26 Oct 2023
HT Vista says paper demonstrating use of thermal imaging and AI is “significant stride toward revolutionising screening of canine dermal and SC masses”.
Paul Imrie
Job Title
A research paper has been published demonstrating the “significant stride towards revolutionising the screening of canine dermal and SC masses” through use of a thermal imaging and artificial intelligence (AI) device.
HT Vista said publication of its training and validation research paper demonstrates the use of the technology in its device to accurately screen between benign masses and those needing further investigation.
The paper, published in Frontiers, revealed the device had a 97% negative predictive value and a sensitivity of 85%, meaning vets will be able to ensure potentially malignant masses on dogs are not missed.
HT Vista labelled the research a “significant stride towards revolutionising the screening of canine dermal and SC masses” in a press statement.
Liron Levy-Hirsch, managing director of HT Vista’s UK subsidiary, said: “We are thrilled to have scientific research validating the success of the HT Vista device.
“The veterinary teams who have already adopted the device into their practice are having great success with it, and with the backing of this newly published paper we hope to reach more practices and ultimately save more dogs’ lives.”
As part of the study, more than 660 masses were evaluated in two phases between 2020-22. The first phase trained the algorithm and the second validated it.
Mr Levy-Harsh added: “It is exciting to see the algorithm improve with every scan. We are very pleased with the results we have and continue to look to the future where we are sure the sensitivity will increase further.”
HT Vista said its device combines thermal imaging technology with AI, and unlike traditional methods, measures heat transfer rate differences between masses and adjacent normal tissues, providing a more accurate analysis.
The data is processed using advanced machine learning algorithms, enabling rapid and precise classification of masses.
Full information is available on the HT Vista website and the paper is available online.
