Literature DB >> 2305355

Interface between the meningioma and the brain on magnetic resonance imaging.

S Nakasu1, Y Nakasu, K Matsumura, M Matsuda, J Handa.   

Abstract

Magnetic resonance imaging of 31 meningiomas in 29 patients was retrospectively reviewed and compared with pathologic specimens in 25 tumors to investigate how magnetic resonance imaging could delineate a tumor-brain interface. The thick, collagenous connective tissue, which was seen around four tumors, was shown as a low signal intensity rim on both a T1-weighted image and a T2-weighted image. A rim of low signal intensity on a T1-weighted image and high signal intensity on a T2-weighted image most likely represented cerebrospinal fluid space: this finding was seen around eight tumors. No distinct rim could be identified in five tumors. Of these five, two tumors grew invasively into the brain. Although mixed features predominated in meningiomas, magnetic resonance imaging could well delineate a tumor-brain relationship in most of the cases.

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Mesh:

Year:  1990        PMID: 2305355     DOI: 10.1016/0090-3019(90)90019-l

Source DB:  PubMed          Journal:  Surg Neurol        ISSN: 0090-3019


  9 in total

1.  Accuracy for predicting adhesion between meningioma and the brain by using brain surface motion imaging: comparison between single and double acquisition methods.

Authors:  Toshiaki Taoka; Syuichi Yamada; Masahiko Sakamoto; Toshiaki Akashi; Toshiteru Miyasaka; Tomoko Ochi; Takeshi Wada; Masato Uchikoshi; Hiroyuki Nakase; Kimihiko Kichikawa
Journal:  Neuroradiology       Date:  2012-06-23       Impact factor: 2.804

2.  Brain surface motion imaging to predict adhesions between meningiomas and the brain surface.

Authors:  Toshiaki Taoka; Syuichi Yamada; Yuya Yamatani; Toshiaki Akashi; Toshiteru Miyasaka; Tomoko Emura; Hiroyuki Nakase; Kimihiko Kichikawa
Journal:  Neuroradiology       Date:  2010-03-24       Impact factor: 2.804

3.  Radiologic and histologic features of the T2 hyperintensity rim of meningiomas on magnetic resonance images.

Authors:  Hiroyuki Uchida; Hirofumi Hirano; F M Moinuddin; Ryosuke Hanaya; Yuko Sadamura; Hiroshi Hosoyama; Hajime Yonezawa; Hiroshi Tokimura; Hitoshi Yamahata; Kazunori Arita
Journal:  Neuroradiol J       Date:  2017-01-06

4.  Prediction of high-grade meningioma by preoperative MRI assessment.

Authors:  Yosuke Kawahara; Mitsutoshi Nakada; Yutaka Hayashi; Yutaka Kai; Yasuhiko Hayashi; Naoyuki Uchiyama; Hiroyuki Nakamura; Jun-Ichi Kuratsu; Jun-Ichiro Hamada
Journal:  J Neurooncol       Date:  2012-02-12       Impact factor: 4.130

5.  Cystic meningiomas.

Authors:  A Kulah; R Ilçayto; C Fiskeci
Journal:  Acta Neurochir (Wien)       Date:  1991       Impact factor: 2.216

6.  Slip Interface Imaging Predicts Tumor-Brain Adhesion in Vestibular Schwannomas.

Authors:  Ziying Yin; Kevin J Glaser; Armando Manduca; Jamie J Van Gompel; Michael J Link; Joshua D Hughes; Anthony Romano; Richard L Ehman; John Huston
Journal:  Radiology       Date:  2015-08-06       Impact factor: 11.105

7.  Preoperative radiologic classification of convexity meningioma to predict the survival and aggressive meningioma behavior.

Authors:  Yi Liu; Silky Chotai; Ming Chen; Shi Jin; Song-tao Qi; Jun Pan
Journal:  PLoS One       Date:  2015-03-18       Impact factor: 3.240

8.  Transformation of a meningioma with atypical imaging.

Authors:  Ashish Kumar; Chandrashekhar Deopujari; Vikram Karmarkar
Journal:  Asian J Neurosurg       Date:  2016 Jul-Sep

9.  Predicting the risk of postoperative recurrence and high-grade histology in patients with intracranial meningiomas using routine preoperative MRI.

Authors:  Dorothee Cäcilia Spille; Alborz Adeli; Peter B Sporns; Katharina Heß; Eileen Maria Susanne Streckert; Caroline Brokinkel; Christian Mawrin; Werner Paulus; Walter Stummer; Benjamin Brokinkel
Journal:  Neurosurg Rev       Date:  2020-04-23       Impact factor: 3.042

  9 in total

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