Abstract
Purpose :
This study analyzes the disease characteristics of choroideremia (CHM) across several imaging modalities including near-infrared autofluoresence (NIR-AF) images acquired from choroideremia patients and CHM carriers. Our aim was to better understand the degenerative process and changes in the retina.
Methods :
A cross-sectional analysis of retinal imaging data was performed on patients diagnosed with CHM (n=10) along with heterozygous female carriers (n=5). Disease-causing mutations in REP1 were confirmed in all subjects by direct sequencing. Principal outcome measures included near-infrared (787-nm excitation, NIR-AF) and short wavelength (488-nm excitation, SW-AF) autofluorescence images that were acquired on a confocal scanning laser ophthalmoloscope. In addition, macula-centered volume spectral domain-optical coherence tomography (SD-OCT) scans were analyzed.
Results :
The CHM probands exhibited characteristic widespread chorioretinal degeneration with residual islands of relatively preserved retina and visual function. Islands that were homogenously hyperautofluorescent on SW-AF were also visibly autofluorescent on corresponding NIR-AF images (Group 1 phenotype, 8/20 eyes); however islands that exhibited a granular, reduced autofluorescent appearance on SW-AF were less discernable on NIR-AF (Group 2 phenotype, 12/20 eyes).
Heterozygous CHM carriers exhibited diffuse patches of RPE atrophy on fundoscopy which corresponded to hypoautofluorescent patches on NIR-AF. Corresponding atrophic patches on SW-AF images were less pronounced. Hyperautofluorescent foci were also observed on NIR-AF imaging.
Conclusions :
The preserved retinal islands in CHM patients can present differently in NIR-AF versus SW-AF images. Ablation of the NIR-AF signal in the presence of SW-AF signal could reveal the extent of RPE layer degeneration and loss of melanin relative to photoreceptors. In CHM carriers the atrophic areas were usually more pronounced on NIR-AF than SW-AF imaging. NIR-AF could be a useful imaging modality in disease assessment.
This is an abstract that was submitted for the 2018 ARVO Annual Meeting, held in Honolulu, Hawaii, April 29 - May 3, 2018.