Histopathological correlations of bulk tissue polarimetric images: Case study

Polarimetric imaging and image analysis have gained increased interest in soft tissue analysis at the cellular level. However, polarimetric imaging has widely been tested on thin tissue sections to provide reliable information correlated with histopathological findings. Polarimetric bulk tissue analysis always offered an overall assessment of various tissue optical properties for diagnosis. In this study, the histopathological correlation of bulk tissue polarimetry images for soft tissues is discussed. The first-hand information on the use of bulk tissue Mueller polarimetry and image analysis as an alternative to tissue histopathology is presented for surgically extracted colon and breast tissues.     

Liver tissue classification of en face images by fractal dimension‐based support vector machine

Full‐field optical coherence tomography (FF‐OCT) has been reported with its label‐free subcellular imaging performance. To realize quantitive cancer detection, the support vector machine model of classifying normal and cancerous human liver tissue is proposed with en face tomographic images. Twenty samples (10 normal and 10 cancerous) were operated from humans and composed of 285 en face tomographic images. Six histogram features and one proposed fractal dimension parameter that reveal the refractive index inhomogeneities of tissue were extracted and made up the training set. The other different 16 samples (8 normal and 8 cancerous) were imaged (190 images) and employed as the test set with the same features. First, a subcellular‐resolution tomographic image library for four histopathological areas in liver tissue was established. Second, the area under the receiver operating characteristics of 0.9378, 0.9858, 0.9391, 0.9517 for prediction of the cancerous hepatic cell, central vein, fibrosis, and portal vein were measured with the test set. The results indicate that the proposed classifier from FF‐OCT images shows promise as a label‐free assessment of quantified tumor detection, suggesting the fractal dimension‐based classifier could aid clinicians in detecting tumor boundaries for resection in surgery in the future.     

3D-Printed high-NA catadioptric thin lens for suppression of XPM background in Stimulated Raman Scattering microscopy

Stimulated Raman Scattering (SRS) is a fast chemical imaging technique with remarkable bioscience applications. Cross Phase Modulation (XPM) is a ubiquitous nonlinear phenomenon that can create spurious background signals that render difficult a high-contrast imaging in SRS measurements. The XPM-induced signal is usually suppressed using high numerical aperture (NA) microscope objectives or condensers to collect the transmitted excitation beam. However, these high NA optics feature short working distances, hence they are not compatible with stage-top incubators, that are necessary to perform live-cell time-lapse experiments in controlled environments. Here, we show a 3D printed high NA compact catadioptric lens that fits inside stage-top incubators and allows the collection of XPM-free SRS signals. The lens delivers SRS images and spectra with a quality comparable to a signal collection with a high-NA microscope objective. We also demonstrate the compatibility of the 3D printed lens with other nonlinear microscopies usually associated with SRS in multimodal microscopes.     

Fast denoising and lossless spectrum extraction in stimulated Raman scattering microscopy

Stimulated Raman scattering (SRS) microscopy is a nonlinear optical imaging method for visualizing chemical content based on molecular vibrational bonds. However, the imaging speed and sensitivity are currently limited by the noise of the light beam probing the Raman process. In this paper, we present a fast non-average denoising and high-precision Raman shift extraction method, based on a self-reinforcing signal-to-noise ratio (SNR) enhancement algorithm, for SRS spectroscopy and microscopy. We compare the results of this method with the filtering methods and the reported experimental methods to demonstrate its high efficiency and high precision in spectral denoising, Raman peak extraction and image quality improvement. We demonstrate a maximum SNR enhancement of 10.3 dB in fixed tissue imaging and 11.9 dB in vivo imaging. This method reduces the cost and complexity of the SRS system and allows for high-quality SRS imaging without use of special laser, complicated system design and Raman tags.     

En‐face optical coherence tomography for the detection of cancer in prostatectomy specimens: Quantitative analysis in 20 patients

The increase histopathological evaluation of prostatectomy specimens rises the workload on pathologists. Automated histopathology systems, preferably directly on unstained specimens, would accelerate the pathology workflow. In this study, we investigate the potential of quantitative analysis of optical coherence tomography (OCT) to separate benign from malignant prostate tissue automatically. Twenty fixated prostates were cut, from which 54 slices were scanned by OCT. Quantitative OCT metrics (attenuation coefficient, residue, goodness‐of‐fit) were compared for different tissue types, annotated on the histology slides. To avoid misclassification, the poor‐quality slides, and edges of annotations were excluded. Accurate registration of OCT data with histology was achieved in 31 slices. After removing outliers, 56% of the OCT data was compared with histopathology. The quantitative data could not separate malignant from benign tissue. Logistic regression resulted in malignant detection with a sensitivity of 0.80 and a specificity of 0.34. Quantitative OCT analysis should be improved before clinical use.     

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 , 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 : 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 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.     

Inside Cover: Efficient and cost‐effective 3D cellular imaging by sub‐voxel‐resolving light‐sheet add‐on microscopy

A type of compact and cost‐effective light‐sheet imaging device, termed sub‐voxel‐resolving light‐sheet add‐on module (SLAM), is developed to cooperate with conventional 2D epifluorescence microscope, allowing high‐contrast, resolution‐improved 3D imaging of various biological samples at high throughput. Further details can be found in the article by Fang Zhao, Yicong Yang, Yi Li, et al. ( e201960243 ).

     

Optical coherence tomography image denoising using a generative adversarial network with speckle modulation

Optical coherence tomography (OCT) is widely used for biomedical imaging and clinical diagnosis. However, speckle noise is a key factor affecting OCT image quality. Here, we developed a custom generative adversarial network (GAN) to denoise OCT images. A speckle‐modulating OCT (SM‐OCT) was built to generate low speckle images to be used as the ground truth. In total, 210 000 SM‐OCT images were used for training and validating the neural network model, which we call SM‐GAN. The performance of the SM‐GAN method was further demonstrated using online benchmark retinal images, 3D OCT images acquired from human fingers and OCT videos of a beating fruit fly heart. The denoise performance of the SM‐GAN model was compared to traditional OCT denoising methods and other state‐of‐the‐art deep learning based denoise networks. We conclude that the SM‐GAN model presented here can effectively reduce speckle noise in OCT images and videos while maintaining spatial and temporal resolutions.     

Three‐dimensional mapping of the attenuation coefficient in optical coherence tomography to enhance breast tissue microarchitecture contrast

Effective intraoperative tumor margin assessment is needed to reduce re‐excision rates in breast‐conserving surgery (BCS). Mapping the attenuation coefficient in optical coherence tomography (OCT) throughout a sample to create an image (attenuation imaging) is one promising approach. For the first time, three‐dimensional OCT attenuation imaging of human breast tissue microarchitecture using a wide‐field (up to ~45 × 45 × 3.5 mm) imaging system is demonstrated. Representative results from three mastectomy and one BCS specimen (from 31 specimens) are presented with co‐registered postoperative histology. Attenuation imaging is shown to provide substantially improved contrast over OCT, delineating nuanced features within tumors (including necrosis and variations in tumor cell density and growth patterns) and benign features (such as sclerosing adenosis). Additionally, quantitative micro‐elastography (QME) images presented alongside OCT and attenuation images show that these techniques provide complementary contrast, suggesting that multimodal imaging could increase tissue identification accuracy and potentially improve tumor margin assessment.     

Hyperspectral imaging as a diagnostic tool to differentiate between amalgam tattoos and other dark pigmented intraoral lesions

The goal of this project is to identify any in-depth benefits and drawbacks in the diagnosis of amalgam tattoos and other pigmented intraoral lesions using hyperspectral imagery collected from amalgam tattoos, benign, and malignant melanocytic neoplasms. Software solutions capable of classifying pigmented lesions of the skin already exist, but conventional red, green and blue images may be reaching an upper limit in their performance. Emerging technologies, such as hyperspectral imaging (HSI) utilize more than a hundred, continuous data channels, while also collecting data in the infrared. A total of 18 paraffin-embedded human tissue specimens of dark pigmented intraoral lesions (including the lip) were analyzed using visible and near-infrared (VIS–NIR) hyperspectral imagery obtained from HE-stained histopathological slides. Transmittance data were collected between 450 and 900 nm using a snapshot camera mounted to a microscope with a halogen light source. VIS–NIR spectra collected from different specimens, such as melanocytic cells and other tissues (eg, epithelium), produced distinct and diagnostic spectra that were used to identify these materials in several regions of interest, making it possible to distinguish between intraoral amalgam tattoos (intramucosal metallic foreign bodies) and melanocytic lesions of the intraoral mucosa and the lip (each with P < .01 using the independent t test). HSI is presented as a diagnostic tool for the rapidly growing field of digital pathology. In this preliminary study, amalgam tattoos were reliably differentiated from melanocytic lesions of the oral cavity and the lip.     

Classifying T cell activity in autofluorescence intensity images with convolutional neural networks

The importance of T cells in immunotherapy has motivated developing technologies to improve therapeutic efficacy. One objective is assessing antigen‐induced T cell activation because only functionally active T cells are capable of killing the desired targets. Autofluorescence imaging can distinguish T cell activity states in a non‐destructive manner by detecting endogenous changes in metabolic co‐enzymes such as NAD(P)H. However, recognizing robust activity patterns is computationally challenging in the absence of exogenous labels. We demonstrate machine learning methods that can accurately classify T cell activity across human donors from NAD(P)H intensity images. Using 8260 cropped single‐cell images from six donors, we evaluate classifiers ranging from traditional models that use previously‐extracted image features to convolutional neural networks (CNNs) pre‐trained on general non‐biological images. Adapting pre‐trained CNNs for the T cell activity classification task provides substantially better performance than traditional models or a simple CNN trained with the autofluorescence images alone. Visualizing the images with dimension reduction provides intuition into why the CNNs achieve higher accuracy than other approaches. Our image processing and classifier training software is available at https://github.com/gitter‐lab/t‐cell‐classification .     

The use of optical coherence tomography and convolutional neural networks to distinguish normal and abnormal oral mucosa

Incomplete surgical resection of head and neck squamous cell carcinoma (HNSCC) is the most common cause of local HNSCC recurrence. Currently, surgeons rely on preoperative imaging, direct visualization, palpation and frozen section to determine the extent of tissue resection. It has been demonstrated that optical coherence tomography (OCT), a minimally invasive, nonionizing near infrared mesoscopic imaging modality can resolve subsurface differences between normal and abnormal head and neck mucosa. Previous work has utilized two‐dimensional OCT imaging which is limited to the evaluation of small regions of interest generated frame by frame. OCT technology is capable of performing rapid volumetric imaging, but the capacity and expertise to analyze this massive amount of image data is lacking. In this study, we evaluate the ability of a retrained convolutional neural network to classify three‐dimensional OCT images of head and neck mucosa to differentiate normal and abnormal tissues with sensitivity and specificity of 100% and 70%, respectively. This method has the potential to serve as a real‐time analytic tool in the assessment of surgical margins.     

Front Cover: Photoacoustic imaging of the human placental vasculature (J. Biophotonics 4/2020)

Successful therapy of twin‐to‐twin transfusion syndrome requires accurate imaging to guide laser photocoagulation of the anastomosing placental vessels. Photoacoustic (PA) imaging is an alternative imaging method that provides contrast for hemoglobin, and in this study, it was used to visualize chorionic superficial and subsurface vasculature in human placentas. The strong potential of PA imaging to guide minimally invasive fetal therapies was demonstrated. Further details can be found in the article by Efthymios Maneas, Rosalind Aughwane, Nam Huynh, et al. ( e201900167 ).

     

High resolution,label‐free photoacoustic imaging of live chicken embryo developing in bioengineered eggshell

Chicken embryos have been proven to be an attractive vertebrate model for biomedical research. They have helped in making significant contributions for advancements in various fields like developmental biology, cancer research and cardiovascular studies. However, a non‐invasive, label‐free method of imaging live chicken embryo at high resolution still needs to be developed and optimized. In this work, we have shown the potential of photoacoustic tomography (PAT) for imaging live chicken embryos cultured in bioengineered eggshells. Laser pulses at wavelengths of 532 and 740 nm were used for attaining cross‐sectional images of chicken embryos at different developmental stages. Cross‐sections along different depths were imaged to gain knowledge of the relative depth of different vessels and organs. Due to high optical absorption of vasculature and embryonic eye, images with good optical contrast could be acquired using this method. We have thus reported a label‐free method of performing cross‐sectional imaging of chicken embryos at high resolution demonstrating the capacity of PAT as a promising tool for avian embryo imaging.     

Front Cover: Wide‐field monitoring and real‐time local recording of microvascular networks on small animals with a dual‐raster‐scanned photoacoustic microscope

A dual‐raster‐scanned photoacoustic microscope (DRS‐PAM) was reported, which integrates a two‐dimensional motorized translation stage for large field‐of‐view imaging and a two‐axis fast galvanometer scanner for real‐time imaging. The DRS‐PAM provides a flexible transition from wide‐field monitoring the vasculature of organs to real‐time imaging of local dynamics. Further details can be found in the article by Fei Yang, Zhiyang Wang, Wuyu Zhang, et al. ( e202000022 ).

     

Jones matrix‐based speckle‐decorrelation angiography using polarization‐sensitive optical coherence tomography

We show that polarization‐sensitive optical coherence tomography angiography (PS‐OCTA) based on full Jones matrix assessment of speckle decorrelation offers improved contrast and depth of vessel imaging over conventional OCTA. We determine how best to combine the individual Jones matrix elements and compare the resulting image quality to that of a conventional OCT scanner by co‐locating and imaging the same skin locations with closely matched scanning setups. Vessel projection images from finger and forearm skin demonstrate the benefits of Jones matrix‐based PS‐OCTA. Our study provides a promising starting point and a useful reference for future pre‐clinical and clinical applications of Jones matrix‐based PS‐OCTA.     

Unique spectral signature of human cutaneous squamous cell carcinoma by photoacoustic imaging

Cutaneous squamous cell carcinoma (cSCC) is a common skin cancer with metastatic potential. To reduce reoperations due to nonradical excision, there is a need to develop a technique for identification of tumor margins preoperatively. Photoacoustic (PA) imaging is a novel imaging technology that combines the strengths of laser optics and ultrasound. Our aim was to determine the spectral signature of cSCC using PA imaging and to use this signature to visualize tumor architecture and borders. Two‐dimensional PA images of 33 cSCCs and surrounding healthy skin were acquired ex vivo, using 59 excitation wavelengths from 680 to 970 nm. The spectral response of the cSCCs was compared to healthy tissue, and the difference was found to be greatest at wavelengths in the range 765 to 960 nm (P < .05). Three‐dimensional PA images were constructed from spectra obtained in the y‐z plane using a linear stepper motor moving along the x‐plane. Spectral unmixing was then performed which provided a clear three‐dimensional view of the distribution of tumor masses and their borders.     

Tissue clearing‐based method for unobstructed three‐dimensional imaging of mouse penis with subcellular resolution

Although mice are widely used to elucidate factors contributing to penile disorders and develop treatment options, quantification of tissue changes upon intervention is either limited to minuscule tissue volume (histology) or acquired with limited spatial resolution (MRI/CT). Thus, imaging method suitable for expeditious acquisition of the entire mouse penis with subcellular resolution is described that relies on both aqueous‐ (clear, unobstructed brain imaging cocktails and computational analysis) and solvent‐based (fluorescence‐preserving capability imaging of solvent‐cleared organs) tissue optical clearing (TOC). The combined TOC approach allows to image mouse penis innervation and vasculature with unprecedented detail and, for the first time, reveals the three‐dimensional structure of murine penis fibrocartilage.     

Inside Cover: Fingerprint‐to‐CH stretch continuously tunable high spectral resolution stimulated Raman scattering microscope (J. Biophotonics 9/2019)

A novel design of an SRS microscope exploiting spectral pulse shaping allows measurement of fingerprint to CH‐stretch SRS spectra without any modification of the optical setup. High spectral resolution over a broad vibrational range allows label‐free quantitative imaging of biological samples. An exemplary SRS broadband spectrum of lipid droplets in a liver cancer cell is shown in the picture. Further details can be found in the article by Sergey P. Laptenok, Vijayakumar P. Rajamanickam, Luca Genchi, et al. ( e201900028 ).

     

Multicomposite super‐resolution microscopy: Enhanced Airyscan resolution with radial fluctuation and sample expansions

Either modulated illumination or temporal fluctuation analysis can assist super‐resolution techniques in overcoming the diffraction limit of conventional optical microscopy. As they are not contradictory to each other, an effective combination of spatial and temporal super‐resolution mechanisms would further improve the resolution of fluorescent images. Here, a super‐resolution imaging method called fluctuation‐enhanced Airyscan technology (FEAST) is proposed, which achieves ~40 nm lateral imaging resolution and is useful for a range of fluorescent proteins and organic dyes. It was demonstrated not only to obtain different subcellular super‐resolution images, but also to improve the accuracy of counting the average human epidermal growth factor receptor 2 (HER2) copy number for diagnosis in breast cancer. Furthermore, the combination of FEAST and sample expansion microscopy (Ex‐FEAST) improves the lateral resolution to ~26 nm.