We use cookies to understand how you use our site and to improve your experience. This includes personalizing content and advertising. To learn more, click here. By continuing to use our site, you accept our use of cookies. Cookie Policy.

Features Partner Sites Information LinkXpress
Sign In
Advertise with Us

Download Mobile App

Pocket-Sized Device Uses Heat Signatures and Bacterial Fluorescence to Identify Infected Wounds Faster

By HospiMedica International staff writers
Posted on 25 Aug 2023
Print article
Image: The Ray 1 hyperspectral imaging device (Photo courtesy of Frontiers in Medicine)
Image: The Ray 1 hyperspectral imaging device (Photo courtesy of Frontiers in Medicine)

Identifying a wound that is becoming infected has long posed challenges for medical professionals. The signs and symptoms are often vague, and methods of detecting bacteria are time-consuming and not always accessible. Consequently, diagnosing a wound infection can be subjective, depending upon the experience of clinicians. The risk of infections delaying the healing process or spreading within the body underscores the urgency of timely treatment to ensure the well-being of patients. Now, an international team of scientists and clinicians have developed a device run from a smartphone or tablet app that enables advanced imaging of a wound in order to identify infection.

Scientists at Western University (Toronto, ON, Canada) and Swift Medical (Toronto, ON, Canada) have built a device that works with smartphones and tablets to capture medical images capable of identifying infected wounds. By capturing both the heat emitted by a wound and the fluorescence of bacteria, this device aids clinicians in distinguishing between inflammation and a potentially dangerous infection. This advancement could expedite interventions, enabling the identification of infections before they escalate into severe health risks. Dubbed the Swift Ray 1, the device attaches to a smartphone and interfaces with the Swift Skin and Wound software. This pairing facilitates the capture of medical-grade photos, infrared thermography images (which measure body heat), and bacterial fluorescence images (which reveal bacteria using violet light).

None of these images, taken individually, would be sufficient to confirm infection. Clinical examination has limited accuracy, as does thermography, which detects heat variations due to inflammation and infection. Bacterial fluorescence alone can only evaluate the wound's surface, which is naturally colonized by bacteria, creating the need for additional methods to differentiate between contamination and an infected wound. The researchers set out to combine these modalities in order to devise an approach that wouldn't require multiple costly devices, would address the shortcomings of each imaging method, and could provide an objective measure of the wound healing progress. To validate their device, they recruited 66 patients with wounds meeting specific criteria. These wounds exhibited no signs of infection spreading, did not contain foreign objects, and had not previously been treated with antibiotics or growth factors. After uncovering, cleaning, and drying the wounds, imaging was performed, followed by routine care.

A researcher who was not present for the wound care process reviewed the images and identified four distinct patterns. Wounds with normal temperature and no bacterial fluorescence were deemed 'non-inflamed', while slightly warmer wounds with minimal bacterial fluorescence were categorized as 'inflamed'. The last two patterns, characterized by significantly elevated temperature, with or without bacterial fluorescence, were both labeled as 'infected', based on the unanimous opinion of clinicians who examined these wounds. Among the 66 wounds, 20 were classified as non-inflamed, 26 as inflamed, and 20 as infected.

To evaluate the device's accuracy, the researchers conducted a principal component analysis and employed the nearest k-neighbor clustering algorithm to assess whether a machine learning model could correctly differentiate these wound categories. Impressively, the model successfully distinguished all three categories with an overall accuracy of 74%. When distinguishing between infected and non-infected wounds, the model accurately identified 100% of infected wounds and 91% of non-infected wounds. The researchers underscored the importance of considering these images within a medical context. For instance, a wound deemed cool enough to be non-inflamed might have compromised blood supply affecting healing. However, the combination of the Swift Ray 1 device with the Swift Skin and Wound software enables doctors to merge multiple infection identification methods, expanding their diagnostic toolkit without the need for multiple expensive devices. In the future, this technology could enable swift, accurate diagnoses for every patient with wounds, and facilitate more effective telemedicine assessments.

“Research has demonstrated bacterial imaging helps guide clinicians’ work to remove nonviable tissue, yet it cannot identify infection by itself,” said Dr. Jose Ramirez-GarciaLuna of McGill University Health Centre, first author of the study. “Thermography provides insight into the inflammatory and circulatory changes happening under the skin.”

Related Links:
Western University 
Swift Medical 

Platinum Supplier
STI Test
Vivalytic Sexually Transmitted Infection (STI) Array
Gold Supplier
IMRT Thorax Phantom
CIRS Model 002LFC
Patient Monitor
LED Light System

Print article


Surgical Techniques

view channel
Image: The ARC-IM Stimulator with brain-computer interface restores arm, hand, and finger function after spinal cord injury (Photo courtesy of ONWARD Medical)

First-in-Human Implant of Thought-Driven Movement Device to Treat Spinal Cord Injury

In order to walk, signals from the brain are sent to neurons in the lumbosacral part of the spinal cord. When a spinal cord injury occurs, it cuts off this essential communication between the brain and... Read more

Patient Care

view channel
Image: The newly-launched solution can transform operating room scheduling and boost utilization rates (Photo courtesy of Fujitsu)

Surgical Capacity Optimization Solution Helps Hospitals Boost OR Utilization

An innovative solution has the capability to transform surgical capacity utilization by targeting the root cause of surgical block time inefficiencies. Fujitsu Limited’s (Tokyo, Japan) Surgical Capacity... Read more

Health IT

view channel
Image: First ever institution-specific model provides significant performance advantage over current population-derived models (Photo courtesy of Mount Sinai)

Machine Learning Model Improves Mortality Risk Prediction for Cardiac Surgery Patients

Machine learning algorithms have been deployed to create predictive models in various medical fields, with some demonstrating improved outcomes compared to their standard-of-care counterparts.... Read more

Point of Care

view channel
Image: The broad-spectrum POC coagulometer is well-suited for emergency room and emergency vehicle use (Photo courtesy of Perosphere)

Novel POC Coagulometer with Lab-Like Precision to Revolutionize Coagulation Testing

In emergency settings, when patients arrive with a bleed or require urgent surgery, doctors rely solely on clinical judgment to determine if a patient is adequately anticoagulated for reversal treatment.... Read more


view channel
Image: The global surgical lights market is expected to grow by close to USD 0.50 billion from 2022 to 2027 (Photo courtesy of Freepik)

Global Surgical Lights Market Driven by Increasing Number of Procedures

The global surgical lights market is set to witness high growth, largely due to the increasing incidence of chronic illnesses, a surge in demand for cosmetic and plastic surgeries, and untapped opportunities... Read more
Copyright © 2000-2023 Globetech Media. All rights reserved.