Optical coherence tomography modeling incorporating scattering, absorption, and multiple reflections

Development of a non-invasive method for skin cholesterol detection: pre-clinical assessment in atherosclerosis screening

BACKGROUND

Establishing a high-accuracy and non-invasive method is essential for evaluating cardiovascular disease. Skin cholesterol is a novel marker for assessing the risk of atherosclerosis and can be used as an independent risk factor of early assessment of atherosclerotic risk.

METHODS

We propose a non-invasive skin cholesterol detection method based on absorption spectroscopy. Detection reagents specifically bind to skin cholesterol and react with indicator to produce colored products, the skin cholesterol content can be obtained through absorption spectrum information on colored products detected by non-invasive technology. Gas chromatography is used to measure cholesterol extracted from the skin to verify the accuracy and reliability of the non-invasive test method. A total of 342 subjects were divided into normal group (n = 115), disease group (n = 110) and risk group (n = 117). All subjects underwent non-invasive skin cholesterol test. The diagnostic accuracy of the measured value was analyzed by receiver-operating characteristic (ROC) curve.

RESULTS

The proposed method is able to identify porcine skin containing gradient concentration of cholesterol. The values measured by non-invasive detection method were significantly correlated with gas chromatography measured results (r = 0.9074, n = 73, p < 0.001). Bland-Altman bias was - 72.78 ± 20.03 with 95% limits of agreement - 112.05 to - 33.51, falling within the prespecified clinically non-significant range. We further evaluated the method of patients with atherosclerosis and risk population as well as normal group, patients and risk atherosclerosis group exhibited higher skin cholesterol content than normal group (all P < 0.001). The area under the ROC curve for distinguishing Normal/Disease group was 0.8642 (95% confidence interval, 0.8138 to 0.9146), meanwhile, the area under the ROC curve for distinguishing Normal/Risk group was 0.8534 (95% confidence interval, 0.8034 to 0.9034).

CONCLUSIONS

The method demonstrated its capability of detecting different concentration of skin cholesterol. This non-invasive skin cholesterol detection system may potentially be used as a risk assessment tool for atherosclerosis screening, especially for a large population.