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: | , , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2012-01-01
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| 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. |
| format | Article |
| id | doaj-art-c26b2c87e0f0487eb55ea4bace719132 |
| institution | OA Journals |
| issn | 2090-1852 2090-1860 |
| language | English |
| publishDate | 2012-01-01 |
| publisher | Wiley |
| record_format | Article |
| 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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