Prospective glioma grading using single-dose dynamic contrast-enhanced perfusion MRI

K K Jain1, P Sahoo2, R Tyagi1

  • 1Department of Radiology and Imaging, Fortis Memorial Research Institute, Gurgaon, India.

Clinical Radiology
|July 9, 2015
PubMed
Abstract

Insights

Single-dose dynamic contrast-enhanced MRI effectively grades gliomas with high sensitivity and specificity. This method correlates well with histopathology, offering a reliable tool for brain tumor evaluation.

Area of Science:

  • Neuroradiology
  • Oncology
  • Medical Imaging

Background:

  • Glioma grading is crucial for treatment planning and prognosis.
  • Accurate grading often relies on histopathology, which can be invasive.
  • Dynamic contrast-enhanced (DCE) perfusion MRI offers a non-invasive method for assessing tumor characteristics.

Purpose of the Study:

  • To assess the sensitivity and specificity of single-dose DCE perfusion MRI for glioma grading.
  • To correlate relative cerebral blood volume (rCBV) values with histopathological markers (mitotic and Ki-67 indexes).
  • To evaluate the efficacy of a single-dose contrast protocol for glioma grading.

Main Methods:

  • 53 patients with histologically confirmed gliomas underwent single-dose DCE-perfusion MRI.
  • Gliomas were prospectively graded into low and high grade using an rCBV cutoff value of 3.
  • Sensitivity, specificity, mitotic index, and Ki-67 index were calculated.

Main Results:

  • Single-dose DCE-MRI demonstrated high sensitivity (97.22%) and specificity (100%) for glioma grading.
  • A significant correlation was observed between rCBV values and mitotic/Ki-67 indexes when combining low- and high-grade tumors.
  • The single-dose protocol proved effective for differentiating glioma grades.

Conclusions:

  • Single-dose DCE-perfusion MRI is a highly sensitive and specific tool for glioma grading.
  • This method is as effective as double-dose protocols and can be integrated into routine brain tumor imaging protocols.
  • DCE-MRI provides valuable non-invasive data for glioma evaluation.

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