scholarly journals Multilevel Clustering-Evolutionary Random Support Vector Machine Cluster Algorithm-Based Blood Oxygenation Level-Dependent Functional Magnetic Resonance Imaging Images in Analysis of Therapeutic Effects on Cerebral Ischemic Stroke

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Zhili Zhang ◽  
Guo Cheng ◽  
Guifang Liu ◽  
Gaixia Li
Keyword(s):  
Magnetic Resonance Imaging ◽  
Support Vector Machine ◽  
Magnetic Resonance ◽  
Functional Magnetic Resonance Imaging ◽  
Motor Area ◽  
Support Vector ◽  
Functional Magnetic Resonance ◽  
Resonance Imaging ◽  
Activation Rate ◽  
Sensory Motor

The study aimed to explore the relationship between cerebral ischemic stroke (CIS) and the patient’s limb movement through the blood oxygenation level-dependent functional magnetic resonance imaging (BOLD-fMRI) based on multilevel clustering-evolutionary random support vector machine cluster (MCRSVMC). Specifically, 20 CIS patients were defined as the experimental group; another 20 healthy volunteers were defined as the control group. All subjects performed finger movement and verb association task. The performance of support vector machine (SVM) and MCRSVMC algorithm was compared and applied to functional magnetic resonance imaging (fMRI) of blood oxygen level in all subjects. The results showed that the average accuracy of MCRSVMC algorithm was significantly higher than that of support vector machine (86.75%, 65.84%; P < 0.05 ). The sensitivity of MCRSVMC algorithm was significantly higher than that of support vector machine (92.52%, 75.41%; P < 0.05 ). In addition, the specificity of MCRSVMC algorithm was significantly higher than that of support vector machine (86.39%, 68.24%; P < 0.05 ). When CIS patients performed finger exercise, the sensory motor areas on both sides were significantly activated, and the activated sensory motor areas on both sides were significantly bigger than the ipsilateral area. The activation rate of the left-sensory motor area (L-SM1) was 87.5%, the activation rate of the right-sensory motor area (R-SM1) was 25%, the activation rate of the left-side auxiliary motor area (L-SMA) was 62.5%, and the activation rate of the right-side auxiliary motor area (R-SMA) was 37.5%. In conclusion, the MCRSVMC algorithm proposed in this study is highly efficient and stable. BOLD-fMRI diagnosis of motor function in CIS patients is mainly related to compensation around the lesion, which occurs on the healthy side after recovery.

scholarly journals Applying 3DPCANet and Functional Magnetic Resonance Imaging to Aided Diagnosis of Alzheimer’s Disease

2021 ◽  
Author(s):  
Yu Wang ◽  
Hongfei Jia ◽  
Yifan Duan ◽  
Hongbing Xiao
Keyword(s):  
Magnetic Resonance Imaging ◽  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Magnetic Resonance ◽  
Functional Magnetic Resonance Imaging ◽  
Brain Regions ◽  
Support Vector ◽  
Functional Magnetic Resonance ◽  
Resonance Imaging ◽  
Public Data

Abstract Alzheimer's disease (AD) is a progressive neurodegenerative disease, which changes the structure of brain regions by some hidden causes. In this paper for assisting doctors to make correct judgments, an improved 3DPCANet method is proposed to classify AD by combining the mean (mALFF) of the whole brain. The main idea includes that firstly, the functional magnetic resonance imaging (fMRI) data is pre-processed, and mALFF is calculated to get the corresponding matrix. Then the features of mALFF images are extracted via the improved 3DPCANet network. Finally, AD patients with different stages are classified using support vector machine (SVM). Experiments results based on public data from the Alzheimer’s disease neuroimaging initiative (ADNI) show that the proposed approach has better performance compared with state-of-the-art methods. The accuracies of AD vs. significant memory concern (SMC), SMC vs. late mild cognitive impairment (LMCI), and normal control (NC) vs. SMC reach respectively 92.42%, 91.80%, and 89.50%, which testifies the feasibility and effectiveness of the proposed method.

Somatotopy of the Supplementary Motor Area: Evidence from Correlation of the Extent of Surgical Resection with the Clinical Patterns of Deficit

Neurosurgery ◽  
2002 ◽  
Vol 50 (2) ◽  
pp. 297-305 ◽  
Author(s):  
Denys Fontaine ◽  
Laurent Capelle ◽  
Hugues Duffau
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Functional Magnetic Resonance Imaging ◽  
Supplementary Motor Area ◽  
Clinical Symptoms ◽  
Motor Area ◽  
Functional Magnetic Resonance ◽  
Resonance Imaging ◽  
Clinical Patterns ◽  
Sma Resection

ABSTRACT OBJECTIVE This study, which aimed to confirm or invalidate the somatotopic organization of the supplementary motor area (SMA), correlates the pattern of clinical symptoms observed after SMA removal with the extent of resection. METHODS Eleven patients with medial precentral glioma underwent partial or complete tumoral resection of the SMA. Seven patients underwent preoperative functional magnetic resonance imaging that incorporated speech and motor tasks. During the operation, the primary motor and speech areas and pathways (in the dominant side) were identified by use of intraoperative direct cortical or subcortical stimulation, and these areas were respected. RESULTS SMA resection resulted in motor deficits, language deficits, or both; the deficits were always regressive, and they corresponded to the SMA syndrome. The topography and severity of these deficits were correlated to the extent of the SMA resection. The location of the deficit corresponded to SMA somatotopy: the representations of the lower limb, the upper limb, the face, and language (in the left-dominant SMA) were located from posterior to anterior. This somatotopy was also observed with functional magnetic resonance imaging. CONCLUSION Correlation between clinical patterns of deficit and the extent of SMA resection, guided by means of pre- and intraoperative functional methods, provides strong arguments in favor of somatotopy in this area. This knowledge should allow clinicians to base preoperative predictions of the pattern of postsurgical deficit and recovery on the planned resection, thus allowing them to inform patients accurately before the procedure.

Sign in / Sign up

Export Citation Format

Share Document