Cargando…

Grading of Gliomas by Using Radiomic Features on Multiple Magnetic Resonance Imaging (MRI) Sequences

BACKGROUND: Gliomas are the most common primary brain neoplasms. Misdiagnosis occurs in glioma grading due to an overlap in conventional MRI manifestations. The aim of the present study was to evaluate the power of radiomic features based on multiple MRI sequences – T2-Weighted-Imaging-FLAIR (FLAIR)...

Descripción completa

Detalles Bibliográficos
Autores principales:	Qin, Jiang-bo, Liu, Zhenyu, Zhang, Hui, Shen, Chen, Wang, Xiao-chun, Tan, Yan, Wang, Shuo, Wu, Xiao-feng, Tian, Jie
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	International Scientific Literature, Inc. 2017
Materias:	Diagnostic Techniques
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5436423/ https://www.ncbi.nlm.nih.gov/pubmed/28478462 http://dx.doi.org/10.12659/MSM.901270

Ejemplares similares

Brain magnetic resonance imaging radiomics features associated with hepatic encephalopathy in adult cirrhotic patients
por: Sparacia, Gianvincenzo, et al.
Publicado: (2022)

Multi-modal magnetic resonance imaging-based grading analysis for gliomas by integrating radiomics and deep features
por: Ning, Zhenyuan, et al.
Publicado: (2021)

Conventional MRI features can predict the molecular subtype of adult grade 2–3 intracranial diffuse gliomas
por: Lasocki, Arian, et al.
Publicado: (2022)

Radiomic features from multiparametric magnetic resonance imaging predict molecular subgroups of pediatric low-grade gliomas
por: Liu, Zhen, et al.
Publicado: (2023)

The combination of radiomics features and VASARI standard to predict glioma grade
por: You, Wei, et al.
Publicado: (2023)

Radiomics and Qualitative Features From Multiparametric MRI Predict Molecular Subtypes in Patients With Lower-Grade Glioma
por: Sun, Chen, et al.
Publicado: (2022)

Perfusion imaging with arterial spin labeling (ASL)–MRI predicts malignant progression in low‑grade (WHO grade II) gliomas
por: Flies, Christina M., et al.
Publicado: (2021)

Application of Indirect Signs of Magnetic Resonance Imaging (MRI) in Prenatal Diagnosis of Abnormally Invasive Placenta
por: Huang, Fang, et al.
Publicado: (2020)

Magnetic Resonance Imaging (MRI) Evaluation for Anterior Disc Displacement of the Temporomandibular Joint
por: Yang, Zhongjun, et al.
Publicado: (2017)

A Radiomics Model for Predicting Early Recurrence in Grade II Gliomas Based on Preoperative Multiparametric Magnetic Resonance Imaging
por: Wang, Zhen-hua, et al.
Publicado: (2021)

Predictive value of magnetic resonance imaging radiomics-based machine learning for disease progression in patients with high-grade glioma
por: Li, Zhibin, et al.
Publicado: (2022)

Predicting IDH Mutation Status in Low-Grade Gliomas Based on Optimal Radiomic Features Combined with Multi-Sequence Magnetic Resonance Imaging
por: He, Ailing, et al.
Publicado: (2022)

Application of Enhanced T1WI of MRI Radiomics in Glioma Grading
por: Zhou, Hongzhang, et al.
Publicado: (2022)

Radiomics Profiling Identifies the Incremental Value of MRI Features beyond Key Molecular Biomarkers for the Risk Stratification of High-Grade Gliomas
por: Yang, Guoqiang, et al.
Publicado: (2022)

Machine-Learning-Based Radiomics for Classifying Glioma Grade from Magnetic Resonance Images of the Brain
por: Kumar, Anuj, et al.
Publicado: (2023)

Diagnostic value of MRI radiomics in differentiating high‑grade glioma from low‑grade glioma: A meta‑analysis
por: Wang, Jiefang, et al.
Publicado: (2023)

The Rate of Magnetic Resonance Imaging in Patients With Spinal Cord Stimulation
por: Desai, Mehul J., et al.
Publicado: (2015)

Multiparametric MRI Features Predict the SYP Gene Expression in Low-Grade Glioma Patients: A Machine Learning-Based Radiomics Analysis
por: Xiao, Zheng, et al.
Publicado: (2021)

Radiomics Analysis of Postoperative Epilepsy Seizures in Low-Grade Gliomas Using Preoperative MR Images
por: Sun, Kai, et al.
Publicado: (2020)

Correlating MRI features with additional genetic markers and patient survival in histological grade 2-3 IDH-mutant astrocytomas
por: Lasocki, Arian, et al.
Publicado: (2023)

Physiological MRI of microvascular architecture, neovascularization activity, and oxygen metabolism facilitate early recurrence detection in patients with IDH-mutant WHO grade 3 glioma
por: Stadlbauer, Andreas, et al.
Publicado: (2021)

Prognostic value of magnetic resonance imaging features in low-grade gliomas
por: Deng, Liang, et al.
Publicado: (2019)

PROX1 is a predictor of survival for gliomas WHO grade II
por: Elsir, T, et al.
Publicado: (2011)

Feasibility of generalised diffusion kurtosis imaging approach for brain glioma grading
por: Pogosbekian, E. L., et al.
Publicado: (2021)

An In Vitro Study of the Intervertebral Disc Structure Using 3 T Magnetic Resonance Imaging
por: Wijayathunga, Vithanage N., et al.
Publicado: (2019)

High-order radiomics features based on T2 FLAIR MRI predict multiple glioma immunohistochemical features: A more precise and personalized gliomas management
por: Li, Jing, et al.
Publicado: (2020)

Cerebral Glioma Grading Using Bayesian Network with Features Extracted from Multiple Modalities of Magnetic Resonance Imaging
por: Hu, Jisu, et al.
Publicado: (2016)

Radiomics Features on Magnetic Resonance Images Can Predict C5aR1 Expression Levels and Prognosis in High-Grade Glioma
por: Wu, Zijun, et al.
Publicado: (2023)

Significance of Magnetic Resonance Imaging (MRI) T2 Hyperintense Endo-Vessels Sign in Progressive Posterior Circulation Infarction
por: Xu, Jialiang, et al.
Publicado: (2018)

MRI follow-up after magnetic resonance-guided focused ultrasound for non-invasive thalamotomy: the neuroradiologist’s perspective
por: Keil, Vera C., et al.
Publicado: (2020)

Radiomics analysis allows for precise prediction of epilepsy in patients with low-grade gliomas
por: Liu, Zhenyu, et al.
Publicado: (2018)

Radiomics Features Predict CIC Mutation Status in Lower Grade Glioma
por: Zhang, Luyuan, et al.
Publicado: (2020)

Prediction of pituitary adenoma surgical consistency: radiomic data mining and machine learning on T2-weighted MRI
por: Cuocolo, Renato, et al.
Publicado: (2020)

Model incorporating multiple diffusion MRI features: development and validation of a radiomics-based model to predict adult-type diffuse gliomas grade
por: Wang, Peng, et al.
Publicado: (2023)

IDH mutant and 1p/19q co-deleted oligodendrogliomas: tumor grade stratification using diffusion-, susceptibility-, and perfusion-weighted MRI
por: Lin, Yu, et al.
Publicado: (2017)

Differentiation of Brain Abscess From Cystic Glioma Using Conventional MRI Based on Deep Transfer Learning Features and Hand-Crafted Radiomics Features
por: Bo, Linlin, et al.
Publicado: (2021)

Multimodal MRI-Based Radiomic Nomogram for the Early Differentiation of Recurrence and Pseudoprogression of High-Grade Glioma
por: Jing, Hui, et al.
Publicado: (2022)

Distinct pattern of microsusceptibility changes on brain magnetic resonance imaging (MRI) in critically ill patients on mechanical ventilation/oxygenation
por: Thurnher, Majda M., et al.
Publicado: (2021)

Application of radiomics feature captured from MRI for prediction of recurrence for glioma patients
por: Liu, Canyu, et al.
Publicado: (2022)

Correction: Cerebral Glioma Grading Using Bayesian Network with Features Extracted from Multiple Modalities of Magnetic Resonance Imaging
por: Hu, Jisu, et al.
Publicado: (2016)

Cannot write session to /tmp/vufind_sessions/sess_l55stmc3cc7938ii1ocqqen2f7