328 related articles for article (PubMed ID: 30315419)
1. Radiomics based on multicontrast MRI can precisely differentiate among glioma subtypes and predict tumour-proliferative behaviour.
Su C; Jiang J; Zhang S; Shi J; Xu K; Shen N; Zhang J; Li L; Zhao L; Zhang J; Qin Y; Liu Y; Zhu W
Eur Radiol; 2019 Apr; 29(4):1986-1996. PubMed ID: 30315419
[TBL] [Abstract][Full Text] [Related]
2. T2-FLAIR, DWI and DKI radiomics satisfactorily predicts histological grade and Ki-67 proliferation index in gliomas.
Su C; Chen X; Liu C; Li S; Jiang J; Qin Y; Zhang S
Am J Transl Res; 2021; 13(8):9182-9194. PubMed ID: 34540034
[TBL] [Abstract][Full Text] [Related]
3. Correlation of diffusion tensor, dynamic susceptibility contrast MRI and (99m)Tc-Tetrofosmin brain SPECT with tumour grade and Ki-67 immunohistochemistry in glioma.
Alexiou GA; Zikou A; Tsiouris S; Goussia A; Kosta P; Papadopoulos A; Voulgaris S; Kyritsis AP; Fotopoulos AD; Argyropoulou MI
Clin Neurol Neurosurg; 2014 Jan; 116():41-5. PubMed ID: 24309151
[TBL] [Abstract][Full Text] [Related]
4. Radiomics MRI Phenotyping with Machine Learning to Predict the Grade of Lower-Grade Gliomas: A Study Focused on Nonenhancing Tumors.
Park YW; Choi YS; Ahn SS; Chang JH; Kim SH; Lee SK
Korean J Radiol; 2019 Sep; 20(9):1381-1389. PubMed ID: 31464116
[TBL] [Abstract][Full Text] [Related]
5. High-order radiomics features based on T2 FLAIR MRI predict multiple glioma immunohistochemical features: A more precise and personalized gliomas management.
Li J; Liu S; Qin Y; Zhang Y; Wang N; Liu H
PLoS One; 2020; 15(1):e0227703. PubMed ID: 31968004
[TBL] [Abstract][Full Text] [Related]
6. Textural features of dynamic contrast-enhanced MRI derived model-free and model-based parameter maps in glioma grading.
Xie T; Chen X; Fang J; Kang H; Xue W; Tong H; Cao P; Wang S; Yang Y; Zhang W
J Magn Reson Imaging; 2018 Apr; 47(4):1099-1111. PubMed ID: 28845594
[TBL] [Abstract][Full Text] [Related]
7. Radiomics strategy for glioma grading using texture features from multiparametric MRI.
Tian Q; Yan LF; Zhang X; Zhang X; Hu YC; Han Y; Liu ZC; Nan HY; Sun Q; Sun YZ; Yang Y; Yu Y; Zhang J; Hu B; Xiao G; Chen P; Tian S; Xu J; Wang W; Cui GB
J Magn Reson Imaging; 2018 Dec; 48(6):1518-1528. PubMed ID: 29573085
[TBL] [Abstract][Full Text] [Related]
8. Non-invasive genotype prediction of chromosome 1p/19q co-deletion by development and validation of an MRI-based radiomics signature in lower-grade gliomas.
Han Y; Xie Z; Zang Y; Zhang S; Gu D; Zhou M; Gevaert O; Wei J; Li C; Chen H; Du J; Liu Z; Dong D; Tian J; Zhou D
J Neurooncol; 2018 Nov; 140(2):297-306. PubMed ID: 30097822
[TBL] [Abstract][Full Text] [Related]
9. Diffusion-weighted imaging and arterial spin labeling radiomics features may improve differentiation between radiation-induced brain injury and glioma recurrence.
Zhang J; Wu Y; Wang Y; Zhang X; Lei Y; Zhu G; Mao C; Zhang L; Ma L
Eur Radiol; 2023 May; 33(5):3332-3342. PubMed ID: 36576544
[TBL] [Abstract][Full Text] [Related]
10. Fusion Radiomics Features from Conventional MRI Predict MGMT Promoter Methylation Status in Lower Grade Gliomas.
Jiang C; Kong Z; Liu S; Feng S; Zhang Y; Zhu R; Chen W; Wang Y; Lyu Y; You H; Zhao D; Wang R; Wang Y; Ma W; Feng F
Eur J Radiol; 2019 Dec; 121():108714. PubMed ID: 31704598
[TBL] [Abstract][Full Text] [Related]
11. Non-Gaussian diffusion MR imaging of glioma: comparisons of multiple diffusion parameters and correlation with histologic grade and MIB-1 (Ki-67 labeling) index.
Yan R; Haopeng P; Xiaoyuan F; Jinsong W; Jiawen Z; Chengjun Y; Tianming Q; Ji X; Mao S; Yueyue D; Yong Z; Jianfeng L; Zhenwei Y
Neuroradiology; 2016 Feb; 58(2):121-32. PubMed ID: 26494463
[TBL] [Abstract][Full Text] [Related]
12. Accuracy of Radiomics-Based Feature Analysis on Multiparametric Magnetic Resonance Images for Noninvasive Meningioma Grading.
Laukamp KR; Shakirin G; Baeßler B; Thiele F; Zopfs D; Große Hokamp N; Timmer M; Kabbasch C; Perkuhn M; Borggrefe J
World Neurosurg; 2019 Dec; 132():e366-e390. PubMed ID: 31476455
[TBL] [Abstract][Full Text] [Related]
13. Predicting the grade of hepatocellular carcinoma based on non-contrast-enhanced MRI radiomics signature.
Wu M; Tan H; Gao F; Hai J; Ning P; Chen J; Zhu S; Wang M; Dou S; Shi D
Eur Radiol; 2019 Jun; 29(6):2802-2811. PubMed ID: 30406313
[TBL] [Abstract][Full Text] [Related]
14. Radiomics-based MRI for predicting Erythropoietin-producing hepatocellular receptor A2 expression and tumor grade in brain diffuse gliomas.
Liu X; Li J; Liao X; Luo Z; Xu Q; Pan H; Zhou Q; Tao Y; Shi F; Lu G; Zhang Z
Neuroradiology; 2022 Feb; 64(2):323-331. PubMed ID: 34368897
[TBL] [Abstract][Full Text] [Related]
15. Glioma grading using a machine-learning framework based on optimized features obtained from T
Sengupta A; Ramaniharan AK; Gupta RK; Agarwal S; Singh A
J Magn Reson Imaging; 2019 Oct; 50(4):1295-1306. PubMed ID: 30895704
[TBL] [Abstract][Full Text] [Related]
16. Machine learning assisted DSC-MRI radiomics as a tool for glioma classification by grade and mutation status.
Sudre CH; Panovska-Griffiths J; Sanverdi E; Brandner S; Katsaros VK; Stranjalis G; Pizzini FB; Ghimenton C; Surlan-Popovic K; Avsenik J; Spampinato MV; Nigro M; Chatterjee AR; Attye A; Grand S; Krainik A; Anzalone N; Conte GM; Romeo V; Ugga L; Elefante A; Ciceri EF; Guadagno E; Kapsalaki E; Roettger D; Gonzalez J; Boutelier T; Cardoso MJ; Bisdas S
BMC Med Inform Decis Mak; 2020 Jul; 20(1):149. PubMed ID: 32631306
[TBL] [Abstract][Full Text] [Related]
17. Evaluation of diffuse glioma grade and proliferation activity by different diffusion-weighted-imaging models including diffusion kurtosis imaging (DKI) and mean apparent propagator (MAP) MRI.
Xie SH; Lang R; Li B; Zhao H; Wang P; He JL; Ma XY; Wu Q; Wang SY; Zhang HP; Gao Y; Wu JL
Neuroradiology; 2023 Jan; 65(1):55-64. PubMed ID: 35835879
[TBL] [Abstract][Full Text] [Related]
18. Diagnostic performance of texture analysis on MRI in grading cerebral gliomas.
Skogen K; Schulz A; Dormagen JB; Ganeshan B; Helseth E; Server A
Eur J Radiol; 2016 Apr; 85(4):824-9. PubMed ID: 26971430
[TBL] [Abstract][Full Text] [Related]
19. Noninvasive IDH1 mutation estimation based on a quantitative radiomics approach for grade II glioma.
Yu J; Shi Z; Lian Y; Li Z; Liu T; Gao Y; Wang Y; Chen L; Mao Y
Eur Radiol; 2017 Aug; 27(8):3509-3522. PubMed ID: 28004160
[TBL] [Abstract][Full Text] [Related]
20. Association of Glioma Grading With Inflow-Based Vascular-Space-Occupancy MRI: A Preliminary Study at 3T.
Li X; Liao S; Hua J; Guo L; Wang D; Xiao X; Zhou J; Liu X; Tan Y; Lu L; Xu Y; Wu Y
J Magn Reson Imaging; 2019 Dec; 50(6):1817-1823. PubMed ID: 30932289
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
