BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

324 related articles for article (PubMed ID: 31218383)

  • 1. Radiogenomic analysis of PTEN mutation in glioblastoma using preoperative multi-parametric magnetic resonance imaging.
    Li Y; Liang Y; Sun Z; Xu K; Fan X; Li S; Zhang Z; Jiang T; Liu X; Wang Y
    Neuroradiology; 2019 Nov; 61(11):1229-1237. PubMed ID: 31218383
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Genotype prediction of ATRX mutation in lower-grade gliomas using an MRI radiomics signature.
    Li Y; Liu X; Qian Z; Sun Z; Xu K; Wang K; Fan X; Zhang Z; Li S; Wang Y; Jiang T
    Eur Radiol; 2018 Jul; 28(7):2960-2968. PubMed ID: 29404769
    [TBL] [Abstract][Full Text] [Related]  

  • 3. A Coclinical Radiogenomic Validation Study: Conserved Magnetic Resonance Radiomic Appearance of Periostin-Expressing Glioblastoma in Patients and Xenograft Models.
    Zinn PO; Singh SK; Kotrotsou A; Hassan I; Thomas G; Luedi MM; Elakkad A; Elshafeey N; Idris T; Mosley J; Gumin J; Fuller GN; de Groot JF; Baladandayuthapani V; Sulman EP; Kumar AJ; Sawaya R; Lang FF; Piwnica-Worms D; Colen RR
    Clin Cancer Res; 2018 Dec; 24(24):6288-6299. PubMed ID: 30054278
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Radiogenomic analysis of vascular endothelial growth factor in patients with diffuse gliomas.
    Sun Z; Li Y; Wang Y; Fan X; Xu K; Wang K; Li S; Zhang Z; Jiang T; Liu X
    Cancer Imaging; 2019 Oct; 19(1):68. PubMed ID: 31639060
    [TBL] [Abstract][Full Text] [Related]  

  • 5. MRI features predict p53 status in lower-grade gliomas via a machine-learning approach.
    Li Y; Qian Z; Xu K; Wang K; Fan X; Li S; Jiang T; Liu X; Wang Y
    Neuroimage Clin; 2018; 17():306-311. PubMed ID: 29527478
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Conventional magnetic resonance imaging-based radiomic signature predicts telomerase reverse transcriptase promoter mutation status in grade II and III gliomas.
    Jiang C; Kong Z; Zhang Y; Liu S; Liu Z; Chen W; Liu P; Liu D; Wang Y; Lyu Y; Zhao D; Wang Y; You H; Feng F; Ma W
    Neuroradiology; 2020 Jul; 62(7):803-813. PubMed ID: 32239241
    [TBL] [Abstract][Full Text] [Related]  

  • 7. MRI Radiomic Features to Predict IDH1 Mutation Status in Gliomas: A Machine Learning Approach using Gradient Tree Boosting.
    Sakai Y; Yang C; Kihira S; Tsankova N; Khan F; Hormigo A; Lai A; Cloughesy T; Nael K
    Int J Mol Sci; 2020 Oct; 21(21):. PubMed ID: 33121211
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Prediction of IDH1 Mutation Status in Glioblastoma Using Machine Learning Technique Based on Quantitative Radiomic Data.
    Lee MH; Kim J; Kim ST; Shin HM; You HJ; Choi JW; Seol HJ; Nam DH; Lee JI; Kong DS
    World Neurosurg; 2019 May; 125():e688-e696. PubMed ID: 30735871
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Machine learning-based radiomic evaluation of treatment response prediction in glioblastoma.
    Patel M; Zhan J; Natarajan K; Flintham R; Davies N; Sanghera P; Grist J; Duddalwar V; Peet A; Sawlani V
    Clin Radiol; 2021 Aug; 76(8):628.e17-628.e27. PubMed ID: 33941364
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Noninvasive O
    Hajianfar G; Shiri I; Maleki H; Oveisi N; Haghparast A; Abdollahi H; Oveisi M
    World Neurosurg; 2019 Dec; 132():e140-e161. PubMed ID: 31505292
    [TBL] [Abstract][Full Text] [Related]  

  • 11. MRI Features May Predict Molecular Features of Glioblastoma in
    Park CJ; Han K; Kim H; Ahn SS; Choi D; Park YW; Chang JH; Kim SH; Cha S; Lee SK
    AJNR Am J Neuroradiol; 2021 Mar; 42(3):448-456. PubMed ID: 33509914
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Radiogenomic Analysis of Vascular Endothelial Growth Factor in Patients With Glioblastoma.
    Zheng F; Chen B; Zhang L; Chen H; Zang Y; Chen X; Li Y
    J Comput Assist Tomogr; 2023 Nov-Dec 01; 47(6):967-972. PubMed ID: 37948373
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Machine Learning-Based Multiparametric Magnetic Resonance Imaging Radiomics for Prediction of H3K27M Mutation in Midline Gliomas.
    Kandemirli SG; Kocak B; Naganawa S; Ozturk K; Yip SSF; Chopra S; Rivetti L; Aldine AS; Jones K; Cayci Z; Moritani T; Sato TS
    World Neurosurg; 2021 Jul; 151():e78-e85. PubMed ID: 33819703
    [TBL] [Abstract][Full Text] [Related]  

  • 14. IDH1 mutation prediction using MR-based radiomics in glioblastoma: comparison between manual and fully automated deep learning-based approach of tumor segmentation.
    Choi Y; Nam Y; Lee YS; Kim J; Ahn KJ; Jang J; Shin NY; Kim BS; Jeon SS
    Eur J Radiol; 2020 Jul; 128():109031. PubMed ID: 32417712
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Development and Validation of a MRI-Based Radiomics Prognostic Classifier in Patients with Primary Glioblastoma Multiforme.
    Chen X; Fang M; Dong D; Liu L; Xu X; Wei X; Jiang X; Qin L; Liu Z
    Acad Radiol; 2019 Oct; 26(10):1292-1300. PubMed ID: 30660472
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Radiomics for predicting MGMT status in cerebral glioblastoma: comparison of different MRI sequences.
    Zheng F; Zhang L; Chen H; Zang Y; Chen X; Li Y
    J Radiat Res; 2024 May; 65(3):350-359. PubMed ID: 38650477
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Radiogenomics of lower-grade gliomas: a radiomic signature as a biological surrogate for survival prediction.
    Qian Z; Li Y; Sun Z; Fan X; Xu K; Wang K; Li S; Zhang Z; Jiang T; Liu X; Wang Y
    Aging (Albany NY); 2018 Oct; 10(10):2884-2899. PubMed ID: 30362964
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Radiogenomics to characterize the immune-related prognostic signature associated with biological functions in glioblastoma.
    Liu D; Chen J; Ge H; Yan Z; Luo B; Hu X; Yang K; Liu Y; Liu H; Zhang W
    Eur Radiol; 2023 Jan; 33(1):209-220. PubMed ID: 35881182
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Machine learning and radiomic phenotyping of lower grade gliomas: improving survival prediction.
    Choi YS; Ahn SS; Chang JH; Kang SG; Kim EH; Kim SH; Jain R; Lee SK
    Eur Radiol; 2020 Jul; 30(7):3834-3842. PubMed ID: 32162004
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Differentiation between pilocytic astrocytoma and glioblastoma: a decision tree model using contrast-enhanced magnetic resonance imaging-derived quantitative radiomic features.
    Dong F; Li Q; Xu D; Xiu W; Zeng Q; Zhu X; Xu F; Jiang B; Zhang M
    Eur Radiol; 2019 Aug; 29(8):3968-3975. PubMed ID: 30421019
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 17.