Literature DB >> 12546355

Determination of histopathological tumor grade in neuroepithelial brain tumors by using spectral pattern analysis of in vivo spectroscopic data.

Sebastian Herminghaus1, Thomas Dierks, Ulrich Pilatus, Walter Möller-Hartmann, Jörg Wittsack, Gerhard Marquardt, Christoph Labisch, Heinrich Lanfermann, Wolfgang Schlote, Friedhelm E Zanella.   

Abstract

OBJECT: In this study, 1H magnetic resonance (MR) spectroscopy was prospectively tested as a reliable method for presurgical grading of neuroepithelial brain tumors.
METHODS: Using a database of tumor spectra obtained in patients with histologically confirmed diagnoses, 94 consecutive untreated patients were studied using single-voxel 1H spectroscopy (point-resolved spectroscopy; TE 135 msec, TE 135 msec, TR 1500 msec). A total of 90 tumor spectra obtained in patients with diagnostic 1H MR spectroscopy examinations were analyzed using commercially available software (MRUI/VARPRO) and classified using linear discriminant analysis as World Health Organization (WHO) Grade I/II, WHO Grade III, or WHO Grade IV lesions. In all cases, the classification results were matched with histopathological diagnoses that were made according to the WHO classification criteria after serial stereotactic biopsy procedures or open surgery. Histopathological studies revealed 30 Grade I/II tumors, 29 Grade III tumors, and 31 Grade IV tumors. The reliability of the histological diagnoses was validated considering a minimum postsurgical follow-up period of 12 months (range 12-37 months). Classifications based on spectroscopic data yielded 31 tumors in Grade I/II, 32 in Grade III, and 27 in Grade IV. Incorrect classifications included two Grade II tumors, one of which was identified as Grade III and one as Grade IV; two Grade III tumors identified as Grade II; two Grade III lesions identified as Grade IV; and six Grade IV tumors identified as Grade III. Furthermore, one glioblastoma (WHO Grade IV) was classified as WHO Grade I/II. This represents an overall success rate of 86%, and a 95% success rate in differentiating low-grade from high-grade tumors.
CONCLUSIONS: The authors conclude that in vivo 1H MR spectroscopy is a reliable technique for grading neuroepithelial brain tumors.

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Mesh:

Year:  2003        PMID: 12546355     DOI: 10.3171/jns.2003.98.1.0074

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


  14 in total

Review 1.  A systematic literature review of magnetic resonance spectroscopy for the characterization of brain tumors.

Authors:  W Hollingworth; L S Medina; R E Lenkinski; D K Shibata; B Bernal; D Zurakowski; B Comstock; J G Jarvik
Journal:  AJNR Am J Neuroradiol       Date:  2006-08       Impact factor: 3.825

Review 2.  Update on brain tumor imaging: from anatomy to physiology.

Authors:  S Cha
Journal:  AJNR Am J Neuroradiol       Date:  2006-03       Impact factor: 3.825

Review 3.  The diagnostic performance of magnetic resonance spectroscopy in differentiating high-from low-grade gliomas: A systematic review and meta-analysis.

Authors:  Qun Wang; Hui Zhang; JiaShu Zhang; Chen Wu; WeiJie Zhu; FangYe Li; XiaoLei Chen; BaiNan Xu
Journal:  Eur Radiol       Date:  2015-10-15       Impact factor: 5.315

4.  Characterization of brain tumors by MRS, DWI and Ki-67 labeling index.

Authors:  J A Calvar; F J Meli; C Romero; M L Calcagno; P Yánez; A R Martinez; H Lambre; A L Taratuto; G Sevlever
Journal:  J Neurooncol       Date:  2005-05       Impact factor: 4.130

5.  The diagnostic value of high-frequency power-based diffusion-weighted imaging in prediction of neuroepithelial tumour grading.

Authors:  Zhiye Chen; Peng Zhou; Bin Lv; Mengqi Liu; Yan Wang; Yulin Wang; Xin Lou; Qiuping Gui; Huiguang He; Lin Ma
Journal:  Eur Radiol       Date:  2017-06-12       Impact factor: 5.315

6.  Proton magnetic resonance spectroscopy predicts proliferative activity in diffuse low-grade gliomas.

Authors:  Remy Guillevin; Carole Menuel; Hugues Duffau; Michel Kujas; Laurent Capelle; Agnès Aubert; Sophie Taillibert; Ahmed Idbaih; Joan Pallud; Giovanni Demarco; Robert Costalat; Khê Hoang-Xuan; Jacques Chiras; Jean-Noel Vallée
Journal:  J Neurooncol       Date:  2007-12-28       Impact factor: 4.130

7.  Arterial spin-labeling and MR spectroscopy in the differentiation of gliomas.

Authors:  S Chawla; S Wang; R L Wolf; J H Woo; J Wang; D M O'Rourke; K D Judy; M S Grady; E R Melhem; H Poptani
Journal:  AJNR Am J Neuroradiol       Date:  2007-09-24       Impact factor: 3.825

8.  Proton MR spectroscopy in the evaluation of cerebral metabolism in patients with fibromyalgia: comparison with healthy controls and correlation with symptom severity.

Authors:  M Petrou; R E Harris; B R Foerster; S A McLean; A Sen; D J Clauw; P C Sundgren
Journal:  AJNR Am J Neuroradiol       Date:  2008-03-13       Impact factor: 3.825

Review 9.  [MR spectroscopy in brain tumors].

Authors:  P Papanagiotou; M Backens; I Q Grunwald; G Farmakis; M Politi; C Roth; W Reith
Journal:  Radiologe       Date:  2007-06       Impact factor: 0.635

10.  Predictive value of multimodality MRI using conventional, perfusion, and spectroscopy MR in anaplastic transformation of low-grade oligodendrogliomas.

Authors:  Chadi Hlaihel; Laurent Guilloton; Jacques Guyotat; Nathalie Streichenberger; Jerome Honnorat; François Cotton
Journal:  J Neurooncol       Date:  2009-08-29       Impact factor: 4.130

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