Quantifying Retinal Microvascular Changes in Uveitis Using Spectral-Domain Optical Coherence Tomography Angiography.
OBJECTIVE
To quantify retinal capillary density and morphology in uveitis using spectral-domain optical coherence tomography angiography (SD-OCTA).


METHODS
Cross-sectional, observational study.


METHODS
Healthy and uveitic subjects were recruited from 2 tertiary care eye centers. Prototype SD-OCTA devices (Cirrus; Carl Zeiss Meditec, Inc, Dublin, California, USA) were used to generate 3 × 3-mm2OCTA images centered on the fovea. Subjects were placed into 3 groups based on the type of optical microangiography (OMAG) algorithm used for image processing (intensity and/or phase) and type of retinal segmentation (automatic or manual). A semi-automated method was used to calculate skeleton density (SD), vessel density (VD), fractal dimension (FD), and vessel diameter index (VDI). Retinal vasculature was assessed in the superficial retinal layer (SRL), deep retinal layer (DRL), and nonsegmented retinal layer (NS-RL). A generalized estimating equations model was used to analyze associations between the OCTA measures and disease status within each retinal layer. A P value < .05 was accepted as significant. Reproducibility and repeatability were assessed using the intraclass correlation coefficient (ICC).


RESULTS
The SD, VD, and FD of the parafoveal capillaries were lower in uveitic eyes compared with healthy eyes in all retinal segments. In addition, SD and VD were significantly lower in the DRL of subjects with uveitic macular edema. There was no correlation in any capillary parameters and anatomic classification of uveitis.


CONCLUSIONS
Quantitative analysis of parafoveal capillary density and morphology in uveitis demonstrates significantly lower capillary density and complexity. SD-OCTA algorithms are robust enough to detect these changes and can provide a novel diagnostic index of disease for uveitis subjects.
Department of Ophthalmology, USC Roski Eye Institute, Keck School of Medicine of the University of Southern California, Los Angeles, California.
Alice Y
AY
Kim
Department of Ophthalmology, USC Roski Eye Institute, Keck School of Medicine of the University of Southern California, Los Angeles, California.
Damien C
DC
Rodger
Department of Ophthalmology, USC Roski Eye Institute, Keck School of Medicine of the University of Southern California, Los Angeles, California.
Anoush
A
Shahidzadeh
Department of Bioengineering, University of Washington, Seattle, Washington; Department of Ophthalmology, University of Washington, Seattle, Washington.
Zhongdi
Z
Chu
Department of Ophthalmology, USC Roski Eye Institute, Keck School of Medicine of the University of Southern California, Los Angeles, California.
Nicole
N
Koulisis
Department of Ophthalmology, USC Roski Eye Institute, Keck School of Medicine of the University of Southern California, Los Angeles, California.
Bruce
B
Burkemper
Department of Ophthalmology, USC Roski Eye Institute, Keck School of Medicine of the University of Southern California, Los Angeles, California.
Xuejuan
X
Jiang
Department of Ophthalmology, University of Washington, Seattle, Washington.
Kathryn L
KL
Pepple
Department of Bioengineering, University of Washington, Seattle, Washington; Department of Ophthalmology, University of Washington, Seattle, Washington.
Ruikang K
RK
Wang
Department of Ophthalmology, USC Roski Eye Institute, Keck School of Medicine of the University of Southern California, Los Angeles, California.
Carmen A
CA
Puliafito
Department of Ophthalmology, USC Roski Eye Institute, Keck School of Medicine of the University of Southern California, Los Angeles, California.
Narsing A
NA
Rao
Department of Ophthalmology, USC Roski Eye Institute, Keck School of Medicine of the University of Southern California, Los Angeles, California. Electronic address: ahkashan@usc.edu.
Amir H
AH
Kashani
D000328:Adult; D000368:Aged; D000465:Algorithms; D003430:Cross-Sectional Studies; D005260:Female; D005451:Fluorescein Angiography / Q000379:methods*; D005654:Fundus Oculi; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008297:Male; D008833:Microcirculation; D055806:Microvessels / Q000000981:diagnostic imaging*; D008875:Middle Aged; D015203:Reproducibility of Results; D012171:Retinal Vessels / Q000000981:diagnostic imaging*; D012189:Retrospective Studies; D041623:Tomography, Optical Coherence / Q000379:methods*; D014605:Uveitis / Q000175:diagnosis* / Q000503:physiopathology; D055815:Young Adult