Novel compact device for clinicians could spot infected wounds faster

Written By :  Isra Zaman
Medically Reviewed By :  Dr. Kamal Kant Kohli
Published On 2023-08-25 03:45 GMT   |   Update On 2023-08-25 09:43 GMT

Infection can stall the healing of wound or its spread into the body if it isn't treated quickly, putting a patient's health in grave danger. An international team of scientists and clinicians thinks they have the solution: a device run from a smartphone or tablet app that allows advanced imaging of a wound to identify infection. The scientists developed a device called the Swift Ray 1 which can be attached to a smartphone and connected to the Swift Skin and Wound software. This can take medical-grade photographs, infrared thermography images, and bacterial fluorescence images.

To test their device, they recruited 66 wounded patients. Their wounds showed no sign of infection spreading further, did not contain foreign bodies, and had not previously been treated with antibiotics or growth factors. The images were reviewed by a researcher who wasn’t present for the wound care process. Four patterns were identified.

Wounds where the wound was not warmer than healthy skin and no bacterial fluorescence was present were considered ‘non-inflamed’, while wounds that were slightly warmer than healthy skin and had no or slight bacterial fluorescence were considered ‘inflamed’. The last two patterns — wounds that were substantially warmer, with or without bacterial fluorescence — were both designated as ‘infected’, because all the clinicians who had examined these wounds had considered them infected.

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Out of the 66 wounds, 20 were considered non-inflamed, 26 were inflamed, and 20 were infected. The researchers performed principal component analysis and used an algorithm called nearest k-neighbor clustering to see if a machine learning model could accurately identify these different categories of wound. They found that the model could identify all three very well, with an overall accuracy of 74%. When differentiating between infected vs. non-infected wounds, the model correctly identified 100% of infected wounds and 91% of non-infected wounds.

Reference: Frontiers in Medicine, DOI 10.3389/fmed.2023.1165281, Is my Wound Infected? A Study on the Use of Hyperspectral Imaging to Assess a Wound's Infectious Status

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Article Source : Frontiers in Medicine

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