Artificial intelligence (AI) is a branch of computer science in which computer systems are designed to perform tasks that mimic human intelligence. Today, AI is reshaping day-to-day life and has numerous emerging medical applications poised to profoundly reshape the practice of veterinary medicine. In this Currents in One Health, we discuss the essential elements of AI for veterinary practitioners with the aim to help them make informed decisions in applying AI technologies into their practices. Veterinarians will play an integral role in ensuring the appropriate uses and good curation of data. The expertise of veterinary professionals will be vital to ensuring good data and, subsequently, AI that meets the needs of the profession. Readers interested in an in-depth description of AI and veterinary medicine are invited to explore a complementary manuscript of this Currents in One Health available in the May 2022 issue of the American Journal of Veterinary Research.

Veterinary medicine is a broad and growing discipline that includes topics such as companion animal health, population medicine and zoonotic diseases, and agriculture. In this article, we provide insight on how artificial intelligence works and how it is currently applied in veterinary medicine. We also discuss its potential in veterinary medicine. Given the rapid pace of research and commercial product developments in this area, the next several years will pose challenges to understanding, interpreting, and adopting this powerful and evolving technology. Artificial intelligence has the potential to enable veterinarians to perform tasks more efficiently while providing new insights for the management and treatment of disorders. It is our hope that this will translate to better quality of life for animals and those who care for them.

Chronic kidney disease (CKD) is a major health condition in cats that can lead to poor quality of life and financial implications for therapy. Currently staging and identification of CKD is limited by diagnostic testing such as creatinine and urine‐specific gravity, which do not change until late in the disease course. Other methods to evaluate CKD would be valuable in the clinical setting. Shear wave elastography is one novel ultrasound method, which has shown promise in identifying increases in tissue stiffness and identifying CKD in people. As CKD is often histologically characterized by tubulointerstitial fibrosis, shear wave elastography has the potential to identify CKD and differentiate between stages of CKD in cats. This prospective observational case‐control study with 78 cats found no difference in shear wave velocities between groups (P = 0.33), a contradictory finding to one prior publication. There was no effect of weight (P = 0.65), nor the presence of mineralization (P = 0.31) or infarction (P = 0.52) on cortical shear wave velocities. There was a significant effect of age on shear wave velocity (P = 0.018) where velocities increased with age. The intraclass correlation coefficient was only moderate (0.62). Possible reasons for the difference in results between our work and that published prior, include differences in methodology and differences in instrumentation. Variability in measurements in our population may be due to the effects of respiratory motion or limitations in shear wave elastography software. As such, shear wave elastography is not currently recommended as a tool to evaluate CKD in cats and further work is necessary.

Surgical removal is the treatment of choice for subcutaneous (SC), intermuscular (InterM), and intramuscular (IntraM) mast cell tumors (MCTs). Advanced imaging (CT or MRI) is frequently used for presurgical planning, but InterM and IntraM MCTs can be difficult to identify and delineate on CT. Aims of the current retrospective, diagnostic accuracy, observer agreement study were to describe the imaging features of SC, InterM, and IntraM MCTs on CT and to assess the limitation of CT to identify the full local extent of the MCT. Inclusion criteria for the study were dogs with a cytologically or histologically diagnosed MCTs determined to be SC, InterM, or IntraM MCT based on histology and/or a CT scan performed in the gross disease setting.Two board-certified veterinary radiologists reviewed the CT images and recorded location, contrast enhancement pattern, and delineation between the normal and abnormal tissue. Sensitivity and specificity of CT for determining location (SC/InterM versus IntraM) was 85.71% and 55.56%, respectively, when compared to consensus location based on surgical pathology report/CT/MRI review. There was a low interrater agreement for delineation (kappa: 0.150 (−0.070 to 0.370) and measurement had a low/moderate correlation (rho: 0.4667 to 0.5792). Upon review by a surgical oncologist, CT findings were deemed insufficient for curative surgical planning in 13 of 16 due to inadequate definition of tumor depth, compartment boundary (fascial plane) or MCT margins. The use of CT for presurgical planning of SC/InterM/IntraM MCT dogs has limitations, especially when differentiating MCT from the adjacent muscle.

OBJECTIVE To report the perioperative characteristics and outcomes of dogs undergoing laparoscopic-assisted splenectomy (LAS). ANIMALS 136 client-owned dogs. PROCEDURES Multicentric retrospective study. Medical records of dogs undergoing LAS for treatment of naturally occurring splenic disease from January 1, 2014, to July 31, 2020, were reviewed. History, signalment, physical examination and preoperative diagnostic test results, procedural information, complications, duration of hospitalization, histopathologic diagnosis, and perioperative outcomes were recorded. Perioperative complications were defined using the Veterinary Cooperative Oncology Group – Common Terminology Criteria for Adverse Events (VCOG-CTCAE v2) guidelines. RESULTS LAS was performed for treatment of a splenic mass (124/136 [91%]), immune-mediated disease (7/136 [5%]), splenomegaly (4/136 [3%]), or immune-mediated disease in conjunction with a splenic mass (1/136 [1%]). Median splenic mass size was 1.3 cm3/kg body weight. Conversion to open laparotomy occurred in 5.9% (8/136) of dogs. Complications occurred in 78 dogs, with all being grade 2 or lower. Median surgical time was 47 minutes, and median postoperative hospital stay was 28 hours. All but 1 dog survived to discharge, the exception being postoperative death due to a suspected portal vein thrombus. CLINICAL RELEVANCE In the dogs of this report, LAS was associated with low rates of major complications, morbidity, and mortality when performed for a variety of splenic pathologies. Minimally invasive surgeons can consider the LAS technique to perform total splenectomy in dogs without hemoabdomen and with spleens with modest-sized splenic masses up to 55.2 cm3/kg, with minimal rates of complications, morbidity, and mortality.