Polarization-resolved second harmonic microscopy of skeletal muscle in sepsis

Investigating cartilage-related diseases by polarization-resolved second harmonic generation (P-SHG) imaging

Establishing quantitative parameters for differentiating between healthy and diseased cartilage tissues by examining collagen fibril degradation patterns facilitates the understanding of tissue characteristics during disease progression. These findings could also complement existing clinical methods used to diagnose cartilage-related diseases. In this study, cartilage samples from normal, osteoarthritis (OA), and rheumatoid arthritis (RA) tissues were prepared and analyzed using polarization-resolved second harmonic generation (P-SHG) imaging and quantitative image texture analysis. The enhanced molecular contrast obtained from this approach is expected to aid in distinguishing between healthy and diseased cartilage tissues. P-SHG image analysis revealed distinct parameters in the cartilage samples, reflecting variations in collagen fibril arrangement and organization across different pathological states. Normal tissues exhibited distinct χ33/χ31 values compared with those of OA and RA, indicating collagen type transition and cartilage erosion with chondrocyte swelling, respectively. Compared with those of normal tissues, OA samples demonstrated a higher degree of linear polarization, suggesting increased tissue birefringence due to the deposition of type-I collagen in the extracellular matrix. The distribution of the planar orientation of collagen fibrils revealed a more directional orientation in the OA samples, associated with increased type-I collagen, while the RA samples exhibited a heterogeneous molecular orientation. This study revealed that the imaging technique, the quantitative analysis of the images, and the derived parameters presented in this study could be used as a reference for disease diagnostics, providing a clear understanding of collagen fibril degradation in cartilage.

Categorization of collagen type I and II blend hydrogel using multipolarization SHG imaging with ResNet regression

Previously, the discrimination of collagen types I and II was successfully achieved using peptide pitch angle and anisotropic parameter methods. However, these methods require fitting polarization second harmonic generation (SHG) pixel-wise information into generic mathematical models, revealing inconsistencies in categorizing collagen type I and II blend hydrogels. In this study, a ResNet approach based on multipolarization SHG imaging is proposed for the categorization and regression of collagen type I and II blend hydrogels at 0%, 25%, 50%, 75%, and 100% type II, without the need for prior time-consuming model fitting. A ResNet model, pretrained on 18 progressive polarization SHG images at 10° intervals for each percentage, categorizes the five blended collagen hydrogels with a mean absolute error (MAE) of 0.021, while the model pretrained on nonpolarization images exhibited 0.083 MAE. Moreover, the pretrained models can also generally regress the blend hydrogels at 20%, 40%, 60%, and 80% type II. In conclusion, the multipolarization SHG image-based ResNet analysis demonstrates the potential for an automated approach using deep learning to extract valuable information from the collagen matrix.

SEMPAI: a Self-Enhancing Multi-Photon Artificial Intelligence for Prior-Informed Assessment of Muscle Function and Pathology

Deep learning (DL) shows notable success in biomedical studies. However, most DL algorithms work as black boxes, exclude biomedical experts, and need extensive data. This is especially problematic for fundamental research in the laboratory, where often only small and sparse data are available and the objective is knowledge discovery rather than automation. Furthermore, basic research is usually hypothesis-driven and extensive prior knowledge (priors) exists. To address this, the Self-Enhancing Multi-Photon Artificial Intelligence (SEMPAI) that is designed for multiphoton microscopy (MPM)-based laboratory research is presented. It utilizes meta-learning to optimize prior (and hypothesis) integration, data representation, and neural network architecture simultaneously. By this, the method allows hypothesis testing with DL and provides interpretable feedback about the origin of biological information in 3D images. SEMPAI performs multi-task learning of several related tasks to enable prediction for small datasets. SEMPAI is applied on an extensive MPM database of single muscle fibers from a decade of experiments, resulting in the largest joint analysis of pathologies and function for single muscle fibers to date. It outperforms state-of-the-art biomarkers in six of seven prediction tasks, including those with scarce data. SEMPAI's DL models with integrated priors are superior to those without priors and to prior-only approaches.

Characterization of collagen response to bone fracture healing using polarization-SHG

In this study, we extend on the three parameter analysis approach of utilizing a noninvasive dual-liquid-crystal-based polarization-resolved second harmonic generation (SHG) microscopy to facilitate the quantitative characterization of collagen types I and II in fracture healing tissues. The SHG images under various linear and circular polarization states are analyzed and quantified in terms of the peptide pitch angle (PA), SHG-circular dichroism (CD), and anisotropy parameter (AP). The results show that the collagen PA has a value of 49.26° after 2 weeks of fracture healing (collagen type II domination) and 49.05° after 4 weeks (collagen type I domination). Moreover, the SHG-CD and AP values of the different collagen types differ by 0.05. The change tendencies of the extracted PA, SHG-CD, and AP parameters over the healing time are consistent with the collagen properties of healthy nonfractured bone. Thus, the feasibility of the proposed dual-liquid-crystal-based polarization-SHG method for differentiating between collagen types I and II in bone fracture healing tissue is confirmed.

Machine learning-enabled cancer diagnostics with widefield polarimetric second-harmonic generation microscopy

The extracellular matrix (ECM) collagen undergoes major remodeling during tumorigenesis. However, alterations to the ECM are not widely considered in cancer diagnostics, due to mostly uniform appearance of collagen fibers in white light images of hematoxylin and eosin-stained (H&E) tissue sections. Polarimetric second-harmonic generation (P-SHG) microscopy enables label-free visualization and ultrastructural investigation of non-centrosymmetric molecules, which, when combined with texture analysis, provides multiparameter characterization of tissue collagen. This paper demonstrates whole slide imaging of breast tissue microarrays using high-throughput widefield P-SHG microscopy. The resulting P-SHG parameters are used in classification to differentiate tumor from normal tissue, resulting in 94.2% for both accuracy and F1-score, and 6.3% false discovery rate. Subsequently, the trained classifier is employed to predict tumor tissue with 91.3% accuracy, 90.7% F1-score, and 13.8% false omission rate. As such, we show that widefield P-SHG microscopy reveals collagen ultrastructure over large tissue regions and can be utilized as a sensitive biomarker for cancer diagnostics and prognostics studies.

Phasor approach of Mueller matrix optical scanning microscopy for biological tissue imaging

Mueller matrix microscopy is an advanced imaging technique providing a full characterization of the optical polarization fingerprint of a sample. The Lu-Chipman (LC) decomposition, a method based on the modeling of elementary polarimetric arrangements and matrix inversions, is the gold standard to extract each polarimetric component separately. However, this models the optical system as a small number of discrete optical elements and requires a priori knowledge of the order in which these elements occur. In stratified media or when the ordering is not known, the interpretation of the LC decomposition becomes difficult. In this work, we propose a new, to our knowledge, representation dedicated to the study of biological tissues that combines Mueller matrix microscopy with a phasor approach. We demonstrate that this method provides an easier and direct interpretation of the retardance images in any birefringent material without the use of mathematical assumptions regarding the structure of the sample and yields comparable contrast to the LC decomposition. By validating this approach through numerical simulations, we demonstrate that it is able to give access to localized structural information, resulting in a simple determination of the birefringent parameters at the microscopic level. We apply our novel, to our knowledge, method to typical biological tissues that are of interest in the field of biomedical diagnosis.

Review on Complete Mueller Matrix Optical Scanning Microscopy Imaging

Optical scanning microscopy techniques based on the polarization control of the light have the capability of providing non invasive label-free contrast. By comparing the polarization states of the excitation light with its transformation after interaction with the sample, the full optical properties can be summarized in a single 4×4 Mueller matrix. The main challenge of such a technique is to encode and decode the polarized light in an optimal way pixel-by-pixel and take into account the polarimetric artifacts from the optical devices composing the instrument in a rigorous calibration step. In this review, we describe the different approaches for implementing such a technique into an optical scanning microscope, that requires a high speed rate polarization control. Thus, we explore the recent advances in term of technology from the industrial to the medical applications.

Passive stiffness of fibrotic skeletal muscle in mdx mice relates to collagen architecture

KEY POINTS

The amount of fibrotic material in dystrophic mouse muscles relates to contractile function, but not passive function. Collagen fibres in skeletal muscle are associated with increased passive muscle stiffness in fibrotic muscles. The alignment of collagen is independently associated with passive stiffness in dystrophic skeletal muscles. These outcomes demonstrate that collagen architecture rather than collagen content should be a target of anti-fibrotic therapies to treat muscle stiffness.

ABSTRACT

Fibrosis is prominent in many skeletal muscle pathologies including dystrophies, neurological disorders, cachexia, chronic kidney disease, sarcopenia and metabolic disorders. Fibrosis in muscle is associated with decreased contractile forces and increased passive stiffness that limits joint mobility leading to contractures. However, the assumption that more fibrotic material is directly related to decreased function has not held true. Here we utilize novel measurement of extracellular matrix (ECM) and collagen architecture to relate ECM form to muscle function. We used mdx mice, a model for Duchenne muscular dystrophy that becomes fibrotic, and wildtype mice. In this model, extensor digitorum longus (EDL) muscle was significantly stiffer, but with similar total collagen, while the soleus muscle did not change stiffness, but increased collagen. The stiffness of the EDL was associated with increased collagen crosslinking as determined by collagen solubility. Measurement of ECM alignment using polarized light microscopy showed a robust relationship between stiffness and alignment for wildtype muscle that broke down in mdx muscles. Direct visualization of large collagen fibres with second harmonic generation imaging revealed their relative abundance in stiff muscles. Collagen fibre alignment was linked to stiffness across all muscles investigated and the most significant factor in a multiple linear regression-based model of muscle stiffness from ECM parameters. This work establishes novel characteristics of skeletal muscle ECM architecture and provides evidence for a mechanical function of collagen fibres in muscle. This finding suggests that anti-fibrotic strategies to enhance muscle function and excessive stiffness should target large collagen fibres and their alignment rather than total collagen.

Linear diattenuation imaging of biological tissues with near infrared Mueller scanning microscopy

Among the multitude of optical polarization contrasts that can be observed in complex biological specimens, linear diattenuation (LD) imaging has received little attention. It is indeed challenging to image LD with basic polarizing microscopes because it is often relatively small in comparison with linear retardance (LR). In addition, interpretation of LD images is not straightforward when experiments are conducted in the visible range because LD can be produced by both dichroism and anisotropic scattering. Mueller polarimetry is a powerful implementation of polarization sensing able to differentiate and measure the anisotropies of specimens. In this article, near infrared transmission Mueller scanning microscopy is used to image LD in thin biological specimen sections made of various proteins with unprecedented resolution and sensitivity. The near infrared spectral range makes it possible to lower the contribution of dichroism to the total linear diattenuation in order to highlight anisotropic scattering. Pixel-by-pixel comparison of LD images with LR and multiphoton images demonstrates that LD is produced by under-resolved structures that are not revealed by other means, notably within the sarcomere of skeletal muscles. LD microscopy appears as a powerful tool to provide new insights into the macro-molecular organization of biological specimens at the sub-microscopic scale without labelling.

Internal structure and remodeling in dystrophin-deficient cardiomyocytes using second harmonic generation

Duchenne muscular dystrophy (DMD) is a debilitating disorder related to dystrophin encoding gene mutations, often associated with dilated cardiomyopathy. However, it is still unclear how dystrophin deficiency affects cardiac sarcomere remodeling and contractile dysfunction. We employed second harmonic generation (SHG) microscopy, a nonlinear optical imaging technique that allows studying contractile apparatus organization without histologic fixation and immunostaining. Images were acquired on alive DMD (mdx) and wild type cardiomyocytes at different ages and at various external calcium concentrations. An automated image processing was developed to identify individual myofibrils and extract data about their organization. We observed a structural aging-dependent remodeling in mdx cardiomyocytes affecting sarcomere sinuosity, orientation and length that could not be anticipated from standard optical imaging. These results revealed for the first time the interest of SHG to evaluate the intracellular and sarcomeric remodeling of DMD cardiac tissue in an age-dependent manner that could participate in progressive contractile dysfunction.

Dual- and single-shot susceptibility ratio measurements with circular polarizations in second-harmonic generation microscopy

Polarization-resolved second-harmonic generation (P-SHG) microscopy is a technique capable of characterizing nonlinear optical properties of noncentrosymmetric biomaterials by extracting the nonlinear susceptibility tensor components ratio χzzz2'/χzxx2' , with z-axis parallel and x-axis perpendicular to the C₆ symmetry axis of molecular fiber, such as a myofibril or a collagen fiber. In this paper, we present two P-SHG techniques based on incoming and outgoing circular polarization states for a fast extraction of χzzz2'/χzxx2' : A dual-shot configuration where the SHG circular anisotropy generated using incident right- and left-handed circularly-polarized light is measured; and a single-shot configuration for which the SHG circular anisotropy is measured using only one incident circular polarization state. These techniques are used to extract the χzzz2'/χzxx2' of myosin fibrils in the body wall muscles of Drosophila melanogaster larva. The results are in good agreement with values obtained from the double Stokes-Mueller polarimetry. The dual- and single-shot circular anisotropy measurements can be used for fast imaging that is independent of the in-plane orientation of the sample. They can be used for imaging of contracting muscles, or for high throughput imaging of large sample areas.