These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

194 related articles for article (PubMed ID: 34460616)

  • 1. The Potential Use of Radiomics with Pre-Radiation Therapy MR Imaging in Predicting Risk of Pseudoprogression in Glioblastoma Patients.
    Baine M; Burr J; Du Q; Zhang C; Liang X; Krajewski L; Zima L; Rux G; Zhang C; Zheng D
    J Imaging; 2021 Jan; 7(2):. PubMed ID: 34460616
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Incorporating diffusion- and perfusion-weighted MRI into a radiomics model improves diagnostic performance for pseudoprogression in glioblastoma patients.
    Kim JY; Park JE; Jo Y; Shim WH; Nam SJ; Kim JH; Yoo RE; Choi SH; Kim HS
    Neuro Oncol; 2019 Feb; 21(3):404-414. PubMed ID: 30107606
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Machine learning-based radiomic, clinical and semantic feature analysis for predicting overall survival and MGMT promoter methylation status in patients with glioblastoma.
    Lu Y; Patel M; Natarajan K; Ughratdar I; Sanghera P; Jena R; Watts C; Sawlani V
    Magn Reson Imaging; 2020 Dec; 74():161-170. PubMed ID: 32980505
    [TBL] [Abstract][Full Text] [Related]  

  • 4. 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]  

  • 5. Radiomic Analysis to Predict Outcome in Recurrent Glioblastoma Based on Multi-Center MR Imaging From the Prospective DIRECTOR Trial.
    Vils A; Bogowicz M; Tanadini-Lang S; Vuong D; Saltybaeva N; Kraft J; Wirsching HG; Gramatzki D; Wick W; Rushing E; Reifenberger G; Guckenberger M; Weller M; Andratschke N
    Front Oncol; 2021; 11():636672. PubMed ID: 33937035
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Different diagnostic values of imaging parameters to predict pseudoprogression in glioblastoma subgroups stratified by MGMT promoter methylation.
    Yoon RG; Kim HS; Paik W; Shim WH; Kim SJ; Kim JH
    Eur Radiol; 2017 Jan; 27(1):255-266. PubMed ID: 27048531
    [TBL] [Abstract][Full Text] [Related]  

  • 7. 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]  

  • 8. Multiregional radiomics features from multiparametric MRI for prediction of MGMT methylation status in glioblastoma multiforme: A multicentre study.
    Li ZC; Bai H; Sun Q; Li Q; Liu L; Zou Y; Chen Y; Liang C; Zheng H
    Eur Radiol; 2018 Sep; 28(9):3640-3650. PubMed ID: 29564594
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Combination of IVIM-DWI and 3D-ASL for differentiating true progression from pseudoprogression of Glioblastoma multiforme after concurrent chemoradiotherapy: study protocol of a prospective diagnostic trial.
    Liu ZC; Yan LF; Hu YC; Sun YZ; Tian Q; Nan HY; Yu Y; Sun Q; Wang W; Cui GB
    BMC Med Imaging; 2017 Feb; 17(1):10. PubMed ID: 28143434
    [TBL] [Abstract][Full Text] [Related]  

  • 10. 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]  

  • 11. Radiomics and MGMT promoter methylation for prognostication of newly diagnosed glioblastoma.
    Sasaki T; Kinoshita M; Fujita K; Fukai J; Hayashi N; Uematsu Y; Okita Y; Nonaka M; Moriuchi S; Uda T; Tsuyuguchi N; Arita H; Mori K; Ishibashi K; Takano K; Nishida N; Shofuda T; Yoshioka E; Kanematsu D; Kodama Y; Mano M; Nakao N; Kanemura Y
    Sci Rep; 2019 Oct; 9(1):14435. PubMed ID: 31594994
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Structural and advanced imaging in predicting MGMT promoter methylation of primary glioblastoma: a region of interest based analysis.
    Han Y; Yan LF; Wang XB; Sun YZ; Zhang X; Liu ZC; Nan HY; Hu YC; Yang Y; Zhang J; Yu Y; Sun Q; Tian Q; Hu B; Xiao G; Wang W; Cui GB
    BMC Cancer; 2018 Feb; 18(1):215. PubMed ID: 29467012
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Assessing the added value of apparent diffusion coefficient, cerebral blood volume, and radiomic magnetic resonance features for differentiation of pseudoprogression versus true tumor progression in patients with glioblastoma.
    Leone R; Meredig H; Foltyn-Dumitru M; Sahm F; Hamelmann S; Kurz F; Kessler T; Bonekamp D; Schlemmer HP; Bo Hansen M; Wick W; Bendszus M; Vollmuth P; Brugnara G
    Neurooncol Adv; 2023; 5(1):vdad016. PubMed ID: 36968291
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Pseudoprogression prediction in high grade primary CNS tumors by use of radiomics.
    Ari AP; Akkurt BH; Musigmann M; Mammadov O; Blömer DA; Kasap DNG; Henssen DJHA; Nacul NG; Sartoretti E; Sartoretti T; Backhaus P; Thomas C; Stummer W; Heindel W; Mannil M
    Sci Rep; 2022 Apr; 12(1):5915. PubMed ID: 35396525
    [TBL] [Abstract][Full Text] [Related]  

  • 15. 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]  

  • 16. Radiomic Analysis to Predict Histopathologically Confirmed Pseudoprogression in Glioblastoma Patients.
    McKenney AS; Weg E; Bale TA; Wild AT; Um H; Fox MJ; Lin A; Yang JT; Yao P; Birger ML; Tixier F; Sellitti M; Moss NS; Young RJ; Veeraraghavan H
    Adv Radiat Oncol; 2023; 8(1):100916. PubMed ID: 36711062
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Predicting survival in patients with glioblastoma using MRI radiomic features extracted from radiation planning volumes.
    Geraghty BJ; Dasgupta A; Sandhu M; Malik N; Maralani PJ; Detsky J; Tseng CL; Soliman H; Myrehaug S; Husain Z; Perry J; Lau A; Sahgal A; Czarnota GJ
    J Neurooncol; 2022 Feb; 156(3):579-588. PubMed ID: 34981301
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Radiomics signature: A potential biomarker for the prediction of MGMT promoter methylation in glioblastoma.
    Xi YB; Guo F; Xu ZL; Li C; Wei W; Tian P; Liu TT; Liu L; Chen G; Ye J; Cheng G; Cui LB; Zhang HJ; Qin W; Yin H
    J Magn Reson Imaging; 2018 May; 47(5):1380-1387. PubMed ID: 28926163
    [TBL] [Abstract][Full Text] [Related]  

  • 19. The application of decision tree model based on clinicopathological risk factors and pre-operative MRI radiomics for predicting short-term recurrence of glioblastoma after total resection: a retrospective cohort study.
    Du P; Wu X; Liu X; Chen J; Chen L; Cao A; Geng D
    Am J Cancer Res; 2023; 13(8):3449-3462. PubMed ID: 37693142
    [TBL] [Abstract][Full Text] [Related]  

  • 20. 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]  

    [Next]    [New Search]
    of 10.