SUMMARY
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.4791How 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.4791This 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.