Notebook: November 2020

News briefs from across the industry and beyond. This month’s articles include: $2 billion in government aid to practices, feline DNA microarray study to study cancer, academic partnerships to increase diversity, artificial intelligence and vet med, sea lion receives CT scan, global veterinary imaging market news, animal facial recognition software, and MRI and dog speech recognition.

Veterinary Imaging Market to Reach
$2.72 Billion by 2027

The global veterinary imaging market is forecasted to reach $2.72 billion by 2027, according to a new report by Reports and Data ( The report states that increasing competition for magnetic resonance imaging for the treatment of different animal health conditions is one of the factors driving the veterinary imaging market. Increasing healthcare expenditure on companion animals, coupled with strong footholds of notable players in North America, will also boost the business of veterinary imaging techniques.

Facial Recognition Software in the Animal Realm

With nearly 630 million facial recognition cameras in place throughout China, entrepreneurs are working to apply the technology to livestock operations. Tech giant Alibaba is developing voice recognition technology for pigs to detect whether they are in pain, while startup Beijing Unitrace Tech’s facial recognition software detects patterns and shapes on an animal’s face and hide to identify individual cows. Farmers load information such as health conditions, insemination dates, and pregnancy test results into the Unitrace Tech system, which syncs up with cameras installed above troughs and milking stations. Signs of illness or unusual behavior can be detected and treated quickly, rather than relying on farmers to inspect the herd for potential problems.

Here in the US, facial recognition software is being used to identify and locate lost pets. AI startup Megvii uses multiple photos of a dog’s nose to create a unique profile in its database and says it can verify a dog’s identity against its records with 95% accuracy. Finding Rover, a smartphone app based on a machine learning algorithm developed at the University of Utah, collects photos of missing dogs from pet owners and matches them against a database of dogs found by shelters or other app users. The app’s founder says more than 15,000 pets have been reunited with their owners so far.


“The secret of change is to focus all your energy not on fighting the old but on building the new.”


Programs Aim to Increase Diversity in the Field of Veterinary Medicine

Two new programs at historically Black colleges and universities are aimed at increasing diversity in the field of veterinary medicine.

First, Tennessee State University has partnered with the University of Tennessee College of Veterinary Medicine (UTCVM) to help agriculture students at Tennessee State transition to veterinary school once they complete their bachelor’s degrees.

Qualified first-year students at Tennessee State will be set on an academic trajectory to meet the requirements for admission into the UTCVM or other institutions of veterinary medicine. Mentors will work with the students to monitor their progress and support other training opportunities, such as summer jobs or internships.

The new partnership “will help increase minorities in the veterinary profession and help us prepare our students appropriately for veterinary college. Healthcare for pets is a huge demand in society today. Many of our students are interested in the veterinary profession and we welcome this opportunity to prepare and place students in this competitive and demanding field,” said Chandra Reddy, dean of the College of Agriculture at Tennessee State.

Second, improving diversity, equity, and inclusion within the veterinary sphere is the goal of a new scholarship program at Tuskegee University College of Veterinary Medicine (TUCVM).
The college, which is the only veterinary program located on the campus of a historically Black college or university in the US, has received a $45,000 endowment from Hill’s Pet Nutrition to fund the program. Tuskegee’s veterinary scholarship committee will identify awardees annually, starting with the 2021–2022 academic year, based on criteria to be developed by the college and the American Veterinary Medical Foundation (AVMF). Tuskegee is the alma mater of 20% of Black veterinarians practicing in the US, according to the AVMF.

“We at Tuskegee focus on our students being career-ready veterinarians when they complete the curriculum and encourage their pursuits of the vast areas of career choices in the veterinary profession,” said TUCVM’s dean, Ruby L. Perry, DVM, MS, PhD, DACVR. “The generosity of Hill’s will help our students achieve this goal.”

MRI Used to Detect Dog Speech Response

In an article recently published in the journal Scientific Reports, researchers at the Department of Ethology, Faculty of Science, Eötvös Loránd University in Budapest, Hungary, used MRI technology on awake dogs to establish speech processing similarities between humans and a speechless species. Researchers found that dog brains, just as human brains, process speech hierarchically: intonations at lower stages and word meanings at higher stages.

In this study, dogs listened to known praise words (“clever,” “well done,” “that’s it”) and unknown, neutral words (“such,” “as if,” “yet”) both in praising and in neutral intonation. The results show that dog brains, just like human brains, process intonation at lower stages (mostly in subcortical regions) and known words at higher stages (in cortical regions). The study also found that older dogs distinguished words less than younger dogs.

“Exploring speech processing similarities and differences between dog and human brains can help a lot in understanding the steps that led to the emergence of speech during evolution. . . . Some years ago, we discovered that dog brains, just as human brains, separate intonation and word meaning. But is the hierarchy also similar? To find out, we used a special technique this time: We measured how dog brain activity decreases to repeatedly played stimuli. During brain scanning, sometimes we repeated words, sometimes intonations. Stronger decrease in a given brain region to certain repetitions shows the region’s involvement,” explained Anna Gábor, postdoctoral researcher at the Hungarian Academy of Sciences and Eötvös Loránd University, Budapest’s “Lendület” Neuroethology of Communication Research Group, and lead author of the study.

Speech-responsive auditory regions in the dog brain. Purple spheres (R = 4 mm) are centered on previously functionally defined auditory activity peaks (Andics et al., 2016) using a speech versus silence contrast at the group level with the same dog participants, and used as regional search spaces.

A dog and researchers (Márta Gácsi [left], Attila Andics, Anna Gábor [right]) at the scanner.

NB_06.jpgFeline Microarray Advances Comparative Cancer Genomics

Researchers at the North Carolina State University College of Veterinary Medicine have developed a microarray platform that allows for rapid detection of DNA aberrations in feline tumors. The domestic cat lags behind the domestic dog in terms of integration into translational molecular medicine, and the researchers report that the new platform could lead to the further evolution of the comparative cancer genomics field.

The group used the platform during genomic profiling of a feline injection-site sarcoma case, with several key cancer-associated genes revealed during the procedure.

The research, published in Veterinary Sciences, is coauthored by Matthew Breen, Luke Borst, and Rachael Thomas.

Artificial Intelligence and Veterinary Medicine

The AVMA recently explored the use of artificial intelligence (AI) in veterinary medicine, discussing AI technologies in the areas of radiography, data analysis, and diagnosis.

In a 2019 report, the National Academy of Medicine wrote, “AI has the potential to revolutionize healthcare” and “offers unprecedented opportunities to improve patient and clinical team outcomes, reduce costs, and impact population health.”

The academy also sought to temper expectations about what AI could achieve, however. “One of the greatest near-term risks in the current development of AI tools in medicine is not that it will cause serious unintended harm, but that it simply cannot meet the incredible expectations stoked by excessive hype. Indeed, so-called AI technologies such as deep learning and machine learning are riding atop the utmost peak of inflated expectations for emerging technologies.”

AI technology is used for data analysis functions at the University of California, Davis, Veterinary Medical Teaching Hospital, where veterinary internist Krystle Reagan helped develop an algorithm to detect Addison’s disease with an accuracy rate greater than 99%. There, bloodwork results from more than 1,000 dogs were used to train an AI program to detect complex patterns suggestive of the disease. The computer program used these patterns to determine whether a new patient has Addison’s disease. Reagan is now coding data from canine patients seen at the UC Davis teaching hospital over the past decade in which leptospirosis was diagnosed or suspected but later ruled out.
Radiography is another area where AI is being used with great success, the AVMA reports. Complex algorithms have been shown to be highly accurate in recognizing patterns in imaging data. The National Academy of Medicine estimates that about 100 scientific reports dealing with AI in radiology were published in 2005, but the number of publications had increased to more than 800 in 2017.

“Tasks for which current AI technology seems well suited include prioritizing and tracking findings that mandate early attention, comparing current and prior images, and high-throughput screenings that enable radiologists to concentrate on images most likely to be abnormal,” the academy wrote in its 2019 report. “Over time, however, it is likely that interpretation of routine imaging will be increasingly performed using AI applications.”

Sea Lion with Heart Trouble Receives CT Scan at OSU

In this photo taken in 2017, Oregon Coast Aquarium’s Britt salutes Max, the facility’s oldest California sea lion and their largest. Max was born on May 20, 1990, and arrived at the aquarium on May 1, 1992.

Max visited the Lois Bates Acheson Veterinary Teaching Hospital at Oregon State University’s Carlson College of Veterinary Medicine, where he received a CT scan and an echocardiogram to diagnose congestive heart failure.

Oregon State University’s Lois Bates Acheson Veterinary Teaching Hospital recently received an unusual patient: fan favorite Max the sea lion from the Oregon Coast Aquarium, who presented with breathing problems and needed a computed tomography (CT) scan.

Max’s visit provided a unique learning opportunity for staff veterinarians, residents, and students at the teaching hospital, who are more accustomed to caring for dogs, cats, cows, and horses. The hospital has cared for sea lions before but reports there are no sea lion–specific experts on staff. As Max went through his tests, OSU doctors and students huddled together looking up the most current research on sea lion cardiac disease and treatment.

The sea lion received a CT scan, which produced a full 360-degree image from nose to tail that allowed for a precise diagnosis. OSU veterinarians and technicians also conducted bloodwork to check for infection, ran fecal tests, and performed an echocardiogram. They placed ice bags on his flippers to keep him cool during the procedures.

The scans revealed that Max is suffering from congestive heart failure, with his heart performing at about 50% capacity. Going forward, the aquarium’s team will work with the OSU cardiology team to plan a medication regimen to dissipate some of Max’s blood pressure issues and the fluid in his lungs. In the absence of sea lion–specific expertise, the veterinarians will be treating Max in much the same way they would treat a geriatric dog with congestive heart failure, as dogs are fairly similar physiologically.

Dan Lewer, DVM, director of veterinary services at the aquarium and owner of AAHA-accredited Willamette Veterinary Hospital in Corvallis, said “Maximus” is the favorite of all the animals he’s cared for in his own veterinary practice and in providing veterinary services at the aquarium. “He’s like a big playful yellow lab [who] has flippers and eats fish whole.”

$2 Billion in Government Aid

An AVMA analysis of US Small Business Administration (SBA) data reveals that more than half of US veterinary practices received Paycheck Protection Program (PPP) loans totaling an estimated $2.1 billion. At least 18,657 veterinary practices were helped by the federal program created by the Coronavirus Aid, Relief, and Economic Security Act.

The SBA, which oversees the loan program, issued PPP loans totaling more than $519 billion since the program launched in April. At least 201,900 veterinary jobs were protected with PPP loans, according to SBA data, while more than 80% of loans taken out by individual practices were for less than $150,000.

The greatest amount of PPP loan money given to veterinarians was in states with the most veterinarians: California, $200 million; Texas, $160 million; Florida, $141 million; New York, $109 million; and Illinois, $83 million. The lowest amount of loan money went to veterinarians in Guam, $345,000; the Virgin Islands, $482,000; Puerto Rico, $2.9 million; Washington, DC, $3.2 million; and Alaska, $4 million. The PPP loan deadline closed August 8.

Photo credits: rashadashurov/iStock via Getty Images Plus, mustafagull/iStock via Getty Images Plus, GlobalP/iStock via Getty Images Plus, sdominick/iStock via Getty Images Plus, David-Prado/iStock via Getty Images Plus, photos courtesey of Enikő Kubinyi / Eötvös Loránd University, dra_schwartz/E+ via Getty Images, CreVis2/iStock via Getty Images Plus, Fourleaflover/iStock via Getty Images Plus, Photo courtesy Oregon Coast Aquarium, Photo courtesy OSU



Subscribe to NEWStat