BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

153 related articles for article (PubMed ID: 29682029)

  • 1. Meningioma Consistency: Correlation Between Magnetic Resonance Imaging Characteristics, Operative Findings, and Histopathological Features.
    Alyamany M; Alshardan MM; Jamea AA; ElBakry N; Soualmi L; Orz Y
    Asian J Neurosurg; 2018; 13(2):324-328. PubMed ID: 29682029
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Meningioma consistency prediction utilizing tumor to cerebellar peduncle intensity on T2-weighted magnetic resonance imaging sequences: TCTI ratio.
    Smith KA; Leever JD; Hylton PD; Camarata PJ; Chamoun RB
    J Neurosurg; 2017 Jan; 126(1):242-248. PubMed ID: 27058200
    [TBL] [Abstract][Full Text] [Related]  

  • 3. The Predictive Value of Conventional Magnetic Resonance Imaging Sequences on Operative Findings and Histopathology of Intracranial Meningiomas: A Prospective Study.
    Karthigeyan M; Dhandapani S; Salunke P; Singh P; Radotra BD; Gupta SK
    Neurol India; 2019; 67(6):1439-1445. PubMed ID: 31857531
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Supratentorial Meningioma Consistency Prediction Utilizing Tumor to Cerebellar Peduncle Intensity on T1 and T2-Weighted and Fluid Attenuated Inversion Recovery Magnetic Resonance Imaging Sequences.
    Rabiee S; Kankam SB; Shafizadeh M; Ahmadi M; Khoshnevisan A; Hashemi A
    World Neurosurg; 2023 Feb; 170():e180-e187. PubMed ID: 36328167
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Benefits of Combined MRI Sequences in Meningioma Consistency Prediction: A Prospective Study of 287 Consecutive Patients.
    Limpastan K; Unsrisong K; Vaniyapong T; Norasetthada T; Watcharasaksilp W; Jetjumnong C
    Asian J Neurosurg; 2022 Dec; 17(4):614-620. PubMed ID: 36570751
    [No Abstract]   [Full Text] [Related]  

  • 6. Prediction of hard meningiomas: quantitative evaluation based on the magnetic resonance signal intensity.
    Watanabe K; Kakeda S; Yamamoto J; Ide S; Ohnari N; Nishizawa S; Korogi Y
    Acta Radiol; 2016 Mar; 57(3):333-40. PubMed ID: 25824207
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Diffusion tensor magnetic resonance imaging for predicting the consistency of intracranial meningiomas.
    Romani R; Tang WJ; Mao Y; Wang DJ; Tang HL; Zhu FP; Che XM; Gong Y; Zheng K; Zhong P; Li SQ; Bao WM; Benner C; Wu JS; Zhou LF
    Acta Neurochir (Wien); 2014 Oct; 156(10):1837-45. PubMed ID: 25002281
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Predicting Consistency of Meningioma by Magnetic Resonance Imaging.
    Smith KA; Leever JD; Chamoun RB
    J Neurol Surg B Skull Base; 2015 Jun; 76(3):225-9. PubMed ID: 26225306
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Multi-parametric qualitative and quantitative MRI assessment as predictor of histological grading in previously treated meningiomas.
    Sacco S; Ballati F; Gaetani C; Lomoro P; Farina LM; Bacila A; Imparato S; Paganelli C; Buizza G; Iannalfi A; Baroni G; Valvo F; Bastianello S; Preda L
    Neuroradiology; 2020 Nov; 62(11):1441-1449. PubMed ID: 32583368
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Application of magnetic resonance fingerprinting to differentiate grade I transitional and fibrous meningiomas from meningothelial meningiomas.
    Zhang R; Shen Y; Bai Y; Zhang X; Wei W; Lin R; Feng Q; Wang M; Zhang M; Nittka M; Koerzdoerfer G; Wang M
    Quant Imaging Med Surg; 2021 Apr; 11(4):1447-1457. PubMed ID: 33816181
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Predictors of meningioma consistency: A study in 243 consecutive cases.
    Sitthinamsuwan B; Khampalikit I; Nunta-aree S; Srirabheebhat P; Witthiwej T; Nitising A
    Acta Neurochir (Wien); 2012 Aug; 154(8):1383-9. PubMed ID: 22743797
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Dynamic susceptibility contrast and dynamic contrast-enhanced MRI characteristics to distinguish microcystic meningiomas from traditional Grade I meningiomas and high-grade gliomas.
    Hussain NS; Moisi MD; Keogh B; McCullough BJ; Rostad S; Newell D; Gwinn R; Foltz G; Mayberg M; Aguedan B; Good V; Fouke SJ
    J Neurosurg; 2017 Apr; 126(4):1220-1226. PubMed ID: 27285539
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Magnetic Resonance Fingerprinting for Preoperative Meningioma Consistency Prediction.
    Bai Y; Zhang R; Zhang X; Wang X; Nittka M; Koerzdoerfer G; Gong Q; Wang M
    Acad Radiol; 2022 Aug; 29(8):e157-e165. PubMed ID: 34750066
    [TBL] [Abstract][Full Text] [Related]  

  • 14. 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]  

  • 15. Are there reliable multiparametric MRI criteria for differential diagnosis between intracranial meningiomas and solitary intracranial dural metastases?
    Wu H; Beylerli O; Gareev I; Beilerli A; Ilyasova T; Talybov R; Sufianov A; Guo X
    Oncol Lett; 2023 Aug; 26(2):350. PubMed ID: 37427340
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Histogram analysis of tensor-valued diffusion MRI in meningiomas: Relation to consistency, histological grade and type.
    Brabec J; Szczepankiewicz F; Lennartsson F; Englund E; Pebdani H; Bengzon J; Knutsson L; Westin CF; Sundgren PC; Nilsson M
    Neuroimage Clin; 2022; 33():102912. PubMed ID: 34922122
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Use of preoperative magnetic resonance imaging T1 and T2 sequences to determine intraoperative meningioma consistency.
    Hoover JM; Morris JM; Meyer FB
    Surg Neurol Int; 2011; 2():142. PubMed ID: 22059137
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Correlation between magnetic resonance imaging grading and pathological grading in meningioma.
    Lin BJ; Chou KN; Kao HW; Lin C; Tsai WC; Feng SW; Lee MS; Hueng DY
    J Neurosurg; 2014 Nov; 121(5):1201-8. PubMed ID: 25148010
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Predicting the consistency of intracranial meningiomas using apparent diffusion coefficient maps derived from preoperative diffusion-weighted imaging.
    Miyoshi K; Wada T; Uwano I; Sasaki M; Saura H; Fujiwara S; Takahashi F; Tsushima E; Ogasawara K
    J Neurosurg; 2020 Nov; 135(3):969-976. PubMed ID: 33186907
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Application of MAGnetic resonance imaging compilation in acute ischemic stroke.
    Wang Q; Wang G; Sun Q; Sun DH
    World J Clin Cases; 2021 Dec; 9(35):10828-10837. PubMed ID: 35047594
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 8.