Literature DB >> 25124513

Validation of a laser-assisted wound measurement device in a wound healing model.

Ryan S Constantine1, Jessica D Bills1, Lawrence A Lavery1, Kathryn E Davis2.   

Abstract

In the treatment and monitoring of a diabetic or chronic wound, accurate and repeatable measurement of the wound provides indispensable data for the patient's medical record. This study aims to measure the accuracy of the laser-assisted wound measurement (LAWM) device against traditional methods in the measurement of area, depth and volume. We measured four 'healing' wounds in a Play-Doh(®) -based model over five subsequent states of wound healing progression in which the model was irregularly filled in to replicate the healing process. We evaluated the LAWM device against traditional methods including digital photograph assessment with National Institutes of Health ImageJ software, measurements of depth with a ruler and weight-to-volume assessment with dental paste. Statistical analyses included analysis of variance (ANOVA) and paired t-tests. We demonstrate that there are significantly different and nearly statistically significant differences between traditional ruler depth measurement and LAWM device measurement, but there are no statistically significant differences in area measurement. Volume measurements were found to be significantly different in two of the wounds. Rate of percentage change was analysed for volume and depth in the wound healing model, and the LAWM device was not significantly different than the traditional measurement technique. While occasionally inaccurate in its absolute measurement, the LAWM device is a useful tool in the clinician's arsenal as it reliably measures rate of percentage change in depth and volume and offers a potentially aseptic alternative to traditional measurement techniques.
© 2014 The Authors. International Wound Journal © 2014 Medicalhelplines.com Inc and John Wiley & Sons Ltd.

Entities:  

Keywords:  ARANZ; Medical imaging; Wound healing; Wound measurement; Wound volume

Mesh:

Year:  2014        PMID: 25124513      PMCID: PMC7949841          DOI: 10.1111/iwj.12328

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


  18 in total

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Authors:  Catherine E Hammond; Mark A Nixon
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  4 in total

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Journal:  Adv Wound Care (New Rochelle)       Date:  2019-10-23       Impact factor: 4.730

4.  Software-Based Method for Automated Segmentation and Measurement of Wounds on Photographs Using Mask R-CNN: a Validation Study.

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  4 in total

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