LBT’s WoundVue technology uses artificial intelligence to assist clinicians in the assessment and care of chronic wounds.
WoundVue is able to calculate a wound’s surface area and volume, as well as objectively classifying the different tissue types within the wound.
Challenges for Clinicians
It is estimated that 20,000,000 people worldwide, including 400,000 Australians, are living with a chronic wound or ulcer at any given time.
Increased demand for the treatment of chronic wounds is being driven by factors including an ageing population, obesity and the increasing incidence of diabetes.
The treatment of chronic wounds and ulcers is estimated to cost 2% of total Australian health expenditure. This equates to over $4.22 billion each year.
Existing techniques are manual and rely on user experience. There is a need for objective techniques to provide measurements for evidence-based care.
Working with the Australian Institute of Machine Learning, LBT has applied its platform AI technology and combined it with 3D imaging capabilities to develop a prototype that is capable of supporting clinicians in the management and care of wounds. The device is able to:
- Accurately measure the surface area and volume of the wound; and
- Provide an objective classification of eight different tissue types within the wound, such as slough, necrosis, granulation and skin.
In summary, the work performed to date has shown that:
- There is an unmet need in the chronic wound market for a hand-held device that objectively assesses wounds;
- LBT’s prototype can accurately measure wound surface area and volume;
- LBT’s image analysis algorithms have demonstrated the capability to classify different wound tissue characteristics;
- The technology exists to map and morphologically characterise chronic wounds to assist with ongoing clinical assessment
LBT is looking for suitable partners to commercialise this product for the market.