Subretinal Drusenoid Deposit Formation: Insights From Turing Patterns.

PURPOSE

The purpose of this study was to demonstrate that the organized formation of subretinal drusenoid deposits (SDDs) may be a Turing pattern.

METHODS

A Java-based computational model of an inferred reaction-diffusion system using paired partial differential equations was used to create topographic images. Reaction kinetics were varied to illustrate a spectrum of pattern development, which were then compared to dot-like, reticular, and confluent SDD patterns observed clinically.

RESULTS

A reaction-diffusion system using two agents, one an "activator" that increases its own production, and the other an "inhibitor" that decreases the activator's production, can create patterns that match the spectrum of topographic appearance of organized SDD. By varying a single parameter, the strength of the activator, the full spectrum of clinically observed SDD patterns can be generated. A new pattern, confluence with holes, is predicted and identified in one case example.

CONCLUSIONS

The formation of clinically significant SDD and its different patterns can be explained using Turing patterns obtained by simulating a two-component reaction-diffusion system.

TRANSLATIONAL RELEVANCE

This model may be able to guide future risk stratification for patients with SDD, and provide mechanistic insights into the cause of the disease.