The Value of Enhanced MR Radiomics in Estimating the IDH1 Genotype in High-Grade Gliomas
المؤلفون المشاركون
Liu, Xuejun
Niu, Lei
Feng, Wei-hua
Duan, Chong-feng
Liu, Ying-chao
Liu, Ji-hua
المصدر
العدد
المجلد 2020، العدد 2020 (31 ديسمبر/كانون الأول 2020)، ص ص. 1-6، 6ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2020-10-24
دولة النشر
مصر
عدد الصفحات
6
التخصصات الرئيسية
الملخص EN
Background.
The prognosis of IDH1-mutant glioma is significantly better than that of wild-type glioma, and the preoperative identification of IDH mutations in glioma is essential for the formulation of surgical procedures and prognostic assessment.
Purpose.
To explore the value of a radiomic model based on preoperative-enhanced MR images in the assessment of the IDH1 genotype in high-grade glioma.
Materials and Methods.
A retrospective analysis was performed on 182 patients with high-grade glioma confirmed by surgical pathology between December 2012 and January 2019 in our hospital with complete preoperative brain-enhanced MR images, including 79 patients with an IDH1 mutation (45 patients with WHO grade III and 34 patients with WHO grade IV) and 103 patients with wild-type IDH1 (33 patients with WHO grade III and 70 patients with WHO grade IV).
Patients were divided into a primary dataset and a validation dataset at a ratio of 7 : 3 using a stratified random sampling; radiomic features were extracted using A.K.
(Analysis Kit, GE Healthcare) software and were initially reduced using the Kruskal-Wallis and Spearman analyses.
Lasso was finally conducted to obtain the optimized subset of the feature to build the radiomic model, and the model was then tested with cross-validation.
ROC (receiver operating characteristic curve) analysis was performed to evaluate the performance of the model.
Results.
The radiomic model showed good discrimination in both the primary dataset (AUC=0.87, 95% CI: 0.754 to 0.855, ACC=0.798, sensitivity=85.5%, specificity=75.4%, positive predictive value=0.734, and negative predictive value=0.867) and the validation dataset (AUC=0.86, 95% CI: 0.690 to 0.913, ACC=0.789, sensitivity=91.3%, specificity=69.0%, positive predictive value=0.700, and negative predictive value=0.909).
Conclusion.
The radiomic model, based on the preoperative-enhanced MR, can effectively predict the IDH1 genotype in high-grade glioma.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Niu, Lei& Feng, Wei-hua& Duan, Chong-feng& Liu, Ying-chao& Liu, Ji-hua& Liu, Xuejun. 2020. The Value of Enhanced MR Radiomics in Estimating the IDH1 Genotype in High-Grade Gliomas. BioMed Research International،Vol. 2020, no. 2020, pp.1-6.
https://search.emarefa.net/detail/BIM-1134049
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Niu, Lei…[et al.]. The Value of Enhanced MR Radiomics in Estimating the IDH1 Genotype in High-Grade Gliomas. BioMed Research International No. 2020 (2020), pp.1-6.
https://search.emarefa.net/detail/BIM-1134049
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Niu, Lei& Feng, Wei-hua& Duan, Chong-feng& Liu, Ying-chao& Liu, Ji-hua& Liu, Xuejun. The Value of Enhanced MR Radiomics in Estimating the IDH1 Genotype in High-Grade Gliomas. BioMed Research International. 2020. Vol. 2020, no. 2020, pp.1-6.
https://search.emarefa.net/detail/BIM-1134049
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1134049
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر