Evaluation of texture parameters for the quantitative description of multimodal nonlinear optical images from atherosclerotic rabbit arteries

Multimodal Method for Differentiating Various Clinical Forms of Basal Cell Carcinoma and Benign Neoplasms In Vivo

Correct classification of skin lesions is a key step in skin cancer screening, which requires high accuracy and interpretability. This paper proposes a multimodal method for differentiating various clinical forms of basal cell carcinoma and benign neoplasms that includes machine learning. This study was conducted on 37 neoplasms, including benign neoplasms and five different clinical forms of basal cell carcinoma. The proposed multimodal screening method combines diffuse reflectance spectroscopy, optical coherence tomography and high-frequency ultrasound. Using diffuse reflectance spectroscopy, the coefficients of melanin pigmentation, erythema, hemoglobin content, and the slope coefficient of diffuse reflectance spectroscopy in the wavelength range 650-800 nm were determined. Statistical texture analysis of optical coherence tomography images was used to calculate first- and second-order statistical parameters. The analysis of ultrasound images assessed the shape of the tumor according to parameters such as area, perimeter, roundness and other characteristics. Based on the calculated parameters, a machine learning algorithm was developed to differentiate the various clinical forms of basal cell carcinoma. The proposed algorithm for classifying various forms of basal cell carcinoma and benign neoplasms provided a sensitivity of 70.6 ± 17.3%, specificity of 95.9 ± 2.5%, precision of 72.6 ± 14.2%, F1 score of 71.5 ± 15.6% and mean intersection over union of 57.6 ± 20.1%. Moreover, for differentiating basal cell carcinoma and benign neoplasms without taking into account the clinical form, the method achieved a sensitivity of 89.1 ± 8.0%, specificity of 95.1 ± 0.7%, F1 score of 89.3 ± 3.4% and mean intersection over union of 82.6 ± 10.8%.

A Single-Cell Atlas of Small Airway Disease in Chronic Obstructive Pulmonary Disease: A Cross-Sectional Study

Rationale: Emerging data demonstrate that the smallest conducting airways, terminal bronchioles, are the early site of tissue destruction in chronic obstructive pulmonary disease (COPD) and are reduced by as much as 41% by the time someone is diagnosed with mild (Global Initiative for Chronic Obstructive Lung Disease [GOLD] stage 1) COPD. Objectives: To develop a single-cell atlas that describes the structural, cellular, and extracellular matrix alterations underlying terminal bronchiole loss in COPD. Methods: This cross-sectional study of 262 lung samples derived from 34 ex-smokers with normal lung function (n = 10) or GOLD stage 1 (n = 10), stage 2 (n = 8), or stage 4 (n = 6) COPD was performed to assess the morphology, extracellular matrix, single-cell atlas, and genes associated with terminal bronchiole reduction using stereology, micro-computed tomography, nonlinear optical microscopy, imaging mass spectrometry, and transcriptomics. Measurements and Main Results: The lumen area of terminal bronchioles progressively narrows with COPD severity as a result of the loss of elastin fibers within alveolar attachments, which was observed before microscopic emphysematous tissue destruction in GOLD stage 1 and 2 COPD. The single-cell atlas of terminal bronchioles in COPD demonstrated M1-like macrophages and neutrophils located within alveolar attachments and associated with the pathobiology of elastin fiber loss, whereas adaptive immune cells (naive, CD4, and CD8 T cells, and B cells) are associated with terminal bronchiole wall remodeling. Terminal bronchiole pathology was associated with the upregulation of genes involved in innate and adaptive immune responses, the interferon response, and the degranulation of neutrophils. Conclusions: This comprehensive single-cell atlas highlights terminal bronchiole alveolar attachments as the initial site of tissue destruction in centrilobular emphysema and an attractive target for disease modification.

Unsupervised determination of lung tumor margin with widefield polarimetric second-harmonic generation microscopy

The extracellular matrix (ECM) is amongst many tissue components affected by cancer, however, morphological changes of the ECM are not well-understood and thus, often omitted from diagnostic considerations. Polarimetric second-harmonic generation (P-SHG) microscopy allows for visualization and characterization of collagen ultrastructure in the ECM, aiding in better understanding of the changes induced by cancer throughout the tissue. In this paper, a large region of hematoxylin and eosin (H&E) stained human lung section, encompassing a tumor margin, connecting a significant tumor portion to normal tissue was imaged with P-SHG microscopy. The resulting polarimetric parameters were utilized in principal components analysis and unsupervised K-Means clustering to separate normal- and tumor-like tissue. Consequently, a pseudo-color map of the clustered tissue regions is generated to highlight the irregularity of the ECM collagen structure throughout the region of interest and to identify the tumor margin, in the absence of morphological characteristics of the cells.

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.

Optical Microscopy and the Extracellular Matrix Structure: A Review

Biological tissues are not uniquely composed of cells. A substantial part of their volume is extracellular space, which is primarily filled by an intricate network of macromolecules constituting the extracellular matrix (ECM). The ECM serves as the scaffolding for tissues and organs throughout the body, playing an essential role in their structural and functional integrity. Understanding the intimate interaction between the cells and their structural microenvironment is central to our understanding of the factors driving the formation of normal versus remodelled tissue, including the processes involved in chronic fibrotic diseases. The visualization of the ECM is a key factor to track such changes successfully. This review is focused on presenting several optical imaging microscopy modalities used to characterize different ECM components. In this review, we describe and provide examples of applications of a vast gamut of microscopy techniques, such as widefield fluorescence, total internal reflection fluorescence, laser scanning confocal microscopy, multipoint/slit confocal microscopy, two-photon excited fluorescence (TPEF), second and third harmonic generation (SHG, THG), coherent anti-Stokes Raman scattering (CARS), fluorescence lifetime imaging microscopy (FLIM), structured illumination microscopy (SIM), stimulated emission depletion microscopy (STED), ground-state depletion microscopy (GSD), and photoactivated localization microscopy (PALM/fPALM), as well as their main advantages, limitations.

Label-Free Multiphoton Microscopy: Much More Than Fancy Images

Multiphoton microscopy has recently passed the milestone of its first 30 years of activity in biomedical research. The growing interest around this approach has led to a variety of applications from basic research to clinical practice. Moreover, this technique offers the advantage of label-free multiphoton imaging to analyze samples without staining processes and the need for a dedicated system. Here, we review the state of the art of label-free techniques; then, we focus on two-photon autofluorescence as well as second and third harmonic generation, describing physical and technical characteristics. We summarize some successful applications to a plethora of biomedical research fields and samples, underlying the versatility of this technique. A paragraph is dedicated to an overview of sample preparation, which is a crucial step in every microscopy experiment. Afterwards, we provide a detailed review analysis of the main quantitative methods to extract important information and parameters from acquired images using second harmonic generation. Lastly, we discuss advantages, limitations, and future perspectives in label-free multiphoton microscopy.

Polarimetric second-harmonic generation microscopy of the hierarchical structure of collagen in stage I-III non-small cell lung carcinoma

Polarimetric second-harmonic generation (P-SHG) microscopy is used to quantify the structural alteration of collagen in stage-I,-II and -III non-small cell lung carcinoma (NSCLC) ex vivo tissue. The achiral and chiral molecular second-order susceptibility tensor components ratios (R and C, respectively), the degree of linear polarization (DLP) and the in-plane collagen fiber orientation (δ) were extracted. Further, texture analysis was performed on the SHG intensity, R, C, DLP and δ. The distributions of R, C, DLP and δ as well as the textural features of entropy, correlation and contrast show significant differences between normal and tumor tissues.

Defective Fibrillar Collagen Organization by Fibroblasts Contributes to Airway Remodeling in Asthma

Rationale: Histologic stains have been used as the gold standard to visualize extracellular matrix (ECM) changes associated with airway remodeling in asthma, yet they provide no information on the biochemical and structural characteristics of the ECM, which are vital to understanding alterations in tissue function.Objectives: To demonstrate the use of nonlinear optical microscopy (NLOM) and texture analysis algorithms to image fibrillar collagen (second harmonic generation) and elastin (two-photon excited autofluorescence), to obtain biochemical and structural information on the remodeled ECM environment in asthma.Methods: Nontransplantable donor lungs from donors with asthma (n = 13) and control (n = 12) donors were used for the assessment of airway collagen and elastin fibers by NLOM, and extraction of lung fibroblasts for in vitro experiments.Measurements and Main Results: Fibrillar collagen is not only increased but also highly disorganized and fragmented within large and small asthmatic airways compared with control subjects, using NLOM imaging. Furthermore, such structural alterations are present in pediatric and adult donors with asthma, irrespective of fatal disease. In vitro studies demonstrated that asthmatic airway fibroblasts are deficient in their packaging of fibrillar collagen-I and express less decorin, important for collagen fibril packaging. Packaging of collagen fibrils was found to be more disorganized in asthmatic airways compared with control subjects, using transmission electron microscopy.Conclusions: NLOM imaging enabled the structural assessment of the ECM, and the data suggest that airway remodeling in asthma involves the progressive accumulation of disorganized fibrillar collagen by airway fibroblasts. This study highlights the future potential clinical application of NLOM to assess airway remodeling in vivo.

Second-harmonic generation imaging analysis can help distinguish sarcoidosis from tuberculoid leprosy

Sarcoidosis and tuberculoid leprosy (TL) are prototypes of granulomatous inflammation in dermatology, which embody one of the histopathology limitations in distinguishing some diseases. Recent advances in the use of nonlinear optical microscopy in skin have enabled techniques, such as second-harmonic generation (SHG), to become powerful tools to study the physical and biochemical properties of skin. We use SHG images to analyze the collagen network, to distinguish differences between sarcoidosis and TL granulomas. SHG images obtained from skin biopsies of 33 patients with TL and 24 with sarcoidosis retrospectively were analyzed using first-order statistics (FOS) and second-order statistics, such as gray-level co-occurrence matrix (GLCM). Among the four parameters evaluated (optical density, entropy, contrast, and second angular moment), only contrast demonstrated statistical significance, being higher in sarcoidosis (p  =  0.02; 4908.31 versus 2822.17). The results may indicate insufficient differentiating power for most tested FOS and GLCM parameters in classifying sarcoidosis and TL granulomas, when used individually. But in combination with histopathology (H&E and complementary stains, such as silver and fast acid stains), SHG analysis, like contrast, can contribute to distinguishing between these diseases. This study can provide a way to evaluate collagen distribution in granulomatous diseases.

Quantitative assessment of radiation-induced changes of bladder and rectum collagen structure using optical methods

The objective of the study is the quantitative analysis of the dose-time dependences of changes occurring in collagen of bladder and rectum after gamma-irradiation using optical methods [nonlinear microscopy in a second harmonic generation (SHG) detection regime and cross-polarization optical coherence tomography (CP OCT)]. For quantitative assessment of the collagen structure, regions of interest on the SHG-images of two-dimensional (2-D) distribution of SHG signal intensity of collagen were chosen in the submucosa. The mean SHG signal intensity and its standard deviation were calculated by ImageJ 1.39p (NIH). For quantitative analysis of CP OCT data, an integral depolarization factor (IDF) was calculated. Quantitative calculation of the SHG signal intensity and the IDF can provide additional information about the processes of the collagen radiation-induced degradation and subsequent remodeling. High positive correlation between the mean SHG signal intensity and the mean IDF of bladder and rectum demonstrates that CP OCT can be used as an "optical biopsy" in the grading of collagen radiation damage.

High-power diode-pumped Kerr-lens mode-locked bulk Yb:KGW laser

A high-power (>1  W) pure Kerr-lens mode-locked bulk Yb:KGW laser with multimode fiber-coupled diode pumping was demonstrated. The laser delivered 240 fs pulses with 2.3 W of average output power at 86.8 MHz, corresponding to 97 kW of peak power and 26 nJ of pulse energy. The shortest generated pulse duration was 120 fs with 1.2 W of output power. The self-starting regime was also observed with a background continuous-wave component. The laser exhibited more than an order of magnitude higher output power when compared to the previously reported bulk Yb-ion-doped lasers with multimode laser diode pumping systems.

Imaging Collagen in Scar Tissue: Developments in Second Harmonic Generation Microscopy for Biomedical Applications

The ability to respond to injury with tissue repair is a fundamental property of all multicellular organisms. The extracellular matrix (ECM), composed of fibrillar collagens as well as a number of other components is dis-regulated during repair in many organs. In many tissues, scaring results when the balance is lost between ECM synthesis and degradation. Investigating what disrupts this balance and what effect this can have on tissue function remains an active area of research. Recent advances in the imaging of fibrillar collagen using second harmonic generation (SHG) imaging have proven useful in enhancing our understanding of the supramolecular changes that occur during scar formation and disease progression. Here, we review the physical properties of SHG, and the current nonlinear optical microscopy imaging (NLOM) systems that are used for SHG imaging. We provide an extensive review of studies that have used SHG in skin, lung, cardiovascular, tendon and ligaments, and eye tissue to understand alterations in fibrillar collagens in scar tissue. Lastly, we review the current methods of image analysis that are used to extract important information about the role of fibrillar collagens in scar formation.

Review of near-infrared methods for wound assessment

Wound management is a challenging and costly problem that is growing in importance as people are living longer. Instrumental methods are increasingly being relied upon to provide objective measures of wound assessment to help guide management. Technologies that employ near-infrared (NIR) light form a prominent contingent among the existing and emerging technologies. We review some of these technologies. Some are already established, such as indocyanine green fluorescence angiography, while we also speculate on others that have the potential to be clinically relevant to wound monitoring and assessment. These various NIR-based technologies address clinical wound management needs along the entire healing trajectory of a wound.

(Second) Harmonic Disharmony: Nonlinear Microscopy Shines New Light on the Pathology of Atherosclerosis

There has been increasing interest in second harmonic generation (SHG) imaging approaches for the investigation of atherosclerosis due to the deep penetration and three-dimensional sectioning capabilities of the nonlinear optical microscope. Atherosclerosis involves remodeling or alteration of the collagenous framework in affected vessels. The disease is often characterized by excessive collagen deposition and altered collagen organization. SHG has the capability to accurately characterize collagen structure, which is an essential component in understanding atherosclerotic lesion development and progression. As a structure-based imaging modality, SHG is most impactful in atherosclerosis evaluation in conjunction with other, chemically specific nonlinear optics (NLO) techniques to identify additional components of the lesion. These include the use of coherent anti-Stokes Raman scattering and two-photon excitation fluorescence for studying atherosclerosis burden, and application of stimulated Raman scattering to image cholesterol crystals. However, very few NLO studies have attempted to quantitate differences in control versus atherosclerotic states or to correlate the application to clinical situations. This review highlights the potential of SHG imaging to directly and indirectly describe atherosclerosis as a pathological condition.

Texture analysis of collagen second-harmonic generation images based on local difference local binary pattern and wavelets differentiates human skin abnormal scars from normal scars

Quantitative methods for noninvasive diagnosis of scars are a challenging issue in medicine. This work aims to implement a texture analysis method for quantitatively discriminating abnormal scars from normal scars based on second-harmonic generation (SHG) images. A local difference local binary pattern (LD-LBP) operator combined with a wavelet transform was explored to extract diagnosis features from scar SHG images that were related to the alteration in collagen morphology. Based on the quantitative parameters including the homogeneity, directional and coarse features in SHG images, the scar collagen SHG images were classified into normal or abnormal scars by a support vector machine classifier in a leave-one-out cross-validation procedure. Our experiments and data analyses demonstrated apparent differences between normal and abnormal scars in terms of their morphological structure of collagen. By comparing with gray level co-occurrence matrix, wavelet transform, and combined basic local binary pattern and wavelet transform with respect to the accuracy and receiver operating characteristic analysis, the method proposed herein was demonstrated to achieve higher accuracy and more reliable classification of SHG images. This result indicated that the extracted texture features with the proposed method were effective in the classification of scars. It could provide assistance for physicians in the diagnostic process.

Collagen morphology and texture analysis: from statistics to classification

In this study we present an image analysis methodology capable of quantifying morphological changes in tissue collagen fibril organization caused by pathological conditions. Texture analysis based on first-order statistics (FOS) and second-order statistics such as gray level co-occurrence matrix (GLCM) was explored to extract second-harmonic generation (SHG) image features that are associated with the structural and biochemical changes of tissue collagen networks. Based on these extracted quantitative parameters, multi-group classification of SHG images was performed. With combined FOS and GLCM texture values, we achieved reliable classification of SHG collagen images acquired from atherosclerosis arteries with >90% accuracy, sensitivity and specificity. The proposed methodology can be applied to a wide range of conditions involving collagen re-modeling, such as in skin disorders, different types of fibrosis and muscular-skeletal diseases affecting ligaments and cartilage.

Accumulating advantages, reducing limitations: multimodal nonlinear imaging in biomedical sciences - the synergy of multiple contrast mechanisms

Multimodal nonlinear microscopy has matured during the past decades to one of the key imaging modalities in life science and biomedicine due to its unique capabilities of label-free visualization of tissue structure and chemical composition, high depth penetration, intrinsic 3D sectioning, diffraction limited resolution and low phototoxicity. This review briefly summarizes first recent advances in the field regarding the methodology, e.g., contrast mechanisms and signal characteristics used for contrast generation as well as novel image processing approaches. The second part deals with technologic developments emphasizing improvements in penetration depth, imaging speed, spatial resolution and nonlinear labeling strategies. The third part focuses on recent applications in life science fundamental research and biomedical diagnostics as well as future clinical applications.

Nonlinear optical microscopy in decoding arterial diseases

Pathological understanding of arterial diseases is mainly attributable to histological observations based on conventional tissue staining protocols. The emerging development of nonlinear optical microscopy (NLOM), particularly in second-harmonic generation, two-photon excited fluorescence and coherent Raman scattering, provides a new venue to visualize pathological changes in the extracellular matrix caused by atherosclerosis progression. These techniques in general require minimal tissue preparation and offer rapid three-dimensional imaging. The capability of label-free microscopic imaging enables disease impact to be studied directly on the bulk artery tissue, thus minimally perturbing the sample. In this review, we look at recent progress in applications related to arterial disease imaging using various forms of NLOM.