BACKGROUND: Gait impairment is closely related to quality of life in patients with Parkinson's disease (PD). This study aimed to explore alterations in brain microstructure in PD patients and healthy controls (HCs) and to identify the correlation of gait impairment in the ON and OFF states of patients with PD, respectively. METHODS: We enrolled 24 PD patients and 29 HCs from the Movement Disorders Program at Beijing Friendship Hospital Capital Medical University between 2019 and 2020. We acquired magnetic resonance imaging (MRI) scans and processed the diffusion kurtosis imaging (DKI) images. Preprocessing of diffusion-weighted data was performed with Mrtrix3 software, using a directional distribution function to track participants' main white matter fiber bundles. Demographic and clinical characteristics were recorded. Quantitative gait and clinical scales were used to assess the status of medication ON and OFF in PD patients. RESULTS: The axial kurtosis (AK), mean kurtosis (MK), and radial kurtosis (RK) of five specific white matter fiber tracts, the bilateral corticospinal tract, left superior longitudinal fasciculus, left anterior thalamic radiation, forceps minor, and forceps major were significantly higher in PD patients compared to HCs. Additionally, the MK values were negatively correlated with Timed Up and Go Test (TUG) scores in both the ON and OFF in PD patients. Within the PD group, higher AK, MK, and RK values, whether the patients were ON or OFF, were associated with better gait performance (i.e., higher velocity and stride length). CONCLUSIONS PD exhibits characteristic regional patterns of white matter microstructural degradation. Correlations between objective gait parameters and DKI values suggest that dopamine-responsive gait function depends on preserved white matter microstructure. DKI-based Tract-Based Spatial Statistics (TBSS) analysis may serve as a tool for evaluating PD-related motor impairments (e.g., gait impairment) and could yield potential neuroimaging biomarkers.
Humans ; Parkinson Disease/diagnostic imaging* ; White Matter/physiopathology* ; Male ; Female ; Middle Aged ; Aged ; Gait/physiology* ; Diffusion Magnetic Resonance Imaging/methods* ; Diffusion Tensor Imaging/methods*

Previous studies have found associations between color discrimination deficits and cognitive impairments besides aging. However, investigations into the microstructural pathology of brain white matter (WM) associated with these deficits remain limited. This study aimed to examine the microstructural characteristics of WM in the non-demented population with abnormal color discrimination, utilizing Neurite Orientation Dispersion and Density Imaging (NODDI), and to explore their correlations with cognitive functions and cognition-related plasma biomarkers. The tract-based spatial statistic analysis revealed significant differences in specific brain regions between the abnormal color discrimination group and the healthy controls, characterized by increased isotropic volume fraction and decreased neurite density index and orientation dispersion index. Further analysis of region-of-interest parameters revealed that the isotropic volume fraction in the bilateral anterior thalamic radiation, superior longitudinal fasciculus, cingulum, and forceps minor was significantly correlated with poorer performance on neuropsychological assessments and to varying degrees various cognition-related plasma biomarkers. These findings provide neuroimaging evidence that WM microstructural abnormalities in non-demented individuals with abnormal color discrimination are associated with cognitive dysfunction, potentially serving as early markers for cognitive decline.
Humans ; White Matter/pathology* ; Male ; Female ; Cognitive Dysfunction/physiopathology* ; Middle Aged ; Aged ; Color Perception/physiology* ; Brain/pathology* ; Neuropsychological Tests ; Diffusion Tensor Imaging

Schizophrenia (SZ) stands as a severe psychiatric disorder. This study applied diffusion tensor imaging (DTI) data in conjunction with graph neural networks to distinguish SZ patients from normal controls (NCs) and showcases the superior performance of a graph neural network integrating combined fractional anisotropy and fiber number brain network features, achieving an accuracy of 73.79% in distinguishing SZ patients from NCs. Beyond mere discrimination, our study delved deeper into the advantages of utilizing white matter brain network features for identifying SZ patients through interpretable model analysis and gene expression analysis. These analyses uncovered intricate interrelationships between brain imaging markers and genetic biomarkers, providing novel insights into the neuropathological basis of SZ. In summary, our findings underscore the potential of graph neural networks applied to multimodal DTI data for enhancing SZ detection through an integrated analysis of neuroimaging and genetic features.
Humans ; Schizophrenia/pathology* ; Diffusion Tensor Imaging/methods* ; Male ; Female ; Adult ; Brain/metabolism* ; Young Adult ; Middle Aged ; White Matter/pathology* ; Gene Expression ; Nerve Net/diagnostic imaging* ; Graph Neural Networks

Humans ; Lupus Vasculitis, Central Nervous System/pathology* ; Magnetic Resonance Imaging/methods* ; Diffusion Tensor Imaging/methods* ; Patients ; Lupus Erythematosus, Systemic/pathology* ; Brain/pathology*

OBJECTIVES: To observe the effects of zhongfeng cutong moxibustion (moxibustion therapy for unblocking and treating stroke) on the motor function and the structure of corticospinal tract (CST) in the patients with motor dysfunction during the recovery period of cerebral infarction, and to explore the central mechanism of this moxibustion therapy for improving the motor function. METHODS: Fifty patients with motor dysfunction during the recovery period of cerebral infarction were randomly divided into an observation group (25 cases, 1 case dropped out) and a control group (25 cases, 1 case dropped out). The patients in both groups underwent the conventional basic treatment. In the control group, acupuncture was applied to Baihui (GV 20) and Shuigou (GV 26), as well as Chize (LU 5), Neiguan (PC 6), Weizhong (BL 40) and Sanyinjiao (SP 6) etc. on the affected side. Besides the intervention of the control group, in the observation group, zhongfeng cutong moxibustion therapy was combined at Baihui (GV 20), Shenque (CV 8) and bilateral Zusanli (ST 36). Both acupuncture and moxibustion therapies were delivered once daily, 5 times a week, for 2 weeks. The scores of Fugl-Meyer assessment scale (FMA) and National Institutes of Health stroke scale (NIHSS) were compared between the two groups before and after treatment. The diffusion tensor imaging technique was used to observe the fractional anisotropy (FA) of CST at the bilateral whole segment, the cerebral cortex, the posterior limb of the internal capsule and the cerebral peduncle before and after treatment in the two groups. RESULTS: The scores of the upper and the lower limbs of FMA, as well as the total FMA score swere increased after treatment when compared with those before treatment in the two groups (P<0.05), the upper limb FMA score and the total FMA score in the observation group were higher than those in the control group (P<0.05), and NIHSS scores of the two groups were dropped compared with those before treatment (P<0.01). FA of CST at the bilateral sides of the posterior limb of the internal capsule and the whole segment on the focal side was improved in comparison with that before treatment in the observation group (P<0.05), and FA of CST at the healthy side of the whole segment was higher than that before treatment in the control group (P<0.05). CONCLUSIONS Zhongfeng cutong moxibustion improves motor function and reduces neurological deficits in the patients with motor dysfunction during the recovery period of cerebral infarction, which may be related to enhancing the remodeling of white matter fiber bundles in the corticospinal tract on the focal side of the whole segment and the bilateral posterior limb of the internal capsule.
Humans ; Moxibustion ; Pyramidal Tracts ; Diffusion Tensor Imaging ; Acupuncture Therapy ; Cerebral Infarction/therapy* ; Stroke/therapy* ; Acupuncture Points ; Treatment Outcome

The glymphatic system can remove metabolic wastes from the brain, which plays a significant role in maintaining the homeostasis of the central nervous system. It is an important basis for advanced cognitive functions such as learning and memory. Studies have analyzed the function of glymphatic system by diffusion tensor imaging analysis along the perivascular space (DTI-ALPS) recently. Compared with other invasive examinations that require fluorescent tracer technique or the injection of contrast agents, DTI-ALPS can evaluate the hydromechanics of the glymphatic system via quantifying the diffusion rate of water molecules in different directions, which turns out to be a non-invasive in vivo neuroimaging method. The ALPS-index calculated by the DTI-ALPS method is significantly correlated with the cognitive function in diseases of central nervous system and other system and can reflect the dynamic changes of diseases. In general, ALPS-index is expected to become a novel neuroimaging biomarker for predicting prognosis and clinical effects.
Glymphatic System/diagnostic imaging* ; Diffusion Tensor Imaging ; Brain/diagnostic imaging* ; Central Nervous System ; Cognition

Alzheimer's disease (AD) is associated with the impairment of white matter (WM) tracts. The current study aimed to verify the utility of WM as the neuroimaging marker of AD with multisite diffusion tensor imaging datasets [321 patients with AD, 265 patients with mild cognitive impairment (MCI), 279 normal controls (NC)], a unified pipeline, and independent site cross-validation. Automated fiber quantification was used to extract diffusion profiles along tracts. Random-effects meta-analyses showed a reproducible degeneration pattern in which fractional anisotropy significantly decreased in the AD and MCI groups compared with NC. Machine learning models using tract-based features showed good generalizability among independent site cross-validation. The diffusion metrics of the altered regions and the AD probability predicted by the models were highly correlated with cognitive ability in the AD and MCI groups. We highlighted the reproducibility and generalizability of the degeneration pattern of WM tracts in AD.
Humans ; White Matter/diagnostic imaging* ; Diffusion Tensor Imaging/methods* ; Alzheimer Disease/complications* ; Reproducibility of Results ; Cognition ; Cognitive Dysfunction/complications* ; Brain/diagnostic imaging*

In transcranial magnetic stimulation (TMS), the conductivity of brain tissue is obtained by using diffusion tensor imaging (DTI) data processing. However, the specific impact of different processing methods on the induced electric field in the tissue has not been thoroughly studied. In this paper, we first used magnetic resonance image (MRI) data to create a three-dimensional head model, and then estimated the conductivity of gray matter (GM) and white matter (WM) using four conductivity models, namely scalar (SC), direct mapping (DM), volume normalization (VN) and average conductivity (MC), respectively. Isotropic empirical conductivity values were used for the conductivity of other tissues such as the scalp, skull, and cerebrospinal fluid (CSF), and then the TMS simulations were performed when the coil was parallel and perpendicular to the gyrus of the target. When the coil was perpendicular to the gyrus where the target was located, it was easy to get the maximum electric field in the head model. The maximum electric field in the DM model was 45.66% higher than that in the SC model. The results showed that the conductivity component along the electric field direction of which conductivity model was smaller in TMS, the induced electric field in the corresponding domain corresponding to the conductivity model was larger. This study has guiding significance for TMS precise stimulation.
Transcranial Magnetic Stimulation ; Diffusion Tensor Imaging ; Electric Conductivity ; Electricity ; Scalp

OBJECTIVE: To propose a diffusion tensor field estimation network based on 3D U-Net and diffusion tensor imaging (DTI) model constraint (3D DTI-Unet) to accurately estimate DTI quantification parameters from a small number of diffusion-weighted (DW) images with a low signal-to-noise ratio. METHODS: The input of 3D DTI-Unet was noisy diffusion magnetic resonance imaging (dMRI) data containing one non-DW image and 6 DW images with different diffusion coding directions. The noise-reduced non-DW image and accurate diffusion tensor field were predicted through 3D U-Net. The dMRI data were reconstructed using the DTI model and compared with the true value of dMRI data to optimize the network and ensure the consistency of the dMRI data with the physical model of the diffusion tensor field. We compared 3D DTI-Unet with two DW image denoising algorithms (MP-PCA and GL-HOSVD) to verify the effect of the proposed method. RESULTS: The proposed method was better than MP-PCA and GL-HOSVD in terms of quantitative results and visual evaluation of DW images, diffusion tensor field and DTI quantification parameters. CONCLUSION The proposed method can obtain accurate DTI quantification parameters from one non-DW image and 6 DW images to reduce image acquisition time and improve the reliability of quantitative diagnosis.
Diffusion Tensor Imaging ; Reproducibility of Results ; Diffusion Magnetic Resonance Imaging ; Algorithms ; Signal-To-Noise Ratio

Objective To investigate the changes in plasma amyloid-β (Aβ) level and their relationship with white matter microstructure in the patients with amnesic mild cognitive impairment(aMCI) and vascular mild cognitive impairment (vMCI).Methods A total of 36 aMCI patients,20 vMCI patients,and 34 sex and age matched healthy controls (HC) in the outpatient and inpatient departments of the First Affiliated Hospital of Anhui Medical University were enrolled in this study.Neuropsychological scales,including the Mini-Mental State Examination,the Montreal Cognitive Assessment,and the Activity of Daily Living Scale,were employed to assess the participants.Plasma samples of all the participants were collected for the measurement of Aβ42 and Aβ40 levels.All the participants underwent magnetic resonance scanning to obtain diffusion tensor imaging (DTI) data.The DTI indexes of 48 white matter regions of each individual were measured (based on the ICBM-DTI-81 white-matter labels atlas developed by Johns Hopkins University),including fractional anisotropy (FA) and mean diffusivity (MD).The cognitive function,plasma Aβ42,Aβ40,and Aβ42/40 levels,and DTI index were compared among the three groups.The correlations between the plasma Aβ42/40 levels and DTI index of aMCI and vMCI patients were analyzed.Results The Mini-Mental State Examination and the Montreal Cognitive Assessment scores of aMCI and vMCI groups were lower than those of the HC group (all P<0.001).There was no significant difference in the Activity of Daily Living Scale score among the three groups (P=0.654).The plasma Aβ42 level showed no significant difference among the three groups (P=0.227).The plasma Aβ40 level in the vMCI group was higher than that in the HC group (P=0.014),while it showed no significant difference between aMCI and HC groups (P=1.000).The plasma Aβ42/40 levels in aMCI and vMCI groups showed no significant differences from that in the HC group (P=1.000,P=0.105),while the plasma Aβ42/40 level was lower in the vMCI group than in the aMCI group (P=0.016).The FA value of the left anterior limb of internal capsule in the vMCI group was lower than those in HC and aMCI groups (all P=0.001).The MD values of the left superior corona radiata,left external capsule,left cingulum (cingulate gyrus),and left superior fronto-occipital fasciculus in the vMCI group were higher than those in HC (P=0.024,P=0.001,P=0.003,P<0.001) and aMCI (P=0.015,P=0.004,P=0.019,P=0.001) groups,while the MD values of the right posterior limb of internal capsule (P=0.005,P=0.001) and left cingulum (hippocampus) (P=0.017,P=0.031) in the aMCI and vMCI groups were higher than those in the HC group.In the aMCI group,plasma Aβ42/40 level was positively correlated with FA of left posterior limb of internal capsule (r=0.403,P=0.015) and negatively correlated with MD of the right fonix (r=-0.395,P=0.017).In the vMCI group,plasma Aβ42/40 level was positively correlated with FA of the right superior cerebellar peduncle and the right anterior limb of internal capsule (r=0.575,P=0.008;r=0.639,P=0.002),while it was negatively correlated with MD of the right superior cerebellar peduncle and the right anterior limb of internal capsule (r=-0.558,P=0.011;r=-0.626,P=0.003).Conclusions Plasma Aβ levels vary differently in the patients with aMCI and vMCI.The white matter regions of impaired microstructural integrity differ in the patients with different dementia types in the early stage.The plasma Aβ levels in the patients with aMCI and vMCI are associated with the structural integrity of white matter,and there is regional specificity between them.
Humans ; Diffusion Tensor Imaging ; White Matter/diagnostic imaging* ; Cognitive Dysfunction ; Outpatients ; Cognition ; Amyloid beta-Peptides