Translational Vision Science & Technology最新文献

Optoretinography is an emerging class of methods designed to probe the function of retinal neurons using noninvasive, optical techniques. Early efforts sought to identify sources of functional signal and measure responses using advanced, research-grade imaging systems. In the past few years, some investigators have demonstrated simplified methods for measuring these signals using equipment very similar to what is used in commercial, clinical systems. The goal of this review is to introduce the reader to the sources of the photoreceptor optoretinographic signal and the technologies that have been developed to measure it.

Purpose: This proof-of-concept study aimed to evaluate the feasibility of targeted, image-guided microperimetry (IGMP) by integrating optical coherence tomography (OCT) and fundus autofluorescence (FAF) for lesion mapping and functional assessment in retinal atrophic diseases.

Methods: Twenty-two eyes were identified, of which 17 had early geographic atrophy (GA) and 5 had Stargardt disease (SD). Disease transition zones (TZs) on OCT and FAF were annotated onto en face infrared images. These were then exported with microperimetry (MP) assessments to custom MATLAB applications. IGMP patterns were thereafter created and imported using macular integrity assessment (MAIA) system and Nidek-MP3/S microperimeters for subsequent scans. Mean procedure and examination times (minutes), retinal sensitivity (decibel [dB]), approach feasibility, and algorithm compatibility of targeted IGMP were reported as outcomes.

Results: Targeted IGMP was quicker than the standard 10-2 grid for both SD and GA lesion assessments. SD cases showed longer mean procedure and examination times and lower mean retinal sensitivity in all zones compared with GA lesions. The targeted IGMP procedure was lengthier for Nidek-MP3/S (29.2 ± 7.1 minutes) than MAIA (17.4 ± 4.3 minutes), although the examination took longer on MAIA (4.0 ± 1.0 minutes) than on Nidek-MP3/S (3.6 ± 1.2 minutes). Overall, the IGMP approach is feasible (100.0%) and the algorithm is compatible (100.0%) on both MP devices for all subjects tested.

Conclusions: This study establishes the feasibility of an IGMP workflow in providing targeted functional assessments in retinal degenerative diseases. Further validation in larger cohorts is needed to assess its broader clinical applicability.

Translational relevance: Our approach may help enhance structure-function correlation and optimize the efficiency of MP integration for clinical trials.

Purpose: Decellularized and cross-linked porcine stromal tissue offers a new option for corneal tissue augmentation. The aim of this study is to characterize the biomechanical properties and enzymatic resistance of processed xenogenic porcine corneal lenticules (XENIA) and compare them to human/porcine specimens.

Methods: Groups of XENIA, human, and porcine corneal lenticules were formed. The dimensions of all lenticules were 7.7 mm in diameter and 80 µm in thickness. Conformité Européenne (CE)-approved XENIA-lenticules were provided by the manufacturer and human/porcine lenticules were generated using a femtosecond laser from the anterior stroma of cadaver eyes. All specimens were analyzed by uniaxial stress-strain measurements (n = 6 per group) and the resulting elastic moduli were compared. To evaluate the enzymatic resistance, all lenticules (n = 5 per group) were treated with collagenase solution (c = 0.1 U/mL) over a 20-day period and the lenticule size was analyzed by photo-documentation.

Results: XENIA-lenticules showed the highest elastic modulus, significantly higher than human and porcine lenticules. At 11% strain, the maximum difference occurred between XENIA and porcine lenticules, with XENIA-lenticules being 23.5-fold stiffer. In the human lenticule group, donor age correlated strongly with the elastic moduli of this group (rs = 0.941, P = 0.005). XENIA-lenticules showed the greatest resistance against enzymatic digestion. On average, human samples were completely digested after 11 ± 4 hours, porcine samples after 91 ± 60 hours, whereas XENIA-lenticules only showed a digested area of 19.2% ± 13.7% after 20 days.

Conclusions: XENIA-lenticules are substantially stiffer (3.9-9.6-fold stiffer than human tissue and 9.0-23.5-fold stiffer than porcine tissue across 5% to 17% strain) and resistant to enzymatic digestion compared to human/porcine probes.

Translational relevance: XENIA-lenticules may help to overcome the lack of human corneal donor tissue and may offer new alternatives for corneal augmentation therapies, such as for corneal melting or keratoconus.

Purpose: Inherited retinal diseases (IRDs) are rare and diverse, posing a diagnostic challenge in ophthalmology. This study aimed to determine whether artificial intelligence (AI)-assisted image processing can improve IRD diagnosis and provide insights into disease characteristics. We used an optical coherence tomography (OCT) segmentation algorithm to characterize retinal features in IRDs. Two control groups were included to enhance the contextual understanding of these features: healthy eyes and eyes with age-related macular degeneration (AMD). An AI-driven classification model was then used to classify the data into disease and control groups.

Methods: We analyzed 327 images from 181 patients with IRD and 146 control individuals, including healthy subjects and patients with AMD. IRD cases were stratified into macular and retinal dystrophies. Automated segmentation of six retinal layers and detection of nine biomarkers were performed on retinal OCT images using the AI-based RetinAI Discovery tool. A random forest classifier differentiated macular IRD, retinal IRD, and controls.

Results: The model detected IRD with 91% accuracy and achieved 91% accuracy in differentiating macular from retinal IRD. Key OCT features for differentiation included reduced perifoveal photoreceptor and outer nuclear layer thicknesses and increased retinal nerve fiber layer thickness in retinal IRD. Macular IRD featured significant foveal photoreceptor and outer nuclear layer thinning.

Conclusions: This study shows that standardized OCT image analysis combined with AI-based classification can accurately detect and stratify IRDs. The model's high accuracy highlights its potential as a reliable diagnostic tool in ophthalmology.

Translational relevance: This AI-assisted OCT evaluation approach enhances ophthalmic diagnostics by improving IRD detection and classification.

Purpose: To assess whether automated analysis of retinal arterioles and venules can identify treatment response in papilledema secondary to idiopathic intracranial hypertension (IIH).

Methods: This retrospective analysis used data from a multicenter, randomized, double-blind, placebo-controlled IIH treatment trial. Participants (n = 165) with mild visual loss were assigned to a dietary/lifestyle modification plus acetazolamide (ACZ) or placebo for 6 months. Color fundus photographs, optical coherence tomography (OCT), and clinical metrics were collected at baseline and at multiple follow-up visits. AutoMorph, a deep learning-based pipeline, quantified venule and arteriole diameters, fractal dimensionality, tortuosity, and vessel density. Venular widths were standardized to arteriolar widths to form a venule-to-arteriole (V:A) ratio, which was correlated with Frisén grade, OCT optic nerve head (ONH) parameters, and cerebrospinal fluid (CSF) opening pressure.

Results: Baseline vascular OCT metrics and Frisén grades were similar between groups. At month 1, ACZ significantly reduced venule diameters (-4.59 µm; P = 0.02), and placebo showed no change (+1.21 µm; P = 0.54). The V:A ratio was consistently lower in the ACZ group than placebo from month 1 (1.20 vs. 1.24, respectively; P = 0.03) to month 6 (1.16 vs. 1.23, P = 0.02). Higher Frisén grades correlated strongly with increased mean V:A values (R2 = 0.91, P = 0.011). The V:A ratio was significantly associated with CSF opening pressure at month 6 (R2 = 0.47, P < 0.001).

Conclusions: Automated retinal vessel analysis provides a promising, non-invasive method for monitoring treatment response in IIH and may complement traditional imaging and clinical assessments.

Translational relevance: Deep learning-based retinal vessel metrics may provide an accessible biomarker for monitoring treatment response in papilledema.

Purpose: To characterize photoreceptor layer thinning in clinically unremarkable regions adjacent to the atrophic lesion in early-stage ABCA4 disease eyes.

Methods: Twenty-seven patients with confined atrophic lesions (≤3.5 mm in diameter) were included. Two pathogenic alleles were confirmed by sequencing of the ABCA4 locus. Multimodal imaging included fundus photography, short-wavelength autofluorescence, and near-infrared autofluorescence imaging (NIR-AF). Total receptor+ (TREC+) thickness was segmented in spectral-domain optical coherence tomography (SD-OCT) scans in patient eyes (n = 27) along with age-matched healthy control eyes (n = 20).

Results: Mean age of the study cohort was 24.1 years, and 15 of 27 (55.6%) patients harbored genotypes consisting of the p.(Gly1961Glu) variant of the ABCA4 gene. Atrophic lesions ranged from 0.61 to 3.13 mm in diameter (μ = 1.73, σ = 0.70). Six patients had mild RPE mottling adjacent to the lesion on NIR-AF. The atrophic lesion corresponded to a disruption of photoreceptor-attributable bands on SD-OCT, while all layers were visibly intact outside the lesion. TREC+ thickness in patient eyes was <0.15 mm (below 4σ) of healthy control thickness immediately adjacent to the lesion edge and gradually normalized to within ±2σ at ≈1.2 mm eccentricity from the fovea.

Conclusions: A uniform subclinical perilesional zone of photoreceptor thinning extends around the perimeter of early-stage atrophic lesions in ABCA4 disease. This region spatially maps to known regions of vision loss and more accurately approximates the extent of photoreceptor abnormality compared to disease changes visible on standard fundus imaging.

Translational relevance: Semi-automated segmentation of SD-OCT scans identifies a consistent subclinical biomarker relevant to early photoreceptor degeneration in ABCA4 disease.

Purpose: To evaluate the performance of the N2V2 denoising algorithm on optical coherence tomography angiography (OCTA) retinal vasculature quantification.

Methods: OCTA scans (3 × 3, 6 × 6, and 21 × 21 mm) were acquired from patients with diabetes using Topcon Triton before/after denoising. Perceived image quality was assessed by three ophthalmologists on a 5-point scale (capillary details in the superficial capillary plexus [SCP] and deep capillary plexus [DCP] of 3 × 3 and 6 × 6 mm scans, and vessel continuity and nonperfusion boundaries in 21 × 21 mm scans), and by objective metrics including contrast-to-noise ratio, peak signal-to-noise ratio, edge preservation index, and structural similarity index measurement. Diagnostic interpretability was evaluated through annotation of microaneurysm and vascular beading counts, foveal avascular zone margins, and peripheral nonperfusion borders. Quantitative reproducibility was assessed for vessel density, foveal avascular zone metrics (area, perimeter, circularity), and peripheral nonperfusion area delineations.

Results: We included 145 eyes (mean patient age, 63.97 ± 9.25 years; 40.26% female) (35.17% no diabetic retinopathy, 33.10% nonproliferative diabetic retinopathy, and 31.72% proliferative diabetic retinopathy). Subjective vessel visualization improved in 3 × 3 (ΔSCP, 1.66 ± 0.39; ΔDCP, 1.90 ± 0.43), 6 × 6 (ΔSCP, 1.68 ± 0.36; ΔDCP, 2.11 ± 0.33), and 21 × 21 mm scans (Δvessels, 1.79 ± 0.37; Δnonperfusion, 1.61 ± 0.38) (all P < 0.001). Denoising objectively increased the contrast-to-noise ratio from poor (1.33-1.68) to moderate (2.90-3.97) (P < 0.001), and the peak signal-to-noise ratio (16.74-18.53 dB), structural similarity index measurement (0.60-0.72), and edge preservation index (0.71-0.79) reached moderate levels. Diagnostic interpretability showed most microaneurysms (64.17% SCP, 87.32% DCP) and venous beading (98.76%) remaining detectable. Vessel density decreased in 3 × 3 mm (ΔSCP, -5.81%; ΔDCP, -4.18%) and 6 × 6 mm scans (ΔSCP, -11.89%; ΔDCP, -5.23%; P < 0.001). The foveal avascular zone area increased slightly (Δ+0.01 mm²; P = 0.02), the perimeter expanded (Δ+0.53 mm; P < 0.001), and circularity decreased (Δ-0.16; P < 0.001), with similar peripheral nonperfusion area (Δ+4.84 mm²; P = 0.49).

Conclusions: N2V2 enhances OCTA quality and visualization, which may support more accurate retinal change assessments.

Translational relevance: The N2V2 denoising algorithm can potentially advance the routine clinical use of OCTA by improving the visualization and features quantification.

Purpose: This work characterizes two extended-depth-of-focus (EDoF) intraocular lenses, the Alcon IQ Vivity and the Bausch & Lomb LuxSmart, using virtual retinal imaging. A simulation-based examination tests these lenses under various conditions, while including dispersion and color effects.

Methods: A custom sequential Monte-Carlo Ray Tracer simulates the propagation of a broadband daylight spectrum through a mathematical eye model. Realistic color images of a pinhole and resolution chart were generated, with variations in object distances and pupil size. A comparison is made with the monofocal Alcon IQ to highlight the benefits of EDoF models.

Results: Simulated images clearly demonstrate the superior acuity and reduced aberrations of these lenses at intermediate vision. There are notable differences between both models: the LuxSmart lens exhibits an increased depth-of-focus under both mesopic and photopic conditions. Conversely, the IQ Vivity lens shows minimal aberrations for far vision under mesopic conditions, making it ideal for night-time driving, albeit with a lesser depth-of-focus compared to the LuxSmart.

Conclusions: Our in silico investigation proves to be a valuable tool for evaluating intraocular lens performance. This study underscores the importance of characterizing lenses under both photopic and mesopic conditions and highlights the impact of chromatic aberration and color vision.

Translational relevance: The simulation-based approach expands the range of methods for assessing intraocular lenses. By providing realistic images, it allows both ophthalmologists and patients to more intuitively understand the aspects of these lenses. The simulation derives visual predictions from a purely mathematical model, thus bridging the gap from technology to clinical application.

Purpose: To investigate the clinical features, antifungal susceptibility patterns, and treatment outcomes of pediatric fungal keratitis (FK) at a tertiary eye center in North China.

Methods: A retrospective study of pediatric FK cases diagnosed between July 2000 and October 2023 at Beijing Tongren Hospital, confirmed by fungal culture or microscopy. Data on demographics, predisposing factors, clinical signs, microbiological findings, treatment, and prognosis were analyzed.

Results: Eighty-eight pediatric FK cases (66 males, 22 females; mean age 10.8 ± 2.3 years) were collected. Trauma history (35.2%) was primarily from toys and writing tools. Dense infiltrates (100%), feathery margins (69.2%), and multifocal lesions (38.5%) were the common features. Hypopyon was less frequent (15.5%); no endothelial plaques, collar-button lesions, and pigment deposits were observed. Fusarium (43.9%) and Aspergillus (25.8%) were the predominant isolates. Amphotericin B demonstrated both in vitro and clinical efficacy. Treatment duration (median 48.1 days) varied by risk factors (P < 0.001), age (P = 0.013), and fungal type (P = 0.016). Multivariate analysis identified ocular surgery (hazard ratio [HR] = 0.04, P < 0.001) and toddler age (HR = 3.67, P = 0.013) as the strongest predictors of prolonged and faster treatment duration, respectively.

Conclusions: Trauma is the leading risk factor of pediatric FK in North China, with Fusarium and Aspergillus being the predominant pathogens. Amphotericin B is the most effective antifungal, and early diagnosis and treatment are critical for improving outcomes.

Translational relevance: This study provides evidence-based data on fungal trends, antifungal susceptibility, and treatment outcomes, guiding optimal drug selection and therapeutic strategies to reduce visual impairment in pediatric FK.