通过设计不同光学参数的组织仿体,研究吸收、散射对组织荧光光谱及组织漫反射光谱的影响规律,优化经验复原算法,以校正吸收、散射的影响,获得组织的固有荧光光谱。结果显示:使用优化的经验复原算法(经验参数k_x和k_m分别为0.9和-0.8)能够有效降低吸收、散射对荧光强度的影响,且荧光强度与荧光成分的浓度线性相关。在基于皮肤组织荧光光谱法筛查糖尿病的应用研究中应用上述光谱复原算法,结果显示:与原始荧光光谱相比,采用复原后的固有荧光光谱进行糖尿病筛查时,受试者工作特征(ROC)曲线覆盖面积由0.54增加至0.81,在特异性同为70.6%时,敏感性由38.6%增至77.6%。采用组织仿体优化生物组织固有荧光光谱经验复原算法能有效提高荧光光谱的临床应用价值。

Tissue phantoms with different optical parameters are designed to study the influence of absorption and scattering on tissue fluorescence and diffuse reflection spectra. An empirical recovery algorithm is optimized to correct the influence of absorption and scattering and obtain the intrinsic fluorescence spectrum of tissues. The results reveal that the empirical recovery algorithm (experience parameters kx and km are 0.9 and -0.8, respectively) can effectively reduce the influence of absorption and scattering on the fluorescence intensity, and the fluorescence intensity is linearly correlated with the concentration of fluorescence components. When we apply spectral recovery algorithm to the screening of diabetes based on skin tissue fluorescence spectrum, the results reveal that, comparing to the fluorescence spectrum before recovery, the area under receiver operating characteristic (ROC) curve increases from 0.54 to 0.81; besides, the sensitivity also increases from 38.6% to 77.6% when the specificity is 70.6%. Therefore, this study makes a major contribution to research on clinical application by optimizing fluorescence spectrum empirical recovery algorithm with tissue phantoms.