Radiomics Features-Based MRI In Glioblastoma Patients
محل انتشار: دومین کنگره بین المللی دانشجویان رادیولوژی کشور
سال انتشار: 1401
نوع سند: مقاله کنفرانسی
زبان: انگلیسی
مشاهده: 209
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RSACONG02_048
تاریخ نمایه سازی: 20 مهر 1401
چکیده مقاله Radiomics Features-Based MRI In Glioblastoma Patients
Introduction: Glioblastoma multiforme (GBM) is the most common and aggressive primary malignant brain tumor and accounts for 60% of brain tumors in adults. This tumor carries a poor prognosis, with a median survival of 12–15 months despite surgery followed by concurrent chemotherapy with temozolomide and radiation therapy(1, 2).In clinical routine, GBMs are usually diagnosed and followed-up with MRI. More recently, the field of radiomics has been introduced to extend the noninvasive study of oncologic tissue beyond established MR imaging metrics, and a large number of quantitative descriptors that reflect textural variations in image intensity, among other features, have been derived from imaging data. The aim of the new studies was to evaluate whether radiomic feature–based imaging signatures allow prediction of survival and stratification of patients with newly diagnosed glioblastoma(3).Material and Methods: Scopus and Google Scholar databases were searched to find articles with relevant content for this presentation.The keywords used included Magnetic resonance imaging, Machine learning, Radiomics and Glioblastoma from 2012 to 2022.From the final results, articles were selected that provide a more relevant and complete explanation of the extraction of radiomics features-based MRI in glioblastoma patients.Results and Discussion: The results of various articles about MRI radiomics features in GBM patients were evaluated. In this presentation, we first introduce the characteristics of glioblastoma patients and then we examine the clinical applications of extracting radiomics features related to the MRI images of these patients.Conclusion: The aim of the new studies was to evaluate whether radiomic feature–based imaging signatures allow prediction of survival and stratification of patients with newly diagnosed glioblastoma.
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نویسندگان مقاله Radiomics Features-Based MRI In Glioblastoma Patients
Mohammad Amin Shahram
Department of Medical Physics, Mashhad University of Medical Sciences, Iran
elham Khakshour
Department of Medical Physics, Mashhad University of Medical Sciences, Iran