Revisión sistemática : uso de imágenes por difusión en RMN, para predecir sobrevida en pacientes adultos con diagnostico de glioblastoma multiforme Thesis

short description

  • Postgraduate thesis

Thesis author

  • Martínez Rodríguez, Laura Paola
  • Medina, Carlos Andrés
  • Plata Bautista, Yamid

abstract

  • introductionGlioblastoma multiforme (GBM) is the most common brain tumor with poor prognosis and low sensitivity to initial treatment. The purpose of this study was to evaluate whether Diffusion MRI (IDRM) is an early biomarker of tumor response, useful for early treatment decisions and forecast information.methodologyThe search was conducted in the databases EMBASE, CENTRAL, MEDLINE, bibliographies were also reviewed. Selected articles were observational studies (case-control, cohort, cross-section), we found no clinical trial, all participants had histopathologic diagnosis of GBM, underwent surgical resection and / or radio-chemotherapy and monitoring response to treatment with IDRM for at least 6 months. Data were independently extracted study type, participants, interventions, monitoring, outcomes (survival, progression / stable disease, death)ResultsFifteen studies met the inclusion criteria. Among the techniques employed to evaluate IDRM radiological response to treatment, were histograms of apparent diffusion coefficient (ADC values ​​compared below average and the 10th percentile of ADC, with higher values​​), generally finding that a low ADC is a strong predictor of survival and / or tumor progression. (This was significant in five studies); functional diffusion maps (FDM) (measured ADC percentage change of baseline vs. post treatment) was shown to be a strong predictor of survival in patients with tumor progression.DISCUSSIONUnfortunately, the quality of the studies was intermediate-low which makes the applicability of the studies is limited.

publication date

  • November 28, 2012 5:09 PM

keywords

  • Diffusion Magnetic Resonance Imaging/methods
  • Glioblastoma/ therapy
  • Treatment Outcome

Document Id

  • cc6cb367-10a7-4709-a999-e5fa7c3e7f3d