Literature DB >> 21723681

Is diffusion-weighted imaging useful in grading and differentiating histopathological subtypes of meningiomas?

S Eser Sanverdi1, Burce Ozgen, Kader K Oguz, Melike Mut, Anil Dolgun, Figen Soylemezoglu, Aysenur Cila.   

Abstract

PURPOSE: Meningiomas are mostly benign, however atypical or malignant subtypes with more aggressive clinical course and higher recurrence rates can also be seen. The purpose of this study was to determine whether histopathological subtypes of meningiomas could be assessed preoperatively using apparent diffusion coefficient (ADC) values.
MATERIALS AND METHODS: Conventional magnetic resonance (MR) and diffusion-weighted (DW) imaging of 177 adult patients with pathologically proven meningiomas were retrospectively evaluated. Tumor size and the degree of associated edema were noted. The signal intensity of the lesions on DW imaging was evaluated and graded. Mean ADC values were obtained as the mean of measurements from three regions of interests within the mass. ADC ratios of meningioma/contralateral normal appearing subcortical parietal white matter were also calculated.
RESULTS: The histopathological analysis revealed 135 benign, 37 atypical and 5 malignant lesions. With classification according to the subtype, the mean ADC values and ratios of benign meningiomas were as 0.99±0.12×10(-3) mm(2)/s and 1.22±0.07, respectively. ADC values for atypical and malignant groups were both 0.84±0.1×10(-3) mm(2)/s. The ADC ratios were 1.05±0.1 and 0.96±0.2 for atypical and malignant subtypes, respectively. There was no statistically significant difference between the mean ADC ratios of the three subtypes (ANOVA test; P≥0.05). Gender, age of the patients and tumor size showed no statistically significant difference between the different histological groups.
CONCLUSION: DW MR imaging was not found to have any additional value in determining histological behaviour nor in differentiating histopathological subtypes of meningiomas.
Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Entities:  

Mesh:

Year:  2011        PMID: 21723681     DOI: 10.1016/j.ejrad.2011.06.031

Source DB:  PubMed          Journal:  Eur J Radiol        ISSN: 0720-048X            Impact factor:   3.528


  35 in total

1.  Relation of apparent diffusion coefficient with Ki-67 proliferation index in meningiomas.

Authors:  Ozdil Baskan; Gokalp Silav; Fatih Han Bolukbasi; Ozlem Canoz; Serdar Geyik; Ilhan Elmaci
Journal:  Br J Radiol       Date:  2015-11-05       Impact factor: 3.039

2.  Grading meningiomas utilizing multiparametric MRI with inclusion of susceptibility weighted imaging and quantitative susceptibility mapping.

Authors:  Shun Zhang; Gloria Chia-Yi Chiang; Jacquelyn Marion Knapp; Christina M Zecca; Diana He; Rohan Ramakrishna; Rajiv S Magge; David J Pisapia; Howard Alan Fine; Apostolos John Tsiouris; Yize Zhao; Linda A Heier; Yi Wang; Ilhami Kovanlikaya
Journal:  J Neuroradiol       Date:  2019-05-25       Impact factor: 3.447

Review 3.  "Dazed and diffused": making sense of diffusion abnormalities in neurologic pathologies.

Authors:  K M O'Connor; G Barest; T Moritani; O Sakai; A Mian
Journal:  Br J Radiol       Date:  2013-10-28       Impact factor: 3.039

4.  Correlation Between Aquaporin 4 Expression and Different DWI Parameters in Grade I Meningioma.

Authors:  Stefan Schob; Alexey Surov; Andreas Wienke; Hans Jonas Meyer; Rolf Peter Spielmann; Eckhard Fiedler
Journal:  Mol Imaging Biol       Date:  2017-02       Impact factor: 3.488

5.  The diagnostic value of using combined MR diffusion tensor imaging parameters to differentiate between low- and high-grade meningioma.

Authors:  Kerim Aslan; Hediye Pinar Gunbey; Leman Tomak; Lutfi Incesu
Journal:  Br J Radiol       Date:  2018-05-31       Impact factor: 3.039

6.  Diffusion-weighted imaging of skull lesions.

Authors:  Daniel T Ginat; Rajiv Mangla; Gabrielle Yeaney; Sven Ekholm
Journal:  J Neurol Surg B Skull Base       Date:  2014-03-12

7.  Diffusion Profiling via a Histogram Approach Distinguishes Low-grade from High-grade Meningiomas, Can Reflect the Respective Proliferative Potential and Progesterone Receptor Status.

Authors:  Georg Alexander Gihr; Diana Horvath-Rizea; Nikita Garnov; Patricia Kohlhof-Meinecke; Oliver Ganslandt; Hans Henkes; Hans Jonas Meyer; Karl-Titus Hoffmann; Alexey Surov; Stefan Schob
Journal:  Mol Imaging Biol       Date:  2018-08       Impact factor: 3.488

8.  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

9.  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

10.  Imaging and extent of surgical resection predict risk of meningioma recurrence better than WHO histopathological grade.

Authors:  William L Hwang; Ariel E Marciscano; Andrzej Niemierko; Daniel W Kim; Anat O Stemmer-Rachamimov; William T Curry; Fred G Barker; Robert L Martuza; Jay S Loeffler; Kevin S Oh; Helen A Shih; Mykol Larvie
Journal:  Neuro Oncol       Date:  2015-11-22       Impact factor: 12.300

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.