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Can dynamic contrast-enhanced magnetic resonance imaging combined with texture analysis differentiate malignant glioneuronal tumors from other glioblastoma?

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  • معلومة اضافية
    • Contributors:
      Plate-forme Rennaise d'Imagerie et Spectroscopie Structurale et Métabolique (PRISM); Institut National de la Recherche Agronomique (INRA)-Université de Rennes (UR)-Centre national du machinisme agricole, du génie rural, des eaux et forêts (CEMAGREF)-Structure Fédérative de Recherche en Biologie et Santé de Rennes ( Biosit : Biologie - Santé - Innovation Technologique ); Service de radiologie et imagerie médicale Rennes = Radiology Rennes; Centre Hospitalier Universitaire de Rennes CHU Rennes = Rennes University Hospital Pontchaillou; Laboratoire Traitement du Signal et de l'Image (LTSI); Université de Rennes (UR)-Institut National de la Santé et de la Recherche Médicale (INSERM); Service de neuropathologie; CRLCC Eugène Marquis (CRLCC); UNICANCER
    • بيانات النشر:
      HAL CCSD
    • الموضوع:
      2012
    • Collection:
      Institut National de la Recherche Agronomique: ProdINRA
    • نبذة مختصرة :
      International audience ; 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.
    • Relation:
      info:eu-repo/semantics/altIdentifier/pmid/22203901; inserm-00664035; https://inserm.hal.science/inserm-00664035; https://inserm.hal.science/inserm-00664035/document; https://inserm.hal.science/inserm-00664035/file/195176.pdf; PRODINRA: 317331; PUBMED: 22203901
    • الرقم المعرف:
      10.1155/2012/195176
    • الدخول الالكتروني :
      https://inserm.hal.science/inserm-00664035
      https://inserm.hal.science/inserm-00664035/document
      https://inserm.hal.science/inserm-00664035/file/195176.pdf
      https://doi.org/10.1155/2012/195176
    • Rights:
      info:eu-repo/semantics/OpenAccess
    • الرقم المعرف:
      edsbas.38D22EED