Evaluation of the optimized surgical illuminant for enhancement of blood oxygen saturation

In open surgery, observing organ blood circulation and distinguishing artery and vein are important to improve precision of surgery. However, there are some difficulties in this judgement and distinction because there are only slight color differences in the color of ischemic or healthy organs. Peripheral vessels between artery and vein also have subtle difference in their color. The difference in absorption coefficients between oxygenated and deoxygenated hemoglobin mainly affects these characteristics. Therefore, if the illuminant spectrum can be optimized based on the optical properties, there is a possibility to enhance the difference between the two types of vessels and blood-oxygenation levels. To achieve these purposes, we conducted a spectroscopic design of a surgical illuminant combining 14 kinds of commercially available light-emitting diode (LED) spectra by maximizing color differences between blood samples. Spectral reflectance of the blood samples whose oxygen saturation (SO2) measured in advance were employed for computer simulation. In this study, we prototyped a spectrally tunable light source which contains the same LED sets used in the simulation of the surgical illuminant. A conventional illuminant and the designed illuminant spectrum were spectrally adjusted by the spectrally tunable light source to evaluate the effectiveness of the optimal illuminant. Two kinds of cattle blood samples that have different SO2 were enclosed in glass cells and covered with cattle artery for subjective evaluation. Research participants were instructed to compare the color of samples and to sort these blood samples in a SO2 order under the two illuminant conditions. The percentage of correct answers under the designed illuminant was superior to that under the conventional illuminant. This results showed the effectiveness of the designed illuminant.

[1]  Geoffrey I. Webb,et al.  Encyclopedia of Machine Learning , 2011, Encyclopedia of Machine Learning.

[2]  Markku Hauta-Kasari,et al.  Spectral Imaging of the Human Retina and Computationally Determined Optimal Illuminants for Diabetic Retinopathy Lesion Detection , 2011 .

[3]  Zhenrong Zheng,et al.  Optimal illumination for local contrast enhancement based on the human visual system , 2015, Journal of biomedical optics.

[4]  Yu-Ping Hsiao,et al.  Identified early stage mycosis fungoides from psoriasis and atopic dermatitis using non-invasive color contrast enhancement by LEDs lighting , 2015 .

[5]  Riccardo Poli,et al.  Particle swarm optimization , 1995, Swarm Intelligence.

[6]  Hsiang-Chen Wang,et al.  Optimal lighting of RGB LEDs for oral cavity detection. , 2012, Optics express.

[7]  Xu Liu,et al.  Investigation of self-adaptive LED surgical lighting based on entropy contrast enhancing method , 2014 .

[8]  Zhenrong Zheng,et al.  Surgical lighting with contrast enhancement based on spectral reflectance comparison and entropy analysis , 2015, Journal of biomedical optics.

[9]  M. Luo,et al.  Uniform colour spaces based on CIECAM02 colour appearance model , 2006 .

[10]  Yukio Kosugi,et al.  Detection and Analysis of the Intestinal Ischemia Using Visible and Invisible Hyperspectral Imaging , 2010, IEEE Transactions on Biomedical Engineering.

[11]  Piotr Bartczak,et al.  Spectrally optimal illuminations for diabetic retinopathy detection in retinal imaging , 2017 .

[12]  Robert P. Francis,et al.  Active DLP hyperspectral illumination: a noninvasive, in vivo, system characterization visualizing tissue oxygenation at near video rates. , 2011, Analytical chemistry.

[13]  Steven W. Brown,et al.  Illuminants as visualization tool for clinical diagnostics and surgery , 2009, BiOS.

[14]  Kazuya Nakano,et al.  Optimization of Surgical Illuminant Spectra for Organ Microstructure Visualization , 2019, IEEE Access.

[15]  Kazuya Nakano,et al.  Optimal design of illuminant for improving intraoperative color appearance of organs , 2018, Artificial Life and Robotics.

[16]  Hideaki Haneishi,et al.  Improving color appearance of organ in surgery by optimally designed LED illuminant , 2013 .

[17]  Meng-Tsan Tsai,et al.  Visual perception enhancement for detection of cancerous oral tissue by multi-spectral imaging , 2013 .