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A Multispectral Method to Analyze Optical In Vivo Tissue Characteristics

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E Wisotzky

E Wisotzky1*, A Hilsmann1 , P Eisert1 , (1) Fraunhofer Heinrich Hertz Institute, Berlin, Germany


SU-K-702-9 (Sunday, July 30, 2017) 4:00 PM - 6:00 PM Room: 702

Purpose: Tissue differentiation during surgery is essential as the surgeon has to save important structures while removing pathological lesions. However, it is often very complex as the visual occurrence of living tissue for the surgeon shows no significant differences. The surgeon has to differentiate all tissue types based on own experience and anatomical knowledge. This entails great risk because abnormal anatomy in the operating field displaces normal structures. The upcoming digitalization of information during surgery provides new opportunities of analyzing and visualizing tissue. We developed a multispectral method for in vivo analysis of tissue characteristics of different tissue types.

Methods: To measure the different optical tissue characteristics we used a digital camera system featuring a CMOS sensor as recording device. Since continuous measuring over the entire visible spectrum is not feasible we isolated the tissue characteristics for different predefined wavelengths using spectral bandpass filters in front of the illumination device allowing only the ray of one wavelength band hitting the tissue. We studied 12 different tissue types of 6 patients over 16 wavelengths ranging from 400nm to 700nm with steps and bandwidths of 20nm. For evaluation we analyzed the different intensities of the tissue types over all captured wavelengths.

Results: The spectral tissue behavior is analyzed in the wavelength domain. We are able to verify the well-known spectral behavior of oxygenated (arterial) and deoxygenated (venous) blood to proof our method. For other tissue types (e.g. bone, muscle or fat) we are able to find similar specific points to classify tissue in vivo. Interesting wavelengths are in the range of 530nm-590nm and 640nm-680nm. Additionally, for some tissue types, near-ultraviolet and near-infrared illumination seems to bring more significant differentiation options which need further investigations.

Conclusion: We developed and investigated a multispectral analyzer to detect optical tissue characteristics not visible for human eyes.

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