Deep learning in cortical surface-based neuroimage analysis:a systematic review

Deep learning approaches,especially convolutional neural networks(CNNs),have become the method of choice in the field of medical image analysis over the last few years.This prevalence is attributed to their excellent abilities to learn features in a more effective and efficient manner,not only for 2D/3D images in the Euclidean space,but also for meshes and graphs in non-Euclidean space such as cortical surfaces in neuroimaging analysis field.The brain cerebral cortex is a highly convoluted and thin sheet of gray matter(GM)that is thus typically represented by triangular surface meshes with an intrinsic spherical topology for each hemisphere.Accordingly,novel tailored deep learning methods have been developed for cortical surface-based analysis of neuroimaging data.This paper reviewsed the representative deep learning techniques relevant to cortical surface-based analysis and summarizes recent major contributions to the field.Specifically,we surveyed the use of deep learning techniques for cortical surface reconstruction,registration,parcellation,prediction,and other applications.We concluded by discussing the open challenges,limitations,and potentials of these techniques,and suggested directions for future research.

A review of the neurotransmitter system associated with cognitive function of the cerebellum in Parkinson's disease

The dichotomized brain system is a concept that was generalized from the‘dual syndrome hypothesis’to explain the heterogeneity of cognitive impairment,in which anterior and posterior brain systems are independent but partially overlap.The dopaminergic system acts on the anterior brain and is responsible for executive function,working memory,and planning.In contrast,the cholinergic system acts on the posterior brain and is responsible for semantic fluency and visuospatial function.Evidence from dopaminergic/cholinergic imaging or functional neuroimaging has shed significant insight relating to the involvement of the cerebellum in the cognitive process of patients with Parkinson’s disease.Previous research has reported evidence that the cerebellum receives both dopaminergic and cholinergic projections.However,whether these two neurotransmitter systems are associated with cognitive function has yet to be fully elucidated.Furthermore,the precise role of the cerebellum in patients with Parkinson’s disease and cognitive impairment remains unclear.Therefore,in this review,we summarize the cerebellar dopaminergic and cholinergic projections and their relationships with cognition,as reported by previous studies,and investigated the role of the cerebellum in patients with Parkinson’s disease and cognitive impairment,as determined by functional neuroimaging.Our findings will help us to understand the role of the cerebellum in the mechanisms underlying cognitive impairment in Parkinson’s disease.

Neuroimaging in atypical normal tension glaucoma:debating routine implementation in the absence of classic neurological findings

●AIM:To assess the necessity of neuroimaging in patients with neurological or atypical findings of normal tension glaucoma(NTG)who do not exhibit typical glaucoma manifestations.●METHODS:A retrospective analysis was conducted on 90 atypical NTG patients who underwent cranial magnetic resonance imaging(MRI)due to atypical symptoms.The demographic characteristics,clinical parameters,and radiological findings were recorded.●RESULTS:Among the patients,66.7%had abnormal radiology results,with the most common findings being gliosis(34.4%),sequelae of cerebrovascular events and vascular malformations(14.4%),and benign intracranial mass lesions(11%).Non-glaucomatous visual field defects were more frequently observed in patients with abnormal neuroimaging results.However,there were no significant differences in intraocular pressure,optic disc parameters,retinal nerve fiber layer thickness,and visual field indices between patients with normal and abnormal radiological results.The mean age of the patients was 58.74y.Interestingly,there was a significant age difference,with the abnormal radiology group having a higher median age(P=0.021).●CONCLUSION:The study highlights the importance of cranial imaging in older NTG patients to detect underlying pathologies and prevent misdiagnosis.It suggests that neuroimaging may be warranted in NTG patients with atypical visual field defects incompatible with glaucoma.However,routine neuroimaging in all NTG patients without classic neurological signs may not be necessary.

Epileptic brain network mechanisms and neuroimaging techniques for the brain network

Epilepsy can be defined as a dysfunction of the brain network,and each type of epilepsy involves different brain-network changes that are implicated diffe rently in the control and propagation of interictal or ictal discharges.Gaining more detailed information on brain network alterations can help us to further understand the mechanisms of epilepsy and pave the way for brain network-based precise therapeutic approaches in clinical practice.An increasing number of advanced neuroimaging techniques and electrophysiological techniques such as diffusion tensor imaging-based fiber tra ctography,diffusion kurtosis imaging-based fiber tractography,fiber ball imagingbased tra ctography,electroencephalography,functional magnetic resonance imaging,magnetoencephalography,positron emission tomography,molecular imaging,and functional ultrasound imaging have been extensively used to delineate epileptic networks.In this review,we summarize the relevant neuroimaging and neuroelectrophysiological techniques for assessing structural and functional brain networks in patients with epilepsy,and extensively analyze the imaging mechanisms,advantages,limitations,and clinical application ranges of each technique.A greater focus on emerging advanced technologies,new data analysis software,a combination of multiple techniques,and the construction of personalized virtual epilepsy models can provide a theoretical basis to better understand the brain network mechanisms of epilepsy and make surgical decisions.

Multimodal abnormalities of brain structures in adolescents and young adults with major depressive disorder:An activation likelihood estimation meta-analysis

BACKGROUND Major depressive disorder(MDD)in adolescents and young adults contributes significantly to global morbidity,with inconsistent findings on brain structural changes from structural magnetic resonance imaging studies.Activation likeli-hood estimation(ALE)offers a method to synthesize these diverse findings and identify consistent brain anomalies.METHODS We performed a comprehensive literature search in PubMed,Web of Science,Embase,and Chinese National Knowledge Infrastructure databases for neuroi-maging studies on MDD among adolescents and young adults published up to November 19,2023.Two independent researchers performed the study selection,quality assessment,and data extraction.The ALE technique was employed to synthesize findings on localized brain function anomalies in MDD patients,which was supplemented by sensitivity analyses.RESULTS Twenty-two studies comprising fourteen diffusion tensor imaging(DTI)studies and eight voxel-based morphome-try(VBM)studies,and involving 451 MDD patients and 465 healthy controls(HCs)for DTI and 664 MDD patients and 946 HCs for VBM,were included.DTI-based ALE demonstrated significant reductions in fractional anisotropy(FA)values in the right caudate head,right insula,and right lentiform nucleus putamen in adolescents and young adults with MDD compared to HCs,with no regions exhibiting increased FA values.VBM-based ALE did not demonstrate significant alterations in gray matter volume.Sensitivity analyses highlighted consistent findings in the right caudate head(11 of 14 analyses),right insula(10 of 14 analyses),and right lentiform nucleus putamen(11 of 14 analyses).CONCLUSION Structural alterations in the right caudate head,right insula,and right lentiform nucleus putamen in young MDD patients may contribute to its recurrent nature,offering insights for targeted therapies.

Resting-state functional magnetic resonance imaging and support vector machines for the diagnosis of major depressive disorder in adolescents

BACKGROUND Research has found that the amygdala plays a significant role in underlying pathology of major depressive disorder(MDD).However,few studies have explored machine learning-assisted diagnostic biomarkers based on amygdala functional connectivity(FC).AIM To investigate the analysis of neuroimaging biomarkers as a streamlined approach for the diagnosis of MDD in adolescents.METHODS Forty-four adolescents diagnosed with MDD and 43 healthy controls were enrolled in the study.Using resting-state functional magnetic resonance imaging,the FC was compared between the adolescents with MDD and the healthy controls,with the bilateral amygdala serving as the seed point,followed by statistical analysis of the results.The support vector machine(SVM)method was then applied to classify functional connections in various brain regions and to evaluate the neurophysiological characteristics associated with MDD.RESULTS Compared to the controls and using the bilateral amygdala as the region of interest,patients with MDD showed significantly lower FC values in the left inferior temporal gyrus,bilateral calcarine,right lingual gyrus,and left superior occipital gyrus.However,there was an increase in the FC value in Vermis-10.The SVM analysis revealed that the reduction in the FC value in the right lingual gyrus could effectively differentiate patients with MDD from healthy controls,achieving a diagnostic accuracy of 83.91%,sensitivity of 79.55%,specificity of 88.37%,and an area under the curve of 67.65%.CONCLUSION The results showed that an abnormal FC value in the right lingual gyrus was effective as a neuroimaging biomarker to distinguish patients with MDD from healthy controls.

Evaluating the role of 7-Tesla magnetic resonance imaging in neurosurgery: Trends in literature since clinical approval

BACKGROUND After approval for clinical use in 2017,early investigations of ultra-high-field abdominal magnetic resonance imaging(MRI)have demonstrated its feasibility as well as diagnostic capabilities in neuroimaging.However,there are no to few systematic reviews covering the entirety of its neurosurgical applications as well as the trends in the literature with regard to the aforementioned application.AIM To assess the impact of 7-Tesla MRI(7T MRI)on neurosurgery,focusing on its applications in diagnosis,treatment planning,and postoperative assessment,and to systematically analyze and identify patterns and trends in the existing literature related to the utilization of 7T MRI in neurosurgical contexts.METHODS A systematic search of PubMed was conducted for studies published between January 1,2017,and December 31,2023,using MeSH terms related to 7T MRI and neurosurgery.The inclusion criteria were:Studies involving patients of all ages,meta-analyses,systematic reviews,and original research.The exclusion criteria were:Pre-prints,studies with insufficient data(e.g.,case reports and letters),non-English publications,and studies involving animal subjects.Data synthesis involved standardized extraction forms,and a narrative synthesis was performed.RESULTS We identified 219 records from PubMed within our defined period,with no duplicates or exclusions before screening.After screening,125 articles were excluded for not meeting inclusion criteria,leaving 94 reports.Of these,2 were irrelevant to neurosurgery and 7 were animal studies,resulting in 85 studies included in our systematic review.Data were categorized by neurosurgical procedures and diseases treated using 7T MRI.We also analyzed publications by country and the number of 7T MRI facilities per country was also presented.Experi-mental studies were classified into comparison and non-comparison studies based on whether 7T MRI was compared to lower field strengths.CONCLUSION 7T MRI holds great potential in improving the characterization and understanding of various neurological and psychiatric conditions that may be neurosurgically treated.These include epilepsy,pituitary adenoma,Parkinson's disease,cerebrovascular diseases,trigeminal neuralgia,traumatic head injury,multiple sclerosis,glioma,and psychiatric disorders.Superiority of 7T MRI over lower field strengths was demonstrated in terms of image quality,lesion detection,and tissue characterization.Findings suggest the need for accelerated global distribution of 7T magnetic resonance systems and increased training for radiologists to ensure safe and effective integration into routine clinical practice.

Enhancement of Visual Attention by Color Revealed Using Electroencephalography

Attention constitutes a fundamental psychological feature guiding our mental effort toward specific objects, concurrent with processes such as memory, reasoning, and imagination. Visual attention, crucial for selecting surrounding information, often decreases in older adults and patients with cerebrovascular disorders. Effective methods to enhance attention are scarce. Here, we investigated whether color information influences visual attention and brain activity during task performance, utilizing EEG. We examined 13 healthy young adults (seven women and six men;mean age: 21.2 ± 0.58 years) using 19-electrode electroencephalograms to assess the impact of color information on visual attention. The Clinical Assessment for Attention cancellation test was conducted under the black, red, and blue color conditions. Wilcoxon’s signed-rank test was used to assess differences in task performance (task time and error) between conditions. Spearman’s rank correlation was utilized to examine the correlation in power levels between task performance and color conditions. Significant variations in total task errors were observed among color conditions. The black condition exhibited the highest error frequency (0.7 ± 0.9 times), followed by the red condition (0.5 ± 0.8 times), with the lowest error frequency occurring in the blue (0.2 ± 0.4 times) condition (black vs. red: P = 0.03;black vs. blue: P = 0.00;red vs. blue: P = 0.032). No time difference was observed. The black condition showed negative delta and high-gamma correlations in the central electrodes. The red condition revealed positive alpha and low-gamma correlations in the frontal and occipital areas. Although no correlations were observed in the blue condition, it enhanced attentional performance. Positive alpha and low-gamma waves might be crucial for spotting attentional errors in key areas. Our findings provide insights into the effects of color information on visual attention and potential neural correlates associated with attentional processes. In conclusion, our study implies a connection between color information and attentional task performance, with blue font associated with the most accurate performance.

Detection of Alzheimer’s disease onset using MRI and PET neuroimaging:longitudinal data analysis and machine learning

The scientists are dedicated to studying the detection of Alzheimer’s disease onset to find a cure, or at the very least, medication that can slow the progression of the disease. This article explores the effectiveness of longitudinal data analysis, artificial intelligence, and machine learning approaches based on magnetic resonance imaging and positron emission tomography neuroimaging modalities for progression estimation and the detection of Alzheimer’s disease onset. The significance of feature extraction in highly complex neuroimaging data, identification of vulnerable brain regions, and the determination of the threshold values for plaques, tangles, and neurodegeneration of these regions will extensively be evaluated. Developing automated methods to improve the aforementioned research areas would enable specialists to determine the progression of the disease and find the link between the biomarkers and more accurate detection of Alzheimer’s disease onset.

Decoding degeneration:the implementation of machine learning for clinical detection of neurodegenerative disorders

Machine learning represents a growing subfield of artificial intelligence with much promise in the diagnosis,treatment,and tracking of complex conditions,including neurodegenerative disorders such as Alzheimer’s and Parkinson’s diseases.While no definitive methods of diagnosis or treatment exist for either disease,researchers have implemented machine learning algorithms with neuroimaging and motion-tracking technology to analyze pathologically relevant symptoms and biomarkers.Deep learning algorithms such as neural networks and complex combined architectures have proven capable of tracking disease-linked changes in brain structure and physiology as well as patient motor and cognitive symptoms and responses to treatment.However,such techniques require further development aimed at improving transparency,adaptability,and reproducibility.In this review,we provide an overview of existing neuroimaging technologies and supervised and unsupervised machine learning techniques with their current applications in the context of Alzheimer’s and Parkinson’s diseases.

Review of deep learning and artificial intelligence models in fetal brain magnetic resonance imaging

Central nervous system abnormalities in fetuses are fairly common,happening in 0.1%to 0.2%of live births and in 3%to 6%of stillbirths.So initial detection and categorization of fetal Brain abnormalities are critical.Manually detecting and segmenting fetal brain magnetic resonance imaging(MRI)could be timeconsuming,and susceptible to interpreter experience.Artificial intelligence(AI)algorithms and machine learning approaches have a high potential for assisting in the early detection of these problems,improving the diagnosis process and follow-up procedures.The use of AI and machine learning techniques in fetal brain MRI was the subject of this narrative review paper.Using AI,anatomic fetal brain MRI processing has investigated models to predict specific landmarks and segmentation automatically.All gestation age weeks(17-38 wk)and different AI models(mainly Convolutional Neural Network and U-Net)have been used.Some models'accuracy achieved 95%and more.AI could help preprocess and postprocess fetal images and reconstruct images.Also,AI can be used for gestational age prediction(with one-week accuracy),fetal brain extraction,fetal brain segmentation,and placenta detection.Some fetal brain linear measurements,such as Cerebral and Bone Biparietal Diameter,have been suggested.Classification of brain pathology was studied using diagonal quadratic discriminates analysis,Knearest neighbor,random forest,naive Bayes,and radial basis function neural network classifiers.Deep learning methods will become more powerful as more large-scale,labeled datasets become available.Having shared fetal brain MRI datasets is crucial because there aren not many fetal brain pictures available.Also,physicians should be aware of AI's function in fetal brain MRI,particularly neuroradiologists,general radiologists,and perinatologists.

Potential sex differences in activation of pain-related brain regions in nonhuman primates with a unilateral spinal nerve ligation

The lack of truly robust analgesics for chronic pain is owed,in part,to the lack of an animal model that reflects the clinical pain state and of a mechanismbased,objective neurological indicator of pain.The present study examined stimulus-evo ked brain activation with functional magnetic resonance imaging in male and female cynomolgus macaques following unilateral L7 spinal nerve ligation and the effects of clinical analgesics pregabalin,duloxetine,and morphine on brain activation in these macaques.A modified straight leg raise test was used to assess pain severity in awake animals and to evo ke regional brain activation in anesthetized animals.The potential effects of clinical analgesics on both awake pain behavior and regional brain activation were examined.Following spinal nerve ligation,both male and female macaques showed significantly decreased ipsilateral straight leg raise thresholds,suggesting the presence of radicula rlike pain.Morphine treatment increased straight leg raise thresholds in both males and females whereas duloxetine and pregabalin did not.In male macaques,the ipsilateral straight leg raise activated contralateral insular and somatosensory cortex(Ins/SII),and thalamus.In female macaques,the ipsilateral leg raise activated cingulate cortex and contralateral insular and somatosensory cortex.Straight leg raises of the contralateral,unligated leg did not evoke brain activation.Morphine reduced activation in all brain regions in both male and female macaques.In males,neither pregabalin nor duloxetine decreased brain activation compared with vehicle treatment.In females,however,pregabalin and duloxetine decreased the activation of cingulate cortex compared with vehicle treatment.The current findings suggest a diffe rential activation of brain areas depending on sex following a peripheral nerve injury.Diffe rential brain activation observed in this study could underlie qualitative sexual dimorphism in clinical chronic pain perception and responses to analgesics.Future pain management approaches for neuropathic pain will need to consider potential sex differences in pain mechanism and treatment efficacy.

Diffusion tensor imaging in the courtroom:Distinction between scientific specificity and legally admissible evidence

Interest and uptake of science and medicine peer-reviewed literature by readers outside of a paper’s topical subject,field or even discipline is ever-expanding.While the application of knowledge from one field or discipline to others can stimulate innovative solutions to problems facing modern society,it is also fraught with danger for misuse.In the practice of law in the United States,academic papers are submitted to the courts as evidence in personal injury litigation from both the plaintiff(complainant)and defendant.Such transcendence of an academic publication over disciplinary boundaries is immediately met with the challenge of application by a group that inherently lacks in-depth knowledge on the scientific method,the practice of evidence-based medicine,or the publication process as a structured and internationally synthesized process involving peer review and guided by ethical standards and norms.A modern-day example of this is the ongoing conflict between the sensitivity of diffusion tensor imaging(DTI)and the legal standards for admissibility of evidence in litigation cases of mild traumatic brain injury(mTBI).In this review,we amalgamate the peer-reviewed research on DTI in mTBI with the court’s rationale underlying decisions to admit or exclude evidence of DTI abnormalities to support claims of brain injury.We found that the papers which are critical of the use of DTI in the courtroom reflect a primary misunderstanding about how diagnostic biomarkers differ legally from relevant and admissible evidence.The clinical use of DTI to identify white matter abnormalities in the brain at the chronic stage is a valid methodology both clinically as well as forensically,contributes data that may or may not corroborate the existence of white matter damage,and should be admitted into evidence in personal injury trials if supported by a clinician.We also delve into an aspect of science publication and peer review that can be manipulated by scientists and clinicians to publish an opinion piece and misrepresent it as an unbiased,evidencebased,systematic research article in court cases,the decisions of which establish precedence for future cases and have implications on future legislation that will impact the lives of every citizen and erode the integrity of science and medicine practitioners.

Recent Advances in HIV-Associated Neurocognitive Disorders

HIV-associated neurocognitive disorders (HAND) are chronic complications of HIV infection in the central nervous system. Clinical presentations include asymptomatic neurocognitive impairment (ANI), mild neurocognitive impairment (MND), and HIV-associated dementia (HAD). In the era of combination antiretroviral therapy (cART), the prevalence of HAD has significantly decreased, but the rates of ANI and MND have increased, impairing patients’ daily functioning, medical adherence, employment, driving abilities, risk of HIV transmission, overall quality of life, and posing challenges to society, economy, families, and public health. This article reviews the latest research findings regarding the pathogenesis, clinical diagnosis and treatment, neuroimaging, and neuropsychological assessment of HAND, aiming to provide insights into the prevention and management of HAND.

Compressive Myelopathy, Spinal Shock, and a Complicated Neurological Exam

The neurological examination, developed and tested since the 1800s has provided physicians with a vital tool to rapidly assess and provide clues to many of the pathological processes lurking inside the brain and spinal cord. With the advent of magnetic resonance imaging, physicians are able to visualize the precise location of the abscess before surgical intervention. In this case report, we present a 51-year-old male with an epidural abscess with multifocal compressive myelopathy, resulting in a complicated neurological examination, making localization a diagnostic challenge. With this case, we would like to stress that complicated multifocal lesions of the cord may present with a large variation in examination findings. This patient’s neurological exam was complicated secondary to a ventrally as well as dorsally located epidural abscess with superimposed spinal shock sequelae. We would like to highlight the importance of a thorough history and the neurological examination but also mention some of its limitations. It is crucial to use clinical judgement to navigate the patient’s history, presentation, and examination to accurately diagnose and treat, particularly so in cases involving compressive myelopathies of the spinal cord.

The Influence and Enlightenment of Neuroimaging Science on Psychiatric Teaching

Psychiatry belongs to the category of cognitive neuroscience,with its development being greatly influenced by neuroscience.Currently,undergraduate teaching in psychiatry still adopts the teacher-centered indoctrination model,leading to ineffective integration of neuroimaging science into the teaching process.In order to improve the quality of psychiatric talent training,the talent training model needs to be adjusted.This article analyzes the current situation of psychiatric teaching,outlines neuroimaging science,summarizes the impact of neuroimaging science on psychiatric teaching,and analyzes the strategies for applying neuroimaging science in psychiatric teaching,with the hope to provide a guideline for relevant teachers.

Diffusion tensor imaging detects Wallerian degeneration of the corticospinal tract early after cerebral infarction

To investigate the feasibility and time window of early detection of Wallerian degeneration in the corticospinal tract after middle cerebral artery infarction, 23 patients were assessed using magnetic resonance diffusion tensor imaging at 3.0T within 14 days after the infarction. The fractional anisotropy values of the affected corticospinal tract began to decrease at 3 days after onset and decreased in all cases at 7 days. The diffusion coefficient remained unchanged. Experimental findings indicate that diffusion tensor imaging can detect the changes associated with Wallerian degeneration of the corticospinal tract as early as 3 days after cerebral infarction.

Diffuse axonal injury after traumatic cerebral microbleeds: an evaluation of imaging techniques

Previous neuropathological studies regarding traumatic brain injury have primarily focused on changes in large structures, for example, the clinical prognosis after cerebral contusion, intrace- rebral hematoma, and epidural and subdural hematoma. In fact, many smaller injuries can also lead to severe neurological disorders. For example, cerebral microbleeds result in the dysfunc- tion of adjacent neurons and the disassociation between cortex and subcortical structures. These tiny changes cannot be adequately visualized on CT or conventional MRI. In contrast, gradient echo sequence-based susceptibility-weighted imaging is very sensitive to blood metabolites and microbleeds, and can be used to evaluate traumatic cerebral microbleeds with high sensitivity and accuracy. Cerebral microbleed can be considered as an important imaging marker for dif- fuse axonal injury with potential relevance for prognosis. For this reason, based on experimental and clinical studies, this study reviews the role of imaging data showing traumatic cerebral microbleeds in the evaluation of cerebral neuronal injury and neurofunctional loss.

Diffusion tensor imaging assesses white matter injury in neonates with hypoxic-ischemic encephalopathy

With improvements in care of at-risk neonates, more and more children survive. This makes it increasingly important to assess, soon after birth, the prognosis of children with hypoxic-ischemic encephalopathy. Computed tomography, ultrasound, and conventional magnetic resonance imaging are helpful to diagnose brain injury, but cannot quantify white matter damage. In this study, ten full-term infants without brain injury and twenty-two full-term neonates with hypoxic-ischemic encephalopathy （14 moderate cases and 8 severe cases） underwent diffusion tensor imaging to assess its feasibility in evaluating white matter damage in this condition. Results demonstrated that fractional anisotropy, voxel volume, and number of fiber bundles were different in some brain areas between infants with brain injury and those without brain injury. The correlation between fractional anisotropy values and neonatal behavioral neurological assessment scores was closest in the posterior limbs of the internal capsule. We conclude that diffusion tensor imaging can quantify white matter injury in neonates with hypoxic-ischemic encephalopathy.

Use of various CT imaging methods for diagnosis of acute ischemic cerebrovascular disease

Thirty-four patients with cerebral infarction and 18 patients with transient ischemic attack were examined by multi-slice spiral CT scan, CT perfusion imaging, and CT angiography within 6 hours after onset. By CT perfusion imaging, 29 cases in the cerebral infarction group and 10 cases in the transient ischemic attack group presented with abnormal blood flow perfusion, which corresponded to the clinical symptoms. By CT angiography, various degrees of vascular stenosis could be detected in 41 patients, including 33 in the cerebral infarction group and eight in the transient ischemic attack group. The incidence of intracranial artery stenosis was higher than that of extracranial artery stenosis. The intracranial artery stenosis was located predominantly in the middle cerebral artery and carotid artery siphon, while the extracranial artery stenosis occurred mainly in the bifurcation of the common carotid artery and the opening of the vertebral artery. There were 34 cases （83%） with convict vascular stenosis and perfusion abnormalities, and five cases （45%） with perfusion abnormalities but without convict vascular stenosis. The incidence of cerebral infarction in patients with National Institutes of Health Stroke Scale scores 〉 5 points during onset was significantly higher than that in patients with National Institutes of Health Stroke Scale scores 〈 5 points. These experimental findings indicate that the combined application of various CT imaging methods allows early diagnosis of acute ischemic cerebrovascular disease, which can comprehensively analyze the pathogenesis and severity of acute ischemic cerebrovascular disease at the morphological and functional levels.