31 results about "White matter" patented technology

The invention discloses a brain-computer interface signal enhancement and evaluation method fusing physical information. The method comprises the following steps: firstly, based on an individual structure magnetic resonance image, constructing a personalized six-layer brain tissue anatomical model comprising a cortex, a white matter, cerebrospinal fluid, a dura mater, a skull and a scalp, and endowing differentiated conductivity parameters; secondly, neuroelectrophysiology priori knowledge such as neurodynamics and white matter anisotropic conduction is converted into a representation rule which can be learned by a neural network; then, the rules are systematically embedded into a physical information neural network in a differentiable physical constraint form, including a cortical neurodynamic equation residual error, a volume conduction equation residual error of each layer and an interlayer interface continuity constraint; and finally, training a network by using the scalp electroencephalogram signals, and jointly outputting high-fidelity intracranial electroencephalogram signals and multi-modal neurophysiological information by minimizing a loss function containing reconstruction and physical constraints. According to the method, the fidelity, the physical rationality and the clinical interpretability of signal enhancement are effectively improved.

The present application relates to reducing the adverse effects of oligodendrocyte loss, astrocyte loss, or white matter loss, including age-related oligodendrocyte loss, astrocyte loss, or white matter loss, in the brain of a subject. The present application also relates to rejuvenating glial progenitor cells or their progeny, or enhancing the developmental potential of glial progenitor cells or their progeny.

The application relates to a mild cognitive impairment development process prediction method and device, computer equipment, a storage medium and a computer program product. The method comprises the following steps: acquiring first diffusion tensor imaging images of a mild cognitive impairment patient in multiple follow-ups; processing each first diffusion tensor imaging image, extracting white matter fibers between all hippocampal voxels and other brain voxels; performing regional segmentation on the hippocampus according to the white matter fibers between all hippocampal voxels and other brain voxels, and constructing hippocampal subregions; constructing a first gradient change feature of the white matter fibers of each hippocampal subregion according to the gradient change of the target feature of the white matter fibers of the hippocampal subregion; and predicting the cognitive impairment development process of the measured object according to the basic information, clinical information and first gradient change feature of the white matter fibers of the hippocampal subregion of the patient. The method can improve disease classification accuracy and specificity, and can predict the cognitive impairment development process of the measured object.

The present invention pertains to the anti-inflammatory therapeutic effect of xantohumol in spinal cord injury (SCI). The continuous administration of xanthohumol for 1-8 weeks to SCI rats resulted in improved results in 4 clinical tests used and in lowering and faster elimination of macrophages from the SCI lesion. Since the infiltration of the SCI lesion by numerous phagocytic macrophages indicates a severe destructive inflammation of extraordinary longevity, administration of xanthohumol is neuroprotective and resulted in a better and faster recovery of the locomotor function and the strength and sensory function in the hind limbs, in a shorter period of paralysis of the urinary bladder and in the recovery of the body weight lost due to the SCI surgery. Since the traumatic brain injury (TBI) involving the white matter, and stroke involving the white matter initiate the severe destructive inflammation as in the SCI, the administration of xanthohumol is expected to be anti-inflammatory and neuroprotective in both brain diseases. Since neurodegenerative diseases including Alzheimer's disease, frontotemporal dementia and Parkinson's disease, immune mediated neuroinflammation including multiple sclerosis and neuromyelitis optica and cerebrospinal infections have inflammatory pathogenesis involving microgliosis and infiltration by macrophages, the administration of xanthohumol is expected to result in therapeutic inhibition of progression of all above diseases as well as of related neurodegenerative, immune mediated and infectious diseases of the brain and of the spinal cord.

A computer-implemented method for adjustable three-dimensional (3D) rendering of locations in a subject includes a step of receiving image data having a discrete spatial resolution for white matter tracts in a subject where the image data is generated by magnetic diffusion imaging. A first stereoscopic image is rendered on a display from the image data. The first stereoscopic image includes image parallax, which allows three-dimensional viewing. An input is received from a pointing device or a hand gesture that enables manipulation of the first stereoscopic image while maintaining proper three-dimensional spatial relationships. The pointing device interacts with the first stereoscopic image in three-dimensional space with six degrees of freedom.

The invention discloses application of steroid saponin of trillium tschonoskii maxim to preparation of a medicine for treating vascular dementia, and relates to the technical field of medicines. Animal experiments prove that the berberis apiacea steroid saponin can improve the spatial reference learning function of cerebral ischemia rats, improve the spatial reference memory function of the cerebral ischemia rats and enhance the long-term memory function of the cerebral ischemia rats. In addition, brain tissue damage and white matter structure damage of rats suffering from cerebral ischemia can be relieved, axonal myelin sheath microstructure reconstruction and white matter fiber reconstruction of the rats suffering from cerebral ischemia are promoted, and myelin sheath regeneration of rats suffering from vascular dementia is promoted. Network pharmacological analysis finds that the age grass total steroid saponin has a wide regulation effect on OPCs and OLs cell components and molecular functions, and further, OPCs differentiation myelin sheath inhibition related factors are regulated and controlled, and white matter myelin sheath regeneration is promoted.

This invention discloses a magnetic resonance imaging (MRI) method for evaluating the therapeutic effect of cerebral palsy rehabilitation in children, relating to the field of medical image processing technology. The method includes: acquiring structural imaging data (T1-weighted imaging and diffusion tensor imaging) and resting-state imaging data for each child patient; extracting brain and tissue boundaries from T1-weighted imaging using a 3D-Unet segmentation model; preprocessing the resting-state and structural imaging data and aligning them to brain boundaries, then registering these data to a standard brain template for children; acquiring and normalizing multiple clinical indicators based on the standard brain template, splicing them into multi-index vector data, inputting them into a pre-trained support vector machine model, and outputting differences in clinical indicators; determining abnormal brain regions for each child based on the differences, and finally generating a multimodal fusion index analysis report to observe changes in brain function and white matter integrity before and after rehabilitation.

This application relates to the field of medical neuroimaging processing and computer-aided diagnosis technology, and discloses a method based on normal white matter. 18 An Alzheimer's Disease (AD) Auxiliary Assessment System Based on F-florbetapir Retention Features. This system includes a data acquisition module for acquiring multimodal brain imaging data of subjects; an image preprocessing and segmentation module for impurity removal and target localization of the image data; a feature extraction module for extracting image features from the processed images; and a joint assessment and prediction module for AD auxiliary assessment based on the extracted features, incorporating a subject performance characteristic model and a logistic regression system. This Alzheimer's Disease (AD) auxiliary assessment system can significantly improve the accuracy of early AD diagnosis, accurately predict the rate of cognitive decline, and dynamically monitor the effect of immunotherapy.

The invention relates to a transcranial ultrasonic nerve regulation and control device and a control method. The transcranial ultrasonic nerve regulation and control device comprises an ultrasonic generation unit, ultrasonic waves are controllably provided to an intracranial target area, and the ultrasonic generation unit is configured to provide the ultrasonic waves with the frequency ranging from 3.0 MHz to 8.0 MHz to the intracranial target area. According to the transcranial ultrasonic nerve regulation device and the control method, the intracranial nerves are stimulated through the high-frequency ultrasonic waves with the working frequency of 3.0-8.0 MHz, the transcranial ultrasonic nerve regulation device and the control method have remarkable advantages in cortex regulation, energy is more easily absorbed by superficial tissue, the stimulated area covers the cerebral cortex and superficial white matter, and interference of a non-targeted deep structure is avoided. Meanwhile, the spatial resolution of the ultrasound of the frequency band can reach the submillimeter level, the ultrasound can be accurately focused on a tiny functional subregion, and the ultrasound is particularly suitable for nerve regulation scenes needing accurate positioning intervention and is suitable for nerve regulation of focal epilepsy, chronic pain syndromes, visual and auditory cortex dysfunction and mental and psychological disorders.

The present invention relates to a method and a system for the segmentation of white matter hyperintensities (WMHs) present in magnetic resonance brain images, comprising: providing an array of trained convolutional neural networks (CNNs) with a magnetic resonance brain image; determining, for each of the CNNs and for each voxel, the probability that the given voxel corresponds to a pathological hyperintensity; calculating the average of all the probabilities determined for each voxel; comparing the averaged probabilities for each voxel with a threshold; generating an image mask with the voxels that exceed the threshold.

This disclosure relates to a flexible electrode for the spinal cord and a method for manufacturing the same. A flexible electrode for the spinal cord is provided, comprising: an attachment portion configured to be able to be placed on the white matter lateral to the epidural space or intradural space, and configured to acquire or apply electrical signals to the surface of the spinal cord; wherein the attachment portion of the flexible electrode includes a first insulating layer and a second insulating layer, and a conductive layer located between the first insulating layer and the second insulating layer; wherein the attachment portion of the flexible electrode further includes one or more electrode sites, each electrode site being electrically coupled to one of the conductive wires in the conductive layer, and contacting the spinal cord after implantation of the flexible electrode to acquire electrical signals from spinal nerves and transmit the acquired electrical signals through the conductive wires, or to apply electrical signals received through the conductive wires to spinal nerves.

The invention discloses a CSVD cognitive impairment prediction method and a CSVD cognitive impairment prediction system based on Transform and domain self-adaptive T2-FLAIR white matter high-signal radiomics characteristics, and belongs to the technical field of medical image processing and auxiliary evaluation. The system comprises a radiomics feature extraction module, a Transform prediction model module, a domain adaptive training module and an interpretability module. According to the method, image omics features of a white matter high-signal area in a T2-FLAIR image are extracted through a full-automatic process, a context relation between the features is modeled through a Transform architecture, the multi-center data generalization ability is improved in combination with a domain self-adaptive mechanism, feature importance visualization is achieved through Grad-CAM, and the method is used for assisting in predicting cognitive disorder risks and related scores of CSVD patients. According to the method, the problems of strong subjectivity, weak generalization ability, poor interpretability and the like in the prior art are solved, and an efficient tool is provided for early risk assessment of CSVD related cognitive impairment.

The invention relates to the technical field of biology, in particular to a medicine and application thereof. The drug is an exosome (DPSCs-Exos) derived from dental pulp stem cells (DPSCs-Exos). The DPSCs-Exos is given after acute cerebral apoplexy, so that sensory movement and cognitive function recovery after cerebral ischemia can be promoted. The DPSCs-Exos can improve ischemia for 45 minutes, and brain tissue injury and neurological function injury of animals after reperfusion for 28 days. The DPSCs-Exos promotes the expression increase of protein arginine methyltransferase (PRMT5) in oligodendroglia precursor cells (OPC), inhibits the expression of a differentiation inhibition factor 2 (ID2) through nucleation, promotes the OPCs to proliferate and differentiate into oligodendroglia cells (OL), and promotes the integrity repair of white matter. In addition, DPSCs-Exos can promote proliferation and migration of vascular endothelial cells and promote blood brain barrier repair.

Systems and methods for treating neurodegenerative disorders with high frequency stimulation are disclosed. A representative method for treating a patient includes applying an electrical signal to the patient via a treatment system that includes a signal delivery element positioned at or within a white matter of the patient's brain, spinal cord, or both, the electrical signal having a frequency of from about 1.5 kHz to about 100 kHz.

The present invention relates to a brain tissue segmentation apparatus and method for precisely segmenting brain tissue on the basis of a CT image to distinguish gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF) with accuracy similar to that of MRI, and more specifically, to technology for normalizing pixel values of a CT image by limiting the pixel values to a specific housefield unit (HU) range, calculating perceptual loss by using a VGG network-based high-dimensional feature map, and analyzing the CT image by optimizing a complex loss function including L1 and L2 losses. The method of the present invention enables reliable brain tissue analysis even in an environment with limited MRI availability by segmenting brain tissue at a level similar to MRI through a deep learning network trained by taking into account structural features of CT images, and thus has the effect of increasing the utility of CT images.

The application provides an autism spectrum disorder identification method and system based on image generation, equipment and a medium, can synthesize an FA image from a conventional MRI image without increasing the scanning time or changing the imaging protocol, extract a quantitative index reflecting the white matter development difference, and realize the accurate distinction between autism spectrum disorder and overall developmental delay. The method avoids the high time cost of DTI scanning, is particularly suitable for children who are not easy to cooperate, and the generated image has good anatomical consistency and biological interpretability, which is helpful for doctors to understand and accept. Compared with the existing multi-modal or EEG method, the application has the advantages of simple structure, stable identification process and wide application range, can be quickly deployed on a conventional imaging device, and significantly improves the efficiency and accessibility of autism early screening and auxiliary diagnosis.

In various embodiments methods and compositions for improving a recovery of a subject after a cerebral ischemic injury, such as white matter stroke are provided. In certain embodiments, the methods involve administering human induced pluripotent glial enriched progenitor cells into the brain of the subject.

Systems and methods use the anatomy of the target brain region to suggest waveforms for optimal stretching of the target tissue for neuromodulation. Cell orientation, white matter tracts, or direction of connection between brain regions of the target region are considered. The timing of waveforms generated is based on time constants relevant to the target brain region and structures. The System can lock into the phase and frequency of the target using physiological measurements provided by EEG or other physiological signals. The system provides recommendations on the number of transducers to use, the placement of the transducers, and other ultrasound stimulation parameters. In an embodiment, the system generates waveforms where the spatial derivates of pressure are maximized to improve the efficacy of the stimulation.

The invention belongs to the technical field of medical image processing and artificial intelligence, and particularly relates to a schizophrenia auxiliary diagnosis method based on a multi-map white matter network and map nerves, and the method comprises the steps: obtaining the diffusion tensor imaging data of a subject, and constructing a plurality of map structures through preprocessing, multi-map feature extraction and the like; extracting a graph-level feature vector of each graph through a graph convolutional network; a panoramic feature vector is obtained through multi-head cross attention fusion, and then a weighted feature vector adapted to individual differences is obtained through adaptive map weighted learning; and splicing the two types of features and inputting the features into a classifier, and outputting the disease probability. According to the method, multi-map complementary information is fused, individual anatomical differences are adapted, the diagnosis accuracy and stability are improved, the cost is reduced, and reliable technical support is provided for schizophrenia auxiliary diagnosis and pathological mechanism research.

The invention provides a multi-source reference map adaptive diffusion magnetic resonance imaging (MRI) brain region fine segmentation method without label dependence, which comprises the following steps: acquiring a reference map of a target brain region and diffusion magnetic resonance (dMRI) data of a subject, preprocessing the dMRI data and then calculating a multi-dimensional diffusion feature map; establishing a mapping relation between a reference map and a dMRI feature space through a nonlinear registration algorithm, and outputting an initial coarse segmentation result as supervision prior; constructing an integrated convolutional neural network and a Mama module, embedding an attention fusion U-Mama deep learning network of a channel attention mechanism, and processing a class imbalance problem through a dichotomy subtask decomposition strategy; in a prediction stage, a target region is registered to an individual space to obtain a coarse segmentation result, the coarse segmentation result and the dMRI multi-modal feature map are input into the trained network, and a high-precision segmentation result of the target brain region is output. The method is used for realizing cross-age group and high-precision individualized white matter brain region segmentation only by depending on the standard map label in an actual clinical application environment.

A computer system may receive medical-imaging data associated with at least an individual. Then, the computer system may compute, based at least in part on the medical-imaging data, a set of white-matter disease biomarkers for different neurological anatomical regions, where, for a given neurological anatomical region, the set of white-matter disease biomarkers includes: an apparent fiber density that corresponds to a total intra-axonal volume, an amount of free water, and a demyelination metric. Next, the computer system may provide feedback information associated with at least the individual based at least in part on interrelationships among the computed set of white-matter disease biomarkers in different neurological anatomical regions. For example, the feedback information may include: diagnostic information, information associated with disease progression (such as a disease stage), information regarding efficacy of a treatment, or a treatment recommendation (e.g., based at least in part on the disease stage).

A chimeric non-human mammal disease model, wherein (1) at least 30% of all the glial cells in the corpus callosum of the chimeric non-human mammal are human glial cells, and / or (2) at least 5% of all of the glial cells in the white matter of the brain and / or brain stem of the chimeric non-human mammal are human glial cells, and wherein the human glial cells comprise a combination of a first group of human glial cells tagged with a first label and a second group of human glial cells tagged with a second label that is distinguishable from the first label.

The invention provides a TREM2 agonist which can be used for preventing and / or treating diseases related to TREM2, including Alzheimer's disease, Parkinson's disease, polycystic adipoid bone dysplasia and sclerotic white matter encephalopathy, cerebral apoplexy, hereditary diffuse white matter encephalopathy accompanied with bulbous axonal, amyotrophic lateral sclerosis and the like.

The application discloses a brain-computer interface signal enhancement and evaluation method fusing physical information. First, based on individual structural magnetic resonance images, a personalized six-layer brain tissue dissection model containing the cortex, white matter, cerebrospinal fluid, dura mater, skull and scalp is constructed, and differentiated conductivity parameters are given. Second, neurophysiological prior knowledge such as neural dynamics and white matter anisotropic conduction is converted into a representation rule that can be learned by a neural network. Then, these rules are embedded in the physical information neural network in the form of differentiable physical constraints, including the residual error of the cortical neural dynamics equation, the residual error of the volume conduction equation of each layer, and the continuity constraint of the interlayer interface. Finally, the scalp electroencephalogram signal is used to train the network, and by minimizing the loss function containing the reconstruction and physical constraints, a high-fidelity intracranial electroencephalogram signal and multi-modal neurophysiological information are jointly output. The application effectively improves the fidelity, physical reasonableness and clinical interpretability of signal enhancement.

A method for predicting the degree of disability of a multiple sclerosis patient, according to exemplary embodiments of the present invention, may comprise the steps of: obtaining information about a brain lesion area of the multiple sclerosis patient; mapping the brain lesion area onto a white matter streamline map including a plurality of voxels and information about the number of white matter streamlines passing through each voxel, thereby identifying voxels in the brain lesion area in the white matter streamline map; obtaining the number of voxels in the brain lesion area and the number of white matter streamlines passing through each voxel in the brain lesion area; determining a white matter path index of the brain lesion area on the basis of the number of voxels in the brain lesion area and the number of white matter streamlines passing through each voxel in the brain lesion area; and predicting the degree of disability of the multiple sclerosis patient on the basis of the white matter path index of the brain lesion area by using a rule-based model or a trained artificial intelligence model.

This invention discloses the application of a PITPα regulator in the preparation of drugs for white matter remyelination repair. This invention increases the expression level of phospholipid transporter α (PITPα) in oligodendrocyte precursor cells by using a PITPα regulator, promoting oligodendrocyte maturation, differentiation, and remyelination, thereby improving white matter structure and neurological function outcomes after ischemic brain injury. The PITPα regulator used is a lipid nanoparticle encapsulating PITPα mRNA, or further, a targeting ligand for oligodendrocyte precursor cells is attached to the surface of the lipid nanoparticle. This invention provides a novel treatment strategy for ischemic brain injury.

A computer-implemented method for adjustable three-dimensional (3D) rendering of locations in a subject includes a step of receiving image data having a discrete spatial resolution for white matter tracts in a subject where the image data is generated by magnetic diffusion imaging. A first stereoscopic image is rendered on a display from the image data. The first stereoscopic image includes image parallax, which allows three-dimensional viewing. An input is received from a pointing device or a hand gesture that enables manipulation of the first stereoscopic image while maintaining proper three-dimensional spatial relationships. The pointing device interacts with the first stereoscopic image in three-dimensional space with six degrees of freedom.

This invention relates to the field of biomedical technology and provides the application of ginsenoside Rg2 in the preparation of drugs for treating multiple sclerosis (MS). Ginsenoside Rg2 exerts its therapeutic effect on MS through the following mechanisms: reducing the expression levels of pro-inflammatory factors, promoting regulatory T cell differentiation, and inhibiting the infiltration of immune cells into the central nervous system; inhibiting NLRP3 signaling pathway activation and reducing neuronal pyroptosis; preventing the immune system from destroying myelin and reducing the ratio of demyelinated area to white matter area; upregulating oligodendrocyte transcription factor expression, promoting oligodendrocyte precursor cell proliferation and differentiation, and promoting myelin regeneration; and inhibiting microglia activation. This invention solves the problems of limited efficacy, significant side effects, only delaying progression, and limited administration methods of existing drugs.

A process for determining an extent of a central nervous system (CNS) specific neurological condition in a subject including collecting a biological sample of biofluid from the subject and measuring a quantity of a first biomarker, or metabolite of or mRNA corresponding to, the first biomarker from the sample from a dried spot or through a microfluidic device. The biofluid is capillary blood or saliva, which affords ease of collection advantages that are attractive for field-, hospital-, and home-based environments. The process being useful in the diagnosis, care, and management of brain specific abnormal neurological conditions in general, and in particular, to traumatic brain injury (TBI) and (TBI-induced) Alzheimer's disease (AD) and Alexander disease, in which a GFAP mutation is implicated in white matter deterioration.

A chimeric non-human mammal disease model, wherein (1) at least 30% of all the glial cells in the corpus callosum of the chimeric non-human mammal are human glial cells, and / or (2) at least 5% of all of the glial cells in the white matter of the brain and / or brain stem of the chimeric non-human mammal are human glial cells, and wherein the human glial cells comprise a combination of a first group of human glial cells tagged with a first label and a second group of human glial cells tagged with a second label that is distinguishable from the first label.