The Thermal Signature of Wound Healing

Despite major efforts in prevention, surgical site infections (SSIs) remain a burden on patients and the healthcare system and are associated with significant morbidity. SSIs are one of the costliest healthcare-associated infections. The diagnosis of SSIs is based mainly on clinical assessment, whic...

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Veröffentlicht in:The Journal of surgical research 2024-11, Vol.303, p.468-475
Hauptverfasser: Benvenisti, Haggai, Cohen, Omer, Feldman, Eti, Assaf, Dan, Jacob, Moran, Bluestein, Eran, Strechman, Gal, Orkin, Boris, Nachman-Farchy, Hezi, Nissan, Aviram
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Sprache:eng
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Zusammenfassung:Despite major efforts in prevention, surgical site infections (SSIs) remain a burden on patients and the healthcare system and are associated with significant morbidity. SSIs are one of the costliest healthcare-associated infections. The diagnosis of SSIs is based mainly on clinical assessment, which may result in a delay in detection. The ability to detect SSIs in subclinical phase and initiate effective therapy earlier may reduce morbidity and hospital stay. In this study, we attempted to utilize long-wave infrared (LWIR) imaging to define the healing process of the surgical site and to detect abnormal healing. In this prospective study, 50 patients undergoing elective abdominal surgery had LWIR images of their incision obtained at determined intervals from their operation to discharge. Images were processed with proprietary algorithms to create a thermal topograph used to define the healing process. Images of 45 patients were available for a final review. Of these 45 patients, 10 patients developed SSIs. Using the thermal topograph, 10 criteria for image analysis were defined, yielding a prediction of six out of the 10 SSIs and 35 out of the 35 normal healing wounds. Sensitivity was 60%, specificity was 100%, positive predictive value was 100%, and negative predictive value was 90.1%, with 92% accuracy. A preliminary program was created that allows trained users to methodically evaluate images providing them with a risk estimate. In this preliminary study, LWIR analysis of surgical wounds was able to identify normal and abnormal wound healing. Further large-scale studies are needed to validate results.
ISSN:0022-4804
1095-8673
1095-8673
DOI:10.1016/j.jss.2024.09.043