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Imaging the WHO 2021 Brain Tumor Classification: Fully Automated Analysis of Imaging Features of Newly Diagnosed Gliomas.
Griessmair, Michael; Delbridge, Claire; Ziegenfeuter, Julian; Bernhardt, Denise; Gempt, Jens; Schmidt-Graf, Friederike; Kertels, Olivia; Thomas, Marie; Meyer, Hanno S; Zimmer, Claus; Meyer, Bernhard; Combs, Stephanie E; Yakushev, Igor; Wiestler, Benedikt; Metz, Marie-Christin.
Afiliação
  • Griessmair M; Department of Neuroradiology, Klinikum Rechts der Isar, TU Munich, 81675 Munich, Germany.
  • Delbridge C; Department of Pathology, Klinikum Rechts der Isar, TU Munich, 81675 Munich, Germany.
  • Ziegenfeuter J; Department of Neuroradiology, Klinikum Rechts der Isar, TU Munich, 81675 Munich, Germany.
  • Bernhardt D; Department of Radiation Oncology, Klinikum Rechts der Isar, TU Munich, 81675 Munich, Germany.
  • Gempt J; Department of Neurosurgery, Klinikum Rechts der Isar, TU Munich, 81675 Munich, Germany.
  • Schmidt-Graf F; Department of Neurosurgery, University Medical Center Hamburg-Eppendorf, 20246 Hamburg, Germany.
  • Kertels O; Department of Neurology, Klinikum Rechts der Isar, TU Munich, 81675 Munich, Germany.
  • Thomas M; Department of Neuroradiology, Klinikum Rechts der Isar, TU Munich, 81675 Munich, Germany.
  • Meyer HS; Department of Neuroradiology, Klinikum Rechts der Isar, TU Munich, 81675 Munich, Germany.
  • Zimmer C; Department of Neurosurgery, Klinikum Rechts der Isar, TU Munich, 81675 Munich, Germany.
  • Meyer B; Department of Neurosurgery, University Medical Center Hamburg-Eppendorf, 20246 Hamburg, Germany.
  • Combs SE; Department of Neuroradiology, Klinikum Rechts der Isar, TU Munich, 81675 Munich, Germany.
  • Yakushev I; Department of Neurosurgery, Klinikum Rechts der Isar, TU Munich, 81675 Munich, Germany.
  • Wiestler B; Department of Radiation Oncology, Klinikum Rechts der Isar, TU Munich, 81675 Munich, Germany.
  • Metz MC; Department of Nuclear Medicine, Klinikum Rechts der Isar, TU Munich, 81675 Munich, Germany.
Cancers (Basel) ; 15(8)2023 Apr 18.
Article em En | MEDLINE | ID: mdl-37190283
ABSTRACT

BACKGROUND:

The fifth version of the World Health Organization (WHO) classification of tumors of the central nervous system (CNS) in 2021 brought substantial changes. Driven by the enhanced implementation of molecular characterization, some diagnoses were adapted while others were newly introduced. How these changes are reflected in imaging features remains scarcely investigated. MATERIALS AND

METHODS:

We retrospectively analyzed 226 treatment-naive primary brain tumor patients from our institution who received extensive molecular characterization by epigenome-wide methylation microarray and were diagnosed according to the 2021 WHO brain tumor classification. From multimodal preoperative 3T MRI scans, we extracted imaging metrics via a fully automated, AI-based image segmentation and processing pipeline. Subsequently, we examined differences in imaging features between the three main glioma entities (glioblastoma, astrocytoma, and oligodendroglioma) and particularly investigated new entities such as astrocytoma, WHO grade 4.

RESULTS:

Our results confirm prior studies that found significantly higher median CBV (p = 0.00003, ANOVA) and lower median ADC in contrast-enhancing areas of glioblastomas, compared to astrocytomas and oligodendrogliomas (p = 0.41333, ANOVA). Interestingly, molecularly defined glioblastoma, which usually does not contain contrast-enhancing areas, also shows significantly higher CBV values in the non-enhancing tumor than common glioblastoma and astrocytoma grade 4 (p = 0.01309, ANOVA).

CONCLUSIONS:

This work provides extensive insights into the imaging features of gliomas in light of the new 2021 WHO CNS tumor classification. Advanced imaging shows promise in visualizing tumor biology and improving the diagnosis of brain tumor patients.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Contexto em Saúde: 2_ODS3 Problema de saúde: 2_cobertura_universal Tipo de estudo: Diagnostic_studies Idioma: En Revista: Cancers (Basel) Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Alemanha

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Contexto em Saúde: 2_ODS3 Problema de saúde: 2_cobertura_universal Tipo de estudo: Diagnostic_studies Idioma: En Revista: Cancers (Basel) Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Alemanha
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