Hyperspectral imaging of blood perfusion and chromophore distribution in skin

Hyperspectral imaging is a modality which combines spatial resolution and spectroscopy in one technique. Analysis of hyperspectral data from biological samples is a demanding task due to the large amount of data, and due to the complex optical properties of biological tissue. In this study it was investigated if depth information could be revealed from hyperspectral images using a combination of image analysis and analytic simulations of skin reflectance. It was also investigated if hyperspectral imaging could be utilized to monitor changes in the distribution of hemoglobin species after smoking. Hyperspectral data in the wavelength range 400-1000 nm were collected from the forearm of 15 non-smokers and 5 smokers. The hyperspectral images were analyzed with respect to the distribution of hemoglobin species and vascular structures. Changes in the vascular system due to smoking were also evaluated. Principal component analysis (PCA), Spectral angle mapping (SAM), and Mixture tuned matched filtering (MTMF) were used to enhance vascular structures. Emphasis was put on identifying apparent and true absorption spectra for the present chromophores by combining image analysis and an analytical photon transport model. The results show that the depth resolution of hyperspectral images can be better understood using analytical simulations. Modulation of the chromophore spectra by the optical properties of overlying tissue was found to be an important mechanism causing the depth resolution in hyperspectral images. It was also found that hyperspectral imaging and image analysis can be successfully applied to quantify skin changes following smoking.