Nonlinear optical microscopy: use of second harmonic generation and two-photon microscopy for automated quantitative liver fibrosis studies

Abstract

Liver fibrosis is associated with an abnormal increase in an extracellular matrix in chronic liver diseases. Quantitative characterization of fibrillar collagen in intact tissue is essential for both fibrosis studies and clinical applications. Commonly used methods, histological staining followed by either semiquantitative or computerized image analysis, have limited sensitivity, accuracy, and operator-dependent variations. The fibrillar collagen in sinusoids of normal livers could be observed through second-harmonic generation (SHG) microscopy. The two-photon excited fluorescence (TPEF) images, recorded simultaneously with SHG, clearly revealed the hepatocyte morphology. We have systematically optimized the parameters for the quantitative SHG/TPEF imaging of liver tissue and developed fully automated image analysis algorithms to extract the information of collagen changes and cell necrosis. Subtle changes in the distribution and amount of collagen and cell morphology are quantitatively characterized in SHG/TPEF images. By comparing to traditional staining, such as Masson's trichrome and Sirius red, SHG/TPEF is a sensitive quantitative tool for automated collagen characterization in liver tissue. Our system allows for enhanced detection and quantification of sinusoidal collagen fibers in fibrosis research and clinical diagnostics.

Precise, motion-free polarization control in Second Harmonic Generation microscopy using a liquid crystal modulator in the infinity space

“…Many metrics have been developed to exploit these differences [13]. For example, several schemes based on analyzing topographic patterns using image processing techniques including fast Fourier transforms, wavelet transforms, Helmholtz analysis, and grey scale co-occurrence matrix have been implemented [11,[14][15][16][17][18].…”

Texture analysis applied to second harmonic generation image data for ovarian cancer classification

“…SHG microscopy has already emerged as a highly sensitive/ specific probe of collagen architecture changes in several diseases, including many cancers, 10,11,[14][15][16][17][18] connective tissue disorders, 19,20 and fibroses. 21,22 All these diseases are characterized by changes in alterations of collagen density, fibrillar organization, collagen isoform distribution, and combinations thereof. We previously utilized three-dimensional (3-D) imaging in combination with the measurement of bulk optical properties and Monte Carlo simulations to differentiate normal ovarian stroma and high grade serous carcinomas.…”

Measurement of Friction-induced Changes in Pig Aorta Fibre Organization by Non-invasive Imaging as a Model for Detecting the Tissue Response to Endovascular Catheters

“…However, despite these advantages, it is only over the last few years that SHG imaging of collagen structures in tissue has begun to be adopted more widely. A recent review was published on the development and burgeoning use of SHG imaging in the clinic to investigate collagen remodelling in cancer in ex vivo and in vivo human tissue [28]; changes in collagen structure during fibrosis are also being monitored; ex vivo in humans, in vivo in animals, by SHG imaging [29][30][31]. In addition SHG imaging is now playing an important role in non-invasive imaging of collagen structure, formation and remodelling in tissue engineering and regenerative medicine, as reviewed recently by Vielreciher et al [32].…”