Quantitative analysis of magnetic resonance images for characterization of blood-brain barrier dysfunction in dogs with brain tumors

Erez Hanael, Shelly Baruch, Orit Chai, Liron Lishitsky, Tal Blum, Kira Rapoport, Marco Ruggeri, Zahi Aizenberg, Dana Peery, Nina Meyerhoff, Holger Andreas Volk, Steven De Decker, Andrea Tipold, Wolfgang Baumgaertner, Alon Friedman, Merav Shamir*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

Abstract

Background: Blood-brain barrier (BBB) permeability can be assessed quantitatively using advanced imaging analysis. Hypothesis/Objectives: Quantification and characterization of blood-brain barrier dysfunction (BBBD) patterns in dogs with brain tumors can provide useful information about tumor biology and assist in distinguishing between gliomas and meningiomas. Animals: Seventy-eight hospitalized dogs with brain tumors and 12 control dogs without brain tumors. Methods: In a 2-arm study, images from a prospective dynamic contrast-enhanced (DCE; n = 15) and a retrospective archived magnetic resonance imaging study (n = 63) were analyzed by DCE and subtraction enhancement analysis (SEA) to quantify BBB permeability in affected dogs relative to control dogs (n = 6 in each arm). For the SEA method, 2 ranges of postcontrast intensity differences, that is, high (HR) and low (LR), were evaluated as possible representations of 2 classes of BBB leakage. BBB score was calculated for each dog and was associated with clinical characteristics and tumor location and class. Permeability maps were generated, using the slope values (DCE) or intensity difference (SEA) of each voxel, and analyzed. Results: Distinctive patterns and distributions of BBBD were identified for intra- and extra-axial tumors. At a cutoff of 0.1, LR/HR BBB score ratio yielded a sensitivity of 80% and specificity of 100% in differentiating gliomas from meningiomas. Conclusions and Clinical Importance: Blood-brain barrier dysfunction quantification using advanced imaging analyses has the potential to be used for assessment of brain tumor characteristics and behavior and, particularly, to help differentiating gliomas from meningiomas.

Original languageEnglish
Pages (from-to)606-617
Number of pages12
JournalJournal of Veterinary Internal Medicine
Volume37
Issue number2
DOIs
StatePublished - 1 Mar 2023

Bibliographical note

Publisher Copyright:
© 2023 The Authors. Journal of Veterinary Internal Medicine published by Wiley Periodicals LLC on behalf of American College of Veterinary Internal Medicine.

Keywords

  • CNS disorders
  • blood-brain barrier
  • epilepsy
  • glioma
  • meningioma
  • neurology
  • structural epilepsy

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