Literature DB >> 26073358

Surgical wound debridement sequentially characterized in a porcine burn model with multispectral imaging.

Darlene R King1, Weizhi Li1, John J Squiers2, Rachit Mohan1, Eric Sellke1, Weirong Mo1, Xu Zhang1, Wensheng Fan1, J Michael DiMaio2, Jeffrey E Thatcher3.   

Abstract

INTRODUCTION: Multispectral imaging (MSI) is an optical technique that measures specific wavelengths of light reflected from wound site tissue to determine the severity of burn wounds. A rapid MSI device to measure burn depth and guide debridement will improve clinical decision making and diagnoses.
METHODOLOGY: We used a porcine burn model to study partial thickness burns of varying severity. We made eight 4 × 4 cm burns on the dorsum of one minipig. Four burns were studied intact, and four burns underwent serial tangential excision. We imaged the burn sites with 400-1000 nm wavelengths.
RESULTS: Histology confirmed that we achieved various partial thickness burns. Analysis of spectral images show that MSI detects significant variations in the spectral profiles of healthy tissue, superficial partial thickness burns, and deep partial thickness burns. The absorbance spectra of 515, 542, 629, and 669 nm were the most accurate in distinguishing superficial from deep partial thickness burns, while the absorbance spectra of 972 nm was the most accurate in guiding the debridement process.
CONCLUSION: The ability to distinguish between partial thickness burns of varying severity to assess whether a patient requires surgery could be improved with an MSI device in a clinical setting.
Copyright © 2015 Elsevier Ltd and ISBI. All rights reserved.

Entities:  

Keywords:  Burns; Debridement; Medical imaging; Multispectral imaging; Optics; Serial tangential excision

Mesh:

Year:  2015        PMID: 26073358     DOI: 10.1016/j.burns.2015.05.009

Source DB:  PubMed          Journal:  Burns        ISSN: 0305-4179            Impact factor:   2.744


  10 in total

Review 1.  Imaging Techniques for Clinical Burn Assessment with a Focus on Multispectral Imaging.

Authors:  Jeffrey E Thatcher; John J Squiers; Stephen C Kanick; Darlene R King; Yang Lu; Yulin Wang; Rachit Mohan; Eric W Sellke; J Michael DiMaio
Journal:  Adv Wound Care (New Rochelle)       Date:  2016-08-01       Impact factor: 4.730

2.  Burn-injured tissue detection for debridement surgery through the combination of non-invasive optical imaging techniques.

Authors:  Juan Heredia-Juesas; Jeffrey E Thatcher; Yang Lu; John J Squiers; Darlene King; Wensheng Fan; J Michael DiMaio; Jose A Martinez-Lorenzo
Journal:  Biomed Opt Express       Date:  2018-03-22       Impact factor: 3.732

3.  Feature Extraction Based Machine Learning for Human Burn Diagnosis From Burn Images.

Authors:  D P Yadav; Ashish Sharma; Madhusudan Singh; Ayush Goyal
Journal:  IEEE J Transl Eng Health Med       Date:  2019-07-18       Impact factor: 3.316

4.  How to create burn porcine models: a systematic review.

Authors:  A Wardhana; R F M Lumbuun; D Kurniasari
Journal:  Ann Burns Fire Disasters       Date:  2018-03-31

5.  Evaluating clinical observation versus Spatial Frequency Domain Imaging (SFDI), Laser Speckle Imaging (LSI) and thermal imaging for the assessment of burn depth.

Authors:  Adrien Ponticorvo; Rebecca Rowland; Melissa Baldado; David M Burmeister; Robert J Christy; Nicole P Bernal; Anthony J Durkin
Journal:  Burns       Date:  2018-10-14       Impact factor: 2.744

6.  Artificial intelligence in the management and treatment of burns: a systematic review.

Authors:  Francisco Serra E Moura; Kavit Amin; Chidi Ekwobi
Journal:  Burns Trauma       Date:  2021-08-19

7.  Deep neural network classification of in vivo burn injuries with different etiologies using terahertz time-domain spectral imaging.

Authors:  Omar B Osman; Zachery B Harris; Mahmoud E Khani; Juin W Zhou; Andrew Chen; Adam J Singer; M Hassan Arbab
Journal:  Biomed Opt Express       Date:  2022-03-03       Impact factor: 3.562

Review 8.  Thermal injury of skin and subcutaneous tissues: A review of experimental approaches and numerical models.

Authors:  Hanglin Ye; Suvranu De
Journal:  Burns       Date:  2016-12-05       Impact factor: 2.744

9.  Machine learning analysis of multispectral imaging and clinical risk factors to predict amputation wound healing.

Authors:  John J Squiers; Jeffrey E Thatcher; David S Bastawros; Andrew J Applewhite; Ronald D Baxter; Faliu Yi; Peiran Quan; Shuai Yu; J Michael DiMaio; Dennis R Gable
Journal:  J Vasc Surg       Date:  2021-07-24       Impact factor: 4.268

Review 10.  Surgical spectral imaging.

Authors:  Neil T Clancy; Geoffrey Jones; Lena Maier-Hein; Daniel S Elson; Danail Stoyanov
Journal:  Med Image Anal       Date:  2020-04-13       Impact factor: 8.545

  10 in total

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