Quantifying dental biofilm growth using cross-polarization optical coherence tomography

Aims: Quantifying the ex vivo growth of complex multispecies dental biofilms using cross‐polarization 1310‐nm optical coherence tomography (CP‐OCT) system was investigated. Methods and Results: Bacterial microcosms, which were derived from plaque samples of paediatric subjects, were incubated in a biofilm reactor system containing discs of different dental materials for 72 h with daily sucrose pulsing (5×). CP‐OCT analysis of biofilm mass was validated with crystal violet (CV) assays at various growth stages of these complex biofilms. CP‐OCT was able to filter out the back‐reflected signals of water layers in the hydrated biofilm and allowed for direct biofilm quantification. The overall depth‐resolved scattering intensity of the biofilm showed very strong positive correlation with CV assay quantification (Spearman’s ρ = 0·92) during the growth phase of the biofilm. Conclusion: CP‐OCT was able to quantify the mass of the biofilm by measuring the overall depth‐resolved scattering of the biofilm. Significance and Impact of the Study: CP‐OCT has the ability to nondestructively monitor biofilm growth and elucidate the growth characteristics of these microcosms on different dental material compositions.     

Imaging depth extension of optical coherence tomography in rabbit eyes using optical clearing agents

Optical coherence tomography has become an indispensable diagnostic tool in ophthalmology for imaging the retina and the anterior segment of the eye. However, the imaging depth of optical coherence tomography is limited by light attenuation in tissues due to optical scattering and absorption. In this study of rabbit eye both ex vivo and in vivo, optical coherence tomography imaging depth of the anterior and posterior segments of the eye was extended by using optical clearing agents to reduce multiple scattering. The sclera, the iris, and the ciliary body were clearly visualized by direct application of glycerol at an incision on the conjunctiva, and the posterior boundary of sclera and even the deeper tissues were detected by submerging the posterior segment of eye in glycerol solution ex vivo or by retro-bulbar injection of glycerol in vivo. The ex vivo rabbit eyes recovered to their original state in 60 s after saline-wash treatment, and normal optical coherence tomography images of the posterior segment of the sample eyes proved the self-recovery of in vivo performance. Signal intensities of optical coherence tomography images obtained before and after glycerol treatment were compared to analysis of the effect of optical clearing. To the best of our knowledge, this is the first study for imaging depth extension of optical coherence tomography in both the anterior and posterior segments of eye by using optical clearing agents.     

Real‐time in vivo imaging of adult Zebrafish brain using optical coherence tomography

We report noninvasive imaging of the brain of adult Zebrafish (Danio rerio) using real time optical coherence tomography (OCT) capable of acquiring cross sectional 2D OCT images @ 8 frames/sec. Anatomic features such as telencephalon, tectum opticum, eminentia Granularis and cerebellum were clearly resolved in the OCT images. A 3D model of Zebrafish brain was reconstructed, for the first time to our knowledge, using these 2D OCT images. (© 2009 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)     

Neoatherosclerosis causing edge in-stent restenosis: optical coherence tomography findings

A patient presenting with ‘edge’ in-stent restenosis 12 years after the implantation of a bare-metal stent in the mid-left anterior descending coronary artery is described. Optical coherence tomography disclosed the presence of ruptured neoatherosclerosis at the stent edge. The value of this imaging technique to unravel this unique underlying anatomic substrate is discussed. The therapy of choice for patients presenting with edge in-stent restenosis (ISR) is reviewed.     

Opto-mechanical characterization of sclera by polarization sensitive optical coherence tomography

Polarization sensitive optical coherence tomography (PSOCT) is an interferometric technique sensitive to birefringence. Since mechanical loading alters the orientation of birefringent collagen fibrils, we asked if PSOCT can be used to measure local mechanical properties of sclera.Infrared (1300 nm) PSOCT was performed during uniaxial tensile loading of fresh scleral specimens of rabbits, cows, and humans from limbal, equatorial, and peripapillary regions. Specimens from 8 human eyes were obtained. Specimens were stretched to failure at 0.01 mm/s constant rate under physiological conditions of temperature and humidity while birefringence was computed every 117 ms from cross-sectional PSOCT. Birefringence modulus (BM) was defined as the rate of birefringence change with strain, and tensile modulus (TM) as the rate of stress change between 0 and 9% strain.In cow and rabbit, BM and TM were positively correlated with slopes of 0.17 and 0.10 GPa, and with correlation coefficients 0.63 and 0.64 (P < 0.05), respectively, following stress-optic coefficients 4.69, and 4.20 GPa⁻¹. In human sclera, BM and TM were also positively correlated with slopes of 0.24 GPa for the limbal, 0.26 GPa for the equatorial, and 0.31 GPa for the peripapillary regions. Pearson correlation coefficients were significant at 0.51, 0.58, and 0.69 for each region, respectively (<0.001). Mean BM decreased proportionately to TM from the limbal to equatorial to peripapillary regions, as stress-optic coefficients were estimated as 2.19, 2.42, and 4.59 GPa⁻¹, respectively.Since birefringence and tensile elastic moduli correlate differently in cow, rabbit, and various regions of human sclera, it might be possible to mechanically characterize the sclera in vivo using PSOCT.     

Imaging atherosclerotic plaque composition with intracoronary optical coherence tomography

Optical coherence tomography (OCT) allows highly accurate diagnosis of atherosclerotic plaques, including measurement of the thickness of fibrous caps, permitting an assessment of the risk of rupture. While the OCT image presents morphological information in highly resolved detail, it relies on interpretation by trained readers for the identification of tissue type. We developed a method for quantitative classification of atherosclerotic plaque constituents. The optical attenuation coefficient μ_t distinguishes different tissue types: necrotic core and macrophage infiltration exhibit strong attenuation, μ_t≥10 mm⁻¹, while calcific and fibrous tissue have a lower μ_t≈2–5 mm⁻¹. (Neth Heart J 2009;17:448-50.)     

Imaging sebaceous gland using optical coherence tomography with deep learning assisted automatic identification

Imaging sebaceous glands and evaluating morphometric parameters are important for diagnosis and treatment of serum problems. In this article, we investigate the feasibility of high-resolution optical coherence tomography (OCT) in combination with deep learning assisted automatic identification for these purposes. Specifically, with a spatial resolution of 2.3 μm × 6.2 μm (axial × lateral, in air), OCT is capable of clearly differentiating sebaceous gland from other skin structures and resolving the sebocyte layer. In order to achieve efficient and timely imaging analysis, a deep learning approach built upon ResNet18 is developed to automatically classify OCT images (with/without sebaceous gland), with a classification accuracy of 97.9%. Based on the result of automatic identification, we further demonstrate the possibility to measure gland size, sebocyte layer thickness and gland density.     

Comparative study of optical coherence tomography angiography algorithms for rodent retinal imaging

Optical coherence tomography angiography (OCTA) is a functional extension of optical coherence tomography for non-invasive in vivo three-dimensional imaging of the microvasculature of biological tissues. Several algorithms have been developed to construct OCTA images from the measured optical coherence tomography signals. In this study, we compared the performance of three OCTA algorithms that are based on the variance of phase, amplitude, and the complex representations of the optical coherence tomography signals for rodent retinal imaging, namely the phase variance, improved speckle contrast, and optical microangiography. The performance of the different algorithms was evaluated by comparing the quality of the OCTA images regarding how well the vasculature network can be resolved. Quantities that are widely used in ophthalmic studies including blood vessel density, vessel diameter index, vessel perimeter index, vessel complexity index were also compared. Results showed that both the improved speckle contrast and optical microangiography algorithms are more robust than phase variance, and they can reveal similar vasculature features while there are statistical differences in the calculated quantities.     

Assessment of simulated osteoporosis in alveolar bone using optical coherence tomography

Steoporosis is a skeletal disorder that compromises bone resistance and its diagnosis is usually performed using dual energy X‐ray absorptiometry. Thus, the search for efficient diagnostic methods that do not involve the emission of ionizing radiation is necessary. This study proposed to use the Optical Coherence Tomography (OCT) to evaluate osteoporosis in alveolar bone. Osteoporosis lesions is simulated in vitro in porcine bones, and imaging is performed by OCT and micro‐computed tomography (micro‐CT). A developed algorithm is proposed to calculate the optical attenuation coefficient ( μ _t), mean optical attenuation coefficient (), integrated reflectivity (ΔR) and bone density ( BD). The , ΔR and BD parameters shows a good correlation to micro‐CT parameters (bone volume/tissue volume and total porosity). The μ _t and methods are negatively impacted by non‐uniform intensities distribution in osteoporosis images. In conclusion, BD and ΔR analysis demonstrates to be potential techniques for diagnosis and monitoring of osteoporosis using OCT.      

Noninvasive cross-sectional observation of three-dimensional cell sheet-tissue-fabrication by optical coherence tomography

Cell sheet engineering allows investigators/clinicians to prepare cell-dense three-dimensional (3-D) tissues, and various clinical trials with these fabricated tissues have already been performed for regenerating damaged tissues. Cell sheets are easily manipulated and 3-D tissues can be rapidly fabricated by layering the cell sheets. This study used optical coherence tomography (OCT) to noninvasively analyze the following processes: (1) adhesions between layered cell sheets, and (2) the beating and functional interaction of cardiac cell sheet-tissues for fabricating functional thicker 3-D tissues. The tight adhesions and functional couplings between layered cell sheets could be observed cross-sectionally and in real time. Importantly, the noninvasive and cross-sectional analyses of OCT make possible to fabricate 3-D tissues by confirming the adherence and functional couplings between layered cell sheets. OCT technology would contribute to cell sheet engineering and regenerative medicine.     

Endoscopic optical coherence tomography angiography using a forward imaging piezo scanner probe

A forward imaging endoscope for optical coherence tomography angiography (OCTA) featuring a piezoelectric fiber scanner is presented. Imaging is performed with an optical coherence tomography (OCT) system incorporating an akinetic light source with a center wavelength of 1300 nm, bandwidth of 90 nm and A‐line rate of 173 kHz. The endoscope operates in contact mode to avoid motion artifacts, in particular, beneficial for OCTA measurements, and achieves a transversal resolution of 12 μm in air at a rigid probe size of 4 mm in diameter and 11.3 mm in length. A spiral scan pattern is generated at a scanning frequency of 360 Hz to sample a maximum field of view of 1.3 mm. OCT images of a human finger as well as visualization of microvasculature of the human palm are presented both in two and three dimensions. The combination of morphological tissue contrast with qualitative dynamic blood flow information within this endoscopic imaging approach potentially enables improved early diagnostic capabilities of internal organs for diseases such as bladder cancer.      

通过光学相干断层扫描图像进行自动视网膜分割评估黄斑水肿的投影面积

在本文中,我们提出了一种自动视网膜分割方法,以评估光学相干断层扫描（OCT）图像中黄斑水肿（ME）在视网膜特定层上的投影面积。首先使用基于权重矩阵的优化的最短路径最快算法对十个视网膜层边界进行分割,这有效降低了算法对血管阴影的敏感性。然而,ME的存在将导致水肿区域的分割不准确。因此,我们使用强度阈值方法提取每个OCT图像中的水肿区域,并将该区域中的值设置为零,并确保获得的分割边界可以自动穿过而不是绕过水肿区域。我们使用最小值投影来计算ME在不同层的投影面积。为了测试我们的方法,我们使用了从Topcon的OCT机器收集的数据。在轴向和B扫描方向上测得的黄斑区域分辨率分别为11.7微米和46.8微米。与手动分割相比,视网膜层边界分割的平均绝对误差和标准偏差为4.5±3.2微米。因此,所提出的方法为评估水肿提供了一种自动,无创和定量的工具。     

Fractal-based analysis of optical coherence tomography data to quantify retinal tissue damage

Background

The sensitivity of Optical Coherence Tomography (OCT) images to identify retinal tissue morphology characterized by early neural loss from normal healthy eyes is tested by calculating structural information and fractal dimension. OCT data from 74 healthy eyes and 43 eyes with type 1 diabetes mellitus with mild diabetic retinopathy (MDR) on biomicroscopy was analyzed using a custom-built algorithm (OCTRIMA) to measure locally the intraretinal layer thickness. A power spectrum method was used to calculate the fractal dimension in intraretinal regions of interest identified in the images. ANOVA followed by Newman-Keuls post-hoc analyses were used to test for differences between pathological and normal groups. A modified p value of <0.001 was considered statistically significant. Receiver operating characteristic (ROC) curves were constructed to describe the ability of each parameter to discriminate between eyes of pathological patients and normal healthy eyes.

Results

Fractal dimension was higher for all the layers (except the GCL + IPL and INL) in MDR eyes compared to normal healthy eyes. When comparing MDR with normal healthy eyes, the highest AUROC values estimated for the fractal dimension were observed for GCL + IPL and INL. The maximum discrimination value for fractal dimension of 0.96 (standard error =0.025) for the GCL + IPL complex was obtained at a FD ≤ 1.66 (cut off point, asymptotic 95% Confidence Interval: lower-upper bound = 0.905-1.002). Moreover, the highest AUROC values estimated for the thickness measurements were observed for the OPL, GCL + IPL and OS. Particularly, when comparing MDR eyes with control healthy eyes, we found that the fractal dimension of the GCL + IPL complex was significantly better at diagnosing early DR, compared to the standard thickness measurement.

Conclusions

Our results suggest that the GCL + IPL complex, OPL and OS are more susceptible to initial damage when comparing MDR with control healthy eyes. Fractal analysis provided a better sensitivity, offering a potential diagnostic predictor for detecting early neurodegeneration in the retina.     

Four‐dimensional imaging of murine subpleural alveoli using high‐speed optical coherence tomography

The investigation of lung dynamics on alveolar scale is crucial for the understanding and treatment of lung diseases, such as acute lung injury and ventilator induced lung injury, and to promote the development of protective ventilation strategies. One approach to this is the establishment of numerical simulations of lung tissue mechanics where detailed knowledge about three‐dimensional alveolar structure changes during the ventilation cycle is required. We suggest four‐dimensional optical coherence tomography (OCT) imaging as a promising modality for visualizing the structural dynamics of single alveoli in subpleural lung tissue with high temporal resolution using a mouse model. A high‐speed OCT setup based on Fourier domain mode locked laser technology facilitated the acquisition of alveolar structures without noticeable motion artifacts at a rate of 17 three‐dimensional stacks per ventilation cycle. The four‐dimensional information, acquired in one single ventilation cycle, allowed calculating the volume‐pressure curve and the alveolar compliance for single alveoli. (© 2013 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)     

Quantitative discrimination of NPC cell lines using optical coherence tomography

We tried to explore the intrinsic differences in the optical properties of the four representative NPC cell lines on the models of radiobiology and metastasis by OCT. The scattering coefficients and anisotropies were extracted by fitting the average a‐scan attenuation curves based on the multiple scatter effect. The values of scattering coefficients and anisotropy factors were 5.21 ± 0.11, 5.30 ± 0.09, 5.92 ± 0.21, 6.97 ± 0.22, and 0.892 ± 0.009, 0.886 ± 0.006, 0.884 ± 0.009, 0.86 ± 0.01 for CNE1, CNE2, 5‐8F and 6‐10B pellets (p < 0.05, P = 0.07 for CNE1 and CNE2), respectively. The results showed that the radiobiology and metastasis cell's model could be distinguished obviously; which implied that the corresponding types of NPC tissue might be potentially differentiated by OCT. (© 2012 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)     

Laser thermal therapy monitoring using complex differential variance in optical coherence tomography

Conventional thermal therapy monitoring techniques based on temperature are often invasive, limited by point sampling, and are indirect measures of tissue injury, while techniques such as magnetic resonance and ultrasound thermometry are limited by their spatial resolution.  The visualization of the thermal coagulation zone at high spatial resolution is particularly critical to the precise delivery of thermal energy to epithelial lesions. In this work, an integrated thulium laser thermal therapy monitoring system was developed based on complex differential variance (CDV), which enables the 2D visualization of the dynamics of the thermal coagulation process at high spatial and temporal resolution with an optical frequency domain imaging system. With proper calibration to correct for noise, the CDV‐based technique was shown to accurately delineate the thermal coagulation zone, which is marked by the transition from high CDV upon heating to a significantly reduced CDV once the tissue is coagulated, in 3 different tissue types ex vivo: skin, retina, and esophagus. The ability to delineate thermal lesions in multiple tissue types at high resolution opens up the possibility of performing microscopic image‐guided procedures in a vast array of epithelial applications ranging from dermatology, ophthalmology, to gastroenterology and beyond. 

     

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.     

Characterization of the human myocardium by optical coherence tomography

Imaging of cardiac tissue structure plays a critical role in the treatment and understanding of cardiovascular disease. Optical coherence tomography (OCT) offers the potential to provide valuable, high‐resolution imaging of cardiac tissue. However, there is a lack of comprehensive OCT imaging data of the human heart, which could improve identification of structural substrates underlying cardiac abnormalities. The objective of this study was to provide qualitative and quantitative analysis of OCT image features throughout the human heart. Fifty human hearts were acquired, and tissues from all chambers were imaged with OCT. Histology was obtained to verify tissue composition. Statistical differences between OCT image features corresponding to different tissue types and chambers were estimated using analysis of variance. OCT imaging provided features that were able to distinguish structures such as thickened collagen, as well as adipose tissue and fibrotic myocardium. Statistically significant differences were found between atria and ventricles in attenuation coefficient, and between adipose and all other tissue types. This study provides an overview of OCT image features throughout the human heart, which can be used for guiding future applications such as OCT‐integrated catheter‐based treatments or ex vivo investigation of structural substrates.     

Improving cerebral microvascular image quality of optical coherence tomography angiography with deep learning-based segmentation

Optical coherence tomography angiography (OCTA) can map the microvascular networks of the cerebral cortices with micrometer resolution and millimeter penetration. However, the high scattering of the skull and the strong noise in the deep imaging region will distort the vasculature projections and decrease the OCTA image quality. Here, we proposed a deep learning-based segmentation method based on a U-Net convolutional neural network to extract the cortical region from the OCT image. The vascular networks were then visualized by three OCTA algorithms. The image quality of the vasculature projections was assessed by two metrics, including the peak signal-to-noise ratio (PSNR) and the contrast-to-noise ratio (CNR). The results show the accuracy of the cortical segmentation was 96.07%. The PSNR and CNR values increased significantly in the projections of the selected cortical regions. The OCTA incorporating the deep learning-based cortical segmentation can efficiently improve the image quality and enhance the vasculature clarity.     

Automatic lumen segmentation using uniqueness of vascular connected region for intravascular optical coherence tomography

We present an automatic lumen segmentation method using uniqueness of connected region for intravascular optical coherence tomography (IVOCT), which can effectively remove the effect on lumen segmentation caused by blood artifacts. Utilizing the uniqueness of vascular wall on A-lines, we detect the A-lines shared by multiple connected regions, identify connected regions generated by blood artifacts using traversal comparison of connected regions' location, shared ratio and area ratio and then remove all artifacts. We compare these three methods by 216 challenging images with severe blood artifacts selected from clinical 1076 IVOCT images. The metrics of the proposed method are evaluated including Dice index, Jaccard index and accuracy of 94.57%, 90.12%, 98.02%. Compared with automatic lumen segmentation based on the previous morphological feature method and widely used dynamic programming method, the metrics of the proposed method are significantly enhanced, especially in challenging images with severe blood artifacts.