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Translational Vision Science &... Sep 2023To examine spatial patterns of retinal sensitivity loss in the three key features of intermediate age-related macular degeneration (iAMD).
PURPOSE
To examine spatial patterns of retinal sensitivity loss in the three key features of intermediate age-related macular degeneration (iAMD).
METHODS
One-hundred individuals (53 iAMD, 47 normal) underwent 10-2 mesopic microperimetry testing in one eye. Pointwise sensitivities (dB) were corrected for age, sex, iAMD status, and co-presence of co-localized key iAMD features: drusen load, pigmentary abnormalities, and reticular pseudodrusen (RPD). Clusters (labeled by ranks of magnitude C-2, C-1, C0) were derived from pointwise sensitivities and then assessed by quadrants and eccentricity/rings.
RESULTS
Two clusters of decreased sensitivities were evident in iAMD versus normal: C-2, -1.67 dB (95% CI (confidence intervals), -2.36 to -0.98; P < 0.0001); C-1, -0.93 dB (95% CI, -1.5 to -0.36; P < 0.01). One cluster of decreased sensitivity was independently associated each with increased drusen load (13.57 µm increase per -1 dB; P < 0.0001), pigmentary abnormalities (C-1: -2.23 dB; 95% CI, -3.36 to -1.1; P < 0.01), and RPD (C-1: -1.07 dB; 95% CI, -2 to -0.14; P < 0.01). Sensitivity loss in iAMD was biased toward the superior and central macula (P = 0.16 to <0.0001), aligning with structural distributions of features. However, sensitivity loss associated with drusen load also extended to the peripheral macula (P < 0.0001) with paracentral sparing, which was discordant with the central distribution of drusen.
CONCLUSIONS
Drusen load, pigmentary abnormalities, and RPD are associated with patterns of retinal sensitivity loss commonly demonstrating superior and central bias. Results highlighted that a clinical focus on these three key iAMD features using structural measures alone does not capture the complex, spatial extent of vision-related functional impairment in iAMD.
TRANSLATIONAL RELEVANCE
Defining the spatial patterns of retinal sensitivity loss in iAMD can facilitate a targeted visual field protocol for iAMD assessment.
Topics: Humans; Retina; Macular Degeneration; Retinal Drusen; Macula Lutea; Transcription Factors
PubMed: 37676679
DOI: 10.1167/tvst.12.9.6 -
Graefe's Archive For Clinical and... Jan 2024Subretinal drusenoid deposits (SDDs) are distinct extracellular alteration anterior to the retinal pigment epithelium (RPE). Given their commonly uniform phenotype, a...
PURPOSE
Subretinal drusenoid deposits (SDDs) are distinct extracellular alteration anterior to the retinal pigment epithelium (RPE). Given their commonly uniform phenotype, a hereditary predisposition seems likely. Hence, we aim to investigate prevalence and determinants in patients' first-degree relatives.
METHODS
We recruited SDD outpatients at their visits to our clinic and invited their relatives. We performed a full ophthalmic examination including spectral domain-optical coherence tomography (SD-OCT) and graded presence, disease stage of SDD as well as percentage of infrared (IR) en face area affected by SDD. Moreover, we performed genetic sequencing and calculated a polygenic risk score (PRS) for AMD. We conducted multivariable regression models to assess potential determinants of SDD and associations of SDD with PRS.
RESULTS
We included 195 participants, 123 patients (mean age 81.4 ± 7.2 years) and 72 relatives (mean age 52.2 ± 14.2 years), of which 7 presented SDD, resulting in a prevalence of 9.7%. We found older age to be associated with SDD presence and area in the total cohort and a borderline association of higher body mass index (BMI) with SDD presence in the relatives. Individuals with SDD tended to have a higher PRS, which, however, was not statistically significant in the multivariable regression.
CONCLUSION
Our study indicates a potential hereditary aspect of SDD and confirms the strong association with age. Based on our results, relatives of SDD patients ought to be closely monitored for retinal alterations, particularly at an older age. Further longitudinal studies with larger sample size and older relatives are needed to confirm or refute our findings.
Topics: Humans; Aged; Aged, 80 and over; Adult; Middle Aged; Retinal Drusen; Prevalence; Retinal Pigment Epithelium; Genetic Risk Score; Tomography, Optical Coherence; Fluorescein Angiography
PubMed: 37672102
DOI: 10.1007/s00417-023-06221-y -
SLAS Technology Jun 2024Age-Related Macular Degeneration (AMD) is a highly prevalent form of retinal disease amongst Western communities over 50 years of age. A hallmark of AMD pathogenesis is...
Age-Related Macular Degeneration (AMD) is a highly prevalent form of retinal disease amongst Western communities over 50 years of age. A hallmark of AMD pathogenesis is the accumulation of drusen underneath the retinal pigment epithelium (RPE), a biological process also observable in vitro. The accumulation of drusen has been shown to predict the progression to advanced AMD, making accurate characterisation of drusen in vitro models valuable in disease modelling and drug development. More recently, deposits above the RPE in the subretinal space, called reticular pseudodrusen (RPD) have been recognized as a sub-phenotype of AMD. While in vitro imaging techniques allow for the immunostaining of drusen-like deposits, quantification of these deposits often requires slow, low throughput manual counting of images. This further lends itself to issues including sampling biases, while ignoring critical data parameters including volume and precise localization. To overcome these issues, we developed a semi-automated pipeline for quantifying the presence of drusen-like deposits in vitro, using RPE cultures derived from patient-specific induced pluripotent stem cells (iPSCs). Using high-throughput confocal microscopy, together with three-dimensional reconstruction, we developed an imaging and analysis pipeline that quantifies the number of drusen-like deposits, and accurately and reproducibly provides the location and composition of these deposits. Extending its utility, this pipeline can determine whether the drusen-like deposits locate to the apical or basal surface of RPE cells. Here, we validate the utility of this pipeline in the quantification of drusen-like deposits in six iPSCs lines derived from patients with AMD, following their differentiation into RPE cells. This pipeline provides a valuable tool for the in vitro modelling of AMD and other retinal disease, and is amenable to mid and high throughput screenings.
Topics: Humans; Induced Pluripotent Stem Cells; Retinal Pigment Epithelium; Retinal Drusen; Macular Degeneration; Image Processing, Computer-Assisted; Microscopy, Confocal
PubMed: 37657710
DOI: 10.1016/j.slast.2023.08.006 -
Translational Vision Science &... Sep 2023The purpose of this study was to determine the impact of prophylactic ranibizumab (PR) injections given every 3 months in eyes with intermediate nonexudative... (Randomized Controlled Trial)
Randomized Controlled Trial
PURPOSE
The purpose of this study was to determine the impact of prophylactic ranibizumab (PR) injections given every 3 months in eyes with intermediate nonexudative age-related macular degeneration (AMD) on drusen volume, macular layer thicknesses, and progression of geographic atrophy (GA) area over 24 months in the PREVENT trial.
METHODS
This post hoc analysis of the prospective PREVENT trial compared eyes with intermediate AMD randomized to PR versus sham injections to determine rates of conversion to neovascular AMD over 24 months. Drusen area and volume, macular thickness and volume, and retinal layer thicknesses were measured on spectral-domain optical coherence tomography images and analyzed. Masked grading of GA area and subretinal drusenoid deposits (SDDs) using fundus autofluorescence images was performed.
RESULTS
There were no statistical differences in drusen area and volumes between groups, and similar reductions in central subfield thickness, mean cube thickness, cube volume, and retinal sublayer thickness from baseline to 24 months (P = 0.018 to < 0.001), with no statistical differences between groups in any of these anatomic parameters. These findings were not impacted by the presence or absence of SDD. Among the 9 eyes with GA in this study, mean GA growth rate from baseline to 24 months was 1.34 +/- 0.79 mm2/year after PR and 1.95 +/- 1.73 mm2/year in sham-treated eyes (P = 0.49), and similarly showed no statistical difference with square root transformation (P = 0.61).
CONCLUSIONS
Prophylactic ranibizumab given every 3 months did not appear to affect drusen volume, macular thinning, or GA progression in eyes with intermediate AMD.
TRANSLATIONAL RELEVANCE
This work investigates the impact of PR on progressive retinal degeneration in a clinical trial.
Topics: Humans; Child, Preschool; Ranibizumab; Angiogenesis Inhibitors; Prospective Studies; Vascular Endothelial Growth Factor A; Visual Acuity; Wet Macular Degeneration; Retina; Geographic Atrophy
PubMed: 37656449
DOI: 10.1167/tvst.12.9.1 -
Frontiers in Medicine 2023The implementation of deep learning models for medical image classification poses significant challenges, including gradual performance degradation and limited...
BACKGROUND
The implementation of deep learning models for medical image classification poses significant challenges, including gradual performance degradation and limited adaptability to new diseases. However, frequent retraining of models is unfeasible and raises concerns about healthcare privacy due to the retention of prior patient data. To address these issues, this study investigated privacy-preserving continual learning methods as an alternative solution.
METHODS
We evaluated twelve privacy-preserving non-storage continual learning algorithms based deep learning models for classifying retinal diseases from public optical coherence tomography (OCT) images, in a class-incremental learning scenario. The OCT dataset comprises 108,309 OCT images. Its classes include normal (47.21%), drusen (7.96%), choroidal neovascularization (CNV) (34.35%), and diabetic macular edema (DME) (10.48%). Each class consisted of 250 testing images. For continuous training, the first task involved CNV and normal classes, the second task focused on DME class, and the third task included drusen class. All selected algorithms were further experimented with different training sequence combinations. The final model's average class accuracy was measured. The performance of the joint model obtained through retraining and the original finetune model without continual learning algorithms were compared. Additionally, a publicly available medical dataset for colon cancer detection based on histology slides was selected as a proof of concept, while the CIFAR10 dataset was included as the continual learning benchmark.
RESULTS
Among the continual learning algorithms, Brain-inspired-replay (BIR) outperformed the others in the continual learning-based classification of retinal diseases from OCT images, achieving an accuracy of 62.00% (95% confidence interval: 59.36-64.64%), with consistent top performance observed in different training sequences. For colon cancer histology classification, Efficient Feature Transformations (EFT) attained the highest accuracy of 66.82% (95% confidence interval: 64.23-69.42%). In comparison, the joint model achieved accuracies of 90.76% and 89.28%, respectively. The finetune model demonstrated catastrophic forgetting in both datasets.
CONCLUSION
Although the joint retraining model exhibited superior performance, continual learning holds promise in mitigating catastrophic forgetting and facilitating continual model updates while preserving privacy in healthcare deep learning models. Thus, it presents a highly promising solution for the long-term clinical deployment of such models.
PubMed: 37644987
DOI: 10.3389/fmed.2023.1227515 -
Medical Hypothesis, Discovery &... 2022Neovascular age-related macular degeneration (nAMD) is one of the main causes of blindness in developed countries. is one of the genes involved in the pathogenesis of...
BACKGROUND
Neovascular age-related macular degeneration (nAMD) is one of the main causes of blindness in developed countries. is one of the genes involved in the pathogenesis of nAMD. This study investigated the rs10737680 polymorphism in and its conferred susceptibility to nAMD in Yogyakarta, Indonesia.
METHODS
This case-control hospital-based study recruited participants consisting of 96 patients with nAMD and 101 controls without nAMD from the Eye Polyclinic of Sardjito Hospital, YAP Eye Hospital, and Hardjolukito Hospital Yogyakarta. nAMD was diagnosed when fundus examination, fundus photographs, and optical coherence tomography revealed hard or soft drusen in the macular area measuring > 63 µm that appeared below the retinal pigment epithelium, with or without macular hypo- or hyperpigmentation, and was accompanied by choroidal neovascularization. Genomic DNA was extracted using a commercial DNA isolation kit. The restriction fragment length polymorphism technique was used to identify the rs10737680 polymorphism in .
RESULTS
The mean (standard deviation [SD]) age of the nAMD group was not homogeneous with that of the control group ( < 0.05); 65.41 (9.74) years versus 68.24 (7.82) years. The number of patients with hypertension in the nAMD group was significantly higher than in the control group ( < 0.05). In the nAMD group, the genotype distribution indicated homozygous risk allele in 34.38%, heterozygous risk allele in 57.29%, and homozygous non-risk allele in 8.33%. In the control group, the genotype distribution indicated homozygous risk allele in 21.78%, heterozygous risk allele in 36.63%, and homozygous non-risk allele in 41.58%. Statistical analysis between the two study groups according to homozygous risk allele genotype (odds ratio [OR], 7.87; 95% confidence interval [CI], 2.88-22.79) and heterozygous genotype (OR, 7.80; 95% CI, 3.11-21.19) showed a significant difference (both < 0.01).
CONCLUSIONS
Homozygous risk allele was less frequent than heterogeneous risk allele in patients with nAMD; however, both increased the risk for nAMD. Although the homozygous or heterozygous risk-alleles were detected in most patients, yet other important genetic or environmental factors could be involved in the pathogenesis of nAMD. Overall, we found a significant association between rs10737680 polymorphism in and the susceptibility to nAMD in Yogyakarta, Indonesia; however, future studies are needed to fully delineate the mechanism.
PubMed: 37641789
DOI: 10.51329/mehdiophthal1448 -
BioRxiv : the Preprint Server For... Aug 2023Age-related macular degeneration (AMD), the leading cause of geriatric blindness, is a multi-factorial disease with retinal-pigmented epithelial (RPE) cell dysfunction...
Age-related macular degeneration (AMD), the leading cause of geriatric blindness, is a multi-factorial disease with retinal-pigmented epithelial (RPE) cell dysfunction as a central pathogenic driver. With RPE degeneration, lysosomal function is a core process that is disrupted. Transcription factors EB/E3 (TFEB/E3) tightly control lysosomal function; their disruption can cause aging disorders, such as AMD. Here, we show that induced pluripotent stem cells (iPSC)-derived RPE cells with the complement factor H variant [ (Y402H)] have increased AKT2, which impairs TFEB/TFE3 nuclear translocation and lysosomal function. Increased AKT2 can inhibit PGC1α, which downregulates SIRT5, an AKT2 binding partner. SIRT5 and AKT2 co-regulate each other, thereby modulating TFEB-dependent lysosomal function in the RPE. Failure of the AKT2/SIRT5/TFEB pathway in the RPE induced abnormalities in the autophagy-lysosome cellular axis by upregulating secretory autophagy, thereby releasing a plethora of factors that likely contribute to drusen formation, a hallmark of AMD. Finally, overexpressing AKT2 in RPE cells in mice led to an AMD-like phenotype. Thus, targeting the AKT2/SIRT5/TFEB pathway could be a potential therapy for atrophic AMD.
PubMed: 37609254
DOI: 10.1101/2023.08.08.552343 -
Oman Journal of Ophthalmology 2023We report a rare case of type-3 macular neovascularization (MNV) in an established case of macular telangiectasia type-2 (MacTel). A 49-year-old healthy Indian woman was...
We report a rare case of type-3 macular neovascularization (MNV) in an established case of macular telangiectasia type-2 (MacTel). A 49-year-old healthy Indian woman was diagnosed with MacTel (Gass and Blodi stage 3 in the right eye [OD] and stage 2 in the left eye [OS]) in our retina clinic in January 2004. She was subsequently seen 10 years later with MacTel progression in OD (stage 4) and drusenoid changes in both eyes. She recently complained of sudden onset diminution of vision in OS of 1 week duration. The best-corrected visual acuity, when she attended this day, was 20/500 (OD) and 20/60 (OS). Fundus revealed pigment deposition in the macula in OD and a large pigment epithelial detachment (PED) in OS with drusen in both eyes, suggesting coexisting age macular degeneration (AMD) and MacTel (stage 4 OD; stage 2 OS) bilaterally. Multimodal imaging with spectral-domain optical coherence tomography showed drusen, a large trapezoid PED with central apical disruption, outer retinal hyperreflective material, intraretinal fluid, and inner retinal cavitation. Indocyanine green angiography revealed "hotspot" at center of the PED with hairpin-loop vessels. Optical coherence tomography angiography demonstrated network at apex of the PED. These features confirmed a diagnosis of type-3 MNV (classical retinal angiomatous proliferation [RAP] lesion) in OS along with features of AMD and MacTel. There was resolution of intraretinal fluid and reduction in height of PED following three loading doses of intravitreal ranibizumab in OS. Although type-3 neovascularization has been described in MacTel, to the best of our knowledge, this is the first documentation of classical RAP features of MNV with all described multimodal imaging features. The type-3 neovascularization typically described in association with MacTel is retinal-retinal, retinal-subretinal, and retinochoroidal anastomosis (RCA). Although RAP is also associated with RCA, the features seen in our case, i.e., triad of erosion at the roof of PED, inverted flap in the PED, and hotspot in the center of PED, have not been documented in association with MacTel.
PubMed: 37602186
DOI: 10.4103/ojo.ojo_15_22 -
Cureus Jul 2023Background Age-related macular degeneration (AMD), diabetic retinopathy (DR), drusen, choroidal neovascularization (CNV), and diabetic macular edema (DME) are...
Background Age-related macular degeneration (AMD), diabetic retinopathy (DR), drusen, choroidal neovascularization (CNV), and diabetic macular edema (DME) are significant causes of visual impairment globally. Optical coherence tomography (OCT) imaging has emerged as a valuable diagnostic tool for these ocular conditions. However, subjective interpretation and inter-observer variability highlight the need for standardized diagnostic approaches. Methods This study aimed to develop a robust deep learning model using artificial intelligence (AI) techniques for the automated detection of drusen, CNV, and DME in OCT images. A diverse dataset of 1,528 OCT images from Kaggle.com was used for model training. The performance metrics, including precision, recall, sensitivity, specificity, F1 score, and overall accuracy, were assessed to evaluate the model's effectiveness. Results The developed model achieved high precision (0.99), recall (0.962), sensitivity (0.985), specificity (0.987), F1 score (0.971), and overall accuracy (0.987) in classifying diseased and healthy OCT images. These results demonstrate the efficacy and efficiency of the model in distinguishing between retinal pathologies. Conclusion The study concludes that the developed deep learning model using AI techniques is highly effective in the automated detection of drusen, CNV, and DME in OCT images. Further validation studies and research efforts are necessary to evaluate the generalizability and integration of the model into clinical practice. Collaboration between clinicians, policymakers, and researchers is essential for advancing diagnostic tools and management strategies for AMD and DR. Integrating this technology into clinical workflows can positively impact patient care, particularly in settings with limited access to ophthalmologists. Future research should focus on collecting independent datasets, addressing potential biases, and assessing real-world effectiveness. Overall, the use of machine learning algorithms in conjunction with OCT imaging holds great potential for improving the detection and management of drusen, CNV, and DME, leading to enhanced patient outcomes and vision preservation.
PubMed: 37565126
DOI: 10.7759/cureus.41615 -
Frontiers in Medicine 2023The aim of this study is to apply deep learning techniques for the development and validation of a system that categorizes various phases of dry age-related macular...
PURPOSE
The aim of this study is to apply deep learning techniques for the development and validation of a system that categorizes various phases of dry age-related macular degeneration (AMD), including nascent geographic atrophy (nGA), through the analysis of optical coherence tomography (OCT) images.
METHODS
A total of 3,401 OCT macular images obtained from 338 patients admitted to Shenyang Aier Eye Hospital in 2019-2021 were collected for the development of the classification model. We adopted a convolutional neural network (CNN) model and introduced hierarchical structure along with image enhancement techniques to train a two-step CNN model to detect and classify normal and three phases of dry AMD: atrophy-associated drusen regression, nGA, and geographic atrophy (GA). Five-fold cross-validation was used to evaluate the performance of the multi-label classification model.
RESULTS
Experimental results obtained from five-fold cross-validation with different dry AMD classification models show that the proposed two-step hierarchical model with image enhancement achieves the best classification performance, with a f1-score of 91.32% and a kappa coefficients of 96.09% compared to the state-of-the-art models. The results obtained from the ablation study demonstrate that the proposed method not only improves accuracy across all categories in comparison to a traditional flat CNN model, but also substantially enhances the classification performance of nGA, with an improvement from 66.79 to 81.65%.
CONCLUSION
This study introduces a novel two-step hierarchical deep learning approach in categorizing dry AMD progression phases, and demonstrates its efficacy. The high classification performance suggests its potential for guiding individualized treatment plans for patients with macular degeneration.
PubMed: 37547613
DOI: 10.3389/fmed.2023.1221453