胶质母细胞瘤诊断和综合治疗客观化的放射学研究

Ya. O. Nikulshina, A. N. Redkin, A. Kolpakov, M. A. Zakharov
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引用次数: 0

摘要

介绍胶质母细胞瘤是一种主要起源于星形细胞的神经上皮恶性脑瘤,其病程具有侵袭性,预后极为不利。由于胶质母细胞瘤综合治疗(包括手术治疗、放射治疗和化疗)后的总生存期中位数为14.6个月,因此迫切需要开发一种个性化的胶质母细胞癌诊断和治疗方法。材料和方法。在以下MRI扫描仪上对一名接受胶质母细胞瘤G4放化疗的患者进行MRI检查:Philips Ingenia 1.5T和Philips Ingonia Ambient 1.5T。使用Matlab 2021应用程序对MR图像进行分析。结果和讨论。在手术前后以及一个疗程的放化疗后对MR图像进行分析。通过统计纹理参数描述的病变图像的局部亮度分布的统计特征被分析为病变区域在图像上的信息特征。已经获得了使用病变区域的T2 MR图像的上述统计参数来客观化诊断和治疗的能力的初步确认。结论该领域进一步研究的目的是利用放射组学研究来规划和监测高级别胶质瘤的治疗,估计疾病结果,并以预测的方式分析对复杂治疗的反应。
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Radiomic Study for Objectification of Diagnostics and Complex Treatment of Glioblastoma
Introduction. Glioblastoma is a neuroepithelial malignant brain tumour of predominantly astrocytic origin with an aggressive course and an extremely unfavorable prognosis. Since the median of overall survival with glioblastoma is 14.6 months after complex treatment that includes a combination of surgical treatment, radiation therapy and chemotherapy, the development a personalized approach in the diagnosis and treatment of glioblastomas is appeared to be urgent.Materials and methods. MRIs of a patient undergoing chemoradiotherapy for glioblastoma G4 were performed on the following MRI scanners: Philips Ingenia 1.5T and Philips Ingenia Ambient 1.5T. The analysis of MR-images was carried out using the Matlab 2021 apps.Results and discussion. MR-images were analyzed before and after surgery, and after a course of chemoradiotherapy. The statistical characteristics of the local brightness distribution of the lesion image, which are described by statistical texture parameters, were analyzed as informative features of the lesion area on the images. Initial confirmation of the ability to objectify diagnosis and treatment using the above statistical parameters of T2 MR images of lesion area has been obtained.Conclusion. The aim of further research in this area is to use radiomic study for planning and monitoring the treatment of high-grade gliomas, estimate disease outcomes, and analyze the response to complex treatments in a predictive way.
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