Previously submitted to: JMIR Medical Informatics (no longer under consideration since Jun 23, 2021)
Date Submitted: Jun 13, 2020
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Medical Monitoring Data of Dynamic Contrast Enhanced Intelligent Information Image with MR in Postoperative Infection of Intracranial Gliomas
ABSTRACT
Background:
Background:
Intracranial gliomas is the most common primary malignant tumor, accounting for about half of all the primary malignant tumors in the brain, with a high rate of disability and death. Because of the invasive growth of gliomas, it is difficult to completely distinguish the boundaries of tumor removal and the sensitivity of radiotherapy and chemotherapy is not high, so most patients have poor prognosis. However, with the development of radiotherapy technology and the development of new chemotherapy drugs, the prognosis of glioma patients has improved to some extent, but the situation is still not optimistic. At present, the pathogenesis of glioma is not clear, so it is one of the most difficult to treat tumors, with high mortality, recurrence rate and low cure rate.
Objective:
Objective:
The objective is to study the medical monitoring data of dynamic contrast enhanced intelligent information image with MR in postoperative infection of intracranial gliomas.
Methods:
Methods:
Forty-nine patients who undergo total resection of gliomas in our hospital are selected as the subjects of this study. The subjects are divided into two groups: pseudo progression group (14 cases) and recurrence group (35 cases). All patients have complete follow-up data, and all patients undergo MRI. The acquired MRI images are processed and analyzed, and the quantitative parameters Ktrans, Ve, Kep and semi quantitative parameters iAUC of DCE-MRI images are obtained. Statistical analysis software is used to analyze these values.
Results:
Results:
The values of Ktrans and iAUC in the pseudo progression group are significantly lower than those in the recurrence group (P < 0.05). There is no significant difference in Ve and Kep between the two groups (P > 0.05). The value of Ktrans and iAUC in DCE-MRI images have a certain effect on the diagnosis of intracranial gliomas after operation, and the accuracy of Ktrans is higher than iAUC.
Conclusions:
Conclusion: In this study, the DCE-MRI image has a certain diagnostic value in this respect, which provides a basis for the intelligent diagnosis and treatment of specific conditions after surgery, and has a certain value in improving the prognosis of intracranial glioma.
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