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Concurrent validation and reliability of digital image analysis of granulation tissue color for clinical pressure ulcers
Author(s) -
Iizaka Shinji,
Sugama Junko,
Nakagami Gojiro,
Kaitani Toshiko,
Naito Ayumi,
Koyanagi Hiroe,
Matsuo Junko,
Kadono Takafumi,
Konya Chizuko,
Sanada Hiromi
Publication year - 2011
Publication title -
wound repair and regeneration
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.847
H-Index - 109
eISSN - 1524-475X
pISSN - 1067-1927
DOI - 10.1111/j.1524-475x.2011.00686.x
Subject(s) - erythema , granulation tissue , intraclass correlation , colorimeter , intensity (physics) , biomedical engineering , reliability (semiconductor) , medicine , materials science , reproducibility , mathematics , surgery , optics , wound healing , statistics , physics , power (physics) , quantum mechanics
Granulation tissue color is one indicator for pressure ulcer (PU) assessment. However, it entails a subjective evaluation only, and quantitative methods have not been established. We developed color indicators from digital image analysis and investigated their concurrent validity and reliability for clinical PUs. A cross‐sectional study was conducted on 47 patients with 55 full‐thickness PUs. After color calibration, a wound photograph was converted into three images representing red color: erythema index (EI), modified erythema index with additional color calibration (granulation red index [GRI]), and , which represents the artificially created red–green axis of L * a * b * color space. The mean intensity of the granulation tissue region and the percentage of pixels exceeding the optimal cutoff intensity (% intensity) were calculated. Mean GRI (ρ=0.39, p =0.007) and (ρ=0.55, p <0.001), as well as their % intensity indicators, showed positive correlations with a * measured by tristimulus colorimeter, but erythema index did not. They were correlated with hydroxyproline concentration in wound fluid, healthy granulation tissue area, and blood hemoglobin level. Intra‐ and interrater reliability of the indicator calculation using both GRI and had an intraclass correlation coefficient >0.9. GRI and from digital image analysis can quantitatively evaluate granulation tissue color of clinical PUs.