The optical properties of human tissues are an important parameter in medical diagnostics and therapy. The knowledge of these parameters can encourage the development of automated, computer-driven optical tissue analysis methods. We determine the absorption coefficient μa and scattering coefficient of different tissue types obtained during parotidectomy in the wavelength range of 250 to 800 nm. These values are determined by high precision integrating sphere measurements in combination with an optimized inverse Monte Carlo simulation. To conserve the optical behavior of living tissues, the optical spectroscopy measurements are performed immediately after tissue removal. Our study includes fresh samples of the ear, nose, and throat (ENT) region, as muscle tissue, nervous tissue, white adipose tissue, stromal tissue, parotid gland, and tumorous tissue of five patients. The measured behavior of adipose corresponds well with the literature, which sustains the applied method. It is shown that muscle is well supplied with blood as it features the same characteristic peaks at 430 and 555 nm in the absorption curve. The parameter decreases for all tissue types above 570 nm. The accuracy is adequate for the purposes of providing μa and of different human tissue types as muscle, fat, nerve, or gland tissue, which are embedded in large complex structures such as in the ENT area. It becomes possible for the first time to present reasonable results for the optical behavior of human soft tissue located in the ENT area and in the near-UV, visual, and near-infrared areas.
The absorption coefficient μa and scattering coefficient μ´s of different tissue types obtained during parotidectomy are determined in the wavelength range of 250 nm to 800 nm. These values are obtained by high precision integrating sphere measurements in combination with an optimized inverse Monte Carlo simulation (iMCS). To conserve the optical behavior of living tissues, the optical spectroscopy measurements are performed directly after tissue removal. This study includes fresh samples of the ear, nose and throat (ENT) region, as muscle tissue, nervous tissue, white adipose tissue, stromal tissue and parotid gland of five patients. The measured behavior of adipose corresponds well to the literature, which sustains the applied method. It is shown, that muscle is well supplied with blood as it features the same characteristic peaks at 430 nm and 555 nm in the absorption curve. The parameter μ´s decreases for all tissues type above 570 nm. The accuracy is adequate for the purposes of providing μa and μ´s of different human tissue types as muscle, fat or gland tissue, which are embedded in large complex structures such as in the ENT area. It is therefore possible for the first time to present reasonable results for the optical behavior of human soft tissue located in the ENT area and in the near-UV, visual and near-IR areas.
Proc. SPIE. 10951, Medical Imaging 2019: Image-Guided Procedures, Robotic Interventions, and Modeling
KEYWORDS: Signal to noise ratio, Hyperspectral imaging, Optical filters, LED lighting, Visualization, Tissues, Cameras, Sensors, Calibration, Reflectivity, Xenon, Multispectral imaging, In vivo imaging, Tissue optics, Color reproduction
Hyperspectral imaging (HSI) is a non-contact optical imaging technique with the potential to serve as an intraoperative computer-aided diagnostic tool. This work analyzes the optical properties of visible structures in the surgical field for automatic tissue categorization. Building an HSI-based computer-aided tissue analysis system requires accurate ground truth and validation of optical soft tissue properties as these show large variability. In this paper, we introduce and validate two different hyperspectral intraoperative imaging setups and their use for the analysis of optical tissue properties. First, we present an improved multispectral filter-wheel setup integrated into a fully digital microscope. Second, we present a novel setup of two hyperspectral snapshot cameras for intraoperative usage. Both setups are operating in the spectral range of 400 nm up to 975 nm. They are calibrated and validated using the same database and calibration set. For validation, a color chart with 18 well-defined color spectra in the visual range is analyzed. Thus, the results acquired with both settings become transferable and comparable to each other as well as between different interventions. Clinical in-vivo data of two different oral and maxillofacial surgical procedures underline the potential of HSI as an intraoperative diagnostic tool and the clinical usability of both setups. Thereby, we demonstrate their feasibility for the in-vivo analysis and differentiation of different human soft tissues.
We address the automatic differentiation of human tissue using multispectral imaging with promising potential for automatic visualization during surgery. Currently, tissue types have to be continuously differentiated based on the surgeon’s knowledge only. Further, automatic methods based on optical in vivo properties of human tissue do not yet exist, as these properties have not been sufficiently examined. To overcome this, we developed a hyperspectral camera setup to monitor the different optical behavior of tissue types in vivo. The aim of this work is to collect and analyze these behaviors to open up optical opportunities during surgery. Our setup uses a digital camera and several bandpass filters in front of the light source to illuminate different tissue types with 16 specific wavelength ranges. We analyzed the different intensities of eight healthy tissue types over the visible spectrum (400 to 700 nm). Using our setup and sophisticated postprocessing in order to handle motion during capturing, we are able to find tissue characteristics not visible for the human eye to differentiate tissue types in the 16-dimensional wavelength domain. Our analysis shows that this approach has the potential to support the surgeon’s decisions during treatment.