Comparison of application values of CT and MRI in the diagnosis of early Lacunar Infarction

He, Yi; Wei, Liping; Li, Wenbo

doi:10.12669/pjms.341.13619

Cited by 4 publications

(4 citation statements)

References 13 publications

(11 reference statements)

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“…The detection ability of MRI for small lesions of cerebral infarction was significantly stronger than that of CT. He et al [ 21 ] compared the role of nuclear magnetic resonance detection and CT detection in the diagnosis of early interstitial infarction and compared 88 patients. MRI detected 441 lesions, while CT detected 145 lesions.…”

Section: Discussionmentioning

confidence: 99%

Artificial Intelligence Algorithm-Based MRI in Evaluating the Treatment Effect of Acute Cerebral Infarction

Liu

Zou

et al. 2022

Computational and Mathematical Methods in Medicine

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The study is aimed at exploring the application of artificial intelligence algorithm-based magnetic resonance imaging (MRI) in the diagnosis of acute cerebral infarction, expected to provide a reference for diagnosis and effect evaluation of acute cerebral infarction. In this study, 80 patients diagnosed with suspected acute cerebral infarction per Diagnostic Criteria for Cerebral Infarction were selected as the research subjects. MRI images were reconstructed by deep dictionary learning to improve their recognition ability. At the same time, the same diagnostic operation was performed by Computed Tomography (CT) images to compare with MRI. The results of the interalgorithm comparison showed the image reconstruction effect of the deep dictionary learning model is significantly better than SAE reconstruction, single-layer dictionary reconstruction model, and KAVD reconstruction. After comparison, the results of MRI based on artificial intelligence algorithm and CT evaluation were statistically significant ( P < 0.05 ). In the lesion image, the diameter of MRI lesions ( 3.81 ± 0.77 cm) based on artificial intelligence algorithm and the diameter of lesions in CT ( 3.66 ± 1.65 cm) also had significant statistical significance ( P < 0.05 ). The results showed that MRI based on deep learning was more sensitive than CT imaging for diagnosis and evaluation of patients with acute cerebral infarction, with only 1 case misdiagnosed. The rate of disease detection and lesion image quality had a higher improvement. The results can provide effective support for the clinical application of MRI based on artificial intelligence algorithm in the diagnosis of acute cerebral infarction.

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Section: Discussionmentioning

confidence: 99%

Artificial Intelligence Algorithm-Based MRI in Evaluating the Treatment Effect of Acute Cerebral Infarction

Liu

Zou

et al. 2022

Computational and Mathematical Methods in Medicine

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Section: Discussionmentioning

confidence: 99%

“…Among the four values, Ktrans had the highest sensitivity and specificity, indicating that Ktrans was used to evaluate tumor blood perfusion and predict the therapeutic effect, which was consistent with most scholars. 11,12 The advantages of using dynamic contrastive enhanced MAGNETIC resonance quantitative parameters to evaluate the efficacy of lung cancer are as follows: first, morphological changes of the lesions and the supply of tumor microvessels can be observed at the same time to obtain rich diagnostic information, and the evaluation method is more accurate and objective. 13 Second, this examination has no radiation effect and is more suitable for long-term follow-up reviews than CT and other examination methods.…”

Section: Accordingmentioning

confidence: 99%

The Application Value of Magnetic Resonance Imaging (MRI)in the Clinical Diagnosis in Hospital Management

2021

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Background & Objective: To evaluate the application value of dynamic enhanced magnetic resonance imaging (DCE-MRI) in the clinical diagnosis in hospital based on the fuzzy C-means clustering algorithm and conduct its cost-benefit analysis in practice. Methods: This study was conducted from October 11th 2020 to November 25, 2020. Eighteen patients with lung cancer confirmed by pathology were collected and examined by DCE-MRI one day before and one month after surgery using a fuzzy C-means clustering algorithm. And then, taking Guang’an District People’s Hospital as an example, the present paper conducts the cost-benefit analysis with the utilization of net present value (NPV). Results: After 1-month review, eleven patients with effective treatment, four numerical Ktrans, Kep, Ve, Vp compared with preoperative decreased, which Ktrans, Kep, the change of the Ve was statistically significant (P < 0.05), the Vp of decline has no statistical significance (P > 0.05), the experimental and ineffective group after an operation, compared to four numerical Ktrans and Vp difference was statistically significant (P < 0.05), the corresponding AUC (area under the curve) to 1 and 0.818, the sensitivity of 100% and 85.7%, a specific degree of 100% and 72.7%. The NPV analysis results showed that the hospital could achieve profit and loss balance in the third year after purchasing MRI equipment and then gradually obtain positive cash inflow. Conclusion: The application of MRI in the Clinical Diagnosis helps hospital promote the therapeutic effect, thus having great practical value, and also contributes to increasing benefits in the long run. Abbreviations: DCE-MRI: Dynamic enhanced magnetic resonance imaging. NPV: Net Present Value. RECIST: Reliable Tumor Evaluation Criteria. CR: Complete Response. doi: https://doi.org/10.12669/pjms.37.6-WIT.4791 How to cite this:Chen Y, Zhou HM, Jiang QJ. The Application Value of Magnetic Resonance Imaging (MRI) in the Clinical Diagnosis in Hospital Management. Pak J Med Sci. 2021;37(6):1710-1713. doi: https://doi.org/10.12669/pjms.37.6-WIT.4791 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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“…In contrast, infarction size was categorized into small (≤5 mm in diameter), medium (6-14 mm in diameter), and large (≥15 mm in diameter), which was a modification of the categories used in previous studies. 17,18 Subjects were categorized as having hypertension if they had a systolic blood pressure of ≥140 mmHg, and/or diastolic blood pressure ≥90 mmHg, and/or any use of antihypertensive medication, and/or self-reported history of hypertension. They were categorized as having diabetes mellitus if they had fasting blood glucose levels of ≥126 mg/dL (7.0 mmol/L), and/or any use of anti-diabetic medication, and/or self-reported history of diabetes mellitus as described in previous studies.…”

Section: Methodsmentioning

confidence: 99%

Characteristics of Cognitive Status in Sub-Population of Sub-Acute Stage of Ischemic Stroke Patients in West Nusa Tenggara, Indonesia

Harahap

Akbar

Tammasse

et al. 2021

Kesmas: National Public Health Journal

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Cognitive decline is a significant complication that affects most stroke survivors. Early detection of cognitive decline in ischemic stroke patients and identification of risk factors improves their clinical outcomes. This study aimed to determine the characteristics of cognitive status in the sub-acute phase of ischemic stroke. A cross-sectional study was conducted on 89 sub-acute ischemic stroke patients in three hospitals in West Nusa Tenggara recruited consecutively from August 2019 to April 2020. The data collected were demographic and clinical characteristics, cognitive status, and functional outcome. The association between clinical and demographic characteristics and cognitive decline was analyzed using logistic regression. In addition, the relationship between cognitive status and functional outcomes of these patients was examined using the chi-square test. This study revealed that the prevalence of cognitive decline in these subjects was 71.9%. Multiple logistic regression showed that age was the only characteristic associated with cognitive decline in the subjects (OR = 5.12,95% CI = 1.08-24.28). Furthermore, the frequency of cognitive decline in these subjects was significantly associated with functional outcomes (p-value =0.014). Thus, there was a high prevalence of cognitive decline in sub-acute ischemic stroke patients associated with increasing age and poor functional outcomes.

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Comparison of application values of CT and MRI in the diagnosis of early Lacunar Infarction

Cited by 4 publications

References 13 publications

Artificial Intelligence Algorithm-Based MRI in Evaluating the Treatment Effect of Acute Cerebral Infarction

Artificial Intelligence Algorithm-Based MRI in Evaluating the Treatment Effect of Acute Cerebral Infarction

The Application Value of Magnetic Resonance Imaging (MRI)in the Clinical Diagnosis in Hospital Management

Characteristics of Cognitive Status in Sub-Population of Sub-Acute Stage of Ischemic Stroke Patients in West Nusa Tenggara, Indonesia

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