Delineating papillary dermis around basal cell carcinomas by high and ultrahigh resolution optical coherence tomography—A pilot study

Bedside diagnosis of skin cancer remains a challenging task. The real-time noninvasive technology of optical coherence tomography (OCT) masters a high diagnostic accuracy in basal cell carcinoma (BCC) but a lower specificity in recognizing imitators and other carcinomas. We investigate the delicate signal of papillary dermis using an in-house developed ultrahigh resolution OCT (UHR-OCT) system with shadow compensation and a commercial multi-focus high resolution OCT (HR-OCT) system for clinical BCC imaging. We find that the HR-OCT system struggled to resolve the dark band signal of papillary dermis where the UHR-OCT located this in all cases and detected changes in signal width. UHR-OCT is able to monitor extension and position of papillary dermis suggesting a novel feature for delineating superficial BCCs in pursuit of a fast accurate diagnosis. Comprehensive studies involving more patients are imperative in order to corroborate results.     

Optical coherence tomography as a noninvasive 3D real time imaging tool for the rapid evaluation of phenotypic variations in insect embryonic development

Noninvasive visualization of embryos at different development stages is crucial for the understanding of the basic developmental biology. It is therefore desirable to have an imaging tool capable of rapidly evaluating the effects of gene manipulation or genome editing in developing embryos for the studies of gene functions and genetic engineering. Here, we propose and demonstrate a novel use of optical coherence tomography (OCT) to noninvasively exam the embryonic development of the migratory locusts in real time with 3‐dimensional (3D) view capability. In particular, we obtain the sufficiently high spatial resolution tomographic 2D and 3D images of live locust embryos throughout their development processes. We show that not only we are able to noninvasively observe all previously known forms of blastokinesis as an embryo develops, such as anatrepsis, katatrepsis, revolution, rotation and diapauses, and determine their precise occurring time or duration, but also discover an unreported rotation form we named “twist.” In addition, with the OCT images we determined the exact occurring time of diapauses of the locusts from Tibetan plateau for the first time. Finally, we demonstrate that OCT systems can be used to rapidly capture the development defects of genetically modified embryos in which certain genes essential for embryonic development were suppressed by RNA interference. Our work shows that OCT is an enabling imaging tool with sufficient spatial resolution for the rapid evaluation of embryonic variations of small animals.     

A spatial resolution evaluation method of endoscopic optical coherence tomography system using the annular phantom

As an important biomedical imaging method, endoscopic optical coherence tomography (OCT) is necessary to check its performance regularly. The ordinary plane phantoms are only able to evaluate part of image tangent to the probe. In this research, a spatial resolution estimate method of the endoscope OCT system is proposed. The annular phantom, made by uniformly distributing golden scattered microparticles in polydimethylsiloxane (PDMS), can provide dynamic scanning imaging evaluation of endoscopic OCT system, closer to its actual working status. The point spread function analysis method is used to analyze the imaging results of the annular phantom with the endoscopic OCT system. And many scattered particles are statistically analyzed to determine the spatial resolution of the endoscope OCT system. The method is low in cost, simple and convenient. It is valuable for the development of test standards for endoscope OCT systems.     

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.     

Phase unwrapping for Doppler spectral domain optical coherence tomography flow measurement

Doppler optical coherence tomography (OCT) offers additional flow velocity information, which extends the application of OCT. Phase wrapping is the inherent problem that limits measureable range of Doppler OCT. We propose a phase unwrapping method which is suitable for correcting phase in Doppler OCT images. Points (pixels) in flow region are divided into groups according to the radial distance. Points in the same group are supposed to have close velocity. Phase unwrapping algorithm begins at the boundary layer group and is performed sequentially toward the center. Using the proposed criterion, points in a group are separated into two categories, signal points and noise points. Wrapping rounds are determined for signal points phase unwrapping. Mean value of the corrected signal points replaces the noise points for noise reduction. The method is validated with capillary tube flow phantom and in vivo blood flow.     

Retinal cross-section motion correction in three-dimensional retinal optical coherence tomography

Motion correction is an important issue in ophthalmic optical coherence tomography (OCT), and can improve the ability of data sets to reflect the physiological structures of tissues and make visualization and subsequent analysis easier. In this study, we present a novel method to correct the cross-sectional motion artifacts in retinal OCT volumes. Motion along the x-direction (fast-scan direction) is corrected through the normalized cross-correlation algorithm, while axial motion compensation is performed using the polynomial fitting method on the inner segment/outer segment (IS/OS) layer segmented by the shortest path faster algorithm (SPFA). The results of volunteers with central serous chorioretinopathy demonstrate that the proposed method effectively corrects motion artifacts in OCT volumes and may have potential application value in the evaluation of ophthalmic diseases such as diabetic retinopathy, glaucoma and age-related macular degeneration.     

Contrast‐enhanced optical coherence tomography for melanoma detection: An in vitro study

Optical coherence tomography (OCT), with a high‐spatial resolution (<10 microns), intermediate penetration depth (~1.5 mm) and volumetric imaging capability is a great candidate to be used as a diagnostic‐assistant modality in dermatology. At this time, the accuracy of OCT for melanoma detection is lower than anticipated. In this letter, we studied for the first time, the use of a novel contrast agent consist of ultra‐small nanoparticles conjugated to a melanoma biomarker to improve the accuracy of OCT for differentiation of melanoma cells from nonmelanoma cells, in vitro. We call this approach SMall nanoparticle Aggregation‐enhanced Radiomics of Tumor (SMART)‐OCT imaging. This initial proof of concept study is the first step toward the broad utilization of this method for high accuracy all types of tumor detection applications.     

N2NSR-OCT: Simultaneous denoising and super-resolution in optical coherence tomography images using semisupervised deep learning

Optical coherence tomography (OCT) imaging shows a significant potential in clinical routines due to its noninvasive property. However, the quality of OCT images is generally limited by inherent speckle noise of OCT imaging and low sampling rate. To obtain high signal-to-noise ratio (SNR) and high-resolution (HR) OCT images within a short scanning time, we presented a learning-based method to recover high-quality OCT images from noisy and low-resolution OCT images. We proposed a semisupervised learning approach named N2NSR-OCT, to generate denoised and super-resolved OCT images simultaneously using up- and down-sampling networks (U-Net (Semi) and DBPN (Semi)). Additionally, two different super-resolution and denoising models with different upscale factors (2× and 4× ) were trained to recover the high-quality OCT image of the corresponding down-sampling rates. The new semisupervised learning approach is able to achieve results comparable with those of supervised learning using up- and down-sampling networks, and can produce better performance than other related state-of-the-art methods in the aspects of maintaining subtle fine retinal structures.     

早期胚胎全场OCT图像的边界去模糊研究

全场光学相干层析成像技术(全场OCT)是研究早期胚胎形态发育的最理想成像设备,然而所采集图像难免受噪声干扰.这些噪声可模糊早期胚胎内不同组织结构的边界,从而给基于图像边界的结构划分带来干扰.为解决这一问题,本文运用中值滤波、维纳滤波、各向异性扩散算法处理全场OCT获得的早期胚胎图像,并运用信噪比、均方误差、峰值信噪比和边缘保留等指标评价图像处理效果.结果表明:经各向异性扩散算法处理的早期胚胎图像,可完整地保留原始图像信息,且边界最清晰,视觉效果最好.     

Diagnosing colorectal abnormalities using scattering coefficient maps acquired from optical coherence tomography

Optical coherence tomography (OCT) has shown potential in differentiating normal colonic mucosa from neoplasia. In this study of 33 fresh human colon specimens, we report the first use of texture features and computer vision-based imaging features acquired from en face scattering coefficient maps to characterize colorectal tissue. En face scattering coefficient maps were generated automatically using a new fast integral imaging algorithm. From these maps, a gray-level cooccurrence matrix algorithm was used to extract texture features, and a scale-invariant feature transform algorithm was used to derive novel computer vision-based features. In total, 25 features were obtained, and the importance of each feature in diagnosis was evaluated using a random forest model. Two classifiers were assessed on two different classification tasks. A support vector machine model was found to be optimal for distinguishing normal from abnormal tissue, with 94.7% sensitivity and 94.0% specificity, while a random forest model performed optimally in further differentiating abnormal tissues (i.e., cancerous tissue and adenomatous polyp) with 86.9% sensitivity and 85.0% specificity. These results demonstrated the potential of using OCT to aid the diagnosis of human colorectal disease.     

Optical coherence tomography-based non-invasive evaluation of premalignant lesions in SKH-1 mice

Non-invasively diagnosis of actinic keratoses (AK) is important for preventing cutaneous squamous cell carcinoma (cSCC). Optical coherence tomography (OCT) can be used to detect the cross-sectional skin micromorphology with sufficient resolution and imaging depth. It has the capability to reveal the changes in skin microstructure during the development of AK. Therefore, OCT can serve as a tool for diagnosing AK. This study explores the feasibility of OCT in evaluating the structural changes in mouse skin at the different stages following exposure to ultraviolet radiation. The performance of OCT is compared with histology, the gold standard in this context. The imaging results demonstrate that a wave-shaped irregular dermo-epidermal junction (DEJ), as well as the continuous thickening of the epidermis, are useful diagnostic parameters for diagnosing AK. Histological examinations confirm these observations. These findings emphasize the need for effective skin protection or medical treatment once changes in the DEJ and epidermis are detected. OCT shows strong potential for non-invasive evaluation of such changes and AK development, and can be used for the prevention of cSCC without the necessity of taking biopsies.     

Gingivitis resolution followed by optical coherence tomography and fluorescence imaging: A case study

Gingivitis is highly prevalent in adults, and if left untreated, can progress to periodontitis. In this article, we present an interesting case study where the resolution of gingivitis was followed over a period of 10 days using optical coherence tomography (OCT) and light-induced autofluorescence (LIAF). We demonstrate that OCT and its functional angiography can distinctively capture the changes during the resolution of gingivitis; while LIAF can detect red-fluorescent signals associated with mature plaque present at the inflamed site. The acute inflammatory region showed evidence of angiogenesis based on the quantification of vessel density and number; while no angiogenesis was detected within the less inflamed region. Gingival thickness showed a reduction of 140 ± 26 μm on average, measured between the peak gingivitis event and the period wherein the inflammation was resolved. Vessels in the angiogenesis site was found to reduce exponentially. The mildly inflamed site showed a decreasing trend in the vessel size, which however was within the error of the measurement.     

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.     

Determination and correction of aberrations in full field optical coherence tomography using phase gradient autofocus by maximizing the likelihood function

A method for numerical estimation and correction of aberrations of the eye in fundus imaging with optical coherence tomography (OCT) is presented. Aberrations are determined statistically by using the estimate based on likelihood function maximization. The method can be considered as an extension of the phase gradient autofocusing algorithm in synthetic aperture radar imaging to 2D optical aberration correction. The efficacy of the proposed method has been demonstrated in OCT fundus imaging with 6λ aberrations. After correction, single photoreceptors were resolved. It is also shown that wave front distortions with high spatial frequencies can be determined and corrected.     

Optical coherence hyperspectral microscopy with a single supercontinuum light source

In the paper, we have developed an optical coherence hyperspectral microscopy with a single supercontinuum light source. The microscopy consists of optical coherence tomography (OCT) and hyperspectral imaging (HSI), which can visualize the structural and functional characteristics of biological tissues. The 500 to 700 nm band is selected for HSI and OCT imaging, where HSI enables imaging of oxygen saturation and hemoglobin (Hb) content, while OCT acquires structural characteristics to assess the morphology of biological tissues. The system performance of the optical coherence hyperspectral microscopy is verified by normal mice ears, and the practical applications of the microscopy is further performed in 4T1 and inflammation Balb/c mice ears in vivo. The experimental results demonstrate that the microscopy has potential to provide complementary information for clinical applications.     

Comparative study of deep neural networks with unsupervised Noise2Noise strategy for noise reduction of optical coherence tomography images

As a powerful diagnostic tool, optical coherence tomography (OCT) has been widely used in various clinical setting. However, OCT images are susceptible to inherent speckle noise that may contaminate subtle structure information, due to low-coherence interferometric imaging procedure. Many supervised learning-based models have achieved impressive performance in reducing speckle noise of OCT images trained with a large number of noisy-clean paired OCT images, which are not commonly feasible in clinical practice. In this article, we conducted a comparative study to investigate the denoising performance of OCT images over different deep neural networks through an unsupervised Noise2Noise (N2N) strategy, which only trained with noisy OCT samples. Four representative network architectures including U-shaped model, multi-information stream model, straight-information stream model and GAN-based model were investigated on an OCT image dataset acquired from healthy human eyes. The results demonstrated all four unsupervised N2N models offered denoised OCT images with a performance comparable with that of supervised learning models, illustrating the effectiveness of unsupervised N2N models in denoising OCT images. Furthermore, U-shaped models and GAN-based models using UNet network as generator are two preferred and suitable architectures for reducing speckle noise of OCT images and preserving fine structure information of retinal layers under unsupervised N2N circumstances.     

Optimized skin optical clearing for optical coherence tomography monitoring of encapsulated drug delivery through the hair follicles

Hair follicles (HF) represent a drug delivery reservoir for improved treatment of skin disorders. Although various particulate systems play an important role in HF‐targeting, their optical monitoring in skin is challenging due to strong light scattering. Optical clearing is an effective approach allowing the increasing of particle detection depth in skin. The enhancement of optical probing depth (OPD) and optical detection depth (ODD) of particle localization using optical coherence tomography (OCT) was evaluated under application of various optical clearing agents (OCAs) together with skin permeability enhancers ex vivo in rats. Efficient OPD increasing was demonstrated for all investigated OCAs. However, skin dehydration under action of hyperosmotic agents led to the worsening of OCT‐contrast in dermis decreasing the ODD. Lipophilic agents provided optical clearing of epidermis without its dehydration. The highest ODD was obtained at application of a PEG‐400/oleic acid mixture. This OCA was tested in vivo showing beneficial ODD and OPD enhancement.     

Cross‐scanning optical coherence tomography angiography for eye motion correction

We propose a cross‐scanning optical coherence tomography (CS‐OCT) system to correct eye motion artifacts in OCT angiography images. This system employs a dual‐illumination configuration with two orthogonally polarized beams, each of which simultaneously perform raster scanning in perpendicular direction with each other over the same area. In the reference arm, a polarization delay unit is used to acquire the two orthogonally polarized interferograms with a single photo detector by introducing different optical delay lines. The two cross‐scanned volume data are affected by the same eye motion but in two orthogonal directions. We developed a motion correction algorithm, which removes artifacts in the slow axis of each angiogram using the other and merges them through a nonrigid registration algorithm. In this manner, we obtained a motion‐corrected angiogram within a single volume scanning time without additional eye‐tracking devices.     

Noninvasive detection of nanoscale structural changes in cornea associated with cross‐linking treatment

Corneal cross‐linking (CXL) using ultraviolet‐A (UVA) irradiation with a riboflavin photosensitizer has grown from an interesting concept to a practical clinical treatment for corneal ectatic diseases globally, such as keratoconus. To characterize the corneal structural changes, existing methods such as X‐ray microscopy, transmission electron microscopy, histology and optical coherence tomography (OCT) have been used. However, these methods have various drawbacks such as invasive detection, the impossibility for in vivo measurement, or limited resolution and sensitivity to structural alterations. Here, we report the application of oversampling nanosensitive OCT for probing the corneal structural alterations. The results indicate that the spatial period increases slightly after 30 minutes riboflavin instillation but decreases significantly after 30 minutes UVA irradiation following the Dresden protocol. The proposed noninvasive method can be implemented using existing OCT systems, without any additional components, for detecting nanoscale changes with the potential to assist diagnostic assessment during CXL treatment, and possibly to be a real‐time monitoring tool in clinics.     

A novel automatic 3D stitching algorithm for optical coherence tomography angiography and its application in dermatology

Optical coherence tomography (OCT) and OCT angiography (OCTA) techniques offer numerous advantages in clinical skin applications but the field of view (FOV) of current commercial systems are relatively limited to cover the entire skin lesion. The typical method to expand the FOV is to apply wide field objective lens. However, lateral resolution is often sacrificed when scanning with these lenses. To overcome this drawback, we developed an automated 3D stitching method for creating high-resolution skin structure and vascular volumes with large field of view, which was realized by montaging multiple adjacent OCT and OCTA volumes. The proposed stitching method is demonstrated by montaging 3 × 3 OCT and OCTA volumes (nine OCT/OCTA volumes as one data set with each volume covers 2.5 cm × 2.5 cm area) of healthy thin and thick skin from six volunteers. The proposed stitching protocol achieves high flexibility and repeatable for all the participants. Moreover, according to evaluation of structural similarity index and feature similarity index, our proposed stitched result has a superior similarity to single scanning protocol in large-scaled. We had also verified its improved performance through assessing metrics of vessel contrast-noise-ratio (CNR) from 2.07 ± 0.44 (single large-scaled scanning protocol) to 3.05 ± 0.51 (proposed 3 × 3 sub-volume stitching method).