Analysis of second-harmonic-generation microscopy in a mouse model of ovarian carcinoma

A Perspective Review: Analyzing Collagen Alterations in Ovarian Cancer by High-Resolution Optical Microscopy

High-grade serous ovarian cancer (HGSOC) is the predominant subtype of ovarian cancer (OC), occurring in more than 80% of patients diagnosed with this malignancy. Histological and genetic analysis have confirmed the secretory epithelial of the fallopian tube (FT) as a major site of origin of HGSOC. Although there have been significant strides in our understanding of this disease, early stage detection and diagnosis are still rare. Current clinical imaging modalities lack the ability to detect early stage pathogenesis in the fallopian tubes and the ovaries. However, there are several microscopic imaging techniques used to analyze the structural modifications in the extracellular matrix (ECM) protein collagen in ex vivo FT and ovarian tissues that potentially can be modified to fit the clinical setting. In this perspective, we evaluate and compare the myriad of optical tools available to visualize these alterations and the invaluable insights these data provide on HGSOC initiation. We also discuss the clinical implications of these findings and how these data may help novel tools for early diagnosis of HGSOC.

On the quantitative analysis of lamellar collagen arrangement with second-harmonic generation imaging

Second harmonic generation (SHG) allows for the examination of collagen structure in collagenous tissues. Collagen is a fibrous protein found in abundance in the human body, present in bones, cartilage, the skin, and the cornea, among other areas, providing structure, support, and strength. Its structural arrangement is deeply intertwined with its function. For instance, in the cornea, alterations in collagen organization can result in severe visual impairments. Using SHG imaging, various metrics have demonstrated the potential to study collagen organization. The discrimination between healthy, keratoconus, and crosslinked corneas, assessment of injured tendons, or the characterization of breast and ovarian tumorous tissue have been demonstrated. Nevertheless, these metrics have not yet been objectively evaluated or compared. A total of five metrics were identified and implemented from the literature, and an additional approach adapted from texture analysis was proposed. In this study, we analyzed their effectiveness on a ground-truth set of artificially generated fibrous images. Our investigation provides the first comprehensive assessment of the performance of multiple metrics, identifying both the strengths and weaknesses of each approach and providing valuable insights for future applications of SHG imaging in medical diagnostics and research.

Squeezing the eggs to grow: The mechanobiology of mammalian folliculogenesis

The formation of functional eggs (oocyte) in ovarian follicles is arguably one of the most important events in early mammalian development since the oocytes provide the bulk genetic and cytoplasmic materials for successful reproduction. While past studies have identified many genes that are critical to normal ovarian development and function, recent studies have highlighted the role of mechanical force in shaping folliculogenesis. In this review, we discuss the underlying mechanobiological principles and the force-generating cellular structures and extracellular matrix that control the various stages of follicle development. We also highlight emerging techniques that allow for the quantification of mechanical interactions and follicular dynamics during development, and propose new directions for future studies in the field. We hope this review will provide a timely and useful framework for future understanding of mechano-signalling pathways in reproductive biology and diseases.

Multiscale anisotropy analysis of second-harmonic generation collagen imaging of mouse skin

SIGNIFICANCE

Morphological collagen signatures are important for tissue function, particularly in the tumor microenvironment. A single algorithmic framework with quantitative, multiscale morphological collagen feature extraction may further the use of collagen signatures in understanding fundamental tumor progression.

AIM

A modification of the 2D wavelet transform modulus maxima (WTMM) anisotropy method was applied to both digitally simulated collagen fibers and second-harmonic-generation imaged collagen fibers of mouse skin to calculate a multiscale anisotropy factor to detect collagen fiber organization.

APPROACH

The modified 2D WTMM anisotropy method was initially validated on synthetic calibration images to establish the robustness and sensitivity of the multiscale fiber organization tool. Upon validation, the algorithm was applied to collagen fiber organization in normal wild-type skin, melanoma stimulated skin, and integrin α10KO skin.

RESULTS

Normal wild-type skin collagen fibers have an increased anisotropy factor at all sizes scales. Interestingly, the multiscale anisotropy differences highlight important dissimilarities between collagen fiber organization in normal wild-type skin, melanoma stimulated, and integrin α10KO skin. At small scales (∼2 to 3  μm), the integrin α10KO skin was vastly different than normal skin (p-value  ∼  10  -  8), whereas the melanoma stimulated skin was vastly different than normal at large scales (∼30 to 40  μm, p-value  ∼  10  -  15).

CONCLUSIONS

This objective computational collagen fiber organization algorithm is sensitive to collagen fiber organization across multiple scales for effective exploration of collagen morphological alterations associated with melanoma and the lack of α10 integrin binding.

A biphasic response of polymerized Type 1 collagen architectures to dermatan sulfate

Collagen I, the most abundant extracellular matrix (ECM) protein in vertebrate tissues provides mechanical durability to tissue microenvironments and regulates cell function. Its fibrillogenesis in biological milieu is predominantly regulated by dermatan sulfate proteoglycans, proteins conjugated with iduronic acid-containing dermatan sulfate (DS) glycosaminoglycans (GAG). Although DS is known to regulate tissue function through its modulation of Coll I architecture, a precise understanding of the latter remains elusive. We investigated this problem by visualizing the fibrillar pattern of fixed Coll I gels polymerized in the presence of varying concentrations of DS using second harmonic generation microscopy. Measuring mean second harmonic generation signal (which estimates the ordering of the fibrils), and surface occupancy (which estimates the space occupied by fibrils) supported by confocal reflectance microscopy, our observations indicated that the effect on fibril pattern of DS is contextual upon the latter's concentrations: Lower levels of DS resulted in sparse disorganized fibrils; higher levels restore organization, with fibrils occupying greater space. An appropriate change in elasticity as a result of DS levels was also observed through atomic force microscopy. Examination of dye-based GAG staining and scanning electron microscopy suggested distinct constitutions of Coll I gels when polymerized with higher and lower levels of DS. We observed that adhesion of the invasive ovarian cancer cells SKOV3 decreased for lower DS levels but was partially restored at higher DS levels. Our study shows how the Coll I gel pattern-tuning of DS is of relevance for understanding its biomaterial applications and possibly, pathophysiological functions.

Rapid identification of human ovarian cancer in second harmonic generation images using radiomics feature analyses and tree-based pipeline optimization tool

Ovarian cancer is currently one of the most common cancers of the female reproductive organs, and its mortality rate is the highest among all types of gynecologic cancers. Rapid and accurate classification of ovarian cancer plays an important role in the determination of treatment plans and prognoses. Nevertheless, the most commonly used classification method is based on histopathological specimen examination, which is time-consuming and labor-intensive. Thus, in this study, we utilize radiomics feature extraction methods and the automated machine learning tree-based pipeline optimization tool (TOPT) for analysis of 3D, second harmonic generation images of benign, malignant and normal human ovarian tissues, to develop a high-efficiency computer-aided diagnostic model. Area under the receiver operating characteristic curve values of 0.98, 0.96 and 0.94 were obtained, respectively, for the classification of the three tissue types. Furthermore, this approach can be readily applied to other related tissues and diseases, and has great potential for improving the efficiency of medical diagnostic processes.

Harmonic Generation Microscopy 2.0: New Tricks Empowering Intravital Imaging for Neuroscience

Optical harmonic generation, e.g., second- (SHG) and third-harmonic generation (THG), provides intrinsic contrasts for three-dimensional intravital microscopy. Contrary to two-photon excited fluorescence (TPEF), however, they have found relatively specialized applications, such as imaging collagenous and non-specific tissues, respectively. Here we review recent advances that broaden the capacity of SHG and THG for imaging the central nervous system in particular. The fundamental contrast mechanisms are reviewed as they encode novel information including molecular origin, spectroscopy, functional probes, and image analysis, which lay foundations for promising future applications in neuroscience.

Stromal alterations in ovarian cancers via wavelength dependent Second Harmonic Generation microscopy and optical scattering

BACKGROUND

Ovarian cancer remains the most deadly gynecological cancer with a poor aggregate survival rate; however, the specific rates are highly dependent on the stage of the disease upon diagnosis. Current screening and imaging tools are insufficient to detect early lesions and are not capable of differentiating the subtypes of ovarian cancer that may benefit from specific treatments.

METHOD

As an alternative to current screening and imaging tools, we utilized wavelength dependent collagen-specific Second Harmonic Generation (SHG) imaging microscopy and optical scattering measurements to probe the structural differences in the extracellular matrix (ECM) of normal stroma, benign tumors, endometrioid tumors, and low and high-grade serous tumors.

RESULTS

The SHG signatures of the emission directionality and conversion efficiency as well as the optical scattering are related to the organization of collagen on the sub-micron size scale and encode structural information. The wavelength dependence of these readouts adds additional characterization of the size and distribution of collagen fibrils/fibers relative to the interrogating wavelengths. We found a strong wavelength dependence of these metrics that are related to significant structural differences in the collagen organization and are consistent with the dualistic classification of type I and II serous tumors. Moreover, type I endometrioid tumors have strongly differing ECM architecture than the serous malignancies. The SHG metrics and optical scattering measurements were used to form a linear discriminant model to classify the tissues, and we obtained high accuracy (>90%) between high-grade serous tumors from the other tissue types. High-grade serous tumors account for ~70% of ovarian cancers, and this delineation has potential clinical applications in terms of supplementing histological analysis, understanding the etiology, as well as development of an in vivo screening tool.

CONCLUSIONS

SHG and optical scattering measurements provide sub-resolution information and when combined provide superior diagnostic power over clinical imaging modalities. Additionally the measurements are able to delineate the different subtypes of ovarian cancer and may potentially assist in treatment protocols. Understanding the altered collagen assembly can supplement histological analysis and provide new insight into the etiology. These methods could become an in vivo screening tool for earlier detection which is important since ovarian malignancies can metastasize while undetectable by current clinical imaging resolution.

Epithelial Ovarian Cancer Diagnosis of Second-Harmonic Generation Images: A Semiautomatic Collagen Fibers Quantification Protocol

A vast number of human pathologic conditions are directly or indirectly related to tissular collagen structure remodeling. The nonlinear optical microscopy second-harmonic generation has become a powerful tool for imaging biological tissues with anisotropic hyperpolarized structures, such as collagen. During the past years, several quantification methods to analyze and evaluate these images have been developed. However, automated or semiautomated solutions are necessary to ensure objectivity and reproducibility of such analysis. This work describes automation and improvement methods for calculating the anisotropy (using fast Fourier transform analysis and the gray-level co-occurrence matrix). These were applied to analyze biopsy samples of human ovarian epithelial cancer at different stages of malignancy (mucinous, serous, mixed, and endometrial subtypes). The semiautomation procedure enabled us to design a diagnostic protocol that recognizes between healthy and pathologic tissues, as well as between different tumor types.

A Novel Intravital Imaging Window for Longitudinal Microscopy of the Mouse Ovary

The ovary is a dynamic organ that undergoes dramatic remodeling throughout the ovulatory cycle. Maturation of the ovarian follicle, release of the oocyte in the course of ovulation as well as formation and degradation of corpus luteum involve tightly controlled remodeling of the extracellular matrix and vasculature. Ovarian tumors, regardless of their tissue of origin, dynamically interact with the ovarian microenvironment. Their activity in the tissue encompasses recruitment of host stroma and immune cells, attachment of tumor cells to mesothelial layer, degradation of the extracellular matrix and tumor cell migration. High-resolution dynamic imaging of such processes is particularly challenging for internal organs. The implementation of a novel imaging window as reported here enabled longitudinal microscopy of ovarian physiology and orthotopic tumor invasion.

Applications of second-harmonic generation imaging microscopy in ovarian and breast cancer

In this perspective, we discuss how the nonlinear optical technique of second-harmonic generation (SHG) microscopy has been used to greatly enhance our understanding of the tumor microenvironment (TME) of breast and ovarian cancer. Striking changes in collagen architecture are associated with these epithelial cancers, and SHG can image these changes with great sensitivity and specificity with submicrometer resolution. This information has not historically been exploited by pathologists but has the potential to enhance diagnostic and prognostic capabilities. We summarize the utility of image processing tools that analyze fiber morphology in SHG images of breast and ovarian cancer in human tissues and animal models. We also describe methods that exploit the SHG physical underpinnings that are effective in delineating normal and malignant tissues. First we describe the use of polarization-resolved SHG that yields metrics related to macromolecular and supramolecular structures. The coherence and corresponding phase-matching process of SHG results in emission directionality (forward to backward), which is related to sub-resolution fibrillar assembly. These analyses are more general and more broadly applicable than purely morphology-based analyses; however, they are more computationally intensive. Intravital imaging techniques are also emerging that incorporate all of these quantitative analyses. Now, all these techniques can be coupled with rapidly advancing miniaturization of imaging systems to afford their use in clinical situations including enhancing pathology analysis and also in assisting in real-time surgical determination of tumor margins.

Second-harmonic generation imaging of cancer

The last 30 years has seen great advances in optical microscopy with the introduction of sophisticated fluorescence-based imaging methods such as confocal and multiphoton laser scanning microscopy. There is increasing interest in using these methods to quantitatively examine sources of intrinsic biological contrast including autofluorescent endogenous proteins and light interactions such as second-harmonic generation (SHG) in collagen. In particular, SHG-based microscopy has become a widely used quantitative modality for imaging noncentrosymmetric proteins such as collagen in a diverse range of tissues. Due to the underlying physical origin of the SHG signal, it is highly sensitive to collagen fibril/fiber structure and, importantly, to collagen-associated changes that occur in diseases such as cancer, fibrosis, and connective tissue disorders. An overview of SHG physics background and technologies is presented with a focused review on applications of SHG primarily as applied to cancer.

Diagnostic potential of multimodal imaging of ovarian tissue using optical coherence tomography and second-harmonic generation microscopy

Ovarian cancer is particularly deadly because it is usually diagnosed after it has metastasized. We have previously identified features of ovarian cancer using optical coherence tomography (OCT) and second-harmonic generation (SHG) microscopy (targeting collagen). OCT provides an image of the ovarian microstructure while SHG provides a high-resolution map of collagen fiber bundle arrangement. Here we investigated the diagnostic potential of dual-modality OCT and SHG imaging. We conducted a fully crossed, multi-reader, multi-case study using seven human observers. Each observer classified 44 ex vivo mouse ovaries (16 normal and 28 abnormal) as normal or abnormal from OCT, SHG, and simultaneously viewed, co-registered OCT and SHG images and provided a confidence rating on a six-point scale. We determined the average receiver operating characteristic (ROC) curves, area under the ROC curves (AUC), and other quantitative figures of merit. The results show that OCT has diagnostic potential with an average AUC of 0.91 ± 0.06. The average AUC for SHG was less promising at 0.71 ± 0.13. The average AUC for simultaneous OCT and SHG was not significantly different from OCT alone, possibly due to the limited SHG field of view. The high performance of OCT and co-registered OCT and SHG warrants further investigation.

Nonlinear optical microscopy signal processing strategies in cancer

This work reviews the most relevant present-day processing methods used to improve the accuracy of multimodal nonlinear images in the detection of epithelial cancer and the supporting stroma. Special emphasis has been placed on methods of non linear optical (NLO) microscopy image processing such as: second harmonic to autofluorescence ageing index of dermis (SAAID), tumor-associated collagen signatures (TACS), fast Fourier transform (FFT) analysis, and gray level co-occurrence matrix (GLCM)-based methods. These strategies are presented as a set of potential valuable diagnostic tools for early cancer detection. It may be proposed that the combination of NLO microscopy and informatics based image analysis approaches described in this review (all carried out on free software) may represent a powerful tool to investigate collagen organization and remodeling of extracellular matrix in carcinogenesis processes.

Simultaneous multiplane imaging of human ovarian cancer by volume holographic imaging

Ovarian cancer is the most deadly gynecologic cancer, a fact which is attributable to poor early detection and survival once the disease has reached advanced stages. Intraoperative laparoscopic volume holographic imaging has the potential to provide simultaneous visualization of surface and subsurface structures in ovarian tissues for improved assessment of developing ovarian cancer. In this ex vivo ovarian tissue study, we assembled a benchtop volume holographic imaging system (VHIS) to characterize the microarchitecture of 78 normal and 40 abnormal tissue specimens derived from ovarian, fallopian tube, uterine, and peritoneal tissues, collected from 26 patients aged 22 to 73 undergoing bilateral salpingo-oophorectomy, hysterectomy with bilateral salpingo-oophorectomy, or abdominal cytoreductive surgery. All tissues were successfully imaged with the VHIS in both reflectance- and fluorescence-modes revealing morphological features which can be used to distinguish between normal, benign abnormalities, and cancerous tissues. We present the development and successful application of VHIS for imaging human ovarian tissue. Comparison of VHIS images with corresponding histopathology allowed for qualitatively distinguishing microstructural features unique to the studied tissue type and disease state. These results motivate the development of a laparoscopic VHIS for evaluating the surface and subsurface morphological alterations in ovarian cancer pathogenesis.

Computational segmentation of collagen fibers from second-harmonic generation images of breast cancer

Second-harmonic generation (SHG) imaging can help reveal interactions between collagen fibers and cancer cells. Quantitative analysis of SHG images of collagen fibers is challenged by the heterogeneity of collagen structures and low signal-to-noise ratio often found while imaging collagen in tissue. The role of collagen in breast cancer progression can be assessed post acquisition via enhanced computation. To facilitate this, we have implemented and evaluated four algorithms for extracting fiber information, such as number, length, and curvature, from a variety of SHG images of collagen in breast tissue. The image-processing algorithms included a Gaussian filter, SPIRAL-TV filter, Tubeness filter, and curvelet-denoising filter. Fibers are then extracted using an automated tracking algorithm called fiber extraction (FIRE). We evaluated the algorithm performance by comparing length, angle and position of the automatically extracted fibers with those of manually extracted fibers in twenty-five SHG images of breast cancer. We found that the curvelet-denoising filter followed by FIRE, a process we call CT-FIRE, outperforms the other algorithms under investigation. CT-FIRE was then successfully applied to track collagen fiber shape changes over time in an in vivo mouse model for breast cancer.

Current microscopic methods for the neural ECM analysis

The extracellular matrix (ECM) occupies the space between both neurons and glial cells and thus provides a microenvironment that regulates multiple aspects of neural activities. Because of the vital role of ECM as a natural environment of cells in vivo, there is a growing interest to develop methodology allowing for the detailed structural and functional analyses of ECM. In this chapter, we provide the detailed overview of current microscopic methods used for ECM analysis and also describe general labeling strategies for ECM visualization. Since ECM remodeling involves the proteolytic cleavage of ECM, we will also describe current experimental approaches to image the proteolytic reorganization and/or degradation of ECM. The special focus of this chapter is set to the application of Förster resonance energy transfer-based approaches to monitor intracellular and extracellular matrix functions with high spatiotemporal resolution.

In vivo time-serial multi-modality optical imaging in a mouse model of ovarian tumorigenesis

Identification of the early microscopic changes associated with ovarian cancer may lead to development of a diagnostic test for high-risk women. In this study we use optical coherence tomography (OCT) and multiphoton microscopy (MPM) (collecting both two photon excited fluorescence [TPEF] and second harmonic generation [SHG]) to image mouse ovaries in vivo at multiple time points. We demonstrate the feasibility of imaging mouse ovaries in vivo during a long-term survival study and identify microscopic changes associated with early tumor development. These changes include alterations in tissue microstructure, as seen by OCT, alterations in cellular fluorescence and morphology, as seen by TPEF, and remodeling of collagen structure, as seen by SHG. These results suggest that a combined OCT-MPM system may be useful for early detection of ovarian cancer.

The severity of Osteogenesis imperfecta and type I collagen pattern in human skin as determined by nonlinear microscopy: proof of principle of a diagnostic method

BACKGROUND

The confirmatory diagnosis of Osteogenesis Imperfecta (OI) requires invasive, commonly bone biopsy, time consuming and destructive methods. This paper proposes an alternative method using a combination of two-photon excitation fluorescence (TPEF) and second-harmonic generation (SHG) microscopies from easily obtained human skin biopsies. We show that this method can distinguish subtypes of human OI.

METHODOLOGY/PRINCIPAL FINDINGS

Different aspects of collagen microstructure of skin fresh biopsies and standard H&E-stained sections of normal and OI patients (mild and severe forms) were distinguished by TPEF and SHG images. Moreover, important differences between subtypes of OI were identified using different methods of quantification such as collagen density, ratio between collagen and elastic tissue, and gray-level co-occurrence matrix (GLCM) image-pattern analysis. Collagen density was lower in OI dermis, while the SHG/autofluorescence index of the dermis was significantly higher in OI as compared to that of the normal skin. We also showed that the energy value of GLCM texture analysis is useful to discriminate mild from severe OI and from normal skin.

CONCLUSIONS/SIGNIFICANCE

This work demonstrated that nonlinear microscopy techniques in combination with image-analysis approaches represent a powerful tool to investigate the collagen organization in skin dermis in patients with OI and has the potential to distinguish the different types of OI. The procedure outlined in this paper requires a skin biopsy, which is almost painless as compared to the bone biopsy commonly used in conventional methods. The data presented here complement existing clinical diagnostic techniques and can be used as a diagnostic procedure to confirm the disease, evaluate its severity and treatment efficacy.