Xiaowei Chen
Huazhong University of Science and Technology
6 Papers
Xiaowei Chen is an academic researcher from Huazhong University of Science and Technology. The author has contributed to research in topics: Medicine & Glioma. The author has an hindex of 3, co-authored 6 publications.
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Papers
Grading and proliferation assessment of diffuse astrocytic tumors with monoexponential, biexponential, and stretched-exponential diffusion-weighted imaging and diffusion kurtosis imaging
TL;DR: MK could effectively characterize microstructural changes throughout the malignant transformation of DATs and provided useful complementary information for grading and has considerable potential to predict the degree of proliferation of D ATs.
33
•Journal Article
Stretched-exponential model diffusion-weighted imaging as a potential imaging marker in preoperative grading and assessment of proliferative activity of gliomas.
Xiaowei Chen,Jingjing Jiang,Nanxi Shen,Lingyun Zhao,Jiaxuan Zhang,Yuanyuan Qin,Shun Zhang,Li Li,Wenzhen Zhu +8 more
TL;DR: SEM-D WI offers a better approach for glioma grading than MEM-DWI, and DDC may be a better imaging biomarker for grading and evaluating the proliferative activity of brain gliomas.
15
Application of Neurite Orientation Dispersion and Density Imaging in Assessing Glioma Grades and Cellular Proliferation
Shihui Li,Ri-Feng Jiang,Ju Zhang,Changliang Su,Xiaowei Chen,Jiaxuan Zhang,Jingjing Jiang,Wenzhen Zhu +7 more
TL;DR: NODDI is a promising method in grading gliomas and predicting cellular proliferation and may be of great significance for the clinical diagnosis and treatment of glioma.
10
•Journal Article
T2-FLAIR, DWI and DKI radiomics satisfactorily predicts histological grade and Ki-67 proliferation index in gliomas.
TL;DR: In this article, the authors build highly predictive performance models for glioma stratification with radiomics features from non-invasive MRI, including the apparent diffusion coefficient (ADC), mean diffusion coefficient(Dmean), fractional anisotropy (FA), and mean kurtosis (MK).
6
Predicting cancer malignancy and proliferation in glioma patients: intra-subject inter-metabolite correlation analyses using MRI and MRSI contrast scans.
Changliang Su,Shihui Li,Xiaowei Chen,Chengxia Liu,Mehran Shaghaghi,Jingjing Jiang,Shun Zhang,Yuanyuan Qin,Kejia Cai +8 more
TL;DR: Glioma patients showed stronger inter-metabolite correlations than control subjects, and the IMCCs were significantly correlated with glioma grade and proliferation; the multi-IMCCs combined model further improved the performance of clinical diagnosis.