Literature DB >> 17937223

Prediction of meningioma consistency using fractional anisotropy value measured by magnetic resonance imaging.

Hiroshi Kashimura1, Takashi Inoue, Kuniaki Ogasawara, Hiroshi Arai, Yasunari Otawara, Yoshiyuki Kanbara, Akira Ogawa.   

Abstract

OBJECT: Preoperative planning for meningiomas requires information about tumor consistency as well as location and size. In the present study the authors aimed to determine whether the fractional anisotropy (FA) value calculated on the basis of preoperative magnetic resonance (MR) diffusion tensor (DT) imaging could predict meningioma consistency.
METHODS: In 29 patients with intracranial meningiomas, MR DT imaging was performed preoperatively, and the FA values of the tumors were calculated. Tumor consistency was intraoperatively determined as hard or soft, and the histological diagnosis of the tumor was established.
RESULTS: Of the 29 tumors, 11 were classified as hard and 18 as soft. The FA values of fibroblastic meningiomas were significantly higher than those of meningothelial meningiomas (p = 0.002). The FA values of hard tumors were significantly higher than those of soft tumors (p = 0.0003). Logistic regression analysis demonstrated that the FA value was a significant independent predictor of tumor consistency (p = 0.007).
CONCLUSIONS: The FA value calculated from preoperative MR DT imaging predicts meningioma consistency.

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Year:  2007        PMID: 17937223     DOI: 10.3171/JNS-07/10/0784

Source DB:  PubMed          Journal:  J Neurosurg        ISSN: 0022-3085            Impact factor:   5.115


  18 in total

Review 1.  Predicting Meningioma Consistency on Preoperative Neuroimaging Studies.

Authors:  Mark S Shiroishi; Steven Y Cen; Benita Tamrazi; Francesco D'Amore; Alexander Lerner; Kevin S King; Paul E Kim; Meng Law; Darryl H Hwang; Orest B Boyko; Chia-Shang J Liu
Journal:  Neurosurg Clin N Am       Date:  2016-02-18       Impact factor: 2.509

Review 2.  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

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.  The link between diffusion MRI and tumor heterogeneity: Mapping cell eccentricity and density by diffusional variance decomposition (DIVIDE).

Authors:  Filip Szczepankiewicz; Danielle van Westen; Elisabet Englund; Carl-Fredrik Westin; Freddy Ståhlberg; Jimmy Lätt; Pia C Sundgren; Markus Nilsson
Journal:  Neuroimage       Date:  2016-07-20       Impact factor: 6.556

5.  Diffusion-weighted MR imaging: diagnosing atypical or malignant meningiomas and detecting tumor dedifferentiation.

Authors:  V A Nagar; J R Ye; W H Ng; Y H Chan; F Hui; C K Lee; C C T Lim
Journal:  AJNR Am J Neuroradiol       Date:  2008-03-20       Impact factor: 3.825

6.  Predicting Consistency of Meningioma by Magnetic Resonance Imaging.

Authors:  Kyle A Smith; John D Leever; Roukoz B Chamoun
Journal:  J Neurol Surg B Skull Base       Date:  2015-01-21

7.  Radiomics and machine learning may accurately predict the grade and histological subtype in meningiomas using conventional and diffusion tensor imaging.

Authors:  Yae Won Park; Jongmin Oh; Seng Chan You; Kyunghwa Han; Sung Soo Ahn; Yoon Seong Choi; Jong Hee Chang; Se Hoon Kim; Seung-Koo Lee
Journal:  Eur Radiol       Date:  2018-11-15       Impact factor: 5.315

Review 8.  MR elastography of the brain and its application in neurological diseases.

Authors:  Matthew C Murphy; John Huston; Richard L Ehman
Journal:  Neuroimage       Date:  2017-10-07       Impact factor: 6.556

9.  Quantification of microscopic diffusion anisotropy disentangles effects of orientation dispersion from microstructure: applications in healthy volunteers and in brain tumors.

Authors:  Filip Szczepankiewicz; Samo Lasič; Danielle van Westen; Pia C Sundgren; Elisabet Englund; Carl-Fredrik Westin; Freddy Ståhlberg; Jimmy Lätt; Daniel Topgaard; Markus Nilsson
Journal:  Neuroimage       Date:  2014-10-02       Impact factor: 6.556

10.  Preoperative assessment of meningioma stiffness using magnetic resonance elastography.

Authors:  Matthew C Murphy; John Huston; Kevin J Glaser; Armando Manduca; Fredric B Meyer; Giuseppe Lanzino; Jonathan M Morris; Joel P Felmlee; Richard L Ehman
Journal:  J Neurosurg       Date:  2012-10-19       Impact factor: 5.115

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