Can MRI Really Spot Canine Meningeal Disease? A Look at Accuracy vs. Histology

Canine Meningeal Disease: Associations Between Magnetic Resonance Imaging Signs and Histologic Findings

E.K. Keenihan, B.A. Summers, F.H. David, C.R. Lamb

Background:
Meningeal disease in dogs can result from inflammatory or neoplastic conditions, and magnetic resonance imaging (MRI) is commonly used to support diagnosis. However, the correlation between MRI findings and histopathologic evidence of meningeal disease remains unclear. This study aimed to evaluate the diagnostic accuracy of various MRI sequences in identifying meningeal pathology by comparing imaging findings to histologic examination of the meninges.

Methods:
A retrospective, cross-sectional study was performed using MRI and histopathology data from 60 dogs examined between 2003 and 2011. MRI sequences included T1-weighted pre- and post-gadolinium images, subtraction images, T2-weighted images, and FLAIR sequences. Histopathologic specimens were classified into three grades: normal (0), slightly or inconsistently affected (1), and markedly affected (2). Receiver operating characteristic (ROC) analysis was conducted to evaluate diagnostic performance, and agreement with pathology was measured using weighted kappa statistics.

Results:
Histopathology identified leptomeningeal involvement in 35 dogs and pachymeningeal involvement in 16 dogs. Using relaxed criteria (grades 0–1 = normal), the area under the ROC curve (AUC) was highest for post-gadolinium T1-weighted images (0.74), followed by subtraction (0.70), T2-weighted (0.68), and FLAIR (0.56). With strict criteria (only grade 0 = normal), no sequence had an AUC significantly greater than 0.5. MRI more reliably identified pachymeningeal than leptomeningeal disease. Post-gadolinium T1-weighted and subtraction images were similarly accurate; FLAIR was the least useful. Overall, MRI had low sensitivity for mild or subtle meningeal pathology.

Limitations:
The study was retrospective and relied on archived histologic material, which may not fully represent the meninges sampled in MR images. Patient selection was biased toward dogs with severe disease due to the requirement for histopathologic diagnosis, potentially limiting generalizability. Technical issues with subtraction imaging, such as motion artifacts, may have reduced its diagnostic value.

Conclusions:
MRI has limited sensitivity for detecting meningeal disease in dogs, particularly for mild leptomeningeal changes. Post-gadolinium T1-weighted and subtraction images perform better than T2-weighted or FLAIR sequences, with the latter showing minimal diagnostic utility. Accurate diagnosis of meningeal pathology in dogs remains challenging, and histopathology remains essential for definitive assessment. Improvements in imaging protocols and further study of advanced techniques like dynamic acquisition or subvoxel registration are warranted.

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