Literature DB >> 23238364

Differentiation of glioblastoma and primary CNS lymphomas using susceptibility weighted imaging.

Alexander Radbruch1, Benedikt Wiestler, Linda Kramp, Kira Lutz, Philipp Bäumer, Markus Weiler, Matthias Roethke, Felix Sahm, Heinz-Peter Schlemmer, Wolfgang Wick, Sabine Heiland, Martin Bendszus.   

Abstract

INTRODUCTION: Reliable differentiation between glioblastoma and primary CNS lymphoma (PCNSL) using conventional MR imaging is challenging, since both entities may show similar appearance on structural MR imaging. Here we analyzed if the appearance of intratumoural susceptibility signals (ITSS) on susceptibility weighted imaging (SWI) may differentiate between both entities. METHODS AND MATERIALS: SWI and contrast enhanced T1-weighted images were acquired from 15 patients with newly diagnosed PCNSL (14 B-cell PCNSL, 1 T-cell PCNSL) and 117 patients with newly diagnosed glioblastoma with a 3 Tesla MR. Additional phase images were available in 8 patients with PCNSL and 88 patients with glioblastoma. Appearance of ITSS was assessed by two readers on SWI and the size of the enhancing lesions on contrast enhanced T1-weighted images were measured. Furthermore it was assessed if ITSS displayed more clearly on SWI or on phase images.
RESULTS: ITSS were detected in 106 (reader 1) and 109 (reader 2) glioblastoma, respectively. Both readers identified ITSS within the T-cell PCNSL while both readers did not identify any ITSS within the 14 Bcell PCNSL. Interrarter variability as determined by Cohen κ was excellent for glioblastoma (κ=0.938) and for PCNSL (κ=1). The medium size of the enhancing lesion of the glioblastoma that did not harbour ITSS was significantly smaller than the size of the glioblastoma exhibiting ITSS (p<0.008). All identified ITSS displayed more clearly on SWI than on phase images.
CONCLUSION: Presence of ITSS differentiates reliably between glioblastoma and B-cell PCNSL and provides a fast bases for the clinical decision without causing any postprocessing work.
Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

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Year:  2012        PMID: 23238364     DOI: 10.1016/j.ejrad.2012.11.002

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


  18 in total

Review 1.  [Principles and applications of susceptibility weighted imaging].

Authors:  F T Kurz; M Freitag; H-P Schlemmer; M Bendszus; C H Ziener
Journal:  Radiologe       Date:  2016-02       Impact factor: 0.635

2.  Primary central nervous system lymphoma and atypical glioblastoma: Differentiation using radiomics approach.

Authors:  Hie Bum Suh; Yoon Seong Choi; Sohi Bae; Sung Soo Ahn; Jong Hee Chang; Seok-Gu Kang; Eui Hyun Kim; Se Hoon Kim; Seung-Koo Lee
Journal:  Eur Radiol       Date:  2018-04-06       Impact factor: 5.315

Review 3.  Introduction to Quantitative Susceptibility Mapping and Susceptibility Weighted Imaging.

Authors:  Pascal P R Ruetten; Jonathan H Gillard; Martin J Graves
Journal:  Br J Radiol       Date:  2019-07-26       Impact factor: 3.039

4.  [Application of ultrahigh-field MRI in neuro-oncology].

Authors:  A Radbruch; H-P Schlemmer
Journal:  Radiologe       Date:  2013-05       Impact factor: 0.635

Review 5.  Current Clinical Brain Tumor Imaging.

Authors:  Javier E Villanueva-Meyer; Marc C Mabray; Soonmee Cha
Journal:  Neurosurgery       Date:  2017-09-01       Impact factor: 4.654

Review 6.  Ultra-High-Field MR Neuroimaging.

Authors:  P Balchandani; T P Naidich
Journal:  AJNR Am J Neuroradiol       Date:  2014-12-18       Impact factor: 3.825

7.  Differentiation of Enhancing Glioma and Primary Central Nervous System Lymphoma by Texture-Based Machine Learning.

Authors:  P Alcaide-Leon; P Dufort; A F Geraldo; L Alshafai; P J Maralani; J Spears; A Bharatha
Journal:  AJNR Am J Neuroradiol       Date:  2017-04-27       Impact factor: 3.825

8.  Intra-tumoral susceptibility signal: a post-processing technique for objective grading of astrocytoma with susceptibility-weighted imaging.

Authors:  Tzu-Chao Chuang; Yen-Lin Chen; Wan-Pin Shui; Hsiao-Wen Chung; Shu-Shong Hsu; Ping-Hong Lai
Journal:  Quant Imaging Med Surg       Date:  2022-01

9.  High Resolution Imaging of Viscoelastic Properties of Intracranial Tumours by Multi-Frequency Magnetic Resonance Elastography.

Authors:  M Reiss-Zimmermann; K-J Streitberger; I Sack; J Braun; F Arlt; D Fritzsch; K-T Hoffmann
Journal:  Clin Neuroradiol       Date:  2014-06-12       Impact factor: 3.649

10.  Quantitative susceptibility mapping differentiates between blood depositions and calcifications in patients with glioblastoma.

Authors:  Andreas Deistung; Ferdinand Schweser; Benedikt Wiestler; Mario Abello; Matthias Roethke; Felix Sahm; Wolfgang Wick; Armin Michael Nagel; Sabine Heiland; Heinz-Peter Schlemmer; Martin Bendszus; Jürgen Rainer Reichenbach; Alexander Radbruch
Journal:  PLoS One       Date:  2013-03-21       Impact factor: 3.240

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