Semi-quantitative evaluation of brain gliomas in adults: A focus on neuropathological characteristics

Gac Med Mex. 2019;155(5):439-446. doi: 10.24875/GMM.M20000329.

Abstract

Introduction: Gliomas are neoplasms with high recurrence and mortality. Due to the difficulty to apply the World Health Organization (2016) classification, developing countries continue to use histological evaluation to diagnose and classify these neoplasms.

Objective: To develop a semi-quantitative scale to numerically grade gliomas by its morphological characteristics.

Method: A cohort of patients with gliomas was assessed and followed for 36 months. Tumor tissue sections were analyzed and graded, including aspects such as cell line, cellularity, nuclear pleomorphism, mitosis, endothelial hyperplasia, hypoxic changes, apoptotic bodies, necrosis, hemorrhage and proliferation index.

Results: 58 cases were analyzed. Low-grade gliomas median score was 12 points (9 and 13.5 for percentiles 25 and 75, respectively), whereas for high-grade gliomas it was 17 points (16 and 20.5 for percentiles 25 and 75, respectively) (p < 0.0001). Thirty-six-month survival of patients with low (13/17) and high grade gliomas (6/41) was also significantly different (p < 0.0001).

Conclusions: The semi-quantitative morphological scale allows an objective evaluation of gliomas, with an adequate correlation between the score, tumor grade and survival time.

Keywords: Glioblastoma; Low-grade glioma; Neuropathological assessment; Semi-quantitative grading.

MeSH terms

  • Adult
  • Astrocytoma / mortality
  • Astrocytoma / pathology
  • Brain Neoplasms / classification
  • Brain Neoplasms / mortality
  • Brain Neoplasms / pathology*
  • Cohort Studies
  • Ependymoma / mortality
  • Ependymoma / pathology
  • Female
  • Glioblastoma / mortality
  • Glioblastoma / pathology
  • Glioma / classification
  • Glioma / mortality
  • Glioma / pathology*
  • Humans
  • Male
  • Middle Aged
  • Neoplasm Grading
  • Oligodendroglioma / mortality
  • Oligodendroglioma / pathology
  • Survival Analysis