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

Rapoport, Kira; Mateo, Isidro; Peery, Dana; Mazaki‐Tovi, Michal; Klainbart, Sigal; Kelmer, Efrat; Ruggeri, Marco; Shamir, Merav H.; Chai, Orit

doi:10.1016/j.tvjl.2020.105563

Cited by 5 publications

(3 citation statements)

References 23 publications

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“…Author details 1 Zhaoqing Branch Center of Guangdong Laboratory for Lingnan Modern Agricultural Science and Technology, Zhaoqing 526000, China. 2 School of Life Science and Engineering, Foshan University, Foshan 528225, China. 3 Deja Lab, VetCell Biotechnology Company Limited, Foshan 528225, China.…”

Section: Detection Of No Releasementioning

confidence: 99%

“…Traumatic brain injury (TBI), which is a common disease in dogs with a mortality range from 18–34% [ 1 ], is induced by external forces [ 2 ], resulting in structural damage and physiological disturbance of the brain. TBI has a wide variety of external symptoms, such as ataxia or dystaxia, ocular motor dysfunction, and disequilibrium and pathological changes in the central nervous system including neuronal and glial cell damage, inflammation, brain edema, and increased intracranial pressure [ 3 ].…”

Section: Introductionmentioning

confidence: 99%

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

Jiang,

Luo,

Zhao

et al. 2024

BMC Vet Res

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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.

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Section: Detection Of No Releasementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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

Jiang,

Luo,

Zhao

et al. 2024

BMC Vet Res

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“…For example, whether manual or computer‐aided, region of interest calculation of thyroid uptake on hyperthyroid felines produces a radiomic feature that informs optimal therapy. The Koret CT score for traumatic brain injury in canines 9 is another simple example among many. There is, however, an opportunity to enrich veterinary imaging data with a broadening of radiomic applications.…”

Section: Radiomics In Veterinary Medicinementioning

confidence: 99%

The deep radiomic analytics pipeline

Currie

Rohren

2022

Vet Radiology Ultrasound

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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 computergenerated 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.

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