Optical coherence tomography in gastroenterology: a review and future outlook

Optical Coherence Tomography (OCT): A Brief Look at the Uses and Technological Evolution of Ophthalmology

Medical imaging is the mainstay of clinical diagnosis and management. Optical coherence tomography (OCT) is a non-invasive imaging technology that has revolutionized the field of ophthalmology. Since its introduction, OCT has undergone significant improvements in image quality, speed, and resolution, making it an essential diagnostic tool for various ocular pathologies. OCT has not only improved the diagnosis and management of ocular diseases but has also found applications in other fields of medicine. In this manuscript, we provide a brief overview of the history of OCT, its current uses and diagnostic capabilities to assess the posterior segment of the eye, and the evolution of this technology from time-domain (TD) to spectral-domain (SD) and swept-source (SS). This brief review will also discuss the limitations, advantages, disadvantages, and future perspectives of this technology in the field of ophthalmology.

Multi-window approach enables two-fold improvement in OCT axial resolution with strong side-lobe suppression and improved phase sensitivity

A common processing approach for optical coherence tomography (OCT) uses a window function (e.g., Hann or rectangular window) for spectral shaping prior to calculating the Fourier transform. Here we build on a multi-window approach [Opt. Express8, 5267 (2017)10.1364/BOE.8.005267] that enables improved resolution while still suppressing side-lobe intensity. The shape of the window function defines the trade-off between main-lobe width (resolution) and side-lobe intensity. We have extended the approach to include the interferometric phase for phase-sensitive applications like vibrometry and Doppler OCT. Using the Hann window as a reference, we show that 11 Taylor windows are sufficient to achieve 50% improvement in axial resolution, -31 dB side-lobe intensity, and 20% improvement in phase sensitivity with low computational cost.

Noninvasive diagnosis of oral squamous cell carcinoma by multi-level deep residual learning on optical coherence tomography images

BACKGROUND

Oral Squamous Cell Carcinoma (OSCC) is one of the most severe cancers in the world, and its early detection is crucial for saving patients. There is an inevitable necessity to develop the automatic noninvasive OSCC diagnosis approach to identify the malignant tissues on Optical Coherence Tomography (OCT) images.

METHODS

This study presents a novel Multi-Level Deep Residual Learning (MDRL) network to identify malignant and benign(normal) tissues from OCT images and trains the network in 460 OCT images captured from 37 patients. The diagnostic performances are compared with different methods in the image-level and the resected patch-level.

RESULTS

The MDRL system achieves the excellent diagnostic performance, with 91.2% sensitivity, 83.6% specificity, 87.5% accuracy, 85.3% PPV, and 90.2% NPV in image-level, with 0.92 AUC value. Besides, it also implements 100% sensitivity, 86.7% specificity, 93.1% accuracy, 87.5% PPV, and 100% NPV in the resected patch-level.

CONCLUSION

The developed deep learning system expresses superior performance in noninvasive oral squamous cell carcinoma diagnosis, compared with traditional CNNs and a specialist.

Deep-Learning-Based Automated Identification and Visualization of Oral Cancer in Optical Coherence Tomography Images

Early detection and diagnosis of oral cancer are critical for a better prognosis, but accurate and automatic identification is difficult using the available technologies. Optical coherence tomography (OCT) can be used as diagnostic aid due to the advantages of high resolution and non-invasion. We aim to evaluate deep-learning-based algorithms for OCT images to assist clinicians in oral cancer screening and diagnosis. An OCT data set was first established, including normal mucosa, precancerous lesion, and oral squamous cell carcinoma. Then, three kinds of convolutional neural networks (CNNs) were trained and evaluated by using four metrics (accuracy, precision, sensitivity, and specificity). Moreover, the CNN-based methods were compared against machine learning approaches through the same dataset. The results show the performance of CNNs, with a classification accuracy of up to 96.76%, is better than the machine-learning-based method with an accuracy of 92.52%. Moreover, visualization of lesions in OCT images was performed and the rationality and interpretability of the model for distinguishing different oral tissues were evaluated. It is proved that the automatic identification algorithm of OCT images based on deep learning has the potential to provide decision support for the effective screening and diagnosis of oral cancer.

Rapid Cellular-Resolution Skin Imaging with Optical Coherence Tomography Using All-Glass Multifocal Metasurfaces

Cellular-resolution optical coherence tomography (OCT) is a powerful tool offering noninvasive histology-like imaging. However, like other optical microscopy tools, a high numerical aperture (N.A.) lens is required to generate a tight focus, generating a narrow depth of field, which necessitates dynamic focusing and limiting the imaging speed. To overcome this limitation, we developed a metasurface platform that generates multiple axial foci, which multiplies the volumetric OCT imaging speed by offering several focal planes. This platform offers accurate and flexible control over the number, positions, and intensities of axial foci generated. All-glass metasurface optical elements 8 mm in diameter are fabricated from fused-silica wafers and implemented into our scanning OCT system. With a constant lateral resolution of 1.1 μm over all depths, the multifocal OCT triples the volumetric acquisition speed for dermatological imaging, while still clearly revealing features of stratum corneum, epidermal cells, and dermal-epidermal junctions and offering morphological information as diagnostic criteria for basal cell carcinoma. The imaging speed can be further improved in a sparse sample, e.g., 7-fold with a seven-foci beam. In summary, this work demonstrates the concept of metasurface-based multifocal OCT for rapid virtual biopsy, further providing insights for developing rapid volumetric imaging systems with high resolution and compact volume.

Diseased thyroid tissue classification in OCT images using deep learning: Towards surgical decision support

Intraoperative guidance tools for thyroid surgery based on optical coherence tomography (OCT) could aid distinguish between normal and diseased tissue. However, OCT images are difficult to interpret, thus, real-time automatic analysis could support the clinical decision-making. In this study, several deep learning models were investigated for thyroid disease classification on 2D and 3D OCT data obtained from ex vivo specimens of 22 patients undergoing surgery and diagnosed with several thyroid pathologies. Additionally, two open-access datasets were used to evaluate the custom models. On the thyroid dataset, the best performance was achieved by the 3D vision transformer model with a Matthew's correlation coefficient (MCC) of 0.79 (accuracy = 0.90) for the normal-versus-abnormal classification. On the open-access datasets, the custom models achieved the best performance (MCC > 0.88, accuracy > 0.96). Results obtained for the normal-versus-abnormal classification suggest OCT, complemented with deep learning-based analysis, as a tool for real-time automatic diseased tissue identification in thyroid surgery.

Effect of cigarettes smoke on bonded polymeric restorations: OCT study

Background

Up to date, the effect of cigarette smoke (CS) on the adhesive properties of the restorative materials bonded to tooth structure is still unclear. It is still questionable if it interferes with the durability and clinical success of these restorations. Few numbers of studies reported the assessment of microgaps of dental composite using cross-polarization optical coherence tomography (CP-OCT). The aim of this study was to evaluate the presence of interfacial microgaps between composite resin restoration and the tooth structure with or without exposure to CS under the CP-OCT.

Materials and methods

In this in-vitro study, a standardized round class-V cavities were prepared in twenty extracted, caries-free human molar teeth, and they were divided randomly into two groups (n = 10). Adhesive system (Gluma universal, Kulzer GmbH) was applied followed by filing the prepared cavities with flowable composite restoration (Charisma, Kulzer GmbH). Then, exposure to CS (40 cigarettes/day) was carried out for 14 days and the samples were stored in normal saline solution after each smoke exposure cycle. Next, all samples were immersed in ammoniac silver nitrate for 24 h, followed by immersion in a photo-developing solution for 8 h. Optical comparison was carried out by CP-OCT to assess microgaps percentage between smoke (SG) and non-smoke groups (NSG) at the axial walls (AW) and cavity floor (CF).

Results

Independent T-test showed that there was a significant difference between the two groups (SG, NSG) in AW microgaps percentage (p = 0.008), while there was no difference in CF (p = 0.15).

Conclusion

It can be inferred from the current finding that OCT can be used to predict the adaptability of the bonded restoration under the thermochemical influence. CS has a negative effect on the marginal integrity of the bonded polymeric restorations.

Classification of neck tissues in OCT images by using convolutional neural network

Identification and classification of surrounding neck tissues are very important in thyroid surgery. The advantages of optical coherence tomography (OCT), high resolution, non-invasion, and non-destruction make it have great potential in identifying different neck tissues during thyroidectomy. We studied the automatic classification for neck tissues in OCT images based on convolutional neural network in this paper. OCT images of five kinds of neck tissues were collected firstly by our home-made swept source (SS-OCT) system, and a dataset was built for neural network training. Three image classification neural networks: LeNet, VGGNet, and ResNet, were used to train and test the dataset. The impact of transfer learning on the classification of neck tissue OCT images was also studied. Through the comparison of accuracy, it was found that ResNet has the best classification accuracy among the three networks. In addition, transfer learning did not significantly improve the accuracy, but it can somewhat accelerate the convergence of the network and shorten the network training time.

Optical Coherence Tomography Is a Promising Tool for Zebrafish-Based Research-A Review

The zebrafish is an established vertebrae model in the field of biomedical research. With its small size, rapid maturation time and semi-transparency at early development stages, it has proven to be an important animal model, especially for high-throughput studies. Three-dimensional, high-resolution, non-destructive and label-free imaging techniques are perfectly suited to investigate these animals over various development stages. Optical coherence tomography (OCT) is an interferometric-based optical imaging technique that has revolutionized the diagnostic possibilities in the field of ophthalmology and has proven to be a powerful tool for many microscopic applications. Recently, OCT found its way into state-of-the-art zebrafish-based research. This review article gives an overview and a discussion of the relevant literature and an outlook for this emerging field.

Endoscopic imaging of white matter fiber tracts using polarization-sensitive optical coherence tomography

Polarization sensitive optical coherence tomography (PSOCT) has been shown to image and delineate white matter fibers in a label-free manner by revealing optical birefringence within the myelin sheath using a microscope setup. In this proof-of-concept study, we adapt recent advancements in endoscopic PSOCT to perform depth-resolved imaging of white matter structures deep inside intact porcine brain tissue ex-vivo, through a small, rotational fiber probe. The probe geometry is comparable to microelectrodes currently used in neurosurgical interventions. The presented imaging system is mobile, robust, and uses biologically safe levels of optical radiation making it well suited for clinical translation. In neurosurgery, where accuracy is imperative, endoscopic PSOCT through a narrow-gauge fiber probe could provide intra-operative feedback on the location of critical white matter structures.

Low-Cost In Vivo Full-Range Optical Coherence Tomography Using a Voice Coil Motor

In this work, we demonstrated a novel and low-cost full-range optical coherence tomography (FROCT) method. In comparison with the off-pivot approach, which needs precise control of the deflecting distance and should be adjusted for different situations, our proposed method is more flexible without regulating the system itself. Different from the previous systems reported in the literature, which used a high-cost piezo-driven stage to introduce the phase modulation, our system utilizes a cost-effective voice coil motor for retrieving the complex-valued spectral signal. The complex-valued data, with a twofold increase in the accessible depth range, can be calculated using an algorithm based on the Hilbert transform and Dirac delta function. To confirm the effectivity of our method, both simulation and experiments were performed. In particular, for the in vivo experiment, we presented the FROCT result of a fingernail fold, demonstrating the availability of in vivo imaging. Since the key element of our system is a low-cost voice coil motor, which is flexible and more accessible for most of the clinics, we believe that it has great potential to be a clinical modality in the future.

Investigation of different wavelengths for scattering-based light sheet microscopy

Scattering-based light sheet microscopy (sLSM) is a microscopy technique that can visualize cellular morphologic details based on the scattering signal. While sLSM was previously shown to image animal tissues ex vivo at a cellular resolution, the wavelength used was chosen based on other in vivo microscopy technologies rather than through a comparison of the sLSM imaging performance between different wavelengths. In this paper, we report the development of a multi-wavelength sLSM setup that facilitates the investigation of different wavelengths for sLSM imaging. Preliminary results of imaging human anal tissues ex vivo showed that the sLSM setup allowed for comparisons of the cellular imaging performance at the same tissue location between different wavelengths. Both the quantitative analysis of the image contrast and the visual assessment by a pathologist showed that the imaging depth increased with wavelength, and the imaging depth increase was most notable around 600 nm. The preliminary results showed that the multi-wavelength sLSM setup could be useful in identifying the optimal wavelength for the specific tissue type.

Passively scanned, single-fiber optical coherence tomography probes for gastrointestinal devices

BACKGROUND/OBJECTIVES

Optical coherence tomography (OCT) uses low coherence interferometry to obtain depth-resolved tissue reflectivity profiles (M-mode) and transverse beam scanning to create images of two-dimensional tissue morphology (B-mode). Endoscopic OCT imaging probes typically employ proximal or distal mechanical beam scanning mechanisms that increase cost, complexity, and size. Here, we demonstrate in the gastrointestinal (GI) tracts of unsedated human patients, that a passive, single-fiber probe can be used to guide device placement, conduct device-tissue physical contact sensing, and obtain two-dimensional OCT images via M-to-B-mode conversion.

MATERIALS AND METHODS

We designed and developed ultrasmall, manually scannable, side- and forward-viewing single fiber-optic probes that can capture M-mode OCT data. Side-viewing M-mode OCT probes were incorporated into brush biopsy devices designed to harvest the microbiome and forward-viewing M-mode OCT probes were integrated into devices that measure intestinal potential difference (IPD). The M-mode OCT probe-coupled devices were utilized in the GI tract in six unsedated patients in vivo. M-mode data were converted into B-mode images using an M-to-B-mode conversion algorithm. The effectiveness of physical contact sensing by the M-mode OCT probes was assessed by comparing the variances of the IPD values when the probe was in physical contact with the tissue versus when it was not. The capacity of forward- and side-viewing M-mode OCT probes to produce high-quality B-mode images was compared by computing the percentages of the M-to-B-mode images that showed close contact between the probe and the luminal surface. Passively scanned M-to-B-mode images were qualitatively compared to B-mode images obtained by mechanical scanning OCT tethered capsule endomicroscopy (TCE) imaging devices.

RESULTS

The incorporation of M-mode OCT probes in these nonendoscopic GI devices safely and effectively enabled M-mode OCT imaging, facilitating real-time device placement guidance and contact sensing in vivo. Results showed that M-mode OCT contact sensing improved the variance of IPD measurements threefold and side-viewing probes increased M-to-B-mode image visibility by 10%. Images of the esophagus, stomach, and duodenum generated by the passively scanned probes and M-to-B-mode conversion were qualitatively superior to B-mode images obtained by mechanically scanning OCT TCE devices.

CONCLUSION

These results show that passive, single optical fiber OCT probes can be effectively utilized for nonendoscopic device placement guidance, device contact sensing, and two-dimensional morphologic imaging in the human GI tract in vivo. Due to their small size, lower cost, and reduced complexity, these M-mode OCT probes may provide an easier avenue for the incorporation of OCT functionality into endoscopic/nonendoscopic devices.

Noninvasive oral cancer screening based on local residual adaptation network using optical coherence tomography

Oral cancer is known as one of the relatively common malignancy types worldwide. Despite the easy access of the oral cavity to examination, the invasive biopsy is still essential for final diagnosis, which requires laborious operation and complicated trained specialists. With the development of deep learning, the artificial intelligence (AI) technique is applied for oral cancer examinations and alleviates the workload of manual screening on biopsy. However, existing computer-aided oral cancer diagnostic methods focus on oral cavity environment photos and histology images, which require complicated operations for doctors and are invasive and painful for patients. As a noninvasive, real-time imaging technique, optical coherence tomography (OCT) can express sufficient identical information for oral cancer screening, but it has not been effectively explored for automatic oral cancer diagnosis. This paper proposes a novel deep learning method named Local Residual Adaptation Network (LRAN) for noninvasive oral cancer screening on OCT images, collected from 25 patients in Beijing Stomatological Hospital. Our proposed LRAN consists of a Residual Feature Representation (RFR) module and a Local Distribution Adaptation (LDA) module. Specifically, RFR firstly adopts stacked residual blocks as the backbone network to learn feature representations for training data, optimized by the Cross-Entropy loss, and then deploy Euclidean distance to measure the distribution distance between training and testing OCT images. Finally, LRAN achieves distribution-gap bridging by the LDA module, which integrates local maximum mean discrepancy constraint to estimate and minimize the distribution discrepancy between training and testing sets within the same category. We also collected an OCT-based oral cancer image dataset to evaluate the effectiveness of the proposed method, and it achieves an accuracy of 91.62%, a sensitivity of 91.66%, and a specificity of 92.58% on this self-collected dataset. Furthermore, we conduct a quantitative and qualitative analysis, and the results demonstrate LRAN model has excellent capability to solve the noninvasive oral cancer screening task.

Photoacoustic imaging of fresh human surgically and endoscopically resected gastrointestinal specimens

Objective

Photoacoustic (PA) imaging is a novel noninvasive technique that offers high‐contrast tomographic imaging with ultrasound‐like resolution at depths of centimeters, enabling visualization of deep small vessels. The aim of this pilot study was to survey the characteristics of deep vessel networks in the mucosa of neoplastic gastrointestinal (GI) lesions using PA imaging.

Methods

Specimens of patients who had undergone surgical and endoscopic resection for GI lesions were included in this study. The PA/ultrasound imaging system for clinical research is characterized by a technology that can superimpose a PA image over an ultrasound image. Three‐dimensional PA images were acquired for the resected specimen before fixation. The stomach and colon of live pigs were incised, and the walls were scanned from the mucosa.

Results

A total of 32 specimens (nine esophageal, 12 gastric, 11 colorectal) were scanned. The pathological diagnoses were adenomas (n = 2), intramucosal cancers (n = 14), and invasive cancers (n = 16). The deep vessel networks of all lesions could be visualized. In the intramucosal lesions, the deep vessel network was similar to that of a normal tissue. In invasive cancers, the thick and prominent vessel network was visible in the surface layer of esophageal cancers, infiltrated area of gastric cancers, and surface layer and infiltrated area of colorectal cancers. In the images of living pigs, visualizing the vascular network deeper than the submucosa in both the stomach and large intestine was possible.

Conclusion

Our study confirmed that the deep vessel networks of neoplastic GI lesions were visible by PA imaging.

Video-rate dual-modal photoacoustic and fluorescence imaging through a multimode fibre towards forward-viewing endomicroscopy

Multimode fibres (MMFs) are becoming increasingly attractive in optical endoscopy as they promise to enable unparallelled miniaturisation, spatial resolution and cost. However, high-speed imaging with wavefront shaping has been challenging. Here, we report the development of a video-rate dual-modal photoacoustic (PA) and fluorescence microscopy probe with a high-speed digital micromirror device (DMD) towards forward-viewing endomicroscopy. Optimal DMD patterns were obtained using a real-valued intensity transmission matrix algorithm to raster-scan a 1.5  μ m-diameter focused beam at the distal fibre tip for imaging. The PA imaging speed and spatial resolution were varied from  ∼ 2 to 57 frames per second and from 1.7 to 3  μ m, respectively. Further, high-fidelity PA images of carbon fibres and mouse red blood cells were acquired at unprecedented speed. The capability of dual-modal imaging was demonstrated with phantoms. We anticipate that with further miniaturisation of the ultrasound detector, this probe could be integrated into medical needles to guide minimally invasive procedures.

Effect of Surgical Technique on the Microstructure and Microcirculation of the Small Intestine Stump during Delayed Anastomosis: Multimodal OCT Data

The aim of the study was to use multimodal optical coherence tomography (MM OCT) to evaluate microstructure and microcirculation in the proximal and distal sections of the intestine relative to the resected area in acute mesenteric ischemia.

Lymph vessels visualization from optical coherence tomography data using depth-resolved attenuation coefficient calculation

Multimodal optical coherent tomography grows popularity with researchers and clinicians over the past decade. One of the modalities is lymphangiography, which allows visualization of the lymphatic vessel networks within optical coherence tomography (OCT) imaging volume. In the present study, it is shown that lymphatic vessel visualization obtained from the depth-resolved attenuation coefficient distributions, corrected for the noise, shows improved contrast and detail in comparison with previously proposed approaches. We also argue that the two most popular approaches for lymphatic vessel visualization, namely simple intensity thresholding and vesselness calculation based on local Hessian matrix eigenvalues, imply different definitions of the lymphatic vessel's appearance in the OCT volume and lead to the different networks.

Deep Learning in Biomedical Optics

This article reviews deep learning applications in biomedical optics with a particular emphasis on image formation. The review is organized by imaging domains within biomedical optics and includes microscopy, fluorescence lifetime imaging, in vivo microscopy, widefield endoscopy, optical coherence tomography, photoacoustic imaging, diffuse tomography, and functional optical brain imaging. For each of these domains, we summarize how deep learning has been applied and highlight methods by which deep learning can enable new capabilities for optics in medicine. Challenges and opportunities to improve translation and adoption of deep learning in biomedical optics are also summarized. Lasers Surg. Med. © 2021 Wiley Periodicals LLC.

Compressive sensing for polarization sensitive optical coherence tomography

In this report, we report on the implementation of compressive sensing (CS) and sparse sampling in polarization sensitive optical coherence tomography (PS-OCT) to reduce the number of B-scans (frames consisting of an array of A-scans, where each represents a single depth profile of reflections) required for effective volumetric (3D dataset composed of an array of B-scans) PS-OCT measurements (i.e. OCT intensity, and phase retardation) reconstruction. Sparse sampling of PS-OCT is achieved through randomization of step sizes along the slow-axis of PS-OCT imaging, covering the same spatial ranges as those with equal slow-axis step sizes, but with a reduced number of B-scans. Tested on missing B-scan rates of 25%, 50% and 75%, we found CS could reconstruct reasonably good (as evidenced by a correlation coefficient >0.6) PS-OCT measurements with a maximum reduced B-scan rate of 50%, thereby accelerating and doubling the rate of volumetric PS-OCT measurements.

Computational adaptive optics for polarization-sensitive optical coherence tomography

Defocus aberration in optical systems, including optical coherence tomography (OCT) systems employing Gaussian illumination, gives rise to the well-known compromise between transverse resolution and depth-of-field. This results in blurry images when out-of-focus, whilst other low-order aberrations (e.g., astigmatism, coma, etc.) present in both the OCT system and biological samples further reduce image resolution and contrast. Computational adaptive optics (CAO) is a computed optical interferometric imaging technique that modifies the phase of the OCT data in the spatial frequency domain to correct optical aberrations and provide improvement of the image quality throughout the three-dimensional (3D) volume. In this Letter, we report the first implementation of CAO for polarization-sensitive OCT to correct defocus and other low-order aberrations, providing enhanced polarization-sensitive imaging contrast (i.e., intensity and phase retardation) on a 3D OCT phantom, molded plastics, ex vivo chicken breast tissue, and ex vivo human breast cancer tissue.

Prospects of Intraoperative Multimodal OCT Application in Patients with Acute Mesenteric Ischemia

INTRODUCTION

Despite the introduction of increasingly multifaceted diagnostic techniques and the general advances in emergency abdominal and vascular surgery, the outcome of treatment of patients with acute impaired intestinal circulation remains unsatisfactory. The non-invasive and high-resolution technique of optical coherence tomography (OCT) can be used intraoperatively to assess intestine viability and associated conditions that frequently emerge under conditions of impaired blood circulation. This study aims to demonstrate the effectiveness of multimodal (MM) OCT for intraoperative diagnostics of both the microstructure (cross-polarization OCT mode) and microcirculation (OCT angiography mode) of the small intestine wall in patients with acute mesenteric ischemia (AMI).

METHODS AND PARTICIPANTS

A total of 18 patients were enrolled in the study. Nine of them suffered from AMI in segments II-III of the superior mesenteric artery (AMI group), whereby the ischemic segments of the intestine were examined. Nine others were operated on for adenocarcinoma of the colon (control group), thus allowing areas of their normal small intestine to be examined for comparison. Data on the microstructure and microcirculation in the walls of the small intestine were obtained intraoperatively from the side of the serous membrane using the MM OCT system (IAP RAS, Russia) before bowel resection. The MM OCT data were compared with the results of histological examination.

RESULTS

The study finds that MM OCT visualized the damage to serosa, muscularis externa, and blood vessels localized in these layers in 100% of AMI cases. It also visualized the submucosa in 33.3% of AMI cases. The MM OCT images of non-ischemic (control group), viable ischemic, and necrotic small intestines (AMI group) differed significantly across stratification of the distinguishable layers, the severity of intermuscular fluid accumulations, and the type and density of the vasculature.

CONCLUSION

The MM OCT diagnostic procedure optimally meets the requirements of emergency surgery. Data on the microstructure and microcirculation of the intestinal wall can be obtained simultaneously in real time without requiring contrast agent injections. The depth of visualization of the intestinal wall from the side of the serous membrane is sufficient to assess the volume of the affected tissues. However, the methodology for obtaining MM OCT data needs to be improved to minimize the motion artefacts generated in actual clinical conditions.

Multi-MHz MEMS-VCSEL swept-source optical coherence tomography for endoscopic structural and angiographic imaging with miniaturized brushless motor probes

Swept source optical coherence tomography (SS-OCT) enables volumetric imaging of subsurface structure. However, applications requiring wide fields of view (FOV), rapid imaging, and higher resolutions have been challenging because multi-MHz axial scan (A-scan) rates are needed. We describe a microelectromechanical systems vertical cavity surface-emitting laser (MEMS-VCSEL) SS-OCT technology for A-scan rates of 2.4 and 3.0 MHz. Sweep to sweep calibration and resampling are performed using dual channel acquisition of the OCT signal and a Mach Zehnder interferometer signal, overcoming inherent optical clock limitations and enabling higher performance. We demonstrate ultrahigh speed structural SS-OCT and OCT angiography (OCTA) imaging of the swine gastrointestinal tract using a suite of miniaturized brushless motor probes, including a 3.2 mm diameter micromotor OCT catheter, a 12 mm diameter tethered OCT capsule, and a 12 mm diameter widefield OCTA probe. MEMS-VCSELs promise to enable ultrahigh speed SS-OCT with a scalable, low cost, and manufacturable technology, suitable for a diverse range of imaging applications.

Endoscopic imaging in inflammatory bowel disease: current developments and emerging strategies

INTRODUCTION

Developments in enhanced and magnified endoscopy have signified major advances in endoscopic imaging of ileocolonic pathology in inflammatory bowel disease (IBD). Artificial intelligence is increasingly being used to augment the benefits of these advanced techniques. Nevertheless, treatment of IBD patients is frustrated by high rates of non-response to therapy, while delayed detection and failures to detect neoplastic lesions impede successful surveillance. A possible solution is offered by molecular imaging, which adds functional imaging data to mucosal morphology assessment through visualizing biological parameters. Other label-free modalities enable visualization beyond the mucosal surface without the need of tracers.

AREAS COVERED

A literature search up to May 2020 was conducted in PubMed/MEDLINE in order to find relevant articles that involve the (pre-)clinical application of high-definition white light endoscopy, chromoendoscopy, artificial intelligence, confocal laser endomicroscopy, endocytoscopy, molecular imaging, optical coherence tomography, and Raman spectroscopy in IBD.

EXPERT OPINION

Enhanced and magnified endoscopy have enabled an improved assessment of the ileocolonic mucosa. Implementing molecular imaging in endoscopy could overcome the remaining clinical challenges by giving practitioners a real-time in vivo view of targeted biomarkers. Label-free modalities could help optimize the endoscopic assessment of mucosal healing and dysplasia detection in IBD patients.

Classification of Salivary Gland Tumors Based on Quantitative Optical Coherence Tomography

BACKGROUND AND OBJECTIVES

Visual inspection is the primary diagnostic method for oral diseases, and its accuracy of diagnosis mainly depends on surgeons' experience. Histological examination is still the golden standard, but it is invasive and time-consuming. In order to address these issues, as a noninvasive imaging technique, optical coherence tomography (OCT) can differentiate oral tissue with advantages of real-time, in situ, and high resolution. The aim of this study is to explore optimal quantitative parameters in OCT images to distinguish different salivary gland tumors.

STUDY DESIGN/MATERIALS AND METHODS

OCT images of four salivary gland tumors were obtained from 14 patients, including mucoepidermoid carcinoma (MC), adenoid cystic carcinoma (ACC), basal cell adenoma (BCA), and pleomorphic adenoma (PA). Two parameters of optical attenuation coefficient (OAC) and standard deviation (SD) along the depth of OCT signal were combined to create a computational model of classification, and sensitivity/specificity of classification was calculated statistically to evaluate their results.

RESULTS

A total of 5,919 two-dimensional (2D) OCT images were used for quantitative analysis. The classification sensitivities of 89.6%, 95.0%, 89.5%, 97.8%, and specificities of 97.6%, 99.0%, 98.0%, 98.2%, respectively, were obtained for MC, ACC, BCA, and PA, with the thresholds of 3.6 mm^-1 based on OAC and 0.22/0.18 based on SD.

CONCLUSION

It was demonstrated that OAC and SD could be considered as important parameters in quantitative analysis of OCT images for salivary gland tissue characterization and intraoperative diagnosis. It is of great potential value in promoting the application of this method based on OCT in clinical practice. Lasers Surg. © 2020 Wiley Periodicals LLC.

Optical coherence tomography for the early detection of colorectal dysplasia and cancer: validation in a murine model

BACKGROUND

There is an urgent need to develop a non-invasive imaging technique for detecting colorectal dysplasia and cancer. Technology for early and real-time microscopic assessments to select the most representative biopsy sites would also be of clinical value. In this study, we explored the sensitivity of optical coherence tomography (OCT) in detecting local lesions to demonstrate its potential for the early detection of colorectal dysplasia and cancer.

METHODS

An azoxymethane/dextran sodium sulfate mouse model of colorectal carcinogenesis was utilized. Mice were imaged by OCT, and colorectal tissue sections were observed with hematoxylin and eosin staining. The results of the parallel analyses were compared to evaluate the performance of OCT in imaging and early screening of colorectal lesions.

RESULTS

Dysplasia and cancer could be distinguished from normal colon tissues based on the OCT images. However, simple morphological changes observed in the OCT images were not sufficient to distinguish different degrees of dysplasia or distinguish dysplasia from cancerous tissues. The Youden index and diagnostic efficiency of OCT for colorectal dysplasia and cancer were 62.50% and 82.14%, respectively, while the sensitivity and specificity were 87.50% and 75.00%, respectively. Further, the positive and negative predictive values were 82.35% and 81.82%, respectively.

CONCLUSIONS

Based on our findings, we predict that OCT is a promising non-invasive imaging technique that can offer excellent positive detection rates and diagnostic accuracy for early colorectal dysplasia and cancer. This technique is expected to be valuable in realizing real-time qualitative analysis and guided targeted biopsy.

Hereditary Diffuse Gastric Cancer: Approaches to Screening, Surveillance, and Treatment

Hereditary diffuse gastric cancer (HDGC) is a cancer syndrome associated with a significant lifetime risk of diffuse gastric cancer (DGC), a malignancy characterized by late clinical presentation and poor prognosis, as well as lobular breast cancer. HDGC is linked to germline pathogenic variants in the E-cadherin gene (CDH1) that are inherited in an autosomal dominant pattern; however, in many families with DGC clustering, no genetic cause has been identified. This review discusses key elements that allow risk assessment of potential inherited DGC susceptibility. We provide a practical overview of the recommendations for surveillance and treatment of individuals at risk and patients with early disease. The review also outlines future research avenues to improve our understanding of the genetic background and natural history of the disease, the endoscopic detection of early lesions, and the outcome of prophylactic surgery in young individuals.

Optical coherence tomography: current and future clinical applications in otology

PURPOSE OF REVIEW

This article reviews literature on the use of optical coherence tomography (OCT) in otology and provides the reader with a timely update on its current clinical and research applications. The discussion focuses on the principles of OCT, the use of the technology for the diagnosis of middle ear disease and for the delineation of in-vivo cochlear microarchitecture and function.

RECENT FINDINGS

Recent advances in OCT include the measurement of structural and vibratory properties of the tympanic membrane, ossicles and inner ear in healthy and diseased states. Accurate, noninvasive diagnosis of middle ear disease, such as otosclerosis and acute otitis media using OCT, has been validated in clinical studies, whereas inner ear OCT imaging remains at the preclinical stage. The development of recent microscopic, otoscopic and endoscopic systems to address clinical and research problems is reviewed.

SUMMARY

OCT is a real-time, noninvasive, nonionizing, point-of-care imaging modality capable of imaging ear structures in vivo. Although current clinical systems are mainly focused on middle ear imaging, OCT has also been shown to have the ability to identify inner ear disease, an exciting possibility that will become increasingly relevant with the advent of targeted inner ear therapies.

Identification of oral cancer in OCT images based on an optical attenuation model

Surgery is still the first choice to treat oral cancer, where it is important to detect surgical margins in order to reduce cancer recurrence and maintain oral-maxillofacial function simultaneously. As a non-invasive and in situ imaging technique, optical coherence tomography (OCT) can obtain images close to the resolution of histopathology, which makes it have great potential in intraoperative diagnosis. However, it is not enough to find surgical margins accurately just observing OCT images directly and qualitatively. The purpose of this study is to identify oral cancer in OCT images by investigating the quantitative difference of cancer and non-cancer tissue. Based on an available optical attenuation model and the axial confocal PSF of a home-made swept source OCT system, by using fresh ex vivo human oral tissues from 14 patients of oral squamous cell carcinoma (OSCC) as the samples, diagnosis with sensitivity (97.88%) and specificity (83.77%) was achieved at the attenuation threshold of 4.7 mm^-1, and the accuracy of identification reached 91.15% in our study. Our preliminary results demonstrated that the oral cancer resection will be guided accurately and the clinical application of OCT will be further promoted by deeply mining the information hidden in OCT images.

Real-time colorectal cancer diagnosis using PR-OCT with deep learning

Prior reports have shown optical coherence tomography (OCT) can differentiate normal colonic mucosa from neoplasia, potentially offering an alternative technique to endoscopic biopsy - the current gold-standard colorectal cancer screening and surveillance modality. To help clinical translation limited by processing the large volume of generated data, we designed a deep learning-based pattern recognition (PR) OCT system that automates image processing and provides accurate diagnosis potentially in real-time. Method: OCT is an emerging imaging technique to obtain 3-dimensional (3D) "optical biopsies" of biological samples with high resolution. We designed a convolutional neural network to capture the structure patterns in human colon OCT images. The network is trained and tested using around 26,000 OCT images acquired from 20 tumor areas, 16 benign areas, and 6 other abnormal areas. Results: The trained network successfully detected patterns that identify normal and neoplastic colorectal tissue. Experimental diagnoses predicted by the PR-OCT system were compared to the known histologic findings and quantitatively evaluated. A sensitivity of 100% and specificity of 99.7% can be reached. Further, the area under the receiver operating characteristic (ROC) curves (AUC) of 0.998 is achieved. Conclusions: Our results demonstrate that PR-OCT can be used to give an accurate real-time computer-aided diagnosis of colonic neoplastic mucosa. Future development of this system as an "optical biopsy" tool to assist doctors in real-time for early mucosal neoplasms screening and treatment evaluation following initial oncologic therapy is planned.

Integrating photoacoustic microscopy, optical coherence tomography, OCT angiography, and fluorescence microscopy for multimodal imaging

We have developed a multimodal imaging system, which integrated optical resolution photoacoustic microscopy, optical coherence tomography, optical coherence tomography angiography, and confocal fluorescence microscopy in one platform. The system is able to image complementary features of a biological sample by combining different contrast mechanisms. We achieved fast imaging and large field of view by combining optical scanning with mechanical scanning, similar to our previous publication. We have demonstrated the capability of the multimodal imaging system by imaging a mouse ear in vivo.

Impact statement

Photoacoustic microscopy-based multimodal imaging technology can provide high-resolution complementary information for biological tissues in vivo. It will potentially bring significant impact on the research and diagnosis of diseases by providing combined structural and functional information.

Trans-Serosal Multimodal Optical Coherence Tomography for Visualization of Microstructure and Blood Circulation of the Small Intestine Wall

The aim of the study was to evaluate the performance of trans-serosal multimodal OCT (MM OCT) in in vivo detecting of changes in microstructure and blood circulation of the small intestine wall caused by arteriovenous ischemia resulted from intestine strangulation.

Assessing colitis ex vivo using optical coherence elastography in a murine model

BACKGROUND

Ulcerative colitis (UC) is an inflammatory bowel disease (IBD) that causes regions of ulceration within the interior of the colon. UC is estimated to afflict hundreds of thousands of people in the United States alone. In addition to traditional colonoscopy, ultrasonic techniques can detect colitis, but have limited spatial resolution, which frequently results in underdiagnoses. Nevertheless, clinical diagnosis of colitis is still generally performed via colonoscopy. Optical techniques such as confocal microscopy and optical coherence tomography (OCT) have been proposed to detect UC with higher resolution. However, UC can potentially alter tissue biomechanical properties, providing additional contrast for earlier and potentially more accurate detection. Although clinically available elastography techniques have been immensely useful, they do not have the resolution for imaging small tissues, such as in small mammalian disease models. However, OCT-based elastography, optical coherence elastography (OCE), is well-suited for imaging the biomechanical properties of small mammal colon tissue.

METHODS

In this work, we induced elastic waves in ex vivo mouse colon tissue using a focused air-pulse. The elastic waves were detected using a phase-stabilized swept source OCE system, and the wave velocity was translated into stiffness. Measurements were taken at six positions for each sample to assess regional sample elasticity. Additional contrast between the control and diseased tissue was detected by analyzing the dispersion of the elastic wave and tissue optical properties obtained from the OCT structural image.

RESULTS

The results show distinct differences (P<0.05) in the stiffness between control and colitis disease samples, with a Young's modulus of 11.8±8.0 and 5.1±1.5 kPa, respectively. The OCT signal standard deviations for control and diseased samples were 5.8±0.3 and 5.5±0.2 dB, respectively. The slope of the OCT signal spatial frequency decay in the control samples was 92.7±10.0 and 87.3±4.7 dB∙µm in the colitis samples. The slope of the linearly fitted dispersion curve in the control samples was 1.5 mm, and 0.8 mm in the colitis samples.

CONCLUSIONS

Our results show that OCE can be utilized to distinguish tissue based on stiffness and optical properties. Our estimates of tissue stiffness suggest that the healthy colon tissue was stiffer than diseased tissue. Furthermore, structural analysis of the tissue indicates a distinct difference in tissue optical properties between the healthy and UC-like diseased tissue.

Gastrointestinal diagnosis using non-white light imaging capsule endoscopy

Capsule endoscopy (CE) has proved to be a powerful tool in the diagnosis and management of small bowel disorders since its introduction in 2001. However, white light imaging (WLI) is the principal technology used in clinical CE at present, and therefore, CE is limited to mucosal inspection, with diagnosis remaining reliant on visible manifestations of disease. The introduction of WLI CE has motivated a wide range of research to improve its diagnostic capabilities through integration with other sensing modalities. These developments have the potential to overcome the limitations of WLI through enhanced detection of subtle mucosal microlesions and submucosal and/or transmural pathology, providing novel diagnostic avenues. Other research aims to utilize a range of sensors to measure physiological parameters or to discover new biomarkers to improve the sensitivity, specificity and thus the clinical utility of CE. This multidisciplinary Review summarizes research into non-WLI CE devices by organizing them into a taxonomic structure on the basis of their sensing modality. The potential of these capsules to realize clinically useful virtual biopsy and computer-aided diagnosis (CADx) is also reported.

Ten Years of Gabor-Domain Optical Coherence Microscopy

Gabor-domain optical coherence microscopy (GDOCM) is a high-definition imaging technique leveraging principles of low-coherence interferometry, liquid lens technology, high-speed imaging, and precision scanning. GDOCM achieves isotropic 2 μm resolution in 3D, effectively breaking the cellular resolution limit of optical coherence tomography (OCT). In the ten years since its introduction, GDOCM has been used for cellular imaging in 3D in a number of clinical applications, including dermatology, oncology and ophthalmology, as well as to characterize materials in industrial applications. Future developments will enhance the structural imaging capability of GDOCM by adding functional modalities, such as fluorescence and elastography, by estimating thicknesses on the nano-scale, and by incorporating machine learning techniques.

Optical coherence tomography-guided laser marking with tethered capsule endomicroscopy in unsedated patients

Tethered capsule endomicroscopy (TCE) is an emerging screening technology that comprehensively obtains microstructural OCT images of the gastrointestinal (GI) tract in unsedated patients. To advance clinical adoption of this imaging technique, it will be important to validate TCE images with co-localized histology, the current diagnostic gold standard. One method for co-localizing OCT images with histology is image-targeted laser marking, which has previously been implemented using a driveshaft-based, balloon OCT catheter, deployed during endoscopy. In this paper, we present a TCE device that scans and targets the imaging beam using a low-cost stepper motor that is integrated inside the capsule. In combination with a 4-laser-diode, high power 1430/1450 nm marking laser system (800 mW on the sample and 1s pulse duration), this technology generated clearly visible marks, with a spatial targeting accuracy of better than 0.5 mm. A laser safety study was done on swine esophagus ex vivo, showing that these exposure parameters did not alter the submucosa, with a large, 4-5x safety margin. The technology was demonstrated in living human subjects and shown to be effective for co-localizing OCT TCE images to biopsies obtained during subsequent endoscopy.

Advanced Endoluminal Technologies for Barrett's Esophagus: Focus on Optical Coherence Tomography and Confocal Laser Endomicroscopy

Barrett's esophagus (BE) may progress to dysplasia and adenocarcinoma. The value of Barrett's surveillance with random biopsies is being questioned, but new technologies may enhance detection of progression within BE and guide endoscopic resection and ablation techniques. This review will focus on optical coherence tomography and endomicroscopy for patients with BE.

Three-dimensional endoscopic OCT using sparse sampling with a miniature magnetic-driven scanning probe

We propose to apply sparse sampling and compressive sensing (CS) reconstruction in three-dimensional (3D) endoscopic optical coherence tomography (OCT) to reduce the amount of data required in the imaging process. We used a homemade miniature side-imaging magnetic-driven scanning probe with an outer diameter of 1.4 mm in a 1310 nm swept-source OCT system to acquire two-dimensional (2D) circumferential cross-sectional images of an ex vivo pigeon trachea sample. 3D imaging is then achieved by reconstruction from the multiple 2D images acquired while pulling the sample with a translation stage. Given a total translation distance, we achieved sparse sampling by randomizing the step sizes of the translation stage such that the total number of the acquired 2D frames was reduced compared with conventional 3D imaging with equally spaced step positions. We tested the CS reconstruction with reduced 2D frame numbers of 40%, 60%, and 80% compared with the case of equally spaced step positions. The results show that it is possible to recover reasonable OCT images using sparse sampling with CS reconstruction. Compared with the conventional equally spaced sampling method, our method provides a novel way for image acquisition and reconstruction that could significantly reduce the amount of 3D OCT imaging data, and thus the acquisition time.

Detecting murine Inflammatory Bowel Disease using Optical Coherence Elastography

Ulcerative colitis (UC) is an inflammatory bowel disease (IBD) that causes regions of ulceration within the interior of the colon. UC is estimated to afflict hundreds of thousands of people in the United States alone. Ultrasonic techniques can detect colitis, but have limited spatial resolution, which frequently results in underdiagnoses. Nevertheless, clinical diagnosis of colitis is still generally performed via colonoscopy. Optical techniques such as confocal microscopy and optical coherence tomography (OCT) have been proposed as higher resolution alternative imaging modalities to detect colitis. Additionally, IBD can potentially alter tissue biomechanical properties, which cannot be quantified from structural imaging alone. Elastography is a potential method to assess colon biomechanical properties to provide additional contrast for distinguishing healthy and diseased colon tissue. In this work, we induced elastic waves in ex vivo mouse colon tissue using a focused air-pulse. The elastic waves were detected using a phase-stabilized swept source optical coherence elastography system, and the wave velocity was translated into stiffness. Measurements were taken at six random positions for each sample in order to assess regional sample elasticity. The results show distinct differences ($p \lt 0.05$) in the stiffness between healthy and IBD-diseased samples, with a Young's Modulus of $10.2 \pm 3.7$ kPa and $4.9 \pm 0.3$ kPa, respectively. Dispersion analysis presents another parameter to distinguish tissue health. The high frequency components of the phase velocity dispersion curve indicate a variation between healthy and IBD colonic tissue. Our results show that OCE may be useful for detecting IBD noninvasively.

Optical coherence tomography in Optics Express [Invited]

Optical coherence tomography (OCT) is one of the most successful technologies in the history of biomedical optics. Optics Express played an important role in communicating groundbreaking technological achievements in the field of OCT, and, conversely, OCT papers are among the most frequently cited papers published in Optics Express. On the occasion of the 20th anniversary of the journal, this review analyzes the reasons for the success of OCT papers in Optics Express and discusses possible motivations for researchers to submit some of their best OCT papers to the journal.

Modified wavelength scanning interferometry for simultaneous tomography and topography of the cornea with Fourier domain optical coherence tomography

Visual acuity is dependent on corneal shape and size. A minor variation in surface geometry can cause a deformation of corneal geometry, which affects its optical performance. In this work we demonstrate an algorithm for the simultaneous measurement of corneal tomography and topography with a traditional point-scanning Fourier domain optical coherence tomography (FD-OCT) system. A modified wavelength scanning interferometry (mWSI) algorithm enabled topographical evaluation of the surface with nanometer-scale resolution, which is superior to the micrometer-scale resolution of traditional OCT structural imaging. We validated the technique with an optically flat mirror, standard roughness gauges, and atomic force microscopy (AFM). The mirror results show nanometer-scale sensitivity (~3.5 nm), and the mWSI measurements were in good agreement (error ~5%) with the specifications of the roughness comparator and AFM, demonstrating the accuracy of the technique. Following validation, the measurements were made on pig corneas in situ at various artificially controlled intraocular pressures (IOP) and before and after cross-linking (CXL). The results show that the mean surface roughness increased by ~65% after removal of the epithelium in preparation for CXL but did not change as a function of IOP. The demonstrated method could be used for simultaneous measurement of tissue tomography with micrometer-precision and topography with nanometer-precision.

Recent advances in Barrett's esophagus

Barrett's esophagus (BE) is the only known precursor of esophageal adenocarcinoma, one of the few cancers with increasing incidence in developed countries. The pathogenesis of BE is unclear with regard to either the cellular origin of this metaplastic epithelium or the manner in which malignant transformation occurs, although recent data indicate a possible junctional origin of stem cells for BE. Treatment of BE may be achieved using endoscopic eradication therapy; however, there is a lack of discriminatory tools to identify individuals at sufficient risk for cancer development in whom intervention is warranted. Reduction in gastroesophageal reflux of gastric contents including acid is mandatory to achieve remission from BE after endoscopic ablation, and can be achieved using medical or nonmedical interventions. Research topics of greatest interest include the mechanism of BE development and transformation to cancer, risk stratification methods to identify individuals who may benefit from ablation of BE, optimization of eradication therapy, and surveillance methods to ensure that remission is maintained after eradication is achieved.