25 GD, 28 age-matched HV) males were scanned with structural magnetic resonance imaging (MRI) and DTI. We applied probabilistic tractography based on DTI scanning data, preprocessed and analyzed using permutation testing of individual connectivity weights between regions for group comparison. Permutation-based comparisons between group-averaged connectomes highlighted significant structural differences. The GD group demonstrated increased connectivity, and striatal network reorganisation, contrasted by reduced connectivity within and to frontal lobe nodes. Modularity analysis revealed that the GD group had fewer hubs integrating information across the brain. We highlight GD neural changes involved in controlling risk-seeking behaviors. The observed striatal restructuring converges with previous research, and the increased connectivity affects subnetworks highly active in gambling situations, although these findings are not significant when correcting for multiple comparisons. Modularity analysis underlines that, despite connectivity increases, the GD connectome loses hubs, impeding its neuronal network coherence. Together, these results demonstrate the feasibility of using whole-brain computational modeling in assessing GD.

0528 Effects of continuous positive airway pressure on white matter microstructure in patients with obstructive sleep apnea

Abstract Introduction Obstructive sleep apnea (OSA) has significant effects on quality of life and may lead to cognitive impairments. Continuous positive airway pressure (CPAP) is the standard treatment for OSA, and has been shown to improve sleep disturbances and daytime dysfunction. In this study, we aimed to assess the effects of CPAP on white matter (WM) integrity using longitudinal diffusion tensor imaging (DTI) tests. Methods Twenty-two male patients with moderate to severe OSA were recruited and underwent DTI scanning before and 6-44 months after CPAP treatment. Sixteen male patients with untreated OSA who were not compliant with CPAP were included as a reference group. We compared the functional anisotropy (FA) values between baseline and follow-up MRI in both the CPAP and untreated groups using tract-specific statistical analysis (TSSA) method. Results The TSSA analysis showed that FA values in the middle part of the right CST were increased after treatment in the CPAP group. No significant change in FA value was observed between baseline and post-scan in the untreated group. In the CPAP group, the post-treatment FA value in the anterior part of the right ATR was significantly correlated with durations of CPAP therapy after controlling for age, body mass index, and baseline FA value. Conclusion Our study suggests that long-term CPAP treatment could gradually reverse OSA-induced injury to the WM microstructure, particularly WM associated with the motor and limbic systems. The study findings provide new insights into the mechanisms of cognitive improvement after CPAP treatment in patients with OSA. Support (if any)

Effects of Continuous Positive Airway Pressure on White Matter Microstructure in Patients With Obstructive Sleep Apnea

Background and Objective Obstructive sleep apnea (OSA) has significant effects on quality of life and may lead to cognitive impairments. Continuous positive airway pressure (CPAP) is the standard treatment for OSA and has been shown to improve sleep disturbances and daytime dysfunction. In this study, we aimed to assess the effects of CPAP on white matter (WM) integrity using longitudinal diffusion tensor imaging (DTI) tests.Methods Twenty-two male patients with moderate to severe OSA were recruited, and thepatients underwent DTI scanning before and 6–44 months after CPAP treatment. Sixteen male patients with untreated OSA who were not compliant with CPAP were included as a reference group. We compared the functional anisotropy (FA) values between baseline and follow-up magnetic resonance imaging in both the CPAP and untreated groups using tract-specific statistical analysis (TSSA) method.Results The TSSA analysis showed that FA values in the middle part of the right corticospinal tract were increased after treatment in the CPAP group. In the untreated group, no significant change in FA value was observed between baseline and follow-up. In the CPAP group, the post-treatment FA value in the anterior part of the right anterior thalamic radiation was significantly correlated with the duration of CPAP therapy, after controlling for age, body mass index, and baseline FA value.Conclusions Our study suggests that long-term CPAP treatment could gradually reverse OSA-induced injury to the WM microstructure, particularly WM associated with the motor and limbic systems. The study findings provide new insights into the mechanisms of cognitive improvement after CPAP treatment in patients with OSA.

Cingulum and Uncinate Fasciculus Microstructural Abnormalities in Parkinson’s Disease: A Systematic Review of Diffusion Tensor Imaging Studies

Diffusion tensor imaging (DTI) is gaining traction in neuroscience research as a tool for evaluating neural fibers. The technique can be used to assess white matter (WM) microstructure in neurodegenerative disorders, including Parkinson disease (PD). There is evidence that the uncinate fasciculus and the cingulum bundle are involved in the pathogenesis of PD. These fasciculus and bundle alterations correlate with the symptoms and stages of PD. PRISMA 2022 was used to search PubMed and Scopus for relevant articles. Our search revealed 759 articles. Following screening of titles and abstracts, a full-text review, and implementing the inclusion criteria, 62 papers were selected for synthesis. According to the review of selected studies, WM integrity in the uncinate fasciculus and cingulum bundles can vary according to symptoms and stages of Parkinson disease. This article provides structural insight into the heterogeneous PD subtypes according to their cingulate bundle and uncinate fasciculus changes. It also examines if there is any correlation between these brain structures' structural changes with cognitive impairment or depression scales like Geriatric Depression Scale-Short (GDS). The results showed significantly lower fractional anisotropy values in the cingulum bundle compared to healthy controls as well as significant correlations between FA and GDS scores for both left and right uncinate fasciculus regions suggesting that structural damage from disease progression may be linked to cognitive impairments seen in advanced PD patients. This review help in developing more targeted treatments for different types of Parkinson's disease, as well as providing a better understanding of how cognitive impairments may be related to these structural changes. Additionally, using DTI scans can provide clinicians with valuable information about white matter tracts which is useful for diagnosing and monitoring disease progression over time.

Predicting the efficacy of high-intensity focused ultrasound (HIFU) ablation for uterine leiomyomas based on DTI indicators and imaging features.

To predict the efficacy of high-intensity focused ultrasound (HIFU) ablation for uterine leiomyomas based on diffusion tensor imaging (DTI) indicators and imaging features. Sixty-two patients with 85 uterine leiomyomas were consecutively enrolled in this retrospective study and underwent DTI scanning before HIFU treatment. Based on whether the non-perfused volume ratio (NPVR) was greater than 70%, all patients were assigned to sufficient ablation (NPVR ≥ 70%) or insufficient ablation (NPVR < 70%) groups. The selected DTI indicators and imaging features were incorporated to construct a combined model. The predictive performance of DTI indicators and the combined model were assessed using receiver operating characteristic (ROC) curves. There were 42 leiomyomas in the sufficient ablation group (NPVR ≥ 70%) and 43 leiomyomas in the insufficient ablation group (NPVR < 70%). The fractional anisotropy (FA) and relative anisotropy (RA) values were higher in the sufficient ablation group than in the insufficient ablation group (p < 0.05). Conversely, the volume ratio (VR) and mean diffusivity (MD) values were lower in the sufficient ablation group than those in the insufficient ablation group (p < 0.05). Notably, the combined model composed of the RA and enhancement degree values had high predictive efficiency, with an AUC of 0.915. The combined model demonstrated higher predictive performance than FA and MD alone (p = 0.032 and p < 0.001, respectively) but showed no significant improvement compared with RA and VR (p > 0.05). DTI indicators, especially the combined model incorporating DTI indicators and imaging features, can be a promising imaging tool to assist clinicians in predicting HIFU efficacy for uterine leiomyomas.

Predicting Suicide Attempts among Major Depressive Disorder Patients with Structural Neuroimaging: A Machine Learning Approach

IntroductionEvery year at least one million people die by suicide, with major depressive disorder (MDD) being one of the major causes of suicide deaths. Current suicide risk assessments rely on subjective information, are time consuming, low predictive, and poorly reliable. Thus, finding objective biomarkers of suicidality is crucial to move clinical practice towards a precision psychiatry framework, enhancing suicide risk detection and prevention for MDD.ObjectivesThe present study aimed at applying machine learning (ML) algorithms on both grey matter and white-matter voxel-wise data to discriminate MDD suicide attempters (SA) from non-attempters (nSA).Methods91 currently depressed MDD patients (24 SA, 67 nSA) underwent a structural MRI session. T1-weighted images and diffusion tensor imaging scans were respectively pre-processed using Computational Atlas Toolbox 12 (CAT12) and spatial tract-based statistics (TBSS) on FSL, to obtain both voxel-based morphometry (VBM) and fractional anisotropy (FA) measures. Three classification models were built, entering whole-brain VBM and FA maps alone into a Support Vector Machine (SVM) and combining both modalities into a Multiple Kernel Learning (MKL) algorithm. All models were trained through a 5-fold nested cross-validation with subsampling to calculate reliable estimates of balanced accuracy, specificity, sensitivity, and area under the receiver operator curve (AUC).ResultsModels’ performances are summarized in Table 1.Table 1.Models’ performances.Input featuresAlgorithmSpecificitySensitivityBalanced accuracyAUCVBMSVM55.00%50.00%52.50%0.55FASVM72.00%54.00%63.00%0.62VBM and FAMKL68.00%54.00%61.00%0.58Abbreviations: AUC, area under the receiver operator curve; FA, fractional anisotropy; VBM, voxel-based morphometry.ConclusionsOverall, although overcoming the random classification accuracy (i.e., 50%), performances of all models classifying SA and nSA MDD patients were moderate, possibly due to the imbalanced numerosity of classes, with SVM on FA reaching the highest accuracy. Thus, future studies may enlarge the sample and add different features (e.g., functional neuroimaging data) to develop an objective and reliable predictive model to assess and hence prevent suicide risk among MDD patients.Disclosure of InterestNone Declared

Chronic Cocaine Use and White Matter Coherence: A Diffusion Tensor Imaging Study.

Chronic substance use and its effects on brain function and structure has long been of interest to clinicians and researchers. Prior cross-sectional comparisons of diffusion tensor imaging (DTI) metrics have suggested deleterious effects of chronic substance use (i.e., cocaine use) on white matter coherence. However, it is unclear how these effects may replicate across geographic regions when examined with similar technologies. In this study, we sought to conduct a replication of previous work in this area and determine whether there are any patterns of persistent differences in white matter microstructure between individuals with a history of cocaine use disorder (CocUD, according to the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition) and healthy controls. A total of 46 participants (21 healthy controls, 25 chronic cocaine users) were recruited from the Richmond, Virginia metropolitan area. Information regarding past and current substance use was collected from all participants. Participants also completed structural and DTI scans. Consistent with previous DTI studies, significant differences were found between fractional anisotropy (FA) and axial diffusivity (AD) CocUD and controls, with CocUD showing lower FA and AD in the right inferior and superior longitudinal fasciculus, the genu, body, and splenium of the corpus callosum, and the anterior, posterior, and superior corona radiata, among several other regions. These differences were not significant for other diffusivity metrics. Lifetime alcohol consumption was greater in the CocUD group, but lifetime alcohol consumption did not show a significant linear relationship with any of the DTI metrics in within-group regression analyses. These data align with previously reported declines in white matter coherence in chronic cocaine users. However, it is less clear whether comorbid alcohol consumption results in an additive deleterious effect on white matter microstructure.

The characteristics of brain structural remodeling in patients with unilateral vestibular schwannoma.

Brain structural remodeling alters related brain function. However, few studies have assessed morphological alterations of unilateral vestibular schwannoma (VS) patients. Therefore, this study examined the characteristics of brain structural remodeling in unilateral VS patients. We recruited 39 patients with unilateral VS (19 left, 20 right) and 24 matched normal controls (NCs). We obtained brain structural imaging data using 3T T1-weighted anatomical and diffusion tensor imaging scans. Then, we evaluated both gray and white matter (WM) changes using FreeSurfer software and tract-based spatial statistics, respectively. Furthermore, we constructed a structural covariance network to assess brain structural network properties and the connectivity strength between brain regions. Compared with NCs, VS patients showed cortical thickening in non-auditory areas (e.g., the left precuneus), especially left VS patients, along with reduced cortical thickness in the right superior temporal gyrus (auditory areas). VS patients also showed increased fractional anisotropy in extensive non-auditory-related WM (e.g., the superior longitudinal fasciculus), especially right VS patients. Both left and right VS patients showed increased small-worldness (more efficient information transfer). Left VS patients had a single reduced-connectivity subnetwork in contralateral temporal regions (right-side auditory areas), but increased connectivity between some non-auditory regions (e.g., left precuneus and left temporal pole). VS patients exhibited greater morphological alterations in non-auditory than auditory areas, with structural reductions seen in related auditory areas and a compensatory increase in non-auditory areas. Left and right VS patients show differential patterns of brain structural remodeling. These findings provide a new perspective on the treatment and postoperative rehabilitation of VS.

Amnestik hafif kognitif bozuklukta beyaz cevher değişiklikleri: yolak tabanlı uzamsal istatistik çalışması

Purpose: To compare white matter (WM) structural alterations between the subjects with amnestic mild cognitive impairment (MCI) which is a transitional state to Alzheimer's Disease (AD) and healthy elderly controls.&#x0D; Methods: Diffusion tensor imaging (DTI) scans of 20 subjects with amnestic MCI and 20 healthy control groups who are matched by age, gender, and education with the MCI group between 2011 and 2016 were examined by in this retrospective study. WM structural integrity was analyzed using tract based spatial statistics (TBSS) for voxel-based differences in fractional anisotropy (FA) between the two groups. &#x0D; Results: Fractional anisotropy was found significantly lower in the forceps minor, the body and genu of the corpus callosum, the right anterior thalamic radiation, the right cingulum, the right inferior fronto-occipital fasciculus, the right superior longitudinal fasciculus, and the right superior corona radiata in the MCI group than the control group. &#x0D; Conclusion: TBSS analysis is a promising method to examine structural WM integrity. These findings suggested that the DTI measurements may be useful for the detection of preclinical changes in AD.

The association of diffusion tensor MRI measures of normal appearing white matter and cognition

ObjectiveMedian and peak height of fractional anisotropy (FA) and mean diffusivity (MD) are diffusion tensor imaging (DTI) markers used to quantify white matter microstructure changes. We examine the association of DTI histogram-derived measures in global normal appearing white matter (NAWM) and cognitive decline in patients with normal cognition and cognitive impairment no dementia from a memory clinic in Singapore. MethodsA total of 252 patients (mean age: 71.1 ± 7.6 years, 53.2% women) were included. All patients underwent clinical assessments, a brain MRI scan at baseline, and neuropsychological assessments annually for 2 years. DTI scans were processed to obtain MD and FA histogram-derived measures. The National Institute of Neurological Disorders and Stroke and the Canadian Stroke Network harmonization neuropsychological battery were used to assess cognitive function. Linear regression models with generalised estimating equation (GEE) and logistic regression models were used to examine the association between DTI histogram measures and cognitive decline. ResultsWhen compared to baseline, MD and FA measures at Year 2 were associated with an accelerated worsening in global cognition (all p for interaction <0.001; Year 0 vs 2, MD median: -0.29 (95%CI: -0.49, -0.09) vs -0.45 (95%CI: -0.65,-0.25); MD peak height: 0.22 (95%CI: 0.07, 0.37) vs 0.37 (95%CI: 0.21, 0.53); FA median: 0.11 (95%CI: -0.05, 0.26) vs 0.22 (95%CI: 0.07, 0.37); FA peak height: -0.14 (95%CI: -0.28, 0.00) vs -0.24 (95%CI: -0.38, -0.10);). Similar findings were observed for executive function and visuomotor speed while only MD measures predicted worsening in memory domain. InterpretationThis study shows that DTI histogram measures are associated with accelerated cognitive decline suggesting the utility of DTI as a pre-clinical marker in predicting the worsening of cognition in clinical trials.

Clinical study on application of 3D Slicer software assisted domestic frameless stereotactic robot in biopsy of intracranial lesions

Objective: To examine the application value of 3D Slicer software assisted domestic frameless stereotactic robot in biopsy of intracranial lesions. Methods: A retrospective analysis was performed on 80 patients who admitted consecutively and underwent intracerebral lesions biopsy with the domestic frameless stereotactic robot at Department of Neurosurgery, Aerospace Central Hospital from January 2019 to December 2021. There were 36 males and 44 females, with a mean age of (38.5±18.0) years (range: 6 to 71 years). Before surgery only enhanced T1-weighted three-dimensional magnetization prepared gradient echo sequences and diffusion tensor imaging scans were performed. Self-reconstruction of intracranial lesions, cerebral cortex and blood vessels was carried out using 3D Slicer software system after the DICOM format imaging data of 80 patients were collected. These imaging data were merged to the workstation of the domestic frameless stereotactic robot for preoperative surgical planning and the surgical puncture path was designed to avoid blood vessels in the brain functional area, cerebral cortex and sulcus. Results: All frameless stereotactic biopsy were successfully performed. Postoperative pathological diagnosis included 50 cases of diffuse astrocytic and oligodendroglioma, 15 cases of lymphoma, 5 cases of metastatic tumors, 5 cases of inflammatory demyelinating disease, 2 cases of inflammatory granuloma, 1 case of hemangioma, 1 case of acute lymphoblastic leukemia intracranial invasion and 1 case of seminoma. The positive diagnosis rate was 100% (80/80). Postoperative imaging confirmed that the puncture path and target were accurately implemented according to the preoperative planning, and the target error was (1.32±0.44) mm (range: 0.55 to 1.99 mm). One case of puncture-related bleeding occurred at the target after surgery and improved after treatment. Conclusion: The three-dimensional multimodal images reconstructed by the 3D Slicer software before operation could help the surgeons make the preoperative planning and reduce the risk of stereotactic brain biopsy.

Variation in Diffusion Tensor Imaging Parameters in the Cervical and Thoracic Spinal Cord (C1-C5 and C6-T2) Segments of Normal Beagle Dogs.

This study aimed to determine the characteristics and reference values of each vertebra in the cervicothoracic region by performing diffusion tensor imaging (DTI) scans and analyzing DTI parameters in normal Beagle dogs. In five adult Beagles under anesthetic maintenance, DTI was performed using a 1.5-T magnetic resonance imaging (MRI) scanner. Axial DTI was performed using three overlapping slabs to cover the cervical and thoracic spinal cords. After post-processing, DTI parameters were calculated along the entire spinal cord. Among DTI parameters, fractional anisotropy, relative anisotropy, and axonal diffusivity significantly decreased in the caudal direction. However, the apparent diffusion coefficient, radial diffusivity, and mean diffusivity values were not significantly correlated with vertebral levels. We provide evidence for the existence of segment-dependent DTI parameters in the canine cervical spinal cord. Therefore, comparisons of DTI parameters between lesions at different vertebral levels should be avoided unless normative data are available. Furthermore, the DTI data obtained in this study may contribute to the development of a clinical reference for spinal cord evaluation in dogs using DTI parameters.

The alterations of spontaneous neural activities and white matter microstructures in anti-N-methyl-D-aspartate receptor encephalitis: a resting-state fMRI and DTI study.

Limited studies had jointly excavated the structural and functional changes in cognitive deficit in anti-N-methyl-D-aspartate receptor (NMDAR) encephalitis patients. We aimed to explore these changes in anti-NMDAR patients and their effect on cognitive function. Twenty-three patients and 25 healthy controls (HCs) underwent resting-state functional magnetic resonance imaging, diffusion tensor imaging scanning, and neuroethology tests. The significantly differentiated brain regions via the fractional amplitude of low-frequency fluctuation (fALFF) were defined as regions of interest (ROIs). Granger causal, functional connectivity, and tract-based spatial statistical analyses were applied to explore the functional changes in ROIs and assess the structural changes. HCs outperformed patients in Montreal Cognitive Assessment. The fALFF values of right gyrus rectus (RGR) in patients were significantly reduced. The fractional anisotropy (FA) values of WM in the genu of corpus callosum and right superior corona radiata were significantly decreased and positively associated with neuroethology testing scores. The Granger causal connectivity (GCC) from the left inferior parietal lobule to RGR was significantly decreased and positively associated with inherent vigilance. Indicated by the multiple linear regression result, decreased FA value of the right superior corona radiata might be a reliable marker that reflects the cognitive impairment. Significant changes in spontaneous neural activities, GCC, and WM structures in anti-NMDAR encephalitis were reported. These findings promote the understanding of underlying relationships between cerebral function, structural network alterations, and cognitive dysfunction.

Levodopa responsiveness and white matter alterations in Parkinson's disease: A DTI-based study and brain network analysis: A cross-sectional study.

Patients with Parkinson's disease (PD) present various responsiveness to levodopa, but the cause of such differences in levodopa responsiveness is unclear.Previous studies related the damage of brain white matter (WM) to levodopa responsiveness in PD patients, but no study investigated the relationship between the structural brain network change in PD patients and their levodopa responsiveness. PD patients were recruited and evaluated using the Unified Parkinson's Disease Rating Scale (UPDRS). Each patient received a diffusion tensor imaging (DTI) scan and an acute levodopa challenge test. The improvement rate of UPDRS-III was calculated. PD patients were grouped into irresponsive group (improvement rate<30%) and responsive group (improvement rate ≥ 30%). Tract-based spatial statistics (TBSS), deterministic tracing (DT), region of interest (ROI) analysis, and automatic fiber identification (AFQ) analyses were performed.The structural brain network was also constructed and the topological parameters were calculated. Fifty-four PD patients were included. TBSS identified significant differences in fractional anisotropy (FA) values in the corpus callosum and other regions of the brain. DT and ROI analysis of the corpus callosum found a significant difference in FA between the two groups. Graph theory analysis showed statistical differences in global efficiency, local efficiency, and characteristic path length. PD patients with poor responsiveness to levodopa had WM damage in multiple brain areas, especially the corpus callosum, which might cause disruption of information integration of the structural brain network.

Brain White Matter Structural Alteration in Hemifacial Spasm: A Diffusion Tensor Imaging Study

To analyze the changes in the white matter structure of the whole brain in hemifacial spasm (HFS) patients by using the tract-based spatial statistics (TBSS) method. 29 HFS patients without anxiety and depression and 29 healthy controls with matching age, sex, and education were selected. All subjects received a 3.0T magnetic resonance (MR) brain diffusion tensor imaging scan. Tract-based spatial statistics method was used to analyze the changes in white matter structure in the whole brain and obtained the cerebral white matter fibrous areas exhibiting significant intergroup differences. The fractional anisotropy (FA), mean diffusivity, axial diffusivity, and radial diffusivity of these areas were abstracted. Analyzed the correlation between these diffusion metrics and clinical variables (disease duration, spasm severity). Compared with the healthy controls group, the HFS group exhibited significantly lower FA in the forceps minor, bilateral anterior thalamic radiation, and right superior longitudinal fasciculus ( P <0.05, threshold-free cluster enhancement corrected). Cohen grading scale of HFS patients was negatively correlated with FA of forceps minor. Based on TBSS analysis, the injury of white matter fiber tracts in HFS patients was found, including forceps minor, bilateral anterior thalamic radiation, and right superior longitudinal fasciculus. The changes of FA values in forceps minor were negatively correlated with the Cohen grading scale, suggesting that the alteration of white matter fiber in the genu-of-corpus-callosum-cortex circuit plays an important role in the neuro-pathological mechanism of HFS. Combined with previous research, it is also necessary to further explore the change of the superior longitudinal fasciculus in the future.

Reproducibility of diffusion tensor imaging-derived parameters: implications for the streptozotocin-induced type 1 diabetic rats.

Diffusion tensor imaging (DTI) is a useful approach for studying neuronal integrity in animals. However, the test-retest reproducibility of DTI techniques in animals has not been discussed. Therefore, the first part of this work was to systematically elucidate the reliability of DTI-derived parameters in an animal study. Subsequently, we applied the DTI approach to an animal model of diabetes in a longitudinal manner. In Study 1, nine rats underwent two DTI sessions using the same scanner and protocols, with a gap of 4weeks. The reliability of the DTI-derived parameters was evaluated in terms of sessions and raters. In Study 2, nine rats received a single intraperitoneal injection of 70mg/kg streptozotocin (STZ) to develop diabetes. Longitudinal DTI scans were used to assess brain alterations before and 4weeks after STZ administration. In the test-retest evaluation, the inter-scan coefficient of variation (CoV) ranged from 3.04 to 3.73% and 2.12-2.59% for fractional anisotropy (FA) and mean diffusivity (MD), respectively, in different brain regions, suggesting excellent reproducibility. Moreover, rater-dependence had minimal effects on FA and MD quantification, with all inter-rater CoV values less than 4%. Following the onset of diabetes, FA in striatum and cortex were noted to be significantly lower relative to the period where they had not developed diabetes (both P < 0.05). However, when compared to the control group, a significant change in FA caused by diabetes was detected only in the striatum (P < 0.05), but not in the cortex. These results demonstrate good inter-rater and inter-scan reliability of DTI in animal studies, and the longitudinal setting has a beneficial effect on detecting small changes in the brain due to diseases.

Preliminary findings of accelerated visual memory decline and baseline brain correlates in middle-age and older adults with autism: The case for hippocampal free-water.

Research aimed at understanding cognitive and brain aging in adults with autism spectrum disorder (ASD) is growing, but critical longitudinal work is scant. Adults with ASD struggle with tasks involving visual memory compared with neurotypical adults (NT). This may be related to differences in size or integrity of the hippocampus and its' primary structural connectivity pathway, the fornix. The aim of this study was to describe preliminary findings of longitudinal aging trajectories in short- and long-term visual memory abilities in middle-age and older adults with ASD, compared with matched NT adults. We then evaluated baseline multi-modal imaging metrics of the hippocampal system, including the relatively novel metric of free-water, as potential correlates of longitudinal memory change in the ASD group. Middle-age and older adults with ASD (n = 25) and matched NT adults (n = 25) between the ages of 40 and 70 years were followed longitudinally at ~2-year intervals (range 2-5 years). Participants completed the Wechsler Memory Scale III Visual Reproduction task. Longitudinal mixed models were utilized to detect group differences in memory change with baseline age and sex as covariates. Hippocampal volume was measured via T1-weighted MRI images with FreeSurfer. Fornix fractional anisotropy and hippocampal and fornix free-water were measured from diffusion tensor imaging scans. Exploratory correlations were run between individual hippocampal system metrics and longitudinal slopes of visual memory change. There was a significant group by time interaction for long-term visual memory, such that middle-age and older adults with ASD declined faster than matched NT adults. There was no group by time interaction for short-term visual memory. Baseline hippocampal free-water was the only hippocampal system metric that correlated with long-term visual memory change in the ASD group. As one of the first longitudinal cognitive and brain aging studies in middle-age and older adults with ASD, our findings suggest vulnerabilities for accelerated long-term visual memory decline, compared to matched NT adults. Further, baseline hippocampal free-water may be a predictor of visual memory change in middle-age and older adults with ASD. These preliminary findings lay the groundwork for future prognostic applications of MRI for cognitive aging in middle-age and older adults with ASD.