دورية أكاديمية

Magnetic resonance imaging findings of intracranial extraventricular ependymoma: A retrospective multi‐center cohort study of 114 cases

التفاصيل البيبلوغرافية
العنوان: Magnetic resonance imaging findings of intracranial extraventricular ependymoma: A retrospective multi‐center cohort study of 114 cases
المؤلفون: Liyan Li, Yan Fu, Yinping Zhang, Yipu Mao, Deyou Huang, Xiaoping Yi, Jing Wang, Zeming Tan, Muliang Jiang, Bihong T. Chen
المصدر: Cancer Medicine, Vol 12, Iss 15, Pp 16195-16206 (2023)
بيانات النشر: Wiley, 2023.
سنة النشر: 2023
المجموعة: LCC:Neoplasms. Tumors. Oncology. Including cancer and carcinogens
مصطلحات موضوعية: glioblastoma multiforme (GBM), intracranial extraventricular ependymoma (IEE), magnetic resonance imaging (MRI), visually AcceSAble Rembrandt images (VASARI), Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
الوصف: Abstract Background Intracranial extraventricular ependymoma (IEE) is an ependymoma located in the brain parenchyma outside the ventricles. IEE has overlapping clinical and imaging characteristics with glioblastoma multiforme (GBM) but different treatment strategy and prognosis. Therefore, an accurate preoperative diagnosis is necessary for optimizing therapy for IEE. Methods A retrospective multicenter cohort of IEE and GBM was identified. MR imaging characteristics assessed with the Visually Accessible Rembrandt Images (VASARI) feature set and clinicopathological findings were recorded. Independent predictors for IEE were identified using multivariate logistic regression, which was used to construct a diagnostic score for differentiating IEE from GBM. Results Compared to GBM, IEE tended to occur in younger patients. Multivariate logistic regression analysis identified seven independent predictors for IEE. Among them, 3 predictors including tumor necrosis rate (F7), age, and tumor‐enhancing margin thickness (F11), demonstrated higher diagnostic performance with an Area Under Curve (AUC) of more than 70% in distinguishing IEE from GBM. The AUC was 0.85, 0.78, and 0.70, with sensitivity of 92.98%, 72.81%, and 96.49%, and specificity of 65.50%, 73.64%, and 43.41%, for F7, age, and F11, respectively. Conclusion We identified specific MR imaging features such as tumor necrosis and thickness of enhancing tumor margins that could help to differentiate IEE from GBM. Our study results should be helpful to assist in diagnosis and clinical management of this rare brain tumor.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 2045-7634
Relation: https://doaj.org/toc/2045-7634
DOI: 10.1002/cam4.6279
URL الوصول: https://doaj.org/article/8a7c0c712e324e9eafc36f60d253f79c
رقم الأكسشن: edsdoj.8a7c0c712e324e9eafc36f60d253f79c
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:20457634
DOI:10.1002/cam4.6279