| Photoacoustic imaging and detection methods have the characteristics of high contrast and high penetration depth,and have been widely used in the research of biomedical imaging and detection.The photoacoustic physicochemical spectrum obtained by multi-wavelength photoacoustic measurement can simultaneously reflect the light absorption characteristics and acoustic frequency characteristics of biological tissues.Therefore,it can present biological histochemical composition and microstructure information,and then reflect the "molecular fingerprints of histopathology" "Related disease diagnosis information.The main research content of this paper is the analysis of the quantitative methods of photoacoustic physicochemical spectra.The methods of obtaining chemical information from the photoacoustic physicochemical spectra and the methods of quantification,as well as the methods of obtaining physical information and the methods of quantification are carried out respectively.Research.Taking osteoporosis as the research object,the feasibility of photoacoustic physicochemical spectrum analysis method for the assessment of osteoporosis was explored.Firstly,based on the k-wave fast model and the principle of the generation and propagation of photoacoustic signals,this paper establishes a simulation model of cancellous bone photoacoustic signals,and studies the generation and propagation of photoacoustic signals in bone tissue.Secondly,the numerical simulation was conducted to simulate the photoacoustic signals generated by bone tissues with different bone densities under different wavelength excitations,and the corresponding photoacoustic physicochemical spectrum characteristics are further calculated.Based on the photoacoustic physicochemical spectrum simulation results obtained by numerical simulation,the photoacoustic absorption spectrum(chemical spectrum)is quantitatively analyzed by the spectral unmixing method.The feasibility of the quantitative parameters “relative content” to distinguish the content of various components in different bone tissues is explored.The results show that the relative content of collagen is strongly correlated with the positive staining area of collagen in bone slices,which proves the feasibility of using the quantitative parameter “relative content” obtained by spectral unmixing to quantitatively analyze the chemical composition in bone.Next,in order to further prove the feasibility of the photoacoustic physicochemical spectrum quantification method used,this paper uses the experimental system to obtain the multi-wavelength photoacoustic signals of the osteoporosis group and the control group,and then calculate and obtain their photoacoustic physicochemical spectra respectively.Through the analysis of the experimental results under the laser wavelengths of NIR I and NIR II,it is found that the relative content of collagen is also strongly correlated with the positive staining area in the bone section,which is consistent with the results of the numerical simulation,further verifying the accuracy of the "relative content".At the same time,it also reversed the relative content of other chemical components in bone tissue,including minerals,lipids,water,and blood.By comparing the quantitative results of the osteoporosis group and the control group,it proved that the use of "relative content" can distinguish porous bone and healthy bone.Through quantitative analysis of the experimental results of the photoacoustic power spectrum(physical spectrum)at NIR I,the results show that the slope of the osteoporosis group is generally lower than that of the control group,which verified that The feasibility of the quantitative parameter "slope" of the photoacoustic power spectrum to distinguish the cluster size in the bone.The research in this article proves that the quantitative parameters "relative content" and "slope" of the photoacoustic physicochemical spectrum can be used for the assessment of osteoporosis,and then proves the feasibility of the photoacoustic physicochemical spectrum for bone assessment,and Its application prospects in bone detection. |