Abstract
Purpose :
To study AMD drusenoid deposits “L”, with regard to their density, structure volume and evolution with morphology-structural software to enhance drusenoid deposits “L” knowledge, evolving potential and etiopathogenesis
Methods :
124 eyes of 64 patients, 22 men,42 women, with AMD drusenoid deposits “L”, Lipid Type (soft Drusen, Drusenoid PED “L”). Deposits were evaluated by Autofluorescence, IR imaging, OCT, notably OCT en Face (Spectralis HRA-OCT, spectral domain OCT), and Morphology-Structural software (M-S software). ETDRS visual acuity(VA),complete ophthalmic examination with Fundus exam were added. M-S software let analyze drusenoid deposit volume and contours, 3D deposit reconstruction, display in 3D space, let drusenoid deposit contents analyze, discrimination, differentiation, let grading(volume and contours analyze),let measurements: density(grey levels of deposits), structure(structural measures, texture parameters), volume(in µm3), evaluation and characterization of those “L” type deposits. Evaluation, comparison for each eye, for each patient, between all studied patients, was done every 6 months, so evolution assessment of those drusenoid deposit parameters too. 5 years follow-up.
Results :
AMD Drusenoid Deposits “L” are: dark grey, optical empty, fatty, equal and the same in all cross-section(OCT/OCT enface). From M-S software, “L” have rather Low density, each density parameter having not only its own profile, curve modulation and up and down during evolution, but difference in between, and likeness between both eyes. Structural and Volume parameters have also their own profile and similarity between both eyes. Cycle evolution was seen for all parameters curve, specific for each curve, with also similarity between both eyes. So this allow better AMD Drusenoid Deposits “L” knowledge, physiopathology understanding, evolution assessment, evolving potential, particularly to atrophy.
Conclusions :
AMD Drusenoid deposits “L”, study and knowledge, especially regarding their contents, in particular through Morphology-Structural Software contribute to and improve AMD physiopathology, etiopathogenesis understanding and hypothesis formulations.
This is a 2021 ARVO Annual Meeting abstract.