Practical applications of diffusion magnetic resonance imaging in acute cerebral infarction

1997 ◽  
Vol 4 (4) ◽  
pp. 249-254 ◽  
Author(s):  
Mauricio Castillo ◽  
Suresh K. Mukherji
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Cerebral Infarction ◽  
Diffusion Magnetic Resonance Imaging ◽  
Acute Cerebral Infarction ◽  
Resonance Imaging ◽  
Practical Applications

scholarly journals Optimized CSMRI Algorithm-Based MRI Image Analysis in the Active Rehabilitation Method for Patients with Acute Cerebral Infarction

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Chao Zeng ◽  
Jing Chen ◽  
Wenbing Liu ◽  
Kang Liang ◽  
Hui Li ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Cerebral Infarction ◽  
Activation Volume ◽  
Acute Cerebral Infarction ◽  
Nerve Function ◽  
Resonance Imaging ◽  
Magnetic Resonance Imaging Mri ◽  
Passive Group ◽  
Function Reconstruction

This paper combines optimized CSMRI algorithm (CS) and magnetic resonance imaging (MRI) to shorten the scanning time of MRI image data and improve the imaging quality. At the same time, the paper applies functional magnetic resonance imaging (BOLD-fMRI) based on the principle of blood oxygen level dependence to explore the application value of the nerve function reconstruction therapy system for the rehabilitation of active and passive motor functions in patients with acute cerebral infarction. Methods. In this paper, 20 patients with acute cerebral infarction were included. The random drawing method was used to divide them into active group and passive group, each with 10 cases. Both groups were treated with conventional medication and acupuncture. The active group used the active mode of the nerve function reconstruction treatment system to guide the patients’ limb active exercise; all training in the passive group is provided by the nerve function reconstruction treatment system to passively exercise the patients’ limbs; both groups undergo BOLD-fMRI examination before treatment and after 2 weeks of treatment and observe the activated parts of the brain functional area and corresponding parts of the two groups before and after treatment. We observe the activation volume and, at the same time, the ADL score. Results. After treatment, the activation volume and ADL scores of brain functional areas in the two groups were significantly improved compared with those before treatment, and the difference was statistically significant ( P < 0.05 ). Conclusion. The combination of optimized CSMRI algorithm (CS) and magnetic resonance imaging (MRI) can be used to evaluate the early rehabilitation efficacy of patients with acute cerebral infarction and has certain guiding value for clinical treatment.

scholarly journals Magnetic Resonance Imaging Image Segmentation Under Artificial Intelligence Neural Network for Evaluation of the Effect of Butyphthalide Combined With Edaravone on Neurological Function in Patients With Acute Cerebral Infarction

2021 ◽  
Vol 15 ◽  
Author(s):  
Bin Li ◽  
Guoping Liu
Keyword(s):  
Neural Network ◽  
Magnetic Resonance Imaging ◽  
Artificial Intelligence ◽  
Image Segmentation ◽  
Magnetic Resonance ◽  
Cerebral Infarction ◽  
Acute Cerebral Infarction ◽  
Resonance Imaging ◽  
Vascular Stenosis ◽  
Mri Image

This research was developed to investigate the effect of artificial intelligence neural network-based magnetic resonance imaging (MRI) image segmentation on the neurological function of patients with acute cerebral infarction treated with butylphthalide combined with edaravone. Eighty patients with acute cerebral infarction were selected as the research subjects, and the MRI images of patients with acute cerebral infarction were segmented by convolutional neural networks (CNN) upgraded algorithm model. MRI images of patients before and after treatment of butylphthalide combined with edaravone were compared to comprehensively evaluate the efficacy of this treatment. The results showed that compared with the traditional CNN algorithm, the running time of the CNN upgraded algorithm adopted in this study was significantly shorter, and the Loss value was lower than that of the traditional CNN model. Upgraded CNN model can realize accurate segmentation of cerebral infarction lesions in MRI images of patients. In addition, the degree of cerebral infarction and the degree of arterial stenosis were significantly improved after treatment with butylphthalide and edaravone. Compared with that before treatment, the number of patients with severe cerebral infarction or even vascular stenosis decreased significantly (P &lt; 0.05), and gradually changed to mild vascular stenosis, and the neurological dysfunction of patients was also significantly improved. In short, MRI image segmentation based on artificial intelligence neural network can well-evaluate the efficacy and neurological impairment of butylphthalide combined with edaravone in the treatment of acute cerebral infarction, and it was worthy of promotion in clinical evaluation of the treatment effect of acute cerebral infarction.

scholarly journals Semi-automated segmentation of the lateral periventricular regions using diffusion magnetic resonance imaging

MethodsX ◽  
2020 ◽  
Vol 7 ◽  
pp. 101023
Author(s):  
Albert M. Isaacs ◽  
Rowland H. Han ◽  
Christopher D. Smyser ◽  
David D. Limbrick ◽  
Joshua S. Shimony
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Diffusion Magnetic Resonance Imaging ◽  
Automated Segmentation ◽  
Resonance Imaging

scholarly journals Diffusion Magnetic Resonance Imaging-Based Biomarkers for Neurodegenerative Diseases

2021 ◽  
Vol 22 (10) ◽  
pp. 5216
Author(s):  
Koji Kamagata ◽  
Christina Andica ◽  
Ayumi Kato ◽  
Yuya Saito ◽  
Wataru Uchida ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Diffusion Tensor Imaging ◽  
Magnetic Resonance ◽  
Neurodegenerative Diseases ◽  
Diffusion Magnetic Resonance Imaging ◽  
New Technologies ◽  
Diffusion Tensor ◽  
Free Water ◽  
Diffusion Kurtosis Imaging ◽  
Resonance Imaging

There has been an increasing prevalence of neurodegenerative diseases with the rapid increase in aging societies worldwide. Biomarkers that can be used to detect pathological changes before the development of severe neuronal loss and consequently facilitate early intervention with disease-modifying therapeutic modalities are therefore urgently needed. Diffusion magnetic resonance imaging (MRI) is a promising tool that can be used to infer microstructural characteristics of the brain, such as microstructural integrity and complexity, as well as axonal density, order, and myelination, through the utilization of water molecules that are diffused within the tissue, with displacement at the micron scale. Diffusion tensor imaging is the most commonly used diffusion MRI technique to assess the pathophysiology of neurodegenerative diseases. However, diffusion tensor imaging has several limitations, and new technologies, including neurite orientation dispersion and density imaging, diffusion kurtosis imaging, and free-water imaging, have been recently developed as approaches to overcome these constraints. This review provides an overview of these technologies and their potential as biomarkers for the early diagnosis and disease progression of major neurodegenerative diseases.

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