Quantitative multi-spectral oxygen saturation measurements independent of tissue optical properties

Imaging of tissue oxygenation is important in several applications associated with patient care. Optical sensing is commonly applied for assessing oxygen saturation but is often restricted to local measurements or else it requires spectral and spatial information at the expense of time. Many methods proposed so far require assumptions on the properties of measured tissue. In this study we investigated a computational method that uses only multispectral information and quantitatively computes tissue oxygen saturation independently of tissue optical properties. The method is based on linear transformations of measurements in three isosbestic points. We investigated the ideal isosbestic point combination out of six isosbestic points available for measurement in the visible and near-infrared region that enable accurate oxygen saturation computation. We demonstrate this method on controlled tissue mimicking phantoms having different optical properties and validated the measurements using a gas analyzer. A mean error of 2.9 ± 2.8% O₂Sat was achieved. Finally, we performed pilot studies in tissues in-vivo by measuring dynamic changes in fingers subjected to vascular occlusion, the vasculature of mouse ears and exposed mouse organs. Selected steps of spectral transformations applied to oxygenation spectra. The original reflectance spectrum M(λ) is transformed in step 1 to overlap with reference spectra (grey) in three isosbestic points, resulting in M″(λ). In step 2, the gradient of M″(λ) is computed resulting in M″_grad(λ), which can be used for quantitative oxygenation computation. This paper proposes a new methodology using optical imaging technology for accurate detection of blood oxygenation. Low oxygen saturation values of blood often result from or can be the cause of a variety of diseases, like different types of cancer or diabetes. Accurate blood oxygenation monitoring is therefore crucial and optical imaging offer the possibility of early, rapid and noninvasive detection of malfunctions of the body.