The Relationship Between the Molecular Phenotypes of Brain Gliomas and the Imaging Features and Sensitivity of

Y-R Huang1, H-Q Fan1, Y-Y Kuang1

  • 1Department of Radiation Oncology, Harbin Medical University Cancer Hospital, Harbin, Heilongjiang, China.

Clinical Oncology (Royal College of Radiologists (Great Britain))
|May 31, 2024
PubMed

Insights

This review explores how advanced MRI imaging can reveal glioma molecular phenotypes, aiding in predicting treatment response to radiotherapy and chemotherapy for better brain tumor management.

Area of Science:

  • Neuro-oncology
  • Medical Imaging
  • Molecular Biology

Background:

  • Gliomas are the most common primary malignant brain tumors, comprising 80% of CNS malignancies.
  • Molecular phenotypes are crucial for glioma diagnosis, treatment planning, and prognosis assessment.
  • Tumor heterogeneity and surgical biopsy limitations hinder molecular phenotyping applications.

Purpose of the Study:

  • To review imaging characteristics of different glioma molecular phenotypes.
  • To explore the relationship between molecular phenotypes and glioma radiosensitivity and chemosensitivity.
  • To provide insights into non-invasive evaluation of glioma treatment outcomes.

Main Methods:

  • Literature review of glioma treatment and molecular typing over the past 20 years.
  • Inclusion of the latest 2020 NCCN treatment guidelines.
  • Summarization of imaging characteristics and treatment sensitivities based on molecular phenotypes.

Main Results:

  • Functional MRI offers non-invasive structural and functional information for intracranial lesions.
  • Molecular phenotype information combined with imaging can guide treatment and evaluate outcomes.
  • Different molecular phenotypes exhibit varying sensitivities to radiotherapy and chemotherapy.

Conclusions:

  • Non-invasive imaging, particularly functional MRI, is vital for glioma diagnosis and characterization.
  • Integrating molecular phenotype data with imaging enhances treatment strategy and outcome prediction.
  • Understanding the link between molecular subtypes and treatment response is key to personalized glioma therapy.

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