Saving time, money and energy on X-rays at emergency clinics

Published by Dr. Roy Saldanha | Arlington Animal Hospital and 24 Hour Emergency Center

Saldanha Case Study


Dr. Roy Saldanha is the owner and CEO of Arlington Animal Hospital and 24 Hour Emergency Center. He has been in veterinary medicine for the last 21 years. With 7 veterinarians on call, his staff takes about 15 to 20 radiology studies a day, averaging 150 each week. With 75% of these cases being emergency, and the other being general practice, the staff moves quickly to come to consensus on treatment for patients.


Dr. Saldanha was reading a dvm360 magazine article on the emergence of artificial intelligence when he came across SignalPET. As one of the leading veterinary AI tools, Dr. Saldanha was intrigued and started a trial for Arlington Animal Hospital. He claims that, “Almost all of us now will look at SignalPET to see what it says, because that's our second opinion of what's happening.” Before, it would take 2 or 3 staff members looking at an x-ray to come to a decision. Now a single staff member using SignalPET is comfortable with results.


Emergencies often require immediate action. Dr. Saldanha reveals, “For us, it's about getting an answer a whole lot faster, and being more confident in the answer, or the differential diagnosis that you have.” The staff feels more confident about the gray area cases that come in weekly.

“You get a dog who comes in, it's got an abdomen full of fluid, you really can't see well into the abdomen. And so, you stand and you look at it, and you wonder if there's a mass present or not. And if SignalPET picks up a mass with 100% confidence, you already know, you don't have to send that to anywhere. You already know that there's a mass there. And so, it just makes that decision easier.”

SignalPET gives added confidence, and a second set of eyes to ensure the best treatment for patients. While not all cases are unique and require this, Dr. Saldanha finds that SignalPET has proven to be a great tool in finding missing components in radiograph readings.