Literature DB >> 32830440

Wound assessment, imaging and monitoring systems in diabetic foot ulcers: A systematic review.

Kai Siang Chan1,2, Zhiwen Joseph Lo2,3.   

Abstract

Patients with diabetes mellitus have a lifetime risk of 15% to 25% of developing diabetic foot ulcers (DFUs). DFU is associated with significant morbidity and mortality. Wound imaging systems are useful adjuncts in monitoring of wound progress. Our study aims to review existing literature on the available wound assessment and monitoring systems for DFU. This is a systematic review of articles from PubMed and Embase (1974 - March 2020). All studies related to wound assessment or monitoring systems in DFUs were included. Articles on other types of wounds, review articles, and non-English texts were excluded. Outcomes include clinical use, wound measurement statistics, hospital system integration, and other advantages and challenges. The search identified 531 articles. Seventeen full-text studies were eligible for the final analysis. Five modalities were identified: (a) computer applications or hand-held devices (n = 5), (b) mobile applications (n = 2), (c) optical imaging (n = 2), (d) spectroscopy or hyperspectral imaging (n = 4), and (e) artificial intelligence (n = 4). Most studies (n = 16) reported on wound assessment or monitoring. Only one study reported on data capturing. Two studies on the use of computer applications reported low inter-observer variability in wound measurement (inter-rater reliability >0.99, and inter-observer variability 15.9% respectively). Hand-held commercial devices demonstrated high accuracy (relative error of 2.1%-6.8%). Use of spectroscopy or hyperspectral imaging in prediction of wound healing has a sensitivity and specificity of 80% to 90% and 74%to 86%, respectively. Majority of the commercially available wound assessment systems have not been reviewed in the literature on measurement accuracy. In conclusion, most imaging systems are superior to traditional wound assessment. Wound imaging systems should be used as adjuncts in DFU monitoring.
© 2020 Medicalhelplines.com Inc (3M) and John Wiley & Sons Ltd.

Entities:  

Keywords:  artificial intelligence; diabetic foot; mobile applications; wound healing; wounds and injuries

Year:  2020        PMID: 32830440      PMCID: PMC7948910          DOI: 10.1111/iwj.13481

Source DB:  PubMed          Journal:  Int Wound J        ISSN: 1742-4801            Impact factor:   3.315


  36 in total

1.  Methodological index for non-randomized studies (minors): development and validation of a new instrument.

Authors:  Karem Slim; Emile Nini; Damien Forestier; Fabrice Kwiatkowski; Yves Panis; Jacques Chipponi
Journal:  ANZ J Surg       Date:  2003-09       Impact factor: 1.872

2.  Digital planimetry results in more accurate wound measurements: a comparison to standard ruler measurements.

Authors:  Lee C Rogers; Nicholas J Bevilacqua; David G Armstrong; George Andros
Journal:  J Diabetes Sci Technol       Date:  2010-07-01

3.  Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement.

Authors:  David Moher; Alessandro Liberati; Jennifer Tetzlaff; Douglas G Altman
Journal:  Ann Intern Med       Date:  2009-07-20       Impact factor: 25.391

4.  Time-Saving Comparison of Wound Measurement Between the Ruler Method and the Swift Skin and Wound App.

Authors:  Yunghan Au; Benjamin Beland; John A E Anderson; Denis Sasseville; Sheila C Wang
Journal:  J Cutan Med Surg       Date:  2019 Mar/Apr       Impact factor: 2.092

5.  Boundary determination of foot ulcer images by applying the associative hierarchical random field framework.

Authors:  Lei Wang; Peder C Pedersen; Emmanuel Agu; Diane Strong; Bengisu Tulu
Journal:  J Med Imaging (Bellingham)       Date:  2019-04-21

6.  Diabetic foot complications and their risk factors from a large retrospective cohort study.

Authors:  Khalid Al-Rubeaan; Mohammad Al Derwish; Samir Ouizi; Amira M Youssef; Shazia N Subhani; Heba M Ibrahim; Bader N Alamri
Journal:  PLoS One       Date:  2015-05-06       Impact factor: 3.240

7.  Remote assessment of diabetic foot ulcers using a novel wound imaging system.

Authors:  Frank L Bowling; Laurie King; James A Paterson; Jingyi Hu; Benjamin A Lipsky; David R Matthews; Andrew J M Boulton
Journal:  Wound Repair Regen       Date:  2010-12-06       Impact factor: 3.617

Review 8.  Diabetic foot disease: From the evaluation of the "foot at risk" to the novel diabetic ulcer treatment modalities.

Authors:  Noha Amin; John Doupis
Journal:  World J Diabetes       Date:  2016-04-10

9.  The validity and reliability of remote diabetic foot ulcer assessment using mobile phone images.

Authors:  Jaap J van Netten; Damien Clark; Peter A Lazzarini; Monika Janda; Lloyd F Reed
Journal:  Sci Rep       Date:  2017-08-25       Impact factor: 4.379

10.  Comparison of standardized clinical evaluation of wounds using ruler length by width and Scout length by width measure and Scout perimeter trace.

Authors:  Diane Langemo; James Spahn; Thomas Spahn; V Chowdry Pinnamaneni
Journal:  Adv Skin Wound Care       Date:  2015-03       Impact factor: 2.347

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  4 in total

1.  Wound assessment, imaging and monitoring systems in diabetic foot ulcers: A systematic review.

Authors:  Kai Siang Chan; Zhiwen Joseph Lo
Journal:  Int Wound J       Date:  2020-08-23       Impact factor: 3.315

2.  Risk profiling in the prevention and treatment of chronic wounds using artificial intelligence.

Authors:  Karen Cross; Keith Harding
Journal:  Int Wound J       Date:  2022-10       Impact factor: 3.099

3.  Clinical validation of an artificial intelligence-enabled wound imaging mobile application in diabetic foot ulcers.

Authors:  Kai Siang Chan; Yam Meng Chan; Audrey Hui Min Tan; Shanying Liang; Yuan Teng Cho; Qiantai Hong; Enming Yong; Lester Rhan Chaen Chong; Li Zhang; Glenn Wei Leong Tan; Sadhana Chandrasekar; Zhiwen Joseph Lo
Journal:  Int Wound J       Date:  2021-05-04       Impact factor: 3.315

4.  Clinical validation of a machine-learning-based handheld 3-dimensional infrared wound imaging device in venous leg ulcers.

Authors:  Kai Siang Chan; Shanying Liang; Yuan Teng Cho; Yam Meng Chan; Audrey Hui Min Tan; Sivakami Muthuveerappa; Tina Peiting Lai; Cheng Cheng Goh; Annie Joseph; Qiantai Hong; Enming Yong; Li Zhang; Lester Rhan Chaen Chong; Glenn Wei Leong Tan; Sadhana Chandrasekar; Zhiwen Joseph Lo
Journal:  Int Wound J       Date:  2021-06-14       Impact factor: 3.315

  4 in total

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