Accurate determination of the optical properties of biological tissues enables quantitative understanding of light propagation in these tissues for optical diagnosis and treatment applications.The absorption(μa)and s...Accurate determination of the optical properties of biological tissues enables quantitative understanding of light propagation in these tissues for optical diagnosis and treatment applications.The absorption(μa)and scattering(μs)coe±cients of biological tissues are inversely analyzed from their diffuse re°ectance(R)and total transmittance(T),which are measured using a double integrating spheres(DIS)system.The inversion algorithms,for example,inverse adding doubling method and inverse Monte Carlo method,are sensitive to noise signals during the DIS measurements,resulting in reduced accuracy during determination.In this study,we propose an arti ficial neural network(ANN)to estimateμa andμs at a target wavelength from the R and T spectra measured via the DIS to reduce noise in the optical properties.Approximate models of the optical properties and Monte Carlo calculations that simulated the DIS measurements were used to generate spectral datasets comprisingμa,μs,R and T.Measurement noise signals were added to R and T,and the ANN model was then trained using the noise-added datasets.Numerical results showed that the trained ANN model reduced the effects of noise inμa andμs estimation.Experimental veri fication indicated noise-reduced estimation from the R and T values measured by the DIS with a small number of scans on average,resulting in measurement time reduction.The results demonstrated the noise robustness of the proposed ANN-based method for optical properties determination and will contribute to shorter DIS measurement times,thus reducing changes in the optical properties due to desiccation of the samples.展开更多
A quantitative analysis method of CO_(2) laser treatments promotes laser treatment performance and rapid clinical application of novel treatment devices.The in silico clinical trial approach,which is based on computat...A quantitative analysis method of CO_(2) laser treatments promotes laser treatment performance and rapid clinical application of novel treatment devices.The in silico clinical trial approach,which is based on computational simulation of light-tissue interactions using the mathematical model,can provide quantitative data.Although several simulation methods of laser tissue vaporization with CO_(2) laser treatments have been proposed,validations of the CO_(2) laser wavelength have been insuffcient.In this study,we demonstrated a tissue vaporization simulation using a CO_(2) laser and performed the experimental validation using a hydrogel phantom with constant physical parameters to evaluate the simulation accuracy of the vaporization process.The laser tissue vaporization simulation consists of the calculation of light transport,photothermal conversion,thermal diffusion,and phase change in the tissue.The vaporization width,depth,and area with CO_(2) laser irradiation to a tissue model were simulated.The simulated results differed from the actual vaporization width and depth by approximately 20%and 30%,respectively,because of the solubilization of the hydrogel phantom.Alternatively,the simulation vaporization area for all light irradiation parameters,which is related to the vaporization amount,agreed well with the actual vaporization values.These results suggest that the computational simulation can be used to evaluate the amount of tissue vaporization in the safety and effectiveness analysis of CO_(2) laser treatments.展开更多
基金supported by the Japan Society for the Promotion of Science KAKENHI(Grant numbers:20H04549 and 19K12822)the Japan Science and Technology Agency ACT–X(Grant Number:JPMJAX21K7).
文摘Accurate determination of the optical properties of biological tissues enables quantitative understanding of light propagation in these tissues for optical diagnosis and treatment applications.The absorption(μa)and scattering(μs)coe±cients of biological tissues are inversely analyzed from their diffuse re°ectance(R)and total transmittance(T),which are measured using a double integrating spheres(DIS)system.The inversion algorithms,for example,inverse adding doubling method and inverse Monte Carlo method,are sensitive to noise signals during the DIS measurements,resulting in reduced accuracy during determination.In this study,we propose an arti ficial neural network(ANN)to estimateμa andμs at a target wavelength from the R and T spectra measured via the DIS to reduce noise in the optical properties.Approximate models of the optical properties and Monte Carlo calculations that simulated the DIS measurements were used to generate spectral datasets comprisingμa,μs,R and T.Measurement noise signals were added to R and T,and the ANN model was then trained using the noise-added datasets.Numerical results showed that the trained ANN model reduced the effects of noise inμa andμs estimation.Experimental veri fication indicated noise-reduced estimation from the R and T values measured by the DIS with a small number of scans on average,resulting in measurement time reduction.The results demonstrated the noise robustness of the proposed ANN-based method for optical properties determination and will contribute to shorter DIS measurement times,thus reducing changes in the optical properties due to desiccation of the samples.
基金supported by the Japan Society for the Promotion of Science KAKENHI(contract grant numbers:20H04549,19K12822).
文摘A quantitative analysis method of CO_(2) laser treatments promotes laser treatment performance and rapid clinical application of novel treatment devices.The in silico clinical trial approach,which is based on computational simulation of light-tissue interactions using the mathematical model,can provide quantitative data.Although several simulation methods of laser tissue vaporization with CO_(2) laser treatments have been proposed,validations of the CO_(2) laser wavelength have been insuffcient.In this study,we demonstrated a tissue vaporization simulation using a CO_(2) laser and performed the experimental validation using a hydrogel phantom with constant physical parameters to evaluate the simulation accuracy of the vaporization process.The laser tissue vaporization simulation consists of the calculation of light transport,photothermal conversion,thermal diffusion,and phase change in the tissue.The vaporization width,depth,and area with CO_(2) laser irradiation to a tissue model were simulated.The simulated results differed from the actual vaporization width and depth by approximately 20%and 30%,respectively,because of the solubilization of the hydrogel phantom.Alternatively,the simulation vaporization area for all light irradiation parameters,which is related to the vaporization amount,agreed well with the actual vaporization values.These results suggest that the computational simulation can be used to evaluate the amount of tissue vaporization in the safety and effectiveness analysis of CO_(2) laser treatments.
