Can Dynamic Contrast-Enhanced Magnetic Resonance Imaging Combined with Texture Analysis Differentiate Malignant Glioneuronal Tumors from Other Glioblastoma?

An interesting approach has been proposed to differentiate malignant glioneuronal tumors (MGNTs) as a subclass of the WHO grade III and IV malignant gliomas. MGNT histologically resemble any WHO grade III or IV glioma but have a different biological behavior, presenting a survival twice longer as WH...

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Main Authors: Pierre-Antoine Eliat, Damien Olivié, Stephan Saïkali, Béatrice Carsin, Hervé Saint-Jalmes, Jacques D. de Certaines
Format: Article
Language:English
Published: Wiley 2012-01-01
Series:Neurology Research International
Online Access:http://dx.doi.org/10.1155/2012/195176
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author Pierre-Antoine Eliat
Damien Olivié
Stephan Saïkali
Béatrice Carsin
Hervé Saint-Jalmes
Jacques D. de Certaines
author_facet Pierre-Antoine Eliat
Damien Olivié
Stephan Saïkali
Béatrice Carsin
Hervé Saint-Jalmes
Jacques D. de Certaines
author_sort Pierre-Antoine Eliat
collection DOAJ
description An interesting approach has been proposed to differentiate malignant glioneuronal tumors (MGNTs) as a subclass of the WHO grade III and IV malignant gliomas. MGNT histologically resemble any WHO grade III or IV glioma but have a different biological behavior, presenting a survival twice longer as WHO glioblastomas and a lower occurrence of metastases. However, neurofilament protein immunostaining was required for identification of MGNT. Using two complementary methods, dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and texture analysis (MRI-TA) from the same acquisition process, the challenge is to in vivo identify MGNT and demonstrate that MRI postprocessing could contribute to a better typing and grading of glioblastoma. Results are obtained on a preliminary group of 19 patients a posteriori selected for a blind investigation of DCE T1-weighted and TA at 1.5 T. The optimal classification (0/11 misclassified MGNT) is obtained by combining the two methods, DCE-MRI and MRI-TA.
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series Neurology Research International
spelling doaj-art-c26b2c87e0f0487eb55ea4bace7191322025-08-20T02:19:02ZengWileyNeurology Research International2090-18522090-18602012-01-01201210.1155/2012/195176195176Can Dynamic Contrast-Enhanced Magnetic Resonance Imaging Combined with Texture Analysis Differentiate Malignant Glioneuronal Tumors from Other Glioblastoma?Pierre-Antoine Eliat0Damien Olivié1Stephan Saïkali2Béatrice Carsin3Hervé Saint-Jalmes4Jacques D. de Certaines5PRISM, IFR 140, Biogenouest, Université de Rennes 1, Campus de Villejean, 35043 Rennes, FranceLTSI, INSERM U642, Université de Rennes 1, 35000 Rennes, FranceDepartment of Neuropathology, CHU Rennes, 35000 Rennes, FranceDepartment of Radiology, CHU Rennes, 35000 Rennes, FrancePRISM, IFR 140, Biogenouest, Université de Rennes 1, Campus de Villejean, 35043 Rennes, FrancePRISM, IFR 140, Biogenouest, Université de Rennes 1, Campus de Villejean, 35043 Rennes, FranceAn interesting approach has been proposed to differentiate malignant glioneuronal tumors (MGNTs) as a subclass of the WHO grade III and IV malignant gliomas. MGNT histologically resemble any WHO grade III or IV glioma but have a different biological behavior, presenting a survival twice longer as WHO glioblastomas and a lower occurrence of metastases. However, neurofilament protein immunostaining was required for identification of MGNT. Using two complementary methods, dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and texture analysis (MRI-TA) from the same acquisition process, the challenge is to in vivo identify MGNT and demonstrate that MRI postprocessing could contribute to a better typing and grading of glioblastoma. Results are obtained on a preliminary group of 19 patients a posteriori selected for a blind investigation of DCE T1-weighted and TA at 1.5 T. The optimal classification (0/11 misclassified MGNT) is obtained by combining the two methods, DCE-MRI and MRI-TA.http://dx.doi.org/10.1155/2012/195176
spellingShingle Pierre-Antoine Eliat
Damien Olivié
Stephan Saïkali
Béatrice Carsin
Hervé Saint-Jalmes
Jacques D. de Certaines
Can Dynamic Contrast-Enhanced Magnetic Resonance Imaging Combined with Texture Analysis Differentiate Malignant Glioneuronal Tumors from Other Glioblastoma?
Neurology Research International
title Can Dynamic Contrast-Enhanced Magnetic Resonance Imaging Combined with Texture Analysis Differentiate Malignant Glioneuronal Tumors from Other Glioblastoma?
title_full Can Dynamic Contrast-Enhanced Magnetic Resonance Imaging Combined with Texture Analysis Differentiate Malignant Glioneuronal Tumors from Other Glioblastoma?
title_fullStr Can Dynamic Contrast-Enhanced Magnetic Resonance Imaging Combined with Texture Analysis Differentiate Malignant Glioneuronal Tumors from Other Glioblastoma?
title_full_unstemmed Can Dynamic Contrast-Enhanced Magnetic Resonance Imaging Combined with Texture Analysis Differentiate Malignant Glioneuronal Tumors from Other Glioblastoma?
title_short Can Dynamic Contrast-Enhanced Magnetic Resonance Imaging Combined with Texture Analysis Differentiate Malignant Glioneuronal Tumors from Other Glioblastoma?
title_sort can dynamic contrast enhanced magnetic resonance imaging combined with texture analysis differentiate malignant glioneuronal tumors from other glioblastoma
url http://dx.doi.org/10.1155/2012/195176
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