高分辨率激光散斑成像技术在组织光透明中的应用

Application of High-Resolution Laser Speckle Imaging Technology in Tissue Optical Clearing

摘要: 生物医学成像技术是揭示组织生理功能与诊断疾病的关键工具，但其应用常受限于生物组织(如皮肤、肌肉)内胶原蛋白、细胞等结构引起的光强散射，这已成为制约成像深度与分辨率的根本瓶颈。组织光透明技术通过化学试剂调控组织折射率、破坏散射结构，可显著降低光散射，从而为深层组织成像提供潜在途径。本文设计实验，系统比较了甘油、果糖及柠檬黄三种试剂对离体鸡胸肉的光透明效果，利用USAF 1951分辨率标板定量计算了鸡胸肉样本在甘油、果糖和柠檬黄溶液中浸泡20分钟后的成像分辨率。激光散斑成像(Laser Speckle Imaging, LSCI)作为一种非侵入式血流成像技术，通过分析散斑动态变化实现血流速度与分布的精准量化，但其成像质量高度依赖组织透明度——浑浊组织产生的静态散斑会掩盖血流动态信号，导致分辨率降低。因此，可以在此基础上结合高分辨率激光散斑成像技术，通过计算血流灌注量以及对比度噪声比对活体皮肤光透明的效果进行定量评估。

Abstract: Biomedical imaging technology is a crucial tool for revealing tissue physiological functions and diagnosing diseases. However, its application is often limited by light scattering caused by structures such as collagen and cells within biological tissues (e.g., skin, muscle), which has become a fundamental bottleneck restricting imaging depth and resolution. Tissue optical clearing technology, by using chemical reagents to modulate tissue refractive index and disrupt scattering structures, can significantly reduce light scattering, thereby providing a potential approach for deep tissue imaging. This paper designs experiments to systematically compare the optical clearing effects of three reagents—glycerol, fructose, and tartrazine—on ex vivo chicken breast tissue. The USAF 1951 resolution target was used to quantitatively calculate the imaging resolution of chicken breast samples after immersion in glycerol, fructose, and tartrazine solutions for 20 minutes. Laser Speckle Imaging (LSCI), as a non-invasive blood flow imaging technique, enables precise quantification of blood flow velocity and distribution by analyzing the dynamic changes of speckles. However, its imaging quality highly depends on tissue transparency—static speckles generated by turbid tissues can mask dynamic blood flow signals, leading to reduced resolution. Therefore, based on this, high-resolution laser speckle imaging technology can be combined to quantitatively evaluate the effects of in vivo skin optical clearing by calculating blood perfusion and the contrast-to-noise ratio.