Full-range space-division multiplexing optical coherence tomography angiography.

In this study, we demonstrated a full-range space-division multiplexing optical coherence tomography (FR-SDM-OCT) system. Utilizing the galvanometer-based phase modulation full-range technique, the total imaging range of FR-SDM-OCT can be extended to >20 mm in tissue, with a digitizer sampling rate of 500 MS/s and a laser sweeping rate of 100 kHz. Complex conjugate terms were suppressed in FR-SDM-OCT images with a measured rejection ratio of up to ∼46 dB at ∼1.4 mm depth and ∼30 dB at ∼19.4 mm depth. The feasibility of FR-SDM-OCT was validated by imaging Scotch tapes and human fingernails. Furthermore, we demonstrated the feasibility of FR-SDM-OCT angiography (FR-SDM-OCTA) to perform simultaneous acquisition of human fingernail angiograms from four positions, with a total field-of-view of ∼1.7 mm × âˆ¼7.5 mm. Employing the full-range technique in SDM-OCT can effectively alleviate hardware requirements to achieve the long depth measurement range, which is required by SDM-OCT to separate multiple images at different sample locations. FR-SDM-OCTA creates new opportunities to apply SDM-OCT to obtain wide-field angiography of in vivo tissue samples free of labeling.

Non-invasive red-light optogenetic control of Drosophila cardiac function.

Drosophila is a powerful genetic model system for cardiovascular studies. Recently, optogenetic pacing tools have been developed to control Drosophila heart rhythm noninvasively with blue light, which has a limited penetration depth. Here we developed both a red-light sensitive opsin expressing Drosophila system and an integrated red-light stimulation and optical coherence microscopy (OCM) imaging system. We demonstrated noninvasive control of Drosophila cardiac rhythms using a single light source, including simulated tachycardia in ReaChR-expressing flies and bradycardia and cardiac arrest in halorhodopsin (NpHR)-expressing flies at multiple developmental stages. By using red excitation light, we were able to pace flies at higher efficiency and with lower power than with equivalent blue light excitation systems. The recovery dynamics after red-light stimulation of NpHR flies were observed and quantified. The combination of red-light stimulation, OCM imaging, and transgenic Drosophila systems provides a promising and easily manipulated research platform for noninvasive cardiac optogenetic studies.

FlyNet 2.0: drosophila heart 3D (2D + time) segmentation in optical coherence microscopy images using a convolutional long short-term memory neural network.

A custom convolutional neural network (CNN) integrated with convolutional long short-term memory (LSTM) achieves accurate 3D (2D + time) segmentation in cross-sectional videos of the Drosophila heart acquired by an optical coherence microscopy (OCM) system. While our previous FlyNet 1.0 model utilized regular CNNs to extract 2D spatial information from individual video frames, convolutional LSTM, FlyNet 2.0, utilizes both spatial and temporal information to improve segmentation performance further. To train and test FlyNet 2.0, we used 100 datasets including 500,000 fly heart OCM images. OCM videos in three developmental stages and two heartbeat situations were segmented achieving an intersection over union (IOU) accuracy of 92%. This increased segmentation accuracy allows morphological and dynamic cardiac parameters to be better quantified.

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.

Wide-field Ophthalmic Space-Division Multiplexing Optical Coherence Tomography.

High-speed ophthalmic optical coherence tomography systems are of interest because they allow rapid, motion-free, and wide-field retinal imaging. Space-division multiplexing optical coherence tomography (SDM-OCT) is a high-speed imaging technology which takes advantage of the long coherence length of microelectromechanical vertical cavity surface emitting laser (MEMs VCSEL) sources to multiplex multiple images along a single imaging depth. We demonstrate wide-field retinal OCT imaging, acquired at an effective A-scan rate of 800,000 A-scans/sec with volumetric images covering up to 12.5 mm × 7.4 mm on the retina acquired in less than 1 second. A clinical feasibility study was conducted to compare the ophthalmic SDM-OCT with commercial OCT systems, illustrating the high-speed capability of SDM-OCT in a clinical setting.

Computer-Aided Diagnosis of Label-Free 3-D Optical Coherence Microscopy Images of Human Cervical Tissue.

OBJECTIVE: Ultrahigh-resolution optical coherence microscopy (OCM) has recently demonstrated its potential for accurate diagnosis of human cervical diseases. One major challenge for clinical adoption, however, is the steep learning curve clinicians need to overcome to interpret OCM images. Developing an intelligent technique for computer-aided diagnosis (CADx) to accurately interpret OCM images will facilitate clinical adoption of the technology and improve patient care. METHODS: 497 high-resolution three-dimensional (3-D) OCM volumes (600 cross-sectional images each) were collected from 159 ex vivo specimens of 92 female patients. OCM image features were extracted using a convolutional neural network (CNN) model, concatenated with patient information [e.g., age and human papillomavirus (HPV) results], and classified using a support vector machine classifier. Ten-fold cross-validations were utilized to test the performance of the CADx method in a five-class classification task and a binary classification task. RESULTS: An 88.3 ± 4.9% classification accuracy was achieved for five fine-grained classes of cervical tissue, namely normal, ectropion, low-grade and high-grade squamous intraepithelial lesions (LSIL and HSIL), and cancer. In the binary classification task [low-risk (normal, ectropion, and LSIL) versus high-risk (HSIL and cancer)], the CADx method achieved an area-under-the-curve value of 0.959 with an 86.7 ± 11.4% sensitivity and 93.5 ± 3.8% specificity. CONCLUSION: The proposed deep-learning-based CADx method outperformed four human experts. It was also able to identify morphological characteristics in OCM images that were consistent with histopathological interpretations. SIGNIFICANCE: Label-free OCM imaging, combined with deep-learning-based CADx methods, holds a great promise to be used in clinical settings for the effective screening and diagnosis of cervical diseases.

Ultrahigh-resolution optical coherence microscopy accurately classifies precancerous and cancerous human cervix free of labeling.

Cervical cancer remains the fourth most common cause of cancer worldwide and the third leading cause of cancer deaths for women in developing countries. Traditional screening tools, such as human papillomavirus and Pap tests, cannot provide results in real-time and cannot localize suspicious regions. Colposcopy-directed biopsies are invasive in nature and only a few sites of the cervix may be chosen for investigation. A non-invasive, label-free and real-time imaging method with a resolution approaching that of histopathology is desirable for early detection of the disease. Methods: Ultrahigh-resolution optical coherence microscopy (OCM) is an emerging imaging technique used to obtain 3-dimensional (3-D) "optical biopsies" of biological samples with cellular resolution. In this study, 497 3-D OCM datasets from 159 specimens were collected from 92 patients. Results: Distinctive patterns for normal cervix, squamocolumnar junction, ectropion, low-grade and high-grade squamous intraepithelial lesions (LSIL and HSIL) and invasive cervical lesions were clearly observed from OCM images, which matched well with corresponding histological slides. OCM images demonstrated a sensitivity of 80% (95% confidence interval, CI, 72%-86%) and a specificity of 89% (95% CI, 84%-93%) for detecting high-risk lesions (HSIL and invasive lesions) when blindly tested by three investigators. A substantial inter-observer agreement was observed (κ=0.627), which showed high diagnostic consistency among three investigators. Conclusion: These results laid the foundation for future non-invasive optical evaluation of cervical tissue in vivo, which could lead to a less invasive and more effective screening and "see-and-treat" strategy for the management of cervical cancer.

Optical Coherence Tomography for Brain Imaging and Developmental Biology.

Optical coherence tomography (OCT) is a promising research tool for brain imaging and developmental biology. Serving as a three-dimensional optical biopsy technique, OCT provides volumetric reconstruction of brain tissues and embryonic structures with micrometer resolution and video rate imaging speed. Functional OCT enables label-free monitoring of hemodynamic and metabolic changes in the brain in vitro and in vivo in animal models. Due to its non-invasiveness nature, OCT enables longitudinal imaging of developing specimens in vivo without potential damage from surgical operation, tissue fixation and processing, and staining with exogenous contrast agents. In this paper, various OCT applications in brain imaging and developmental biology are reviewed, with a particular focus on imaging heart development. In addition, we report findings on the effects of a circadian gene (Clock) and high-fat-diet on heart development in Drosophila melanogaster. These findings contribute to our understanding of the fundamental mechanisms connecting circadian genes and obesity to heart development and cardiac diseases.

Drosophila Preparation and Longitudinal Imaging of Heart Function In Vivo Using Optical Coherence Microscopy (OCM).

Longitudinal study of the heartbeat in small animals contributes to understanding structural and functional changes during heart development. Optical coherence microscopy (OCM) has been demonstrated to be capable of imaging small animal hearts with high spatial resolution and ultrahigh imaging speed. The high image contrast and noninvasive properties make OCM ideal for performing longitudinal studies without requiring tissue dissections or staining. Drosophila has been widely used as a model organism in cardiac developmental studies due to its high number of orthologous human disease genes, its similarity of molecular mechanisms and genetic pathways with vertebrates, its short life cycle, and its low culture cost. Here, the experimental protocols are described for the preparation of Drosophila and optical imaging of the heartbeat with a custom OCM system throughout the life cycle of the specimen. By following the steps provided in this report, transverse M-mode and 3D OCM images can be acquired to conduct longitudinal studies of the Drosophila cardiac morphology and function. The en face and axial sectional OCM images and the heart rate (HR) and cardiac activity period (CAP) histograms, were also shown to analyze the heart structural changes and to quantify the heart dynamics during Drosophila metamorphosis, combined with the videos constructed with M-mode images to trace cardiac activity intuitively. Due to the genetic similarity between Drosophila and vertebrates, longitudinal study of heart morphology and dynamics in fruit flies could help reveal the origins of human heart diseases. The protocol here would provide an effective method to perform a wide range of studies to understand the mechanisms of cardiac diseases in humans.