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Investigation of the performance of hyperspectral imaging by principal component analysis in the prediction of healing of diabetic foot ulcers

Yang, Qian; Sun, Shen; Jeffcoate, William; Clark, Daniel; Musgove, Alison; Game, Fran; Morgan, Stephen


Qian Yang

Shen Sun

William Jeffcoate

Daniel Clark

Alison Musgove

Fran Game


Diabetic foot ulcers are a major complication of diabetes and present a considerable burden for both patients and health care providers. As healing often takes many months, a method of determining which ulcers would be most likely to heal would be of great value in identifying patients who require further intervention at an early stage. Hyperspectral imaging (HSI) is a tool that has the potential to meet this clinical need. Due to the different absorption spectra of oxy- and deoxyhemoglobin, in biomedical HSI the majority of research has utilized reflectance spectra to estimate oxygen saturation (SpO2) values from peripheral tissue. In an earlier study, HSI of 43 patients with diabetic foot ulcers at the time of presentation revealed that ulcer healing by 12 weeks could be predicted by the assessment of SpO2 calculated from these images. Principal component analysis (PCA) is an alternative approach to analyzing HSI data. Although frequently applied in other fields, mapping of SpO2 is more common in biomedical HSI. It is therefore valuable to compare the performance of PCA with SpO2 measurement in the prediction of wound healing. Data from the same study group have now been used to examine the relationship between ulcer healing by 12 weeks when the results of the original HSI are analyzed using PCA. At the optimum thresholds, the sensitivity of prediction of healing by 12 weeks using PCA (87.5%) was greater than that of SpO2 (50.0%), with both approaches showing equal specificity (88.2%). The positive predictive value of PCA and oxygen saturation analysis was 0.91 and 0.86, respectively, and a comparison by receiver operating characteristic curve analysis revealed an area under the curve of 0.88 for PCA compared with 0.66 using SpO2 analysis. It is concluded that HSI may be a better predictor of healing when analyzed by PCA than by SpO2.


Yang, Q., Sun, S., Jeffcoate, W., Clark, D., Musgove, A., Game, F., & Morgan, S. (2018). Investigation of the performance of hyperspectral imaging by principal component analysis in the prediction of healing of diabetic foot ulcers. Journal of Imaging, 4(12), Article 144.

Journal Article Type Article
Acceptance Date Dec 4, 2018
Online Publication Date Dec 7, 2018
Publication Date Dec 7, 2018
Deposit Date Dec 20, 2018
Publicly Available Date Dec 21, 2018
Journal Journal of Imaging
Print ISSN 2313-433X
Publisher MDPI
Peer Reviewed Peer Reviewed
Volume 4
Issue 12
Article Number 144
Public URL
Publisher URL


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