Search Results (228)

Myocardial calcification is an uncommon complication associated with end-stage chronic kidney disease (CKD) in feline patients. This report describes the clinical and multimodal imaging features of metastatic calcification in a 10-year-old castrated male mixed-breed cat. The patient presented with dyspnea and anorexia, and was diagnosed with IRIS Stage 4 CKD. Laboratory findings revealed severe hyperphosphatemia and an elevated calcium–phosphorus product (CPP) of 135 mg²/dL², based on total calcium. This value significantly exceeds 70 mg²/dL², a threshold associated with a high probability of inducing soft tissue mineralization. Echocardiography revealed extensive hyperechoic foci with posterior acoustic shadowing in the interventricular septum and left ventricular wall. Functional assessment demonstrated a restrictive diastolic filling pattern, suggesting increased myocardial stiffness and congestive heart failure. Computed tomography (CT) further visualized systemic involvement, showing diffuse, amorphous calcifications (400–900 HU) in the myocardium, multifocal aortic wall, and extracardiac tissues. Despite intensive treatment with diuretics and renal support, the patient was euthanized eight days later due to progressive renal failure. This case illustrates that the interaction between metastatic calcification and uremic cardiomyopathy (UC) can result in refractory heart failure, underscoring the value of combined echocardiography and CT in evaluating end-stage renal disease. Full article

Canine Cognitive Dysfunction Syndrome (CCDS) is a progressive neurodegenerative disease affecting older dogs that shares many pathological mechanisms with human Alzheimer’s disease (AD). Although it is common in geriatric dogs, CCDS is often underdiagnosed in veterinary medicine. Both CCDS and AD involve a gradual decline in cognitive functions such as memory, learning and executive abilities. From a pathological perspective, dogs with CCDS show brain changes similar to those seen in AD, including cerebral atrophy, loss of neurons and accumulation of amyloid-beta plaques. CCDS is diagnosed by exclusion, meaning that other medical or neurological conditions that could cause similar behavioural signs must first be ruled out. Clinical evaluation mainly relies on structured questionnaires completed by owners. Magnetic resonance imaging is used to confirm cerebral atrophy and, at the same time, to exclude other brain disorders, such as cerebrovascular accidents and neoplasia. Current research focuses on identifying fluid biomarkers, such as amyloid-beta, neurofilament light chain and glial fibrillary acidic protein, to support an early and objective diagnosis. The most effective management combines pharmacological therapy, targeted nutrition and non-pharmacological strategies, including environmental enrichment and behavioural support. Early intervention, ideally during mild cognitive impairment, is crucial to slow disease progression and maintain quality of life. Full article

Plasma cell neoplasia is uncommon in cats, and multicentric nodal-predominant involvement has not been well characterized. This report describes a multicentric round cell neoplasia with plasmacytic differentiation in a 14-year-old Domestic Shorthair cat, emphasizing multimodal imaging features and treatment response. Contrast-enhanced computed tomography and magnetic resonance imaging were performed for staging and longitudinal assessment. Cytomorphology supported plasmacytic differentiation, and flow cytometry did not demonstrate an immunophenotype consistent with conventional B- or T-cell lymphoma. Because histopathology, immunohistochemistry, bone marrow evaluation, and assessment for monoclonal gammopathy were not performed, definitive classification was not possible; however, cytomorphology supported plasmacytic differentiation, with plasma cell neoplasia remaining an important diagnostic consideration. A hypofractionated radiotherapy protocol (36 Gy in six fractions) combined with systemic chemotherapy was administered. Serial imaging demonstrated complete radiologic resolution of the irradiated mass, whereas non-irradiated presumed nodal lesions progressed and an extradural spinal lesion subsequently developed. These findings highlight the capacity of round cell neoplasia with plasmacytic differentiation to mimic lymphoma on imaging and illustrate the dissociation between effective local control and ongoing systemic progression. Full article

Pulmonary hypertension is a progressive syndrome characterised by pulmonary vascular dysfunction, inflammation, maladaptive remodelling, and progressive right-ventricular strain. Translational progress remains limited because experimental models reproduce only selected aspects of the complexity of human disease. This narrative review evaluates naturally occurring canine disease as a comparative and spontaneous model of human pulmonary hypertension within a One Health framework. To achieve this, we synthesise recent human and veterinary literature, international consensus statements, and key registry and imaging studies. We outline current human definitions and diagnostic pathways based on right-heart catheterisation, together with the veterinary probability-based approach centred on echocardiography; compare epidemiology across species; and summarise contemporary mechanisms spanning vascular dysfunction, immune and metabolic signalling, and right-ventricular adaptation. We then examine canine conditions that parallel major human pulmonary hypertension phenotypes, including left-heart disease due to myxomatous mitral valve degeneration, fibrotic interstitial lung disease in West Highland White Terriers, sleep-related airway obstruction in brachycephalic breeds, and rare venous and capillary disorders. When combined, these spontaneous models provide opportunities to investigate disease-modifying techniques other than vasodilation and allow for the longitudinal, real-world evaluation of imaging, functional assessments, and circulating biomarkers. To improve care for both veterinary and human patients, we conclude by outlining priorities for mechanism-based clinical trials, shared outcome measures, prospective registries and biobanks, and harmonised definitions. Full article

The rapid increase in companion animal ownership has intensified the demand for innovative tools that support animal health and overall welfare. In recent years, artificial intelligence (AI), particularly machine learning (ML) and deep learning (DL), has emerged as a promising approach in veterinary medicine. However, its application beyond clinical diagnostics, especially in behaviour and personality assessment, remains fragmented and insufficiently integrated into routine practice. This systematic review aims to synthesise current knowledge on AI-based applications in companion animal care, with a focus on behavioural monitoring, personality prediction, and welfare-related challenges. Following PRISMA guidelines, a structured literature search was conducted in the Scopus and PubMed databases from 2020 to 2025. In addition, grey literature sources were searched to capture relevant non-peer-reviewed data. A total of 115 studies met the inclusion criteria and were included in the analysis. Eligibility criteria included studies applying AI methods (machine learning or deep learning) to companion animals (dogs, cats, and exotic pets), while studies on humans, farm animals, or without AI methods were excluded. Due to the heterogeneity of included studies, no formal risk of bias assessment was performed, and results were synthesised narratively. The findings indicate that AI applications are most advanced in diagnostic imaging and clinical decision support, where data availability and methodological maturity are highest. In contrast, AI-based approaches for behaviour and personality prediction remain limited, particularly in cats and exotic companion animals, largely due to small, heterogeneous datasets, potential bias, and a lack of external validation. Emerging technologies such as wearable sensors, computer vision, and multimodal data integration demonstrate substantial potential for continuous behavioural monitoring and early detection of welfare-related issues in real household environments. Nevertheless, significant challenges persist, including data heterogeneity, limited model explainability, ethical considerations, and the absence of regulatory frameworks specifically addressing AI-based veterinary applications. Overall, this review highlights a substantial gap between the technical potential of AI and its current readiness for widespread application in companion animal behaviour and welfare assessment. Future research should prioritise large-scale and standardised data collection, cross-species validation, and interdisciplinary collaboration to ensure that AI-driven tools effectively support veterinary decision-making, animal welfare, and the well-being of owners. Full article

Lesions of the tendons and manica flexoria (MF) within the digital flexor tendon sheath (DFTS) are a common cause for lameness in horses. This prospective study compared and quantified the agreement and disagreement of positive contrast computed tomographic tenography (CTT), positive contrast radiographic tenography (RXT), ultrasonography (US) and tenoscopy for diagnosing naturally occurring lesions within the DFTS, without application of a gold standard. Lesions affecting the deep (DDFT) and/or superficial digital flexor tendon (SDFT), and/or the MF and/or constriction of the palmar/plantar annular ligament (PAL) were evaluated in eighteen horses with distention of the DFTS. For DDFT lesions, comparing CTT with tenoscopy, US, and the combined results of US and RXT (US+RXT) attained the highest agreements, with 83% matching results (κ: 0.65). For SDFT lesions, CTT and tenoscopy showed the highest agreement with 94% matching results (κ: 0.89), followed by tenoscopy with US+RXT (78%; κ: 0.56). The highest agreement for MF-tear detection was found comparing CTT with tenoscopy (83%; κ: 0.67), followed by CTT with RXT (78%; κ: 0.56). None of the modalities agreed on positive diagnoses of PAL constriction. CTT achieved the highest agreement with tenoscopy and US for the diagnosis of lesions within the DDFT and is, therefore, considered the most useful modality for preoperative evaluation. Full article

Effective pain control after orthopedic surgery is essential in veterinary practice, particularly in small-breed dogs with low physiological reserves. This study aimed to compare the analgesic efficacy and tolerability of five postoperative pain protocols across nine surgical procedures. A retrospective analysis was conducted in 205 small-breed dogs (≤7 kg) undergoing orthopedic surgeries. Dogs were assigned to one of five analgesic protocols: (A) carprofen, (B) tramadol–lidocaine–ketamine continuous-rate infusion, (C) butorphanol continuous-rate infusion, (D) hydromorphone continuous-rate infusion, and (E) multimodal analgesia combining local anesthetics, hydromorphone, and meloxicam. Pain was assessed at 6, 12, 24, 48, and 72 h using the Glasgow Composite Measure Pain Scale—Short Form. Analgesic efficacy was evaluated using pain trajectories, area-under-the-curve analysis, and pain resolution rates, and adverse effects were recorded. Dogs receiving multimodal analgesia achieved the most rapid and sustained pain relief, with all patients reaching pain resolution by 48 h. Hydromorphone alone showed comparable efficacy but was associated with more adverse effects, while tramadol–lidocaine–ketamine showed delayed pain relief and the highest rate of severe side effects. Multimodal analgesia provides superior pain control with acceptable safety in small-breed dogs undergoing orthopedic surgery, supporting its use based on surgical invasiveness and individual patient response. Full article

Parasitic infections in veterinary medicine are commonly diagnosed through microscopic examination of fecal samples, yet traditional manual methods are labor-intensive and subject to diagnostic variability. This study investigates YOLOv8 for automated identification of parasitic elements in fecal microscopy images. Six parasitic taxa were analyzed at 1000×, 2500×, and 10,000× magnifications: Spirometra eggs, Dipylidium egg packets, hookworm eggs, Ascaris eggs, Giardia cysts, and Trichomonas trophozoites. The dataset comprised 326 images with 3710 annotated objects, split at the sample level into training (70%), validation (15%), and testing (15%) sets. The YOLOv8n model achieved mean average precision (mAP@0.5) of 0.982 ± 0.015 across 5-fold cross-validation. Per-class AP exceeded 0.97 for five taxa, with Trichomonas achieving 0.952. Inference time averaged under 60 ms per image on a standard CPU. These results demonstrate that YOLOv8 provides accurate and efficient detection of diverse parasitic elements, supporting its potential as a clinical screening tool. Full article

Veterinary forensic pathology is an evolving discipline at the intersection of veterinary medicine, forensic science, and animal welfare law. This article underscores the growing importance of this field in advancing both animal welfare and justice. Drawing on post-mortem examinations, advanced forensic techniques, and real-world case studies, the article highlights how forensic veterinarians differentiate between ante- and post-mortem injuries, estimate time of death, and interpret complex trauma patterns. It also reviews the application of imaging technologies, bloodstain pattern analysis, forensic entomology, and histological tools in forensic investigations. Through illustrative case examples, including neglect, sexual abuse, thermal injuries, firearm wounds, and asphyxia, the article demonstrates the evidentiary value of veterinary pathology in legal contexts. Finally, the article outlines future directions for the field, emphasizing the need for standardized training, interdisciplinary collaboration, and greater legal recognition. Full article

Diagnostic imaging is essential in veterinary practice, and cone-beam computed tomography (CBCT) has emerged as a promising tool to complement radiography. This study aimed to optimize the image quality of a novel multimodality veterinary X-ray prototype integrating direct digital radiography, fluoroscopy and CBCT, and to assess its potential clinical applications, focusing on the CBCT component. The study was conducted in three phases: optimization of CBCT image quality using postmortem samples, comparison of CBCT and 16-slice multidetector CT (MDCT) images of four cadavers (two dogs and two cats), and potential clinical applications in 24 live patients. Comparative evaluation in postmortem scans revealed that CBCT achieved equal quality in 65% of bone compared to MDCT and a slightly inferior quality in 90% of soft-tissue structures using the bone reconstruction protocol, with beam hardening as the main limiting factor. Clinical validation showed that CBCT was particularly useful for identifying small fractures and mineralized structures, providing diagnostic information not clearly visible on radiographs. Integration of radiography, fluoroscopy, and CBCT in a single device facilitated workflow and allowed a more precise diagnosis in most of the patients examined with the prototype, which demonstrated promising diagnostic performance in small-animal and exotic veterinary practice. Full article

The coelomic cavity of sea turtles is affected by congenital, developmental, traumatic, infectious, and organ- or system-specific disorders, making accurate anatomical knowledge essential for veterinary practice. This study presents an open-access, interactive two-dimensional (2D) anatomical atlas of the coelomic cavity of the loggerhead sea turtle (Caretta caretta), developed using images obtained from osteology, gross anatomical dissections, computed tomography (CT), and magnetic resonance imaging (MRI). The atlas comprises six osteology images, sixteen anatomical dissection images, eight transverse CT images acquired using bone and soft-tissue windows, six three-dimensional (3D) volume-rendered CT images, and fourteen MRI images (four transverse, five dorsal, and five sagittal), all provided in PNG format. Relevant anatomical structures were segmented and colour-coded for each figure using manual layer-based segmentation software. The Unity 3D platform was employed for image visualisation and assessment, supporting the development of interactive two-dimensional content. This atlas serves as a useful interactive tool for anatomical learning and clinical reference for professionals and students engaged in the conservation of loggerhead sea turtles. Full article

Glioblastoma (GBM) is the most common and most aggressive malignant primary brain tumor in adults with a median survival of 15 months. One of the main factors responsible for the poor prognosis of GBM is resistance to treatment with temozolomide (TMZ), which has been attributed—among other factors—to autophagy. Preclinical studies have shown that the combination of disulfiram (DSF) with copper (Cu) possesses anti-GBM activity, through various mechanisms, including re-sensitization to TMZ. Herein, we tested for the first time the effects of DSF and Cu in combination with TMZ on the survival of Fischer rats bearing F98 glioma, a model characterized by inherent resistance to TMZ. Tumor size evaluation by Magnetic Resonance Imaging as well as immunofluorescence analysis of two autophagy markers, namely microtubule-associated protein 1 light chain 3 (LC3) and sequestosome-1 (SQSTM1)/p62 (p62), were also performed. According to our results, TMZ-DSF-Cu significantly increased mean survival and induced both LC3 and p62 autophagy markers. Interestingly, these results could not be achieved in the absence of Cu, neither in the presence of TMZ alone, suggesting the importance of combining DSF with Cu in order to sensitize glioma to TMZ, presumably via implication of autophagy modulation. Full article

Fractures are a leading cause of morbidity and mortality in Thoroughbred racehorses, posing a significant threat to their welfare and careers. This study introduces a deep learning model specifically designed to facilitate fracture detection in equine athletes. By leveraging extensive training on human fracture data and refining the model with equine imaging, it highlights the transformative potential of transfer learning across species and medical contexts. This approach is not limited to equine fractures but could be adapted for use in detecting injuries or conditions in other veterinary species and even human healthcare applications. A comprehensive databank of radiographs, sourced from public archives and equine hospitals, was curated to encompass diverse conditions (fracture and non-fracture), ensuring robust pattern recognition. The architecture integrates a Vision Transformer for global context modelling with a ResNet backbone and loss function to optimize local feature extraction and cross-species adaptability. The pipeline achieved 96.7% accuracy for modality classification, 97.2% accuracy for projection recognition, and fracture localization intersection over union values of 0.71–0.84 across equine datasets. This work bridges advancements in human and veterinary medicine, opening pathways for AI-driven solutions that extend beyond fractures, fostering improved diagnostic precision and broader applications across species (felines, canines, etc.). By integrating advanced imaging techniques with AI, this study aims to set a foundation for more comprehensive and versatile health monitoring systems. Full article

Artificial intelligence (AI), including machine learning (ML) and deep learning (DL), is rapidly transforming clinical veterinary practice by enhancing diagnostics, disease surveillance and decision support processes across animal health domains. The safe and effective clinical deployment of these technologies, however, depends critically on the preparedness of the veterinary workforce, positioning veterinary education as a strategic enabler of translational adoption. This narrative review examines the integration of AI within veterinary education as a foundational step toward its responsible application in clinical practice. We synthesize current evidence on AI-driven tools relevant to veterinary curricula, including generative and multimodal large language models, intelligent tutoring systems, virtual and augmented reality platforms and AI-based decision support tools applied to imaging, epidemiology, parasitology, food safety and animal health. Particular attention is given to how the structured educational use of AI mirrors real-world clinical workflows and supports the development of competencies essential for clinical translation, such as data interpretation, uncertainty management, ethical reasoning and professional accountability. The review further addresses ethical, regulatory and cognitive considerations associated with AI adoption, including algorithmic bias, data privacy, equity of access and the risks of overreliance, emphasizing their direct implications for diagnostic reliability and animal welfare. By framing veterinary education as a controlled and reflective environment for AI engagement, this article highlights how pedagogically grounded training can facilitate safer clinical deployment, foster interdisciplinary collaboration and align technological innovation with professional standards in veterinary medicine. Full article

A phytobezoar is a compact mass formed by the accumulation of indigestible food fibers (such as cellulose and lignin) within the stomach and/or intestine. To date, only limited reports describe the clinical management and diagnostic approach to gastrointestinal phytobezoars (GIPs) in dogs and cats. The aim of this study was to describe the clinical features and diagnostic findings obtained through imaging and instrumental investigations in canine and feline cases with GIPs. Medical records of 25 animals diagnosed with GIPs were reviewed, and data on signalment, clinical signs, imaging findings, and follow-up were collected. Seven animals were excluded because the foreign body (FB) consisted of plastic mixed with fibrous material. Eighteen animals (17 dogs and 1 cat) were included: 8 (44.4%) with gastric involvement, 8 (44.4%) with intestinal localization and 2 (11.1%) with both gastric and intestinal localization. The GIP was removed endoscopically in 3 (16.7%) cases, surgically in 7 (38.9%) cases, extracted from the rectal ampulla in 2 (11.1%) cases, and expelled spontaneously through defecation in 6 (33.3%) cases. GIPs are frequently underdiagnosed, as they are associated with nonspecific gastrointestinal signs. Radiography and ultrasonography offer limited diagnostic value, generally suggesting the presence of an FB without definitively confirming it to be GIP. This study contributes to the current literature by detailing the clinical, diagnostic, and interventional features of GIPs in small animals, representing the first report of this condition in veterinary medicine. Full article