By Karen E. Felsted, CPA, MS, DVM, CVPM, CVA
SPONSORED BY SIGNALPET^®

Veterinarians have a clear understanding of the benefits radiology provides — the accurate and timely diagnosis of disease and injury using a safe, quick, affordable and non-invasive modality. However, these benefits are all dependent upon an accurate reading of the radiographic images and this is often harder for DVMs when compared to other diagnostic tools such as laboratory testing.

There are many studies in human medicine that document the difficulties board-certified human radiologists regularly have in reading films. It is safe to assume that the art of reading films is even more challenging for veterinary general practitioners who have less training than either human or veterinary radiologists and must interpret findings from multiple species.

Challenges in reading radiographic images include:

• Long turnaround times with outside readings
• Cost of outside interpretation which may influence a client’s decision to select this service
• Increased demand for outside reading of images by board-certified radiologists resulting in long delays for interpretations and consultations
• Lack of training/experience and limited ability to consult with colleagues
• Innate subjectivity in making interpretations
• Tunnel vision/focus on “expected” findings
• Diagnostic confidence

Fortunately, the rising availability and use of AI (artificial intelligence) options in veterinary radiology can be very helpful to a practice in addressing some of these concerns. AI shouldn’t be thought of as a replacement for the skills and knowledge of any veterinarian, general practitioner, or specialist (particularly a board-certified radiologist). AI is an ancillary tool designed to help improve patient care, the client experience, and veterinary practice efficiency.

SignalPET is a patented software platform that uses artificial intelligence and machine learning to quickly and accurately “read” radiographs. A team of highly skilled veterinarians including general practitioners, board-certified radiologists, and other specialists, created and then used the largest database of annotated veterinary radiographs (over 2M images) in the world to develop the technology.

Utilizing these images, AI has been trained to successfully recognize greater than 50 signs on radiographic films (including thoracic, abdominal, spine, pelvis, forelimb, hind limb, and dental) in animals of varying sizes and weights signaling the presence or absence of specific pathologies.

The use of an AI radiology tool essentially puts another set of “eyes” on the image and either confirms the original findings of the practice team or may identify some additional findings as well. Either will improve the confidence the team has in the reading and offers stronger support for the diagnosis and pet owner recommendations. This is particularly helpful for recent graduates or those with less radiograph interpretation experience.

Implementation of AI in Your Practice
Factors to consider in selecting a radiology AI provider include:

• Development, proprietariness and accuracy of the AI algorithm
• Process for ongoing revision and upgrade of AI algorithm
• Range of body areas and clinical problems assessed
• Ease of integration of AI process into practice’s existing workflow
• Need for additional practice equipment, if any
• Ease of uploading images for reading and interpretation
• Turnaround time for study reports
• Ease of retrieving and reviewing reports
• Quality of reports – usefulness to both clinicians and pet owners
• AI provider support–type, hours
• Cost

The integration of AI radiology into the practice is a good time for the practice to review and/or create its own radiology recommendation standards. Radiology protocol usually cover the situations in which the medical team thinks radiographs should be recommended and the types of films that should be taken.

Not only does the process of creating protocols allow doctors to talk through how they think cases should be best handled but the finished product can also serve as a training tool for all team members.

Summary
The rising availability and use of AI options in veterinary radiology can be very helpful to practices in addressing some of the challenges veterinarians currently face in reading and communicating the benefits and results of radiographs. Fortunately, implementing an AI component into the practice’s workflow doesn’t have to be difficult, costly, or time-consuming, and all parties benefit from utilizing this advanced technology—the pet, the pet owner, the veterinary team, and the practice.

About the author Karen E. Felsted, CPA, MS, DVM, CVPM, CVA, is a CPA as well as a veterinarian and has spent the last 20 years working as a financial and operational consultant to veterinary practices and the animal health industry. She is active in multiple veterinary organizations, has written an extensive number of articles for a wide range of veterinary publications and speaks regularly at national and international veterinary meetings. In 2011 and 2017, she was awarded the Western Veterinary Conference Practice Management Continuing Educator of the Year and in 2014,