Inter-Individual Topographic Variation of Choroidal Thickness in Healthy Eyes on Swept-Source Optical Coherence Tomography.

Purpose: To investigate the topographic characters of inter-individual variations of the macular choroidal thickness (CT). Methods: This was a retrospective study. Macular CT data for 900 0.2 × 0.2-mm grids from 410 healthy eyes were collected from swept-source optical coherence tomography. Following the analysis of factors associated with mean CT, the ß-coefficients of the included associated factors in each grid were summarized for choroidal thickness changes analysis. Additionally, the coefficient of variance (CoV), coefficient of determination (CoD), and coefficient of variance unexplained (CoVU) for CT were calculated in each individual grid to investigate the inter-individual choroidal variations pattern. Results: Sex (ß = -17.26, female vs. male), age (ß = -1.61, per 1 year), and axial length (ß = -18.62, per 1 mm) were associated with mean macular CT. Females had a thinner choroid in all 900 grids (0.5-26.9 µm). As age increased, the CT noticeably decreased (8.74-19.87 µm per 10 years) in the temporal regions. With axial length elongation, the thinning (7.94-24.91 µm per 1 mm) was more evident in subfoveal and nasal regions. Both the CoV (34.69%-58.00%) and CoVU (23.05%-40.78%) were lower in the temporal regions, whereas the CoD (18.41%-39.66%) was higher in the temporal regions. Conclusions: Choroidal thinning is more predominant in the subfoveal and nasal regions with axial length elongation, but in the temporal region with aging. The inter-individual variation of CT is higher and less determined by sex, age, or axial length in the nasal regions. Translational Relevance: Topographic variation should be considered when interpreting choroidal thickness.

An m1A/m6A/m5C-associated long non-coding RNA signature: Prognostic and immunotherapeutic insights into cervical cancer.

BACKGROUND: Cervical cancer (CC) remains a significant clinical challenge, even though its fatality rate has been declining in recent years. Particularly in developing countries, the prognosis for CC patients continues to be suboptimal despite numerous therapeutic advances. METHODS: Using The Cancer Genome Atlas database, we extracted CC-related data. From this, 52 methylation-related genes (MRGs) were identified, leading to the selection of a 10 long non-coding RNA (lncRNA) signature co-expressed with these MRGs. R programming was employed to filter out the methylation-associated lncRNAs. Through univariate, least absolute shrinkage and selection operator (i.e. LASSO) and multivariate Cox regression analysis, an MRG-associated lncRNA model was constructed. The established risk model was further assessed via the Kaplan-Meier method, principal component analysis, functional enrichment annotation and a nomogram. Furthermore, we explored the potential of this model with respect to guiding immune therapeutic interventions and predicting drug sensitivities. RESULTS: The derived 10-lncRNA signature, linked with MRGs, emerged as an independent prognostic factor. Segmenting patients based on their immunotherapy responses allowed for enhanced differentiation between patient subsets. Lastly, we highlighted potential compounds for distinguishing CC subtypes. CONCLUSIONS: The risk model, associated with MRG-linked lncRNA, holds promise in forecasting clinical outcomes and gauging the efficacy of immunotherapies for CC patients.

Uncertainty-inspired open set learning for retinal anomaly identification.

Failure to recognize samples from the classes unseen during training is a major limitation of artificial intelligence in the real-world implementation for recognition and classification of retinal anomalies. We establish an uncertainty-inspired open set (UIOS) model, which is trained with fundus images of 9 retinal conditions. Besides assessing the probability of each category, UIOS also calculates an uncertainty score to express its confidence. Our UIOS model with thresholding strategy achieves an F1 score of 99.55%, 97.01% and 91.91% for the internal testing set, external target categories (TC)-JSIEC dataset and TC-unseen testing set, respectively, compared to the F1 score of 92.20%, 80.69% and 64.74% by the standard AI model. Furthermore, UIOS correctly predicts high uncertainty scores, which would prompt the need for a manual check in the datasets of non-target categories retinal diseases, low-quality fundus images, and non-fundus images. UIOS provides a robust method for real-world screening of retinal anomalies.

Research Trends and Hotspots of Retinal Optical Coherence Tomography: A 31-Year Bibliometric Analysis.

The emergence of optical coherence tomography (OCT) over the past three decades has sparked great interest in retinal research. However, a comprehensive analysis of the trends and hotspots in retinal OCT research is currently lacking. We searched the publications on retinal OCT in the Web of Science database from 1991 to 2021 and performed the co-occurrence keyword analysis and co-cited reference network using bibliometric tools. A total of 25,175 publications were included. There has been a progressive increase in the number of publications. The keyword co-occurrence network revealed five clusters of hotspots: (1) thickness measurements; (2) therapies for macular degeneration and macular edema; (3) degenerative retinal diseases; (4) OCT angiography (OCTA); and (5) vitrectomy for macular hole and epiretinal membrane. The co-citation analysis displayed 26 highly credible clusters (S = 0.9387) with a well-structured network (Q = 0.879). The major trends of research were: (1) thickness measurements; (2) therapies for macular degeneration and macular edema; and (3) OCTA. Recent emerging frontiers showed a growing interest in OCTA, vessel density, choriocapillaris, central serous chorioretinopathy, Alzheimer's disease, and deep learning. This review summarized 31 years of retinal OCT research, shedding light on the hotspots, main themes, and emerging frontiers to assist in future research.

Vitreomacular Interface Disorders in Proliferative Diabetic Retinopathy: An Optical Coherence Tomography Study.

Vitreomacular interface plays an important role in the pathogenesis and progression of proliferative diabetic retinopathy (PDR). This study investigated the prevalence and risk factors of vitreomacular interface disorders (VMID) in PDR. The macular optical coherence tomography (OCT) scans of 493 eyes from 378 PDR patients were retrospectively reviewed to detect VMID, including vitreomacular adhesion (VMA), vitreomacular traction (VMT), epiretinal membrane (ERM), lamellar hole-associated epiretinal proliferation (LHEP), and macular hole (MH). The associations between VMID and baseline factors, intraretinal structure, and visual acuity were analyzed. The prevalence was 78.9% for ERM, 13.4% for VMT, 4.8% for MH, 2.2% for LHEP, and 2.0% for VMA, respectively. On multivariable analyses (odds ratio, 95% confidence interval), fibrovascular proliferation (FVP) was positively associated with MH (8.029, 1.873-34.420), VMT (3.774, 1.827-7.798), and ERM (2.305, 1.460-3.640). High-risk PDR was another risk factor of ERM (1.846, 1.101-3.090). Female gender was positively associated with MH (3.836, 1.132-13.006), while vitreous hemorrhage was negatively associated with MH (0.344, 0.133-0.890). Eyes with all VMID subtypes showed more frequent macular cysts and tractional retinal detachment with poorer visual acuity (p ≤ 0.001). Therefore, the prevalence of VMID was considerably high, indicating that this distinct entity should be considered in interventions for PDR.

Improved Automated Foveal Avascular Zone Measurement in Cirrus Optical Coherence Tomography Angiography Using the Level Sets Macro.

Purpose: To evaluate automated measurements of the foveal avascular zone (FAZ) using the Level Sets macro (LSM) in ImageJ as compared with the Cirrus optical coherence tomography angiography (OCTA) inbuilt algorithm and the Kanno-Saitama macro (KSM). Methods: The eyes of healthy volunteers were scanned four times consecutively on the Zeiss Cirrus HD-OCT 5000 system. The FAZ metrics (area, perimeter, and circularity) were measured manually and automatically by the Cirrus inbuilt algorithm, the KSM, and the LSM. The accuracy and repeatability of all methods and agreement between automated and manual methods were evaluated. Results: The LSM segmented the FAZ with an average Dice coefficient of 0.9243. Compared with the KSM and the Cirrus inbuilt algorithm, the LSM outperformed them by 0.02 and 0.19, respectively, for Dice coefficients. Both the LSM (intraclass correlation coefficient [ICC] = 0.908; coefficient of variation [CoV] = 9.664%) and manual methods (ICC ≥ 0.921, CoV ≤ 8.727%) showed excellent repeatability for the FAZ area, whereas the other methods presented moderate to good repeatability (ICC ≤ 0.789, CoV ≥ 15.788%). Agreement with manual FAZ area measurement was excellent for both the LSM and KSM but not for the Cirrus inbuilt algorithm (LSM, ICC = 0.930; KSM, ICC = 0.928; Cirrus, ICC = 0.254). Conclusions: The LSM exhibited greater accuracy and reliability compared to the KSM and inbuilt automated methods and may be an improved and accessible option for automated FAZ segmentation. Translational Relevance: The LSM may be a suitable automated and customizable tool for FAZ quantification of Cirrus HD-OCT 5000 images, providing results comparable to those for manual measurement.

Reliability of foveal avascular zone metrics automatically measured by Cirrus optical coherence tomography angiography in healthy subjects.

PURPOSE: To investigate the reliability of the foveal avascular zone (FAZ) metrics automatically measured using Cirrus optical coherence tomography angiography (OCTA) embedded algorithm compared to human manual measurement. METHODS: Thirty-five eyes of 35 healthy subjects were enrolled and scanned four times continuously on Zeiss Cirrus HD-OCT 5000. The FAZ metrics (area, circularity and perimeter) of the superficial capillary plexus were measured automatically using the embedded tool and manually measured by the two independent observers using ImageJ. The repeatability of the four scans within all methods of measurements was calculated. The agreement of the manual vs automated measurement was also analyzed. RESULTS: The repeatability of the automated algorithm was only poor to moderate (intraclass correlation coefficients [ICCs] for the area, perimeter and circularity were 0.600, 0.405 and 0.221, respectively) while the repeatability of the manually measured FAZ area and perimeter was good [([ICCs] ranged from 0.845 to 0.877) except the circularity (ICC = 0.538 to 0.608)]. The ranges of 95% limits of agreement between the manual measurements by the two observers were only 20% to 31% of those of automated-manual agreement. The Cirrus inbuilt algorithm obviously outlined the border of FAZ wrongly in 22.9% cases. CONCLUSION: Caution should be taken when using the automated measurement results of FAZ metrics in Cirrus OCTA, because of the low repeatability and poor agreement compared with the manual measurement.