Multifocal noncontact color imaging for depth-sensitive fluorescence measurements of epithelial cancer

Non-contact optical spectroscopy for tumor-sensitive diffuse reflectance and fluorescence measurements on murine subcutaneous tissue models: Monte Carlo modeling and experimental validations

Fiber-optic probes are commonly used in biomedical optical spectroscopy platforms for light delivery and collection. At the same time, it was reported that the inconsistent probe-sample contact could induce significant distortions in measured optical signals, which consequently cause large analysis errors. To address this challenge, non-contact optical spectroscopy has been explored for tissue characterizations. However, existing non-contact optical spectroscopy platforms primarily focused on diffuse reflectance measurements and may still use a fiber probe in which the probe was imaged onto the tissue surface using a lens, which serves as a non-contact probe for the measurements. Here, we report a fiber-probe-free, dark-field-based, non-contact optical spectroscopy for both diffuse reflectance and fluorescence measurements on turbid medium and tissues. To optimize the system design, we developed a novel Monte Carlo method to simulate such a non-contact setup for both diffuse reflectance and fluorescence measurements on murine subcutaneous tissue models with a spherical tumor-like target. We performed Monte Carlo simulations to identify the most tumor-sensitive configurations, from which we found that both the depth of the light focal point in tissue and the lens numerical aperture would dramatically affect the system's tumor detection sensitivity. We then conducted tissue-mimicking phantom studies to solidify these findings. Our reported Monte Carlo technique can be a useful computational tool for designing non-contact optical spectroscopy systems. Our non-contact optical setup and experimental findings will potentially offer a new approach for sensitive optical monitoring of tumor physiology in biological models using a non-contact optical spectroscopy platform to advance cancer research.

Sequential weighted Wiener estimation for extraction of key tissue parameters in color imaging: a phantom study

Key tissue parameters, e.g., total hemoglobin concentration and tissue oxygenation, are important biomarkers in clinical diagnosis for various diseases. Although point measurement techniques based on diffuse reflectance spectroscopy can accurately recover these tissue parameters, they are not suitable for the examination of a large tissue region due to slow data acquisition. The previous imaging studies have shown that hemoglobin concentration and oxygenation can be estimated from color measurements with the assumption of known scattering properties, which is impractical in clinical applications. To overcome this limitation and speed-up image processing, we propose a method of sequential weighted Wiener estimation (WE) to quickly extract key tissue parameters, including total hemoglobin concentration (CtHb), hemoglobin oxygenation (StO2), scatterer density (α), and scattering power (β), from wide-band color measurements. This method takes advantage of the fact that each parameter is sensitive to the color measurements in a different way and attempts to maximize the contribution of those color measurements likely to generate correct results in WE. The method was evaluated on skin phantoms with varying CtHb, StO2, and scattering properties. The results demonstrate excellent agreement between the estimated tissue parameters and the corresponding reference values. Compared with traditional WE, the sequential weighted WE shows significant improvement in the estimation accuracy. This method could be used to monitor tissue parameters in an imaging setup in real time.