Literature DB >> 27012379

Predicting Meningioma Consistency on Preoperative Neuroimaging Studies.

Mark S Shiroishi1, Steven Y Cen2, Benita Tamrazi3, Francesco D'Amore2, Alexander Lerner2, Kevin S King2, Paul E Kim2, Meng Law2, Darryl H Hwang2, Orest B Boyko2, Chia-Shang J Liu2.   

Abstract

This article provides an overview of the neuroimaging literature focused on preoperative prediction of meningioma consistency. A validated, noninvasive neuroimaging method to predict tumor consistency can provide valuable information regarding neurosurgical planning and patient counseling. Most of the neuroimaging literature indicates conventional MRI using T2-weighted imaging may be helpful to predict meningioma consistency; however, further rigorous validation is necessary. Much less is known about advanced MRI techniques, such as diffusion MRI, MR elastography (MRE), and MR spectroscopy. Of these methods, MRE and diffusion tensor imaging appear particularly promising.
Copyright © 2016 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Consistency; Firmness; MRI; Meningioma; Minimally invasive neurosurgery; Neurosurgical planning; Prediction; Texture

Mesh:

Year:  2016        PMID: 27012379      PMCID: PMC4936899          DOI: 10.1016/j.nec.2015.11.007

Source DB:  PubMed          Journal:  Neurosurg Clin N Am        ISSN: 1042-3680            Impact factor:   2.509


  41 in total

1.  Magnetization transfer in MRI: a review.

Authors:  R M Henkelman; G J Stanisz; S J Graham
Journal:  NMR Biomed       Date:  2001-04       Impact factor: 4.044

2.  Prediction of hard meningiomas: quantitative evaluation based on the magnetic resonance signal intensity.

Authors:  Keita Watanabe; Shingo Kakeda; Junkoh Yamamoto; Satoru Ide; Norihiro Ohnari; Shigeru Nishizawa; Yukunori Korogi
Journal:  Acta Radiol       Date:  2015-03-29       Impact factor: 1.990

3.  Predictors of meningioma consistency: A study in 243 consecutive cases.

Authors:  Bunpot Sitthinamsuwan; Inthira Khampalikit; Sarun Nunta-aree; Prajak Srirabheebhat; Teerapol Witthiwej; Akkapong Nitising
Journal:  Acta Neurochir (Wien)       Date:  2012-06-29       Impact factor: 2.216

Review 4.  Meningiomas involving the clivus: a six-year experience with 41 patients.

Authors:  L N Sekhar; P J Jannetta; L E Burkhart; J E Janosky
Journal:  Neurosurgery       Date:  1990-11       Impact factor: 4.654

Review 5.  Imaging of brain tumors: MR spectroscopy and metabolic imaging.

Authors:  Alena Horská; Peter B Barker
Journal:  Neuroimaging Clin N Am       Date:  2010-08       Impact factor: 2.264

6.  Higher-Resolution Magnetic Resonance Elastography in Meningiomas to Determine Intratumoral Consistency.

Authors:  Joshua D Hughes; Nikoo Fattahi; J Van Gompel; Arvin Arani; Fredric Meyer; Giuseppe Lanzino; Michael J Link; Richard Ehman; John Huston
Journal:  Neurosurgery       Date:  2015-10       Impact factor: 4.654

7.  Pterional surgery of meningiomas of the tuberculum sellae and planum sphenoidale: surgical results with special consideration of ophthalmological and endocrinological outcomes.

Authors:  Rudolf Fahlbusch; Werner Schott
Journal:  J Neurosurg       Date:  2002-02       Impact factor: 5.115

8.  Comparison of consistency of meningiomas and CT appearances.

Authors:  B Kendall; P Pullicino
Journal:  Neuroradiology       Date:  1979-10-31       Impact factor: 2.804

9.  Meningiomas: correlation between MRI characteristics and operative findings including consistency.

Authors:  Y Suzuki; T Sugimoto; M Shibuya; K Sugita; S J Patel
Journal:  Acta Neurochir (Wien)       Date:  1994       Impact factor: 2.216

10.  Diffusion tensor magnetic resonance imaging for predicting the consistency of intracranial meningiomas.

Authors:  Rossana Romani; Wei-Jun Tang; Ying Mao; Dai-Jun Wang; Hai-Liang Tang; Feng-Ping Zhu; Xiao-Ming Che; Ye Gong; Kang Zheng; Ping Zhong; Shi-Qi Li; Wei-Min Bao; Christian Benner; Jing-Song Wu; Liang-Fu Zhou
Journal:  Acta Neurochir (Wien)       Date:  2014-07-08       Impact factor: 2.216

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  6 in total

Review 1.  Can MRI predict meningioma consistency?: a correlation with tumor pathology and systematic review.

Authors:  Amy Yao; Margaret Pain; Priti Balchandani; Raj K Shrivastava
Journal:  Neurosurg Rev       Date:  2016-11-21       Impact factor: 3.042

2.  Imaging and diagnostic advances for intracranial meningiomas.

Authors:  Raymond Y Huang; Wenya Linda Bi; Brent Griffith; Timothy J Kaufmann; Christian la Fougère; Nils Ole Schmidt; Jöerg C Tonn; Michael A Vogelbaum; Patrick Y Wen; Kenneth Aldape; Farshad Nassiri; Gelareh Zadeh; Ian F Dunn
Journal:  Neuro Oncol       Date:  2019-01-14       Impact factor: 12.300

Review 3.  Utility of preoperative meningioma consistency measurement with magnetic resonance elastography (MRE): a review.

Authors:  Alexander G Chartrain; Mehmet Kurt; Amy Yao; Rui Feng; Kambiz Nael; J Mocco; Joshua B Bederson; Priti Balchandani; Raj K Shrivastava
Journal:  Neurosurg Rev       Date:  2017-05-31       Impact factor: 3.042

4.  Relationship between Shear Stiffness Measured by MR Elastography and Perfusion Metrics Measured by Perfusion CT of Meningiomas.

Authors:  T Takamura; U Motosugi; M Ogiwara; Y Sasaki; K J Glaser; R L Ehman; H Kinouchi; H Onishi
Journal:  AJNR Am J Neuroradiol       Date:  2021-05-13       Impact factor: 4.966

Review 5.  REVIEW: MR elastography of brain tumors.

Authors:  Adomas Bunevicius; Katharina Schregel; Ralph Sinkus; Alexandra Golby; Samuel Patz
Journal:  Neuroimage Clin       Date:  2019-11-23       Impact factor: 4.881

6.  Preoperative Prediction of Meningioma Consistency via Machine Learning-Based Radiomics.

Authors:  Yixuan Zhai; Dixiang Song; Fengdong Yang; Yiming Wang; Xin Jia; Shuxin Wei; Wenbin Mao; Yake Xue; Xinting Wei
Journal:  Front Oncol       Date:  2021-05-26       Impact factor: 6.244

  6 in total

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