BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

138 related articles for article (PubMed ID: 38644430)

  • 1. Radio-anatomical evaluation of clinical and radiomic profile of multi-parametric magnetic resonance imaging of de novo glioblastoma multiforme.
    Ahmed HS; Devaraj T; Singhvi M; Dasan TA; Ranganath P
    J Egypt Natl Canc Inst; 2024 Apr; 36(1):13. PubMed ID: 38644430
    [TBL] [Abstract][Full Text] [Related]  

  • 2. The University of Pennsylvania glioblastoma (UPenn-GBM) cohort: advanced MRI, clinical, genomics, & radiomics.
    Bakas S; Sako C; Akbari H; Bilello M; Sotiras A; Shukla G; Rudie JD; Santamaría NF; Kazerooni AF; Pati S; Rathore S; Mamourian E; Ha SM; Parker W; Doshi J; Baid U; Bergman M; Binder ZA; Verma R; Lustig RA; Desai AS; Bagley SJ; Mourelatos Z; Morrissette J; Watt CD; Brem S; Wolf RL; Melhem ER; Nasrallah MP; Mohan S; O'Rourke DM; Davatzikos C
    Sci Data; 2022 Jul; 9(1):453. PubMed ID: 35906241
    [TBL] [Abstract][Full Text] [Related]  

  • 3. 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]  

  • 4. Radiomic features from the peritumoral brain parenchyma on treatment-naïve multi-parametric MR imaging predict long versus short-term survival in glioblastoma multiforme: Preliminary findings.
    Prasanna P; Patel J; Partovi S; Madabhushi A; Tiwari P
    Eur Radiol; 2017 Oct; 27(10):4188-4197. PubMed ID: 27778090
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Deep Learning Radiomics for the Assessment of Telomerase Reverse Transcriptase Promoter Mutation Status in Patients With Glioblastoma Using Multiparametric MRI.
    Zhang H; Zhang H; Zhang Y; Zhou B; Wu L; Lei Y; Huang B
    J Magn Reson Imaging; 2023 Nov; 58(5):1441-1451. PubMed ID: 36896953
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Radiomic Analysis Reveals Prognostic Information in T1-Weighted Baseline Magnetic Resonance Imaging in Patients With Glioblastoma.
    Ingrisch M; Schneider MJ; Nörenberg D; Negrao de Figueiredo G; Maier-Hein K; Suchorska B; Schüller U; Albert N; Brückmann H; Reiser M; Tonn JC; Ertl-Wagner B
    Invest Radiol; 2017 Jun; 52(6):360-366. PubMed ID: 28079702
    [TBL] [Abstract][Full Text] [Related]  

  • 7. A radiomics nomogram based on multiparametric MRI might stratify glioblastoma patients according to survival.
    Zhang X; Lu H; Tian Q; Feng N; Yin L; Xu X; Du P; Liu Y
    Eur Radiol; 2019 Oct; 29(10):5528-5538. PubMed ID: 30847586
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Radiomics features to distinguish glioblastoma from primary central nervous system lymphoma on multi-parametric MRI.
    Kim Y; Cho HH; Kim ST; Park H; Nam D; Kong DS
    Neuroradiology; 2018 Dec; 60(12):1297-1305. PubMed ID: 30232517
    [TBL] [Abstract][Full Text] [Related]  

  • 9. The LUMIERE dataset: Longitudinal Glioblastoma MRI with expert RANO evaluation.
    Suter Y; Knecht U; Valenzuela W; Notter M; Hewer E; Schucht P; Wiest R; Reyes M
    Sci Data; 2022 Dec; 9(1):768. PubMed ID: 36522344
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Evaluation of tumor-derived MRI-texture features for discrimination of molecular subtypes and prediction of 12-month survival status in glioblastoma.
    Yang D; Rao G; Martinez J; Veeraraghavan A; Rao A
    Med Phys; 2015 Nov; 42(11):6725-35. PubMed ID: 26520762
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Impact of image preprocessing on the scanner dependence of multi-parametric MRI radiomic features and covariate shift in multi-institutional glioblastoma datasets.
    Um H; Tixier F; Bermudez D; Deasy JO; Young RJ; Veeraraghavan H
    Phys Med Biol; 2019 Aug; 64(16):165011. PubMed ID: 31272093
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Achieving imaging and computational reproducibility on multiparametric MRI radiomics features in brain tumor diagnosis: phantom and clinical validation.
    Cheong EN; Park JE; Park SY; Jung SC; Kim HS
    Eur Radiol; 2024 Mar; 34(3):2008-2023. PubMed ID: 37665391
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Differentiation of Pseudoprogression from True Progressionin Glioblastoma Patients after Standard Treatment: A Machine Learning Strategy Combinedwith Radiomics Features from T
    Sun YZ; Yan LF; Han Y; Nan HY; Xiao G; Tian Q; Pu WH; Li ZY; Wei XC; Wang W; Cui GB
    BMC Med Imaging; 2021 Feb; 21(1):17. PubMed ID: 33535988
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Volume of high-risk intratumoral subregions at multi-parametric MR imaging predicts overall survival and complements molecular analysis of glioblastoma.
    Cui Y; Ren S; Tha KK; Wu J; Shirato H; Li R
    Eur Radiol; 2017 Sep; 27(9):3583-3592. PubMed ID: 28168370
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Deep Learning for Automatic Differential Diagnosis of Primary Central Nervous System Lymphoma and Glioblastoma: Multi-Parametric Magnetic Resonance Imaging Based Convolutional Neural Network Model.
    Xia W; Hu B; Li H; Shi W; Tang Y; Yu Y; Geng C; Wu Q; Yang L; Yu Z; Geng D; Li Y
    J Magn Reson Imaging; 2021 Sep; 54(3):880-887. PubMed ID: 33694250
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Novel Radiomic Features Based on Joint Intensity Matrices for Predicting Glioblastoma Patient Survival Time.
    Chaddad A; Daniel P; Desrosiers C; Toews M; Abdulkarim B
    IEEE J Biomed Health Inform; 2019 Mar; 23(2):795-804. PubMed ID: 29993848
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Multiparameter MRI Predictors of Long-Term Survival in Glioblastoma Multiforme.
    Stringfield O; Arrington JA; Johnston SK; Rognin NG; Peeri NC; Balagurunathan Y; Jackson PR; Clark-Swanson KR; Swanson KR; Egan KM; Gatenby RA; Raghunand N
    Tomography; 2019 Mar; 5(1):135-144. PubMed ID: 30854451
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Cancer Imaging Phenomics via CaPTk: Multi-Institutional Prediction of Progression-Free Survival and Pattern of Recurrence in Glioblastoma.
    Fathi Kazerooni A; Akbari H; Shukla G; Badve C; Rudie JD; Sako C; Rathore S; Bakas S; Pati S; Singh A; Bergman M; Ha SM; Kontos D; Nasrallah M; Bagley SJ; Lustig RA; O'Rourke DM; Sloan AE; Barnholtz-Sloan JS; Mohan S; Bilello M; Davatzikos C
    JCO Clin Cancer Inform; 2020 Mar; 4():234-244. PubMed ID: 32191542
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Radiomic MRI Phenotyping of Glioblastoma: Improving Survival Prediction.
    Bae S; Choi YS; Ahn SS; Chang JH; Kang SG; Kim EH; Kim SH; Lee SK
    Radiology; 2018 Dec; 289(3):797-806. PubMed ID: 30277442
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Analysis of heterogeneity of peritumoral T2 hyperintensity in patients with pretreatment glioblastoma: Prognostic value of MRI-based radiomics.
    Choi Y; Ahn KJ; Nam Y; Jang J; Shin NY; Choi HS; Jung SL; Kim BS
    Eur J Radiol; 2019 Nov; 120():108642. PubMed ID: 31546124
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 7.