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

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.

An Illustrated Scoping Review of the Magnetic Resonance Imaging Characteristics of Canine and Feline Brain Tumors

“…The BBBD score was the percentage of positive voxels representing permeability and was determined in a (LR) low range (mean of PID in temporal muscle plus 1 SD) and a (HR) high range (mean PID in temporal muscle plus 2 SD). Better differentiation of tumor class (88% extra-axial and 90% intra-axial) was achieved using HR, and a significant correlation between tumor size and BBBD score was observed [88]. HT BBBD score alone did not differ significantly between the two tumor classes.…”

“…The advantage of SEA is that it is less technically and computationally demanding than DCE-MRI and can be readily performed on most open-source and proprietary image analysis software platforms. A two-armed study prospectively evaluated DCE-MRI and SEA and retrospectively the SEA of canine brain tumors [88]. Although the retrospective arm of the study included some histologically confirmed tumors, this was not a strict inclusion criterion, and no dogs in the prospective study arm had pathologically confirmed tumors, so this study was ultimately excluded from data extraction.…”

“…Although the retrospective arm of the study included some histologically confirmed tumors, this was not a strict inclusion criterion, and no dogs in the prospective study arm had pathologically confirmed tumors, so this study was ultimately excluded from data extraction. However, it is summarized here as representing one of the few investigations of DCE-MRI for brain tumors [88].…”

“…To determine the SEA, the percentage of intensity difference (PID) was measured and compared to a temporal muscle reference [88]. The BBBD score was the percentage of positive voxels representing permeability and was determined in a (LR) low range (mean of PID in temporal muscle plus 1 SD) and a (HR) high range (mean PID in temporal muscle plus 2 SD).…”

“…LR-BBBD score and LR/HR ratio were significantly higher in gliomas than in meningiomas. A sensitivity of 80% and specificity of 100% were calculated for the ability of the SEA LR/HR ratio to distinguish between meningiomas and gliomas (AUC, 0.95 [CI, 0.87-1]) [88].…”