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

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*

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 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