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*

Among numerous medical imaging modalities, diffusion weighted imaging (DWI) is extremely sensitive to acute ischemic stroke lesions, especially small infarcts. However, magnetic resonance imaging is time-consuming and expensive, and it is also prone to interference from metal implants. Therefore, the aim of this study is to design a medical image synthesis method based on generative adversarial network, Stroke-p2pHD, for synthesizing DWI images from computed tomography (CT). Stroke-p2pHD consisted of a generator that effectively fused local image features and global context information (Global_to_Local) and a multi-scale discriminator (M ²Dis). Specifically, in the Global_to_Local generator, a fully convolutional Transformer (FCT) and a local attention module (LAM) were integrated to achieve the synthesis of detailed information such as textures and lesions in DWI images. In the M ²Dis discriminator, a multi-scale convolutional network was adopted to perform the discrimination function of the input images. Meanwhile, an optimization balance with the Global_to_Local generator was ensured and the consistency of features in each layer of the M ²Dis discriminator was constrained. In this study, the public Acute Ischemic Stroke Dataset (AISD) and the acute cerebral infarction dataset from Yantaishan Hospital were used to verify the performance of the Stroke-p2pHD model in synthesizing DWI based on CT. Compared with other methods, the Stroke-p2pHD model showed excellent quantitative results (mean-square error = 0.008, peak signal-to-noise ratio = 23.766, structural similarity = 0.743). At the same time, relevant experimental analyses such as computational efficiency verify that the Stroke-p2pHD model has great potential for clinical applications.
Humans ; Tomography, X-Ray Computed/methods* ; Diffusion Magnetic Resonance Imaging/methods* ; Cerebral Infarction/diagnostic imaging* ; Stroke/diagnostic imaging* ; Neural Networks, Computer ; Image Processing, Computer-Assisted/methods* ; Algorithms

The internal structures of cells as the basic units of life are a major wonder of the microscopic world. Cellular images provide an intriguing window to help explore and understand the composition and function of these structures. Scientific imagery combined with artistic expression can further expand the potential of imaging in educational dissemination and interdisciplinary applications. This study presents an innovative diffusion model-based approach for style transfer in cellular images, combining scientific rigor with artistic expression. By leveraging training-free large-scale pre-trained diffusion models, the proposed method integrates the intricate morphological and textural features of cellular images with diverse artistic styles. Key techniques such as the inversion of denoising diffusion implicit models (DDIMs), adaptive instance normalization (AdaIN), self-attention style injection, and attention temperature scaling ensure the preservation of cellular structures while enhancing visual expressiveness. The results showcase the potential of this strategy for interdisciplinary applications, enriching both the visualization and educational dissemination of cellular imagery through compelling storytelling and aesthetic appeal.
Humans ; Image Processing, Computer-Assisted/methods* ; Cells ; Diffusion

Objective:To explore the application value of high-resolution temporal bone CT and DW-MRI fusion technology in achieving precise diagnosis and anatomical localization of middle ear cholesteatoma during endoscopic surgery. Methods:Eighteen patients initially diagnosed with middle ear cholesteatoma in the Department of Otolaryngology Head and Neck Surgery, Shaanxi Provincial People's Hospital, from January to June 2024 were enrolled.Preoperative high-resolution temporal bone CT and DW-MRI were performed, and rtStation software was used for image fusion to construct CT-MRI fused images. The involvement of cholesteatoma in six anatomical subregions of the temporal bone was evaluated. Using surgical pathology as the gold standard, and combining surgical videos and anatomical records, the sensitivity, specificity, and accuracy of pure CT, pure DW-MRI, and CT-MRI fused images in evaluating middle ear cholesteatoma lesions were compared. Results:A total of 18 patients were included, and 17 cases were pathologically confirmed as middle ear cholesteatoma postoperatively. The sensitivity of the preoperative of preoperative CT was 100%, but the specificity was only 44.44%, with an overall accuracy of 72.22%; the sensitivity and specificity of DW-MRI evaluation were 81.46% and 85.19%, the accuracy was 83.33%, respectively. In contrast, the sensitivity and specificity of CT-MRI fusion image to the spatial localization of cholesteatoma were higher than that of DW-MRI alone（92.59% vs 81.46%; 98.15% vs 85.19%）, and the diagnostic accuracy was also significantly improved（95.37% vs 83.33%）. The Kappa values for the agreement between HRCT, DW-MRI, and CT-MRI segmentation localization and pathological results were 0.444, 0.667, and 0.907 respectively. The chi-square paired t-test confirmed statistically significant diagnostic differences between groups（P<0.001）. Results demonstrated that CT-MRI significantly outperformed HRCT and DW-MRI in diagnostic efficacy for segmental localization of primary posterior congenital middle ear cholesteatoma. Conclusion:High-resolution temporal bone CT combined with DW-MRI fusion technology demonstrates higher sensitivity, specificity, and accuracy in the diagnosis and spatial localization of middle ear cholesteatoma than single imaging modalities. It can provide more precise evaluation of lesion scope for endoscopic surgery, showing important clinical application value.
Humans ; Cholesteatoma, Middle Ear/diagnostic imaging* ; Tomography, X-Ray Computed ; Temporal Bone/diagnostic imaging* ; Diffusion Magnetic Resonance Imaging ; Female ; Male ; Adult ; Sensitivity and Specificity ; Middle Aged ; Endoscopy

OBJECTIVES: To qualitatively assess the diagnostic performance of dynamic contrast enhancement (DCE), diffusion-weighted imaging (DWI), and T2-weighted imaging (T2WI), alone or in combination, in the evaluation of breast cancer. METHODS: We retrospectively reviewed the records of 394 consecutive patients with pathologically confirmed breast lesions who had undergone 3-T magnetic resonance imaging (MRI). The morphological characteristics of breast lesions were evaluated using DCE, DWI, and T2WI based on BI-RADS lexicon descriptors by trained radiologists. Patients were categorized into mass and non-mass groups based on MRI characteristics of the lesions, and the differences between benign and malignant lesions in each group were compared. Clinical prediction models for breast cancer diagnosis were constructed using logistic regression analysis. Diagnostic efficacies were compared using the area under the receiver operating characteristic curve (AUC) and DeLong test. RESULTS: For mass-like lesions, all the morphological parameters significantly differentiated benign and malignant lesions on consensus DCE, DWI, and T2WI (P<0.05). The combined method (DCE+DWI+T2WI) had a higher AUC (0.865) than any of the individual modality (DCE: 0.786; DWI: 0.793; T2WI: 0.809) (P<0.05). For non-mass-like lesions, DWI signal intensity was a significant predictor of malignancy (P=0.036), but the model using DWI alone had a low AUC (0.669). CONCLUSIONS Morphological assessment using the combination of DCE, DWI, and T2WI provides better diagnostic value in differentiating benign and malignant breast mass-like lesions than assessment with only one of the modalities.
Humans ; Female ; Breast Neoplasms/pathology* ; Retrospective Studies ; Middle Aged ; Adult ; Diffusion Magnetic Resonance Imaging/methods* ; Aged ; Magnetic Resonance Imaging/methods* ; Young Adult ; Aged, 80 and over

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

The rich club, as a community of highly interconnected nodes, serves as the topological center of the network. However, the similarities and differences in how the rich club supports functional integration and segregation in the brain across different species remain unknown. In this study, we first detected and validated the rich club in the structural networks of mouse, monkey, and human brains using neuronal tracing or diffusion magnetic resonance imaging data. Further, we assessed the role of rich clubs in functional integration, segregation, and balance using quantitative metrics. Our results indicate that the presence of a rich club facilitates whole-brain functional integration in all three species, with the functional networks of higher species exhibiting greater integration. These findings are expected to help to understand the relationship between brain structure and function from the perspective of brain evolution.
Animals ; Humans ; Brain/diagnostic imaging* ; Mice ; Male ; Nerve Net/diagnostic imaging* ; Macaca ; Female ; Neural Pathways/diagnostic imaging* ; Magnetic Resonance Imaging ; Biological Evolution ; Adult ; Diffusion Magnetic Resonance Imaging ; Brain Mapping ; Species Specificity ; Mice, Inbred C57BL

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

OBJECTIVE: To observe the clinical efficacy of scalp acupuncture for spastic cerebral palsy (CP), and to explore its possible mechanism based on brain white matter fiber bundles, nerve growth related proteins and inflammatory cytokines. METHODS: A total of 90 children with spastic CP were randomly divided into a scalp acupuncture group and a sham scalp acupuncture group, 45 cases in each group. The children in the two groups were treated with conventional comprehensive rehabilitation treatment. The children in the scalp acupuncture group were treated with scalp acupuncture at the parietal temporal anterior oblique line, parietal temporal posterior oblique line on the affected side, and parietal midline. The children in the sham scalp acupuncture group were treated with scalp acupuncture at 1 cun next to the above point lines. The needles were kept for 30 min, once a day, 5 days a week, for 12 weeks. Before and after treatment, the diffusion tensor imaging (DTI) indexes of magnetic resonance (FA values of corticospinal tract [CST], anterior limb of internal capsule [ICAL], posterior limb of internal capsule [ICPL], genu of internal capsule [ICGL], genu of corpus callosum [GCC], body of corpus callosum [BCC] and splenium of corpus callosum [SCC]), serum levels of nerve growth related proteins (neuron-specific enolase [NSE], glial fibrillary acidic protein [GFAP], myelin basic protein [MBP], ubiquitin carboxy terminal hydrolase-L1 [UCH-L1]) and inflammatory cytokines (interleukin 33 [IL-33], tumor necrosis factor α [TNF-α]), cerebral hemodynamic indexes (mean blood flow velocity [Vm], systolic peak flow velocity [Vs] and resistance index [RI], pulsatility index [PI] of cerebral artery), surface electromyography (SEMG) signal indexes (root mean square [RMS] values of rectus femoris, hamstring muscles, gastrocnemius muscles, tibialis anterior muscles), gross motor function measure-88 (GMFM-88) score, modified Ashworth scale (MAS) score, ability of daily living (ADL) score were observed in the two groups. The clinical effect of the two groups was compared. RESULTS: After treatment, the FA value of each fiber bundle, Vm, Vs, GMFM-88 scores and ADL scores in the two groups were higher than those before treatment (P<0.05), and the above indexes in the scalp acupuncture group were higher than those in the sham scalp acupuncture group (P<0.05). After treatment, the serum levels of NSE, GFAP, MBP, UCH-L1, IL-33, TNF-α as well as RI, PI, MAS scores and RMS values of each muscle were lower than those before treatment (P<0.05), and the above indexes in the scalp acupuncture group were lower than those in the sham scalp acupuncture group (P<0.05). The total effective rate was 95.6% (43/45) in the scalp acupuncture group, which was higher than 82.2% (37/45) in the sham scalp acupuncture group (P<0.05). CONCLUSION Scalp acupuncture could effectively treat spastic CP, improve the cerebral hemodynamics and gross motor function, reduce muscle tension and spasticity, and improve the ability of daily life. The mechanism may be related to repairing the white matter fiber bundles and regulating the levels of nerve growth related proteins and inflammatory cytokines.
Child ; Humans ; Cerebral Palsy/therapy* ; Interleukin-33 ; Diffusion Tensor Imaging/methods* ; Scalp ; Muscle Spasticity ; Tumor Necrosis Factor-alpha ; Acupuncture Therapy ; Cytokines