A number of hardware-based and software-based strategies have been suggested to eliminate motion artifacts for improvement of 3D-optical coherence tomography (OCT) image quality. However, the hardware-based strategies have to employ additional hardware to record motion compensation information. Many software-based strategies have to need additional scanning for motion correction at the expense of longer acquisition time. To address this issue, we propose a motion artifacts correction and motion estimation method for OCT volumetric imaging of anterior segment, without requirements of additional hardware and redundant scanning. The motion correction effect with subpixel accuracy for in vivo 3D-OCT has been demonstrated in experiments. Moreover, the physiological information of imaging object, including respiratory curve and respiratory rate, has been experimentally extracted using the proposed method. The proposed method offers a powerful tool for scientific research and clinical diagnosis in ophthalmology and may be further extended for other biomedical volumetric imaging applications.

Screening for colorectal cancer (CRC) with colonoscopy has improved patient outcomes; however, it remains the third leading cause of cancer-related mortality, novel strategies to improve screening are needed. Here, we propose an optical biopsy technique based on spectroscopic optical coherence tomography (OCT). Depth resolved OCT images are analyzed as a function of wavelength to measure optical tissue properties and used as input to machine learning algorithms. Previously, we used this approach to analyze mouse colon polyps. Here, we extend the approach to examine human biopsied colonic epithelial tissue samples ex vivo. Optical properties are used as input to a novel deep learning architecture, producing accuracy of up to 97.9% in discriminating tissue type. SOCT parameters are used to create false colored en face OCT images and deep learning classifications are used to enable visual classification by tissue type. This study advances SOCT toward clinical utility for analysis of colonic epithelium.

OBJECTIVE: To observe the morphological characteristics of posterior scleral staphyloma (PSS) with or without macular retinoschisis (MRS) using optical coherence tomography (OCT). Additionally, the incidence and severity of other pathologic myopic maculopathy associated with posterior scleral staphyloma was also evaluated.
METHODS: General information and OCT imaging data from 440 patients with posterior scleral staphyloma (PSS) and the PSS curvature > 20×10-3 μm-1 were collected. These patients visited the Department of Ophthalmology at the First Affiliated Hospital of Harbin Medical University from January 2013 to June 2021. The obtained OCT images of PSS were analyzed using the Image J software to measure the curvature along the Bruch\'s membrane. The measured curvature was divided into four levels using the quartile method. The classification of macular retinoschisis (MRS) was based on the anatomical structure of the retina and the location of macular retinoschisis. Patients with PSS accompanied by MRS were assigned to the MRS group, while PSS patients without MRS were assigned to the non-MRS group. Additionally, typical OCT changes in other pathologic myopic maculopathy diseases, such as myopic choroidal neovascularization (mCNV), myopic traction maculopathy (MTM), and myopic foveoschisis (MF), were recorded and evaluated.
RESULTS: A total of 615 eyes (328 right eyes, 287 left eyes) from 440 patients (80 males and 360 females) were recruited in this study. The MRS group consisted of 159 patients (36.1%) with 190 eyes (30.9%), while the non-MRS group consisted of 281 patients (63.9%) with 425 eyes (69.1%). Both groups had a significantly higher proportion of female patients compared to male patients, and the right eye was more commonly affected than the left eye. In the MRS group, the prevalence of MRS increased progressively with the severity of PSS. Among the common posterior pole diseases, epiretinal membrane had the highest prevalence (33.2%), while lamellar macular hole had the lowest prevalence (5.3%). In the non-MRS group, the proportion of PSS in each group decreased progressively (except for an equal prevalence in the third and fourth levels) with increasing severity of PSS. Among the common posterior pole diseases, choroidal neovascularization had the highest prevalence (41.4%), while lamellar macular hole had the lowest prevalence (6.5%). When comparing the two groups, there were no significant differences in age, gender, and eye distribution. The MRS group had a higher prevalence of macular schisis, retinal detachment, and dome-shaped macula (17.9%, 14.2%, 14.8%) compared to the non-MRS group (11.3%, 9.2%, 9.6%). The non-MRS group had a significantly higher prevalence of choroidal neovascularization (41.4%) compared to the MRS group (12.6%), while there were no significant differences in the prevalence of epiretinal membrane and lamellar macular hole between the two groups.
CONCLUSIONS: The prevalence of MRS increased progressively with the severity of PSS, and the MRS occurrence was positively correlated with PSS, which indicated that PSS may lead to MRS, while the proportion of PSS in each group decreases gradually with the severity of PSS in the non-MRS group decreased progressively (except for an equal prevalence in the third and fourth levels). In the MRS group, outer macular retinoschisiss were most relevant to posterior scleral staphyloma, and the prevalence of macular holes and retinal detachments was higher in the MRS group compared to the non-MRS group, indicating that MRS may further turn into complications such as macular holes and retinal detachments, which can significantly affect vision or lead to blindness. The prevalence of choroidal neovascularization (CNV) was significantly higher in the non-MRS group compared to the MRS group, suggesting that PSS with lower severity is more prone to develop into CNV. Dome-shaped macula (DSM) seems to play a protective role in the development of pathologic myopia, and abnormal changes in posterior scleral staphyloma curvature may be an important factor affecting the development and shape of DSM.

The prevalence of vision impairment is increasing at an alarming rate. The goal of the study was to create an automated method that uses optical coherence tomography (OCT) to classify retinal disorders into four categories: choroidal neovascularization, diabetic macular edema, drusen, and normal cases. This study proposed a new framework that combines machine learning and deep learning-based techniques. The utilized classifiers were support vector machine (SVM), K-nearest neighbor (K-NN), decision tree (DT), and ensemble model (EM). A feature extractor, the InceptionV3 convolutional neural network, was also employed. The performance of the models was evaluated against nine criteria using a dataset of 18000 OCT images. For the SVM, K-NN, DT, and EM classifiers, the analysis exhibited state-of-the-art performance, with classification accuracies of 99.43%, 99.54%, 97.98%, and 99.31%, respectively. A promising methodology has been introduced for the automatic identification and classification of retinal disorders, leading to reduced human error and saved time. .

Radiographic examination has been an essential part of the diagnostic workflow in periodontology and implant dentistry. However, radiographic examination unavoidably involves ionizing radiation and its associated risks. Clinicians and researchers have invested considerable efforts in assessing the feasibility and capability of utilizing nonionizing imaging modalities to replace traditional radiographic imaging. Two such modalities have been extensively evaluated in clinical settings, namely, ultrasonography (USG) and magnetic resonance imaging (MRI). Another modality, optical coherence tomography (OCT), has been under investigation more recently. This review aims to provide an overview of the literature and summarize the usage of USG, MRI, and OCT in evaluating health and pathology of periodontal and peri-implant tissues. Clinical studies have shown that USG could accurately measure gingival height and crestal bone level, and classify furcation involvement. Due to physical constraints, USG may be more applicable to the buccal surfaces of the dentition even with an intra-oral probe. Clinical studies have also shown that MRI could visualize the degree of soft-tissue inflammation and osseous edema, the extent of bone loss at furcation involvement sites, and periodontal bone level. However, there was a lack of clinical studies on the evaluation of peri-implant tissues by MRI. Moreover, an MRI machine is very expensive, occupies much space, and requires more time than cone-beam computed tomography (CBCT) or intraoral radiographs to complete a scan. The feasibility of OCT to evaluate periodontal and peri-implant tissues remains to be elucidated, as there are only preclinical studies at the moment. A major shortcoming of OCT is that it may not reach the bottom of the periodontal pocket, particularly for inflammatory conditions, due to the absorption of near-infrared light by hemoglobin. Until future technological breakthroughs finally overcome the limitations of USG, MRI and OCT, the practical imaging modalities for routine diagnostics of periodontal and peri-implant tissues remain to be plain radiographs and CBCTs.

BACKGROUND: Consumer products such as electrical shavers exert a combination of dynamic loading in the form of pressure and shear on the skin. This mechanical stimulus can lead to discomfort and skin tissue responses characterised as \"Skin Sensitivity\". To minimise discomfort following shaving, there is a need to establish specific stimulus-response relationships using advanced tools such as optical coherence tomography (OCT).
OBJECTIVE: To explore the spatial and temporal changes in skin morphology and microvascular function following an electrical shaving stimulus.
METHODS: Ten healthy male volunteers were recruited. The study included a 60-s electrical shaving stimulus on the forearm, cheek and neck. Skin parameters were recorded at baseline, 20 min post stimulus and 24 h post stimulus. Structural and dynamic skin parameters were estimated using OCT, while transepidermal water loss (TEWL) was recorded to provide reference values for skin barrier function.
RESULTS: At baseline, six of the eight parameters revealed statistically significant differences between the forearm and the facial sites, while only surface roughness (Rq) and reflectivity were statistically different (p < 0.05) between the cheek and neck. At 20 min post shaving, there was a significant increase in the TEWL values accompanied by increased blood perfusion, with varying magnitude of change dependent on the anatomical site. Recovery characteristics were observed 24 h post stimulus with most parameters returning to basal values, highlighting the transient influence of the stimulus.
CONCLUSIONS: OCT parameters revealed spatial and temporal differences in the skin tissue response to electrical shaving. This approach could inform shaver design and prevent skin sensitivity.

BACKGROUND: Retinal nerve fiber layer (RNFL) thickness is a promising biomarker of axonal loss and a potential outcome predictor in Multiple Sclerosis (MS). Cognitive impairment (CoI) exhibits a high prevalence in patients with MS (pwMS), even in the early phases of the disease. Our aim was to explore the role of RNFL thickness as a predictor of physical and cognitive disability in pwMS.
METHODS: All newly diagnosed pwMS referred to the MS centre of the University-Hospital \"Policlinico-San Marco\" between 2015-2019 were evaluated at baseline and at 3 years. RNFL and ganglion cell layer (GCL) thickness for right (r.e.) and left eyes (l.e.) were measured with Optical Coherence Tomography (OCT). Disability level and cognitive profile were assessed, using the Expanded Disability Status Scale (EDSS) and the Brief International Cognitive Assessment for Multiple Sclerosis (BICAMS) battery, respectively.
RESULTS: We consecutively enrolled 487 pwMS, including 68 (14.0%) with primary progressive MS (PPMS). At baseline, RNFL and GCL were bilaterally thinner in PPMS (r.e. 90.4 ± 12.7; l.e. 90.2 ± 13.5, and r.e. 80.1 ± 11.2; l.e. 80.3 ± 12.6, respectively) compared to relapsing-remitting MS (RRMS) (r.e. 94.6 ± 13.1; l.e. 94.3 ± 14.8, and r.e. 85.1 ± 9.5; l.e. 84.9 ± 9.3, respectively) (p < 0.01). Both groups exhibited reduced RNFL and GCL thickness, worse cognitive performance and higher EDSS scores at 3-years follow-up compared with baseline. RNFL thickness ≤ 88.0 μm was an independent predictor of CoI (OR = 5.32; 95% CI = 1.84-9.12; p = 0.02) and disability worsening (OR = 3.18; 95% CI = 1.21-10.33; p = 0.05).
CONCLUSIONS: RNFL thickness, as a biomarker of neurodegeneration, could be considered a predictive biomarker of cognitive degeneration and physical disability in MS.

BACKGROUND: Identifying and understanding the microstructural changes within the wall of the pulmonary artery (PA) is crucial for elucidating disease mechanisms and guiding treatment strategies. We assessed the utility of optical coherence tomography (OCT) in identifying such changes within segmental/subsegmental PAs and compared the morphological variations in WHO group 4 pulmonary hypertension associated with Behcet Disease (BD), Takayasu arteritis (TA) and chronic thromboembolic pulmonary hypertension (CTEPH). Idiopathic pulmonary arterial hypertension (IPAH) patients served as controls.Methods and Results: A total of 197 cross-sectional images were analyzed from 20 consecutive patients. BD patients exhibited lower %wall area and mean wall thickness (MWT) compared with CTEPH, TA and, IPAH patients. TA patients showed a notably higher %wall area, which was significant in IPAH and BD patients. Variations in %wall area measurements were observed across distinct cross-sectional segments of the PA within individual patients (22% in CTEPH, 19% in BD, 16% in TA, 23% in IPAH patients). Intravascular webs, bands, and thrombi were observed in BD and CTEPH patients. OCT provided clear delineation of vascular wall calcifications and adventitial vasa vasorum. No procedure-related complications were observed.
CONCLUSIONS: PA involvement differs among the various etiologies of PH, with the PA being heterogeneously affected. OCT offers promise in elucidating microstructural vascular wall changes and providing insights into disease mechanisms and treatment effects.

OBJECTIVE: Optical coherence tomography (OCT) investigations have revealed that the thickness of inner retinal layers becomes decreased in multiple sclerosis (MS) patients, compared to healthy control (HC) individuals. To date, a number of studies have applied machine learning to OCT thickness measurements, aiming to enable accurate and automated diagnosis of the disease. However, there have much less emphasis on other less common retinal imaging modalities, like infrared scanning laser ophthalmoscopy (IR-SLO), for classifying MS. IR-SLO uses laser light to capture high-resolution fundus images, often performed in conjunction with OCT to lock B-scans at a fixed position.
METHODS: We incorporated two independent datasets of IR-SLO images from the Isfahan and Johns Hopkins centers, consisting of 164 MS and 150 HC images. A subject-wise data splitting approach was employed to ensure that there was no leakage between training and test datasets. Several state-of-the-art convolutional neural networks (CNNs), including VGG-16, VGG-19, ResNet-50, and InceptionV3, and a CNN with a custom architecture were employed. In the next step, we designed a convolutional autoencoder (CAE) to extract semantic features subsequently given as inputs to four conventional ML classifiers, including support vector machine (SVM), k-nearest neighbor (K-NN), random forest (RF), and multi-layer perceptron (MLP).
RESULTS: The custom CNN (85 % accuracy, 85 % sensitivity, 87 % specificity, 93 % area under the receiver operating characteristics [AUROC], and 94 % area under the precision-recall curve [AUPRC]) outperformed state-of-the-art models (84 % accuracy, 83 % sensitivity, 87 % specificity, 92 % AUROC, and 94 % AUPRC); however, utilizing a combination of the CAE and MLP yields even superior results (88 % accuracy, 86 % sensitivity, 91 % specificity, 94 % AUROC, and 95 % AUPRC).
CONCLUSIONS: We utilized IR-SLO images to differentiate between MS and HC eyes, with promising results achieved using a combination of CAE and MLP. Future multi-center studies involving more heterogenous data are necessary to assess the feasibility of integrating IR-SLO images into routine clinical practice.

Optic neuritis is a common feature in multiple sclerosis and in 2 other autoimmune demyelinating disorders such as aquaporin-4 IgG antibody-associated neuromyelitis optica spectrum disorder and myelin oligodendrocyte glycoprotein antibody-associated disease. Although serologic testing is critical for differentiating these different autoimmune-mediated disorders, MR imaging, which is the preferred imaging modality for assessing the optic nerve, can provide valuable information, suggesting a specific diagnosis and guiding the appropriate serologic testing.