Detection of blood‐brain barrier dysfunction using advanced imaging methods to predict seizures in dogs with meningoencephalitis of unknown origin - Erez Hanael; Shelly Baruch; Orit Chai; Zohar Nir; Kira Rapoport; Marco Ruggeri; Itzhak Eizenberg; Dana Peery; Alon Friedman; Merav H. Shamir (Journal of Veterinary Internal Medicine, 2022)
Abstract Background The blood‐brain barrier (BBB), which separates the intravascular and neuropil compartments, characterizes the vascular bed of the brain and is essential for its proper function. Recent advances in imaging techniques have driven the development of methods for quantitative assessment of BBB permeability. Hypothesis/Objectives Permeability of the BBB can be assessed quantitatively in dogs with meningoencephalitis of unknown origin (MUO) and its status is associated with the occurrence of seizures. Animals Forty dogs with MUO and 12 dogs without MUO. Methods Retrospective, prospective cohort study. Both dynamic contrast enhancement (DCE) and subtraction enhancement analysis (SEA) methods were used to evaluate of BBB permeability in affected (DCE, n = 8; SEA, n = 32) and control dogs (DCE, n = 6; SEA, n = 6). Association between BBB dysfunction (BBBD) score and clinical characteristics was examined. In brain regions where BBBD was identified by DCE or SEA magnetic resonance imaging (MRI) analysis, immunofluorescent staining for albumin, glial fibrillary acidic protein, ionized calcium binding adaptor molecule, and phosphorylated mothers against decapentaplegic homolog 2 were performed to detect albumin extravasation, reactive astrocytes, activated microglia, and transforming growth factor beta signaling, respectively. Results Dogs with BBBD had significantly higher seizure prevalence (72% vs 19%; P = .01) when compared to MUO dogs with no BBBD. The addition of SEA to routine MRI evaluation increased the identification rate of brain pathology in dogs with MUO from 50% to 72%. Conclusions and Clinical Importance Imaging‐based assessment of BBB integrity has the potential to predict risk of seizures in dogs with MUO.