125 related articles for article (PubMed ID: 38244923)
1. Predicting histological grade in symptomatic meningioma by an objective estimation of the tumoral surface irregularity.
Delgado-López PD; Montalvo-Afonso A; Martín-Alonso J; Martín-Velasco V; Diana-Martín R; Castilla-Díez JM
Neurocirugia (Astur : Engl Ed); 2024; 35(3):113-121. PubMed ID: 38244923
[TBL] [Abstract][Full Text] [Related]
2. The meningioma surface factor: a novel approach to quantify shape irregularity on preoperative imaging and its correlation with WHO grade.
Popadic B; Scheichel F; Pinggera D; Weber M; Ungersboeck K; Kitzwoegerer M; Roetzer T; Oberndorfer S; Sherif C; Freyschlag CF; Marhold F
J Neurosurg; 2022 Jun; 136(6):1535-1541. PubMed ID: 34624861
[TBL] [Abstract][Full Text] [Related]
3. Correlation of volumetric growth and histological grade in 50 meningiomas.
Soon WC; Fountain DM; Koczyk K; Abdulla M; Giri S; Allinson K; Matys T; Guilfoyle MR; Kirollos RW; Santarius T
Acta Neurochir (Wien); 2017 Nov; 159(11):2169-2177. PubMed ID: 28791500
[TBL] [Abstract][Full Text] [Related]
4. Grading meningiomas utilizing multiparametric MRI with inclusion of susceptibility weighted imaging and quantitative susceptibility mapping.
Zhang S; Chiang GC; Knapp JM; Zecca CM; He D; Ramakrishna R; Magge RS; Pisapia DJ; Fine HA; Tsiouris AJ; Zhao Y; Heier LA; Wang Y; Kovanlikaya I
J Neuroradiol; 2020 Jun; 47(4):272-277. PubMed ID: 31136748
[TBL] [Abstract][Full Text] [Related]
5. Ultrarapid Evaluation of Meningioma Malignancy by Intraoperative Flow Cytometry.
Matsuoka G; Eguchi S; Anami H; Ishikawa T; Yamaguchi K; Nitta M; Muragaki Y; Kawamata T
World Neurosurg; 2018 Dec; 120():320-327. PubMed ID: 30144616
[TBL] [Abstract][Full Text] [Related]
6. Predicting the risk of postoperative recurrence and high-grade histology in patients with intracranial meningiomas using routine preoperative MRI.
Spille DC; Adeli A; Sporns PB; Heß K; Streckert EMS; Brokinkel C; Mawrin C; Paulus W; Stummer W; Brokinkel B
Neurosurg Rev; 2021 Apr; 44(2):1109-1117. PubMed ID: 32328854
[TBL] [Abstract][Full Text] [Related]
7. 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]
8. Meningiomas: Preoperative predictive histopathological grading based on radiomics of MRI.
Han Y; Wang T; Wu P; Zhang H; Chen H; Yang C
Magn Reson Imaging; 2021 Apr; 77():36-43. PubMed ID: 33220449
[TBL] [Abstract][Full Text] [Related]
9. Histogram analysis in predicting the grade and histological subtype of meningiomas based on diffusion kurtosis imaging.
Chen X; Lin L; Wu J; Yang G; Zhong T; Du X; Chen Z; Xu G; Song Y; Xue Y; Duan Q
Acta Radiol; 2020 Sep; 61(9):1228-1239. PubMed ID: 31986895
[TBL] [Abstract][Full Text] [Related]
10. Ki-67 index as a predictive marker of meningioma recurrence following surgical resection.
Mizrachi M; Hartley B; Saleem S; Hintz E; Ziemba Y; Li J; Goenka A; Schulder M
J Clin Neurosci; 2024 Jun; 124():15-19. PubMed ID: 38631196
[TBL] [Abstract][Full Text] [Related]
11. 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]
12. Radiomics and machine learning may accurately predict the grade and histological subtype in meningiomas using conventional and diffusion tensor imaging.
Park YW; Oh J; You SC; Han K; Ahn SS; Choi YS; Chang JH; Kim SH; Lee SK
Eur Radiol; 2019 Aug; 29(8):4068-4076. PubMed ID: 30443758
[TBL] [Abstract][Full Text] [Related]
13. The Role of Pre-Operative MRI for Prediction of High-Grade Intracranial Meningioma: A Retrospective Study.
Radeesri K; Lekhavat V
Asian Pac J Cancer Prev; 2023 Mar; 24(3):819-825. PubMed ID: 36974533
[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. Can amide proton transfer-weighted imaging differentiate tumor grade and predict Ki-67 proliferation status of meningioma?
Yu H; Wen X; Wu P; Chen Y; Zou T; Wang X; Jiang S; Zhou J; Wen Z
Eur Radiol; 2019 Oct; 29(10):5298-5306. PubMed ID: 30887206
[TBL] [Abstract][Full Text] [Related]
16. Accuracy of deep learning to differentiate the histopathological grading of meningiomas on MR images: A preliminary study.
Banzato T; Causin F; Della Puppa A; Cester G; Mazzai L; Zotti A
J Magn Reson Imaging; 2019 Oct; 50(4):1152-1159. PubMed ID: 30896065
[TBL] [Abstract][Full Text] [Related]
17. Correlation of apparent diffusion coefficient with Ki-67 proliferation index in grading meningioma.
Tang Y; Dundamadappa SK; Thangasamy S; Flood T; Moser R; Smith T; Cauley K; Takhtani D
AJR Am J Roentgenol; 2014 Jun; 202(6):1303-8. PubMed ID: 24848829
[TBL] [Abstract][Full Text] [Related]
18. Machine learning-based radiomics analysis in predicting the meningioma grade using multiparametric MRI.
Hu J; Zhao Y; Li M; Liu J; Wang F; Weng Q; Wang X; Cao D
Eur J Radiol; 2020 Oct; 131():109251. PubMed ID: 32916409
[TBL] [Abstract][Full Text] [Related]
19. Predicting meningioma grades and pathologic marker expression via deep learning.
Chen J; Xue Y; Ren L; Lv K; Du P; Cheng H; Sun S; Hua L; Xie Q; Wu R; Gong Y
Eur Radiol; 2024 May; 34(5):2997-3008. PubMed ID: 37853176
[TBL] [Abstract][Full Text] [Related]
20. Uptake and tracer kinetics of O-(2-(18)F-fluoroethyl)-L-tyrosine in meningiomas: preliminary results.
Cornelius JF; Stoffels G; Filß C; Galldiks N; Slotty P; Kamp M; el Khatib M; Hänggi D; Sabel M; Felsberg J; Steiger HJ; Coenen HH; Shah NJ; Langen KJ
Eur J Nucl Med Mol Imaging; 2015 Mar; 42(3):459-67. PubMed ID: 25331459
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]