Haggai Benvenisti MD , Omer Cohen Msc , Eti Feldman NP , Dan Assaf MD , Moran Jacob Bsc , Eran Bluestein MBA , Gal Strechman Msc , Boris Orkin MD , Hezi Nachman-Farchy Msc , Aviram Nissan MD
{"title":"伤口愈合的热信号","authors":"Haggai Benvenisti MD , Omer Cohen Msc , Eti Feldman NP , Dan Assaf MD , Moran Jacob Bsc , Eran Bluestein MBA , Gal Strechman Msc , Boris Orkin MD , Hezi Nachman-Farchy Msc , Aviram Nissan MD","doi":"10.1016/j.jss.2024.09.043","DOIUrl":null,"url":null,"abstract":"<div><h3>Background</h3><div>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.</div></div><div><h3>Methods</h3><div>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.</div></div><div><h3>Results</h3><div>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.</div></div><div><h3>Conclusions</h3><div>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.</div></div>","PeriodicalId":17030,"journal":{"name":"Journal of Surgical Research","volume":"303 ","pages":"Pages 468-475"},"PeriodicalIF":1.8000,"publicationDate":"2024-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"The Thermal Signature of Wound Healing\",\"authors\":\"Haggai Benvenisti MD , Omer Cohen Msc , Eti Feldman NP , Dan Assaf MD , Moran Jacob Bsc , Eran Bluestein MBA , Gal Strechman Msc , Boris Orkin MD , Hezi Nachman-Farchy Msc , Aviram Nissan MD\",\"doi\":\"10.1016/j.jss.2024.09.043\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>Background</h3><div>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.</div></div><div><h3>Methods</h3><div>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.</div></div><div><h3>Results</h3><div>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.</div></div><div><h3>Conclusions</h3><div>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.</div></div>\",\"PeriodicalId\":17030,\"journal\":{\"name\":\"Journal of Surgical Research\",\"volume\":\"303 \",\"pages\":\"Pages 468-475\"},\"PeriodicalIF\":1.8000,\"publicationDate\":\"2024-10-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Surgical Research\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0022480424005912\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"SURGERY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Surgical Research","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0022480424005912","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"SURGERY","Score":null,"Total":0}
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.
Methods
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.
Results
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.
Conclusions
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.
期刊介绍:
The Journal of Surgical Research: Clinical and Laboratory Investigation publishes original articles concerned with clinical and laboratory investigations relevant to surgical practice and teaching. The journal emphasizes reports of clinical investigations or fundamental research bearing directly on surgical management that will be of general interest to a broad range of surgeons and surgical researchers. The articles presented need not have been the products of surgeons or of surgical laboratories.
The Journal of Surgical Research also features review articles and special articles relating to educational, research, or social issues of interest to the academic surgical community.