The prognostic value of the Koret CT score in dogs following traumatic brain injury

Evaluation of canine adipose-derived mesenchymal stem cells for neurological functional recovery in a rat model of traumatic brain injury

BACKGROUND

Traumatic brain injury (TBI) is a common condition in veterinary medicine that is difficult to manage.Veterinary regenerative therapy based on adipose mesenchymal stem cells seem to be an effective strategy for the treatment of traumatic brain injury. In this study, we evaluated therapeutic efficacy of canine Adipose-derived mesenchymal stem cells (AD-MSCs)in a rat TBI model, in terms of improved nerve function and anti-neuroinflammation.

RESULTS

Canine AD-MSCs promoted neural functional recovery, reduced neuronal apoptosis, and inhibited the activation of microglia and astrocytes in TBI rats. According to the results in vivo, we further investigated the regulatory mechanism of AD-MSCs on activated microglia by co-culture in vitro. Finally, we found that canine AD-MSCs promoted their polarization to the M2 phenotype, and inhibited their polarization to the M1 phenotype. What's more, AD-MSCs could reduce the migration, proliferation and Inflammatory cytokines of activated microglia, which is able to inhibit inflammation in the central system.

CONCLUSIONS

Collectively, the present study demonstrates that transplantation of canine AD-MSCs can promote functional recovery in TBI rats via inhibition of neuronal apoptosis, glial cell activation and central system inflammation, thus providing a theoretical basis for canine AD-MSCs therapy for TBI in veterinary clinic.

The deep radiomic analytics pipeline

Radiomics refers to the process of extracting useful imaging features from radiological data. Conventional radiomics like standard uptake value, intensity histograms, or phase images involve hand-crafted (manual) or automated regions of interest (computer generated), however, artificial intelligence (AI) segmentation (AI-augmented radiomics) has recently emerged. Radiomic feature extraction extends image insights beyond simply data quantitation and provides additional insights to aid semantic reporting. Deeper layers of a convolutional neural network produce more abstract radiomic features that are referred to as deep radiomics. The application of radiomics in veterinary radiology is already firmly entrenched using hand-crafted and automated computer-generated radiomic features in X-ray, nuclear medicine, CT, ultrasound, and MRI. There is an opportunity for veterinary radiology to capitalize on advances in AI, machine learning, and deep learning to enrich imaging interpretation using deep radiomic feature extraction. This manuscript aims to provide a general understanding of radiomics and deep radiomics, and to arm readers with the vernacular to progress discussion and development of deep radiomics in veterinary imaging.

CT Findings and Histological Evaluation of Red Foxes (Vulpes vulpes) with Chronic Head Trauma Injury: A Retrospective Study

Large numbers of wild animals are injured every year in road traffic accidents. Scant data are available for rescued wild carnivores, in particular for red foxes. Cases of foxes with head trauma were retrospectively considered for inclusion in this study. Clinical examination, modified Glasgow coma scale (MGCS), computed tomography (CT) examination, therapy, outcome, and post mortem findings of the brain were investigated. In all foxes, cranial vaults lesion occurred in single (67%) or multiple sites (33%). Midline shift and hydrocephalus were observed in this population. The mean survival was 290 (±176) days. In our study, we performed CT scans on average 260 days after fox rescue, and we speculate that persisting clinical signs could be attributed to TBI. In our study, only two foxes were alive at the time of writing. Other foxes were euthanized due to the severity of the clinical signs. CT scans help diagnose chronic lesions and their effect on prognostic judgment for animals released to wildlife environments.