Permeability measurement using dynamic susceptibility contrast magnetic resonance imaging enhances differential diagnosis of primary central nervous system lymphoma from glioblastoma

Eur Radiol. 2019 Oct;29(10):5539-5548. doi: 10.1007/s00330-019-06097-9. Epub 2019 Mar 15.

Abstract

Objectives: To test if adding permeability measurement to perfusion obtained from dynamic susceptibility contrast MRI (DSC-MRI) improves diagnostic performance in the differentiation of primary central nervous system lymphoma (PCNSL) from glioblastoma.

Materials and methods: DSC-MRI was acquired in 145 patients with pathologically proven glioblastoma (n = 89) or PCNSL (n = 56). The permeability metrics of contrast agent extraction fraction (Ex), apparent permeability (Ka), and leakage-corrected perfusion of normalized cerebral blood volume (nCBVres) and cerebral blood flow (nCBFres) were derived from a tissue residue function. For comparison purposes, the leakage-corrected normalized CBV (nCBV) and relative permeability constant (K2) were also obtained using the established Weisskoff-Boxerman leakage correction method. The area under the receiver operating characteristics curve (AUC) and cross-validation were used to compare the diagnostic performance of the single DSC-MRI parameters with the performance obtained with the addition of permeability metrics.

Results: PCNSL demonstrated significantly higher permeability (Ex, p < .001) and lower perfusion (nCBVres, nCBFres, and nCBV, all p < .001) than glioblastoma. The combination of Ex and nCBVres showed the highest performance (AUC, 0.96; 95% confidence interval, 0.92-0.99) for differentiating PCNSL from glioblastoma, which was a significant improvement over the single perfusion (nCBV: AUC, 0.84; nCBVres: AUC, 0.84; nCBFres: AUC, 0.82; all p < .001) or Ex (AUC, 0.80; p < .001) parameters.

Conclusions: Analysis of the combined permeability and perfusion metrics obtained from a single DSC-MRI acquisition improves the diagnostic value for differentiating PCNSL from glioblastoma in comparison with single-parameter nCBV analysis.

Key points: • Permeability measurement can be calculated from DSC-MRI with a tissue residue function-based leakage correction. • Adding Exto CBV aids in the differentiation of PCNSL from glioblastoma. • CBV and Exmeasurements from DSC-MRI were highly reproducible.

Keywords: Glioblastoma; Lymphoma; Magnetic resonance imaging; Perfusion magnetic resonance imaging; Permeability.

MeSH terms

  • Adult
  • Aged
  • Brain Neoplasms / diagnostic imaging
  • Brain Neoplasms / physiopathology
  • Central Nervous System Neoplasms / diagnostic imaging*
  • Central Nervous System Neoplasms / physiopathology
  • Cerebral Blood Volume / physiology
  • Cerebrovascular Circulation / physiology
  • Contrast Media
  • Diagnosis, Differential
  • Female
  • Glioblastoma / diagnostic imaging*
  • Glioblastoma / physiopathology
  • Humans
  • Image Interpretation, Computer-Assisted / methods
  • Lymphoma, Non-Hodgkin / diagnostic imaging*
  • Lymphoma, Non-Hodgkin / physiopathology
  • Magnetic Resonance Imaging / methods
  • Male
  • Middle Aged
  • Perfusion
  • Permeability
  • ROC Curve
  • Retrospective Studies

Substances

  • Contrast Media