The Influence of Cataract on Fluorescence Lifetime Imaging Ophthalmoscopy (FLIO)

Abstract

Purpose To investigate the influence of lens opacifications on fluorescence lifetime imaging ophthalmoscopy (FLIO). Methods Forty-seven eyes of 45 patients were included. Mean fluorescence lifetimes ( Tm ) were recorded with a fluorescence lifetime imaging ophthalmoscope in a short spectral channel (SSC) and a long spectral channel (LSC). Retinal and lens autofluorescence lifetimes were measured in subjects before and after cataract surgery. Lens opacification was graded using the Lens Opacities Classification System III (LOCS III) classification. Results The retinal Tm decreased significantly after cataract surgery in both spectral channels (SSC: –53%, P < 0.0001; LSC: –26%, P = 0.0041). The lens Tm differed significantly between the crystalline and the artificial lens in both spectral channels ( P < 0.0001). The “nuclear opacity” and “nuclear color” score of the LOCS III classification correlated significantly with the mean Tm difference in both spectral channels ( P < 0.0001). Conclusions Lens opacification results in significantly longer retinal Tm . Therefore the lens status has to be considered when performing cross-sectional fluorescence lifetime analysis. Cataract-formation and cataract-surgery needs to be considered when conducting longitudinal studies. Grading of nuclear opacity following the LOCS III classification provides an approximate conversion formula for the mean change of lifetimes, which can be helpful in the interpretation of data in patients with lens opacities. Translational Relevance FLIO is significantly influenced by lens opacities. Using a lens opacity grading scheme and measuring fluorescence lifetimes before and after cataract surgery, an approximative conversion formula can be calculated, which enables the comparison of lifetimes after cataract surgery or over the course of time.

Fluorescence Lifetime Imaging Ophthalmoscopy as Predictor of Long-Term Functional Outcome in Macula-Off Rhegmatogenous Retinal Detachment

“…The technique of in vivo fundus autofluorescence lifetime imaging of the retina was initially introduced by Schweitzer et al 23 Previous FLIO studies have focused on describing different disease-specific fluorescence lifetime patterns. 13 , 14 , 16 , 18 , 19 …”

“…The technique of in vivo fundus autofluorescence lifetime imaging of the retina was initially introduced by Schweitzer et al 23 Previous FLIO studies have focused on describing different disease-specific fluorescence lifetime patterns. 13,14,16,18,19 In healthy eyes, FLIO has been shown to display a reproducible specific pattern, in which short fluorescence lifetimes are found within the macula and proposedly emitted by components of the macular pigment such as xanthophyll whereas long fluorescence lifetimes are identified at the optic nerve head as a result of connective tissue. Intermediate lifetimes are displayed by the retina, presumably influenced by lipofuscin.…”

“…Phakic patients were not included to ensure comparability of data. 14 Data were collected on the eye after successful retinal detachment surgery (study eye) and on the healthy fellow eye, which was also pseudophakic and free of any retinal disease. Presumptive duration of retinal detachment was documented before study entry.…”

Imaging Artifacts in Fluorescence Lifetime Imaging Ophthalmoscopy

“…The influence of lens opacification is currently investigated in a separate study that incorporates a standardized classification system for cataract. 32 Considering the influence of the crystalline lens, we suggest to assess the lens status (e.g., clear lens, slight/advanced lens opacifications, and pseudophakic) for every FLIO measurement. There are current attempts for algorithms to correct for possible influence of the natural lens on retinal FLT, especially in subjects with significant lens opacifications.…”

Artificial Intelligence in Fluorescence Lifetime Imaging Ophthalmoscopy (FLIO) Data Analysis—Toward Retinal Metabolic Diagnostics

“…While the studies mentioned above were able to access a sufficiently large datasets for the use of machine learning, one big problem in the clinical FLIO studies is the relatively low sample sizes for machine learning. There are many studies with less than 100 subjects [18][19][20][21], and also a few studies with less than 20 subjects per study group [7,22,23]. Therefore, a machine learning technique that might be able to also analyze small datasets would be desirable.…”