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*

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

Alzheimer Disease ; Brain ; Humans ; White Matter/diagnostic imaging*

Brain/diagnostic imaging* ; Humans ; Magnetic Resonance Imaging ; Neuroimaging ; White Matter/diagnostic imaging*

Constrained spherical deconvolution can quantify white matter fiber orientation distribution information from diffusion magnetic resonance imaging data. But this method is only applicable to single shell diffusion magnetic resonance imaging data and will provide wrong fiber orientation information in white matter tissue which contains isotropic diffusion signals. To solve these problems, this paper proposes a constrained spherical deconvolution method based on multi-model response function. Multi-shell data can improve the stability of fiber orientation, and multi-model response function can attenuate isotropic diffusion signals in white matter, providing more accurate fiber orientation information. Synthetic data and real brain data from public database were used to verify the effectiveness of this algorithm. The results demonstrate that the proposed algorithm can attenuate isotropic diffusion signals in white matter and overcome the influence of partial volume effect on fiber direction estimation, thus estimate fiber direction more accurately. The reconstructed fiber direction distribution is stable, the false peaks are less, and the recognition ability of cross fiber is stronger, which lays a foundation for the further research of fiber bundle tracking technology.
Brain ; White Matter/diagnostic imaging* ; Diffusion Magnetic Resonance Imaging/methods* ; Algorithms ; Databases, Factual ; Image Processing, Computer-Assisted/methods*

As the two essential components, the white matter and gray matter compose the central nervous system of the brain. Widely known that axons of neurons mainly form the white matter, and these formed nerve fibers are responsible for transmitting information among various brain regions to achieve the coordinated operation of the entire brain. Early research on the white matter could only be done by dissecting living animals or human cadavers, until Basser et al. proposed diffusion tensor imaging (DTI) technology in 1994, which could detect the diffusion characteristics of water in the brain in vivo noninvasively. Accordingly, this technology could be applied to investigate the diffusion movement of water in white matter to obtain the information of direction and micro-anatomy of white matter fiber bundles. With the advancement on the display and analysis of the anatomical structure of white matter fiber bundles, the exploration of microscopic pathological changes, and the assistance of clinical diagnosis and neurophysiological research, DTI technology has become one of the most popular topics in brain science research. Chronic pain refers to pain lasting more than three months, which not only seriously affects the patient's physical and social functions, but also dramatically reduces the quality of life. It was reported that long-term pain stimulation might cause pathological remodeling of the central nervous system, and abnormalities in white matter were found in imaging examinations of patients with chronic pain. This review introduces the quantitative analysis methods of white matter fiber bundle microstructure based on DTI and its application in chronic pain, and further discusses the application value of DTI technology on clinical research of chronic pain.
Animals ; Brain ; Chronic Pain/diagnostic imaging* ; Diffusion Tensor Imaging ; Humans ; Quality of Life ; White Matter/diagnostic imaging*

Diffusion tensor imaging technology can provide information on the white matter of the brain, which can be used to explore changes in brain tissue structure, but it lacks the specific description of the microstructure information of brain tissue. The neurite orientation dispersion and density imaging make up for its shortcomings. But in order to accurately estimate the brain microstructure, a large number of diffusion gradients are needed, and the calculation is complex and time-consuming through maximum likelihood fitting. Therefore, this paper proposes a kind of microstructure parameters estimation method based on the proximal gradient network, which further avoids the classic fitting paradigm. The method can accurately estimate the parameters while reducing the number of diffusion gradients, and achieve the purpose of imaging quality better than the neurite orientation dispersion and density imaging model and accelerated microstructure imaging via convex optimization model.
Brain/diagnostic imaging* ; Diffusion Magnetic Resonance Imaging ; Diffusion Tensor Imaging ; Neurites ; White Matter

This study aimed to define the most consistent white matter microarchitecture pattern in Parkinson's disease (PD) reflected by fractional anisotropy (FA), addressing clinical profiles and methodology-related heterogeneity. Web-based publication databases were searched to conduct a meta-analysis of whole-brain diffusion tensor imaging studies comparing PD with healthy controls (HC) using the anisotropic effect size-signed differential mapping. A total of 808 patients with PD and 760 HC coming from 27 databases were finally included. Subgroup analyses were conducted considering heterogeneity with respect to medication status, disease stage, analysis methods, and the number of diffusion directions in acquisition. Compared with HC, patients with PD had decreased FA in the left middle cerebellar peduncle, corpus callosum (CC), left inferior fronto-occipital fasciculus, and right inferior longitudinal fasciculus. Most of the main results remained unchanged in subgroup meta-analyses of medicated patients, early stage patients, voxel-based analysis, and acquisition with 30 diffusion directions. The subgroup meta-analysis of medication-free patients showed FA decrease in the right olfactory cortex. The cerebellum and CC, associated with typical motor impairment, showed the most consistent FA decreases in PD. Medication status, analysis approaches, and the number of diffusion directions have an important impact on the findings, needing careful evaluation in future meta-analyses.
Anisotropy ; Brain/diagnostic imaging* ; Corpus Callosum ; Diffusion Tensor Imaging ; Humans ; Parkinson Disease/diagnostic imaging* ; White Matter/diagnostic imaging*

OBJECTIVE: To construct and verify a standard template of white matter based on Chinese normal 0 to 2 years old infants by using nonlinear high registration accuracy of non-rigid diffeomorphism paradigm (large deformation diffeomorphic metric mapping, LDDMM). METHODS: Full-term spontaneous labor children without maternal pregnancy disease (hypertension, diabetes, etc.), intrauterine hypoxia and ischemia, head trauma, intracranial infection, intracranial surgery history, family history of mental disorders were selected. Diffusion tensor imaging (DTI) data from the 120 normal Chinese infants under 2 years old were acquired after excluding the existence of neurological diseases revealed by neurologists, radiologists and Gesell Developmental Scale. All the data were divided into six groups including group A: 1 day to 1.5 months, group B: 1.5 to 4.5 months, group C: 4.5 to 9.0 months, group D: 9 to 15 months, group E: 15 to 21 months, and group F: 21 to 24 months. Data pre-processing, normalizing, tensor fitting and calculation of all the images were performed by using MRlcron, DtiStudio, DiffeoMap and SPM software package combined with LDDMM image registration method based on the selected single template of each group. And the average templates of each group were constructed by MATLAB software platform. The set of templates included fractional anisotropy figure (FA), color map, T1 weighted image, b0 image and the mean of all DWfs figures. RESULTS: The templates of FA, T1, b0, DWfs and color map for the normal brain magnetic resonance white matter development of the Chinese infants aged 0 to 2 years were successfully established with the subjective scores exceeding 2 points. The objective evaluation root mean squared error was controlled below 0.19, and the cubic chart of brain alternation trend for the children aged 0 to 2 years was consistent with previous literature. CONCLUSION Constructing a standard template of white matter based on Chinese normal infants, by using nonlinear high registration accuracy of non-rigid diffeomorphism paradigm provides not only a foundation of further research on brain development, mechanism and treatment of pediatric diseases associated with brain, but also objective and fair imaging information for medical education and research.
Brain/diagnostic imaging* ; Child ; Child, Preschool ; Diffusion Tensor Imaging ; Humans ; Image Processing, Computer-Assisted ; Infant ; Infant, Newborn ; Magnetic Resonance Spectroscopy ; Software ; White Matter/diagnostic imaging*

OBJECTIVE: To study the value of fast spin-echo diffusion weighted imaging (TSE-DWI) apparent diffusion coefficient (ADC) in children aged 2-12 years with intellectual disability (ID)/global developmental delay (GDD) who have normal conventional brain MRI findings. METHODS: A total of 578 children with normal conventional brain MRI findings who met the diagnostic criteria for ID/GDD and 375 normal children were enrolled. Their imaging and clinical data were collected. All children underwent scanning with brain TSE-DWI sequence and routine sequence. ADC values of each brain region were compared between normal children with different ages, as well as between children with different degrees of ID/GDD in each age group. The influence of Adaptive Behavior Assessment System-II (ABAS-II) score on ADC values of each brain region was analyzed. RESULTS: For the normal children, the ADC values of the frontal and temporal white matter, the corpus callosum, the inner capsule, the centrum semiovale, the cerebellar dentate nucleus, the optic radiation, the thalamus, the lenticular nucleus, and the caudate nucleus gradually decreased with age (P<0.05). ADC values of the deep white matter, the shallow white matter, the deep gray matter nuclei, and the shallow gray matter increased with the increase in the degree of ID/GDD in the ID/GDD children aged 4-6 years (P<0.05). In the children with ID/GDD, the ADC values of the deep white matter, the shallow white matter, and the deep gray matter nuclei decreased with age (P<0.05). The ADC values of the children with ID/GDD decreased with the increase in ABAS-II score (P<0.05). CONCLUSIONS ADC can reflect the subtle structural changes of brain regions in children with ID/GDD who have normal conventional brain MRI findings. It may be associated with social adaptation. It can provide an objective basis for the quantitative diagnosis of ID/GDD in children.
Brain ; Child ; Child, Preschool ; Diffusion Magnetic Resonance Imaging ; Humans ; Intellectual Disability ; diagnostic imaging ; Magnetic Resonance Imaging ; White Matter