Posttreatment high-grade glioma: usefulness of peak height position with semiquantitative MR perfusion histogram analysis in an entire contrast-enhanced lesion for predicting volume fraction of recurrence

Radiology. 2010 Sep;256(3):906-15. doi: 10.1148/radiol.10091461. Epub 2010 Jul 15.

Abstract

Purpose: To determine whether semiquantitative histogram analysis of the normalized cerebral blood volume (CBV) for an entire contrast material-enhanced lesion could be used to predict the volume fraction of posttreatment high-grade glioma recurrence compared with posttreatment change.

Materials and methods: The institutional review board approved this retrospective study. Informed consent was obtained. Thirty-nine patients with pathologically proved predominant tumor recurrence (tumor recurrence group, tumor fraction > or =50% [n = 14]), mixed tumor and posttreatment change (mixed group, tumor fraction > or =20% and <50% [n = 10]), and predominant posttreatment change (treatment change group, tumor fraction <20% [n = 15]) were evaluated. Histogram parameters of normalized CBV-histogram width, peak height position (PHP), and maximum value (MV)-were measured in entire contrast-enhanced lesions and used as discriminative indexes. Ordered logistic regression was used to determine independent factors for predicting the diseases of posttreatment contrast-enhanced lesions. Leave-one-out cross-validation was used to determine diagnostic accuracy.

Results: PHP was an independent predictive factor (P = .003) for differentiating contrast-enhanced lesions in patients with posttreatment gliomas. According to receiver operating characteristic curve analyses, PHP provided sensitivity of 90.2% and specificity of 91.1% for differentiating tumor recurrence from mixed and treatment change groups at an optimum threshold of 1.7 by using leave-one-out cross-validation. MV helped distinguish treatment change group from tumor recurrence and mixed groups at an optimum threshold of 2.6 (sensitivity, 96.5%; specificity, 93.1%).

Conclusion: PHP can be used to predict the volume fraction of posttreatment high-grade glioma recurrence.

MeSH terms

  • Adolescent
  • Adult
  • Aged
  • Brain Neoplasms / pathology*
  • Cerebrovascular Circulation
  • Contrast Media
  • Female
  • Glioma / pathology*
  • Humans
  • Image Interpretation, Computer-Assisted
  • Logistic Models
  • Magnetic Resonance Imaging / methods*
  • Male
  • Middle Aged
  • Neoplasm Recurrence, Local / pathology
  • ROC Curve
  • Retrospective Studies
  • Sensitivity and Specificity

Substances

  • Contrast Media