Magnetic resonance imaging pattern recognition of metabolic and neurodegenerative encephalopathies in dogs and cats

María Miguel-Garcés, Rita Gonalvez, Rodrigo Quintana, et al.

Background
The study focuses on metabolic and neurodegenerative encephalopathies in dogs and cats, which present similar magnetic resonance imaging (MRI) features. These conditions complicate diagnosis due to their overlapping clinical and imaging characteristics. The objectives were to characterize MRI features, establish pattern recognition for classifying conditions by the involvement of brain matter, and correlate these findings with existing literature.

Methods
This was a retrospective, multicentric study involving 100 cases (81 dogs, 19 cats) across 17 veterinary institutions. Inclusion criteria required confirmed diagnoses through clinical, genetic, or histopathological means and a complete high-field MRI study. Cases with incomplete data or alternative diagnoses were excluded. Imaging assessments followed a structured protocol and were analyzed by veterinary radiologists.

Results
Fifteen distinct conditions were identified, including hepatic encephalopathy, thiamine deficiency, and lysosomal storage diseases. MRI findings varied by condition:

• Hepatic encephalopathy commonly presented with forebrain and cerebellar atrophy.
  

• Thiamine deficiency involved deep grey matter nuclei.
  

• Lysosomal storage diseases showed white matter changes and severe brain atrophy. Novel findings included specific white matter involvement in myelinolysis and previously undescribed grey matter changes in certain conditions.

Limitations
The study's retrospective design and small sample sizes for some conditions limit the generalizability of the findings. Variations in MRI protocols across institutions could also impact the consistency of imaging features.

Conclusions
The study established MRI pattern recognition for various metabolic and neurodegenerative encephalopathies, aiding in the differential diagnosis of these conditions. It underscores the role of advanced imaging in veterinary neurology while highlighting the need for further research with larger cohorts.

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