Dataset Information

Growth Modeling for Quantitative, Spatially Resolved Geographic Atrophy Lesion Kinetics.

ABSTRACT:

Purpose

To demonstrate the applicability of a growth modeling framework for quantifying spatial variations in geographic atrophy (GA) lesion kinetics.

Methods

Thirty-eight eyes from 27 patients with GA secondary to age-related macular degeneration were imaged with a commercial swept source optical coherence tomography instrument at two visits separated by 1 year. Local GA growth rates were computed at 6-µm intervals along each lesion margin using a previously described growth model. Corresponding margin eccentricities, margin angles, and growth angles were also computed. The average GA growth rates conditioned on margin eccentricity, margin angle, growth angle, and fundus position were estimated via kernel regression.

Results

A total of 88,356 GA margin points were analyzed. The average GA growth rates exhibited a hill-shaped dependency on eccentricity, being highest in the 0.5 mm to 1.6 mm range and lower on either side of that range. Average growth rates were also found to be higher for growth trajectories oriented away from (smaller growth angle), rather than toward (larger growth angle), the foveal center. The dependency of average growth rate on margin angle was less pronounced, although lesion segments in the superior and nasal aspects tended to grow faster.

Conclusions

Our proposed growth modeling framework seems to be well-suited for generating accurate, spatially resolved GA growth rate atlases and should be confirmed on larger datasets.

Translational relevance

Our proposed growth modeling framework may enable more accurate measurements of spatial variations in GA growth rates.

SUBMITTER: Moult EM

PROVIDER: S-EPMC8237082 | biostudies-literature | 2021 Jun

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Growth Modeling for Quantitative, Spatially Resolved Geographic Atrophy Lesion Kinetics.

Moult Eric M EM Hwang Yunchan Y Shi Yingying Y Wang Liang L Chen Siyu S Waheed Nadia K NK Gregori Giovanni G Rosenfeld Philip J PJ Fujimoto James G JG

Translational vision science & technology 20210601 7

<h4>Purpose</h4>To demonstrate the applicability of a growth modeling framework for quantifying spatial variations in geographic atrophy (GA) lesion kinetics.<h4>Methods</h4>Thirty-eight eyes from 27 patients with GA secondary to age-related macular degeneration were imaged with a commercial swept source optical coherence tomography instrument at two visits separated by 1 year. Local GA growth rates were computed at 6-µm intervals along each lesion margin using a previously described growth mode ...[more]

PMID: 34156431

Similar Datasets

Project description:ImportanceAge-related macular degeneration (AMD) is a common threat to vision loss in individuals older than 50 years. While neovascular complications in AMD are treatable, there is currently no therapy for geographic atrophy secondary to AMD. Geographic atrophy lesion progression over time shows considerable interindividual variability, but little is known about prognostic factors.ObjectiveTo elucidate the contribution of common genetic variants to geographic atrophy lesion growth.Design, setting, and participantsThis pooled analysis combined 4 independent studies: the Fundus Autofluorescence Imaging in Age-Related Macular Degeneration (FAM) study, the Directional Spread in Geographic Atrophy (DSGA) study, the Age-Related Eye Disease Study (AREDS), and the Geographic Atrophy Treatment Evaluation (GATE) study. Each provided data for geographic atrophy lesion growth in specific designs. Patients with geographic atrophy secondary to AMD were recruited to these studies. Genotypes were retrieved through the database of Genotypes and Phenotypes (for AREDS) or generated at the Cologne Center for Genomics (for FAM, DSGA, and GATE).Main outcomesThe correlation between square root-transformed geographic atrophy growth rate and 7 596 219 genetic variants passing quality control was estimated using linear regression. The calculations were adjusted for known factors influencing geographic atrophy growth, such as the presence of bilateral geographic atrophy as well as the number of lesion spots and follow-up times.Main outcomes and measuresSlopes per allele, 95% CIs, and P values of genetic variants correlated with geographic atrophy lesion growth.ResultsA total of 935 patients (mean [SD] age, 74.7 [7.8] years; 547 female participants [59.0%]) were included. Two gene loci with conservative genome-wide significance were identified. Each minor allele of the genome-wide associated variants increased the geographic atrophy growth rate by a mean of about 15% or 0.05 mm per year. Gene prioritization within each locus suggests the protein arginine methyltransferase 6 gene (PRMT6; chromosome 1; slope, 0.046 [95% CI, 0.026-0.066]; P = 4.09 × 10-8) and the lanosterol synthase gene (LSS; chromosome 21; slope, 0.105 [95% CI, 0.068-0.143]; P = 4.07 × 10-7) as the most likely progression-associated genes.Conclusions and relevanceThese data provide further insight into the genetic architecture of geographic atrophy lesion growth. Geographic atrophy is a clinical outcome with a high medical need for effective therapy. The genes PRMT6 and LSS are promising candidates for future studies aimed at understanding functional aspects of geographic atrophy progression and also for designing novel and targeted treatment options.

Project description:PurposePrior versions of the Tool for Reduction and Assessment of Chemical and other environmental Impacts (TRACI) have recognized the need for spatial variability when characterizing eutrophication. However, the method's underlying environmental models had not been updated to reflect the latest science. This new research provides the ability to differentiate locations with a high level of detail within the USA and provides global values at the country level.MethodsIn previous research (Morelli et al. 2018), the authors reviewed a broad range of domain-specific models and life cycle assessment methods for characterization of eutrophication and ranked these by levels of importance to the field and readiness for further development. The current research is rooted in the decision outcome of Morelli et al. (2018) to separate freshwater and marine eutrophication to allow for the most tailored characterization of each category individually. The current research also assumes that freshwater systems are limited by phosphorus and marine systems are limited by nitrogen. Using a combination of spatial modeling methods for soil, air, and water, we calculate midpoint characterization factors for freshwater and marine eutrophication categories and evaluate the results through a US-based case application.Results and discussionMaps of the nutrient inventories, characterization factors, and overall impacts of the case application illustrate the spatial variation and patterns in the results. The importance of variation in geographic location is demonstrated using nutrient-based activity likelihood categories of agricultural (rural fertilizer), non-agricultural (urban fertilizer), and general (human waste processing). Proximity to large bodies of water, as well as individual hydraulic residence times, was shown to affect the comparative values of characterization factors across the USA.ConclusionsIn this paper, we have calculated and applied finely resolved freshwater and marine eutrophication characterization factors for the USA and country-level factors for the rest of the globe. Additional research is needed to provide similarly resolved characterization factors for the entire globe, which would require expansion of publicly available data and further development of applicable fate and transport models. Further scientific advances may also be considered as computing capabilities become more sophisticated and widely accessible.

Dataset Information

Growth Modeling for Quantitative, Spatially Resolved Geographic Atrophy Lesion Kinetics.

Purpose

Methods

Results

Conclusions

Translational relevance

Publications

Growth Modeling for Quantitative, Spatially Resolved Geographic Atrophy Lesion Kinetics.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets