Update on computed tomography and liposarcomas in dogs

November 9, 2017
Eli Cohen, DVM, DACVR

Eli Cohen, DVM, DACVR, is a clinical assistant professor of radiology at North Carolina State Universitys College of Veterinary Medicine and co-owner of Dragonfly Imaging, PLLC.

Do not rule out this fatty form of cancer due to absence of fat on CT, says Dr. Eli Cohen.

Recent computed tomography (CT) research into liposarcomas1 has revealed a surprising update, according to Fetch dvm360 conference speaker Eli Cohen, DVM, DACVR (who is also one of the study's authors).

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While CT is commonly used to evaluate liposarcomas in people, and multiple studies have described liposarcoma characteristics on CT that help differentiate between cancerous and noncancerous tumors and between histologic subtypes, this is the first study to describe the CT appearance of canine liposarcomas. According to the study's authors, “With the increasing widespread availability of CT, identification of imaging findings typical of liposarcoma in dogs could increase clinical suspicion and potentially spare more invasive techniques for diagnosis.”

The retrospective study examined CT images of 24 dogs with 26 histologically confirmed liposarcomas, noting size, location, attenuation, contrast enhancement, border definition, internal homogeneity, local infiltration and mineralization.

While the study found several CT features associated with canine liposarcomas (such as heterogeneous internal attenuation and focal areas of fat attenuation), what Dr. Cohen considers most interesting is what canine liposarcomas don't need to have.

"Not all liposarcomas actually have fat attenuation inside of them. So that means that really any tumor that you might consider for a sarcoma could be a liposarcoma. There doesn't have to be a presence of fat for us to consider that," he says.

To hear more from Dr. Cohen on the findings of study, watch the video below.



1. Fuerst JA, Reichle JK, Szabo D, et al. Computed tomographic findings in 24 dogs with liposarcoma. Vet Radiol Ultrasound 2017;58(1):23-28.