Magnetic resonance imaging and histological classification of intracranial meningiomas in 112 dogs

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Background: Intracranial meningiomas are the most common primary brain tumors in dogs. Classification of meningiomas by tumor grade and subtype has not been reported, and the value of magnetic resonance imaging (MRI) characteristics for predicting tumor subtype and grade has not been investigated. Hypothesis: Canine intracranial meningiomas are a heterogenous group of tumors with differing histological subtypes and grades. Prediction of histopathological classification is possible based on MRI characteristics. Animals: One hundred and twelve dogs with a histological diagnosis of intracranial meningioma. Methods: Retrospective observational study. Results: Meningiomas were overrepresented in the Golden Retriever and Boxer breeds with no sex predilection. The incidence of specific tumor grades was 56% benign (Grade I), 43% atypical (Grade II), and 1% malignant (Grade III). Grade I histological subtypes included meningothelial (43%), transitional (40%), microcystic (8%), psammomatous (6%), and angiomatous (3%). No statistically significant (P < .05) associations were found among tumor subtype or grade and any of the MRI features studied. Conclusions and Clinical Importance: Meningiomas in dogs differ from their counterparts in humans mainly in their higher incidence of atypical (Grade II) tumors observed. MRI characteristics do not allow for prediction of meningioma subtype or grade, emphasizing the necessity of histopathology for antemortem diagnosis. The higher incidence of atypical tumors in dogs may contribute to the poorer therapeutic response in dogs with meningiomas as compared with the response in humans with meningiomas.

Original languageEnglish (US)
Pages (from-to)586-595
Number of pages10
JournalJournal of Veterinary Internal Medicine
Issue number3
StatePublished - May 2008


  • Canine
  • Central nervous system
  • MRI
  • Neoplasia
  • WHO tumor classification

ASJC Scopus subject areas

  • veterinary(all)


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