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MRI features as a helpful tool to predict the molecular subgroups of medulloblastoma: state of the art

Giovanna Stefania Colafati1, Ioan Paul Voicu2, Chiara Carducci3

  • 1Department of Imaging, Neuroradiology Unit, Bambino Gesù Children's Hospital, Rome, Italy.

Therapeutic Advances in Neurological Disorders
|July 7, 2018
PubMed

Insights

Magnetic resonance imaging (MRI) aids in identifying medulloblastoma subgroups, which are distinct pediatric brain tumor types. Early MRI detection of these molecular subgroups (WNT, SHH, Group 3, Group 4) can guide personalized treatment strategies.

Area of Science:

  • Pediatric neuro-oncology
  • Medical imaging
  • Molecular genetics

Background:

  • Medulloblastoma is the most common malignant pediatric brain tumor.
  • It is a heterogeneous disease comprising four distinct molecular subgroups: Wingless (WNT), Sonic Hedgehog (SHH), Group 3, and Group 4.
  • These subgroups exhibit unique genetic aberrations, age distributions, and prognoses.

Purpose of the Study:

  • To review the current state of MRI in facilitating medulloblastoma subgroup identification.
  • To summarize key MRI features associated with medulloblastoma and its molecular subgroups.
  • To discuss the correlation between MRI findings and molecular characteristics.

Main Methods:

  • Review of existing literature on MRI and medulloblastoma molecular subgroups.
  • Analysis of MRI features indicative of specific medulloblastoma subtypes.
  • Synthesis of information on molecular characterization of medulloblastoma.

Main Results:

  • MRI is a crucial tool for medulloblastoma diagnosis, surgical guidance, and follow-up.
  • Several studies suggest MRI can effectively detect medulloblastoma molecular subgroups.
  • Specific MRI features correlate with medulloblastoma subtypes and molecular classifications.

Conclusions:

  • Early identification of medulloblastoma subgroups via MRI can significantly impact treatment decisions.
  • MRI shows promise as a non-invasive method for predicting medulloblastoma molecular subgroups.
  • Continued research integrating advanced MRI techniques and molecular data is essential.
Keywords:
MRIchildhood brain cancermedulloblastomamolecular characterizationmolecular subgroupspediatric brain tumors

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