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ALT'23 The 30th International Conference on Advanced Laser Technologies
B-I-26
Multi-parametric, high-resolution imaging of biological tissues relying on endogenous contrast
Zhiyi Liu
State Key Laboratory of Modern Optical Instrumentation, College of Optical Science and Engineering; International Research Center for Advanced Photonics, Zhejiang University, Hangzhou, Zhejiang 310027, China
Email address: liuzhiyi07@zju.edu.cn Disease progression is associated with subtle changes in both cellular metabolism and extracellular matrix organization [1-3]; therefore, sensitive detection of these changes can lead to a better understanding of diseases. In this work, we use two-photon excited fluorescence (TPEF) and second harmonic generation (SHG) to acquire images from cells and collagen fibers, respectively, without the need for any exogenous labels. Based on these images, we have developed quantitative, multi-parametric measures, including optical redox ratio and mitochondrial clustering corresponding to cellular metabolic activity, as well as a series of metrics to represent collagen fiber orientation and organization. A combination of these quantitative metrics can provide systematic investigations of correlation between cells and matrix during progression of diseases. Figure 1 shows representative feature maps of collagen fibers, including orientation, waviness, alignment (represented by the variance metric) and local coverage within normal, benign and malignant cervical tissues. Different hues in maps among these three groups of samples are observed, indicating that the tumor progression alters the spatial characteristics of collagen fibers.
Orientation Waviness Variance Local coverage
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Figure 1. Representative maps of collagen fibers from normal, benign and malignant cervical tissues, revealing fiber features including orientation, waviness, alignment and local coverage.
Overall, this label-free, multi-parametric, high-resolution imaging method of biological tissues provides complementary insights into the functional and structural alterations in diseases, and offers opportunities to study interactions between cells and extracellular matrix as disease progresses.
[1] Liu, Z. et al. Rapid three-dimensional quantification of voxel-wise collagen fiber orientation. Biomed Opt Express 6, 2294-2310 (2015).
[2] Liu, Z. et al. Automated quantification of three-dimensional organization of fiber-like structures in biological tissues. Biomaterials 116, 34-47 (2017).
[3] Liu, Z. et al. Mapping metabolic changes by noninvasive, multiparametric, high-resolution imaging using endogenous contrast. Sci Adv 4, eaap9302 (2018).
