Alex D Pechauer1, Yali Jia1, Liang Liu1, Simon S Gao1, Chunhui Jiang2, David Huang1. 1. Casey Eye Institute Oregon Health & Science University, Portland, Oregon, United States. 2. Department of Ophthalmology, Eye and ENT Hospital, Fudan University, Shanghai, People's Republic of China.
Abstract
PURPOSE: To measure the change in peripapillary retinal blood flow in response to hyperoxia by using optical coherence tomography (OCT) angiography. METHODS: One eye of each healthy human participants (six) was scanned with a commercial high-speed (70 kHz) spectral OCT. Scans were captured twice after 10-minute exposures to normal breathing (baseline) and hyperoxia. Blood flow was detected by the split-spectrum amplitude-decorrelation angiography (SSADA) algorithm. Peripapillary retinal blood flow index and vessel density were calculated from en face maximum projections of the retinal layers. The experiment was performed on 2 separate days for each participant. Coefficient of variation (CV) was used to measure within-day repeatability and between-day reproducibility. Paired t-tests were used to compare means of baseline and hyperoxic peripapillary retinal blood flow. RESULTS: A decrease of 8.87% ± 3.09% (mean ± standard deviation) in flow index and 2.61% ± 1.50% in vessel density was observed under hyperoxia. The within-day repeatability CV of baseline measurements was 5.75% for flow index and 1.67% for vessel density. The between-day reproducibility CV for baseline flow index and vessel density was 11.1% and 1.14%, respectively. The between-day reproducibility of the hyperoxic response was 3.71% and 1.67% for flow index and vessel density, respectively. CONCLUSIONS: Optical coherence tomography angiography with SSADA was able to detect a decrease in peripapillary retinal blood flow in response to hyperoxia. The response was larger than the variability of baseline measurements. The magnitude of an individual's hyperoxic response was highly variable between days. Thus, reliable assessment may require averaging multiple measurements.
PURPOSE: To measure the change in peripapillary retinal blood flow in response to hyperoxia by using optical coherence tomography (OCT) angiography. METHODS: One eye of each healthy humanparticipants (six) was scanned with a commercial high-speed (70 kHz) spectral OCT. Scans were captured twice after 10-minute exposures to normal breathing (baseline) and hyperoxia. Blood flow was detected by the split-spectrum amplitude-decorrelation angiography (SSADA) algorithm. Peripapillary retinal blood flow index and vessel density were calculated from en face maximum projections of the retinal layers. The experiment was performed on 2 separate days for each participant. Coefficient of variation (CV) was used to measure within-day repeatability and between-day reproducibility. Paired t-tests were used to compare means of baseline and hyperoxic peripapillary retinal blood flow. RESULTS: A decrease of 8.87% ± 3.09% (mean ± standard deviation) in flow index and 2.61% ± 1.50% in vessel density was observed under hyperoxia. The within-day repeatability CV of baseline measurements was 5.75% for flow index and 1.67% for vessel density. The between-day reproducibility CV for baseline flow index and vessel density was 11.1% and 1.14%, respectively. The between-day reproducibility of the hyperoxic response was 3.71% and 1.67% for flow index and vessel density, respectively. CONCLUSIONS: Optical coherence tomography angiography with SSADA was able to detect a decrease in peripapillary retinal blood flow in response to hyperoxia. The response was larger than the variability of baseline measurements. The magnitude of an individual's hyperoxic response was highly variable between days. Thus, reliable assessment may require averaging multiple measurements.
Authors: Yali Jia; Eric Wei; Xiaogang Wang; Xinbo Zhang; John C Morrison; Mansi Parikh; Lori H Lombardi; Devin M Gattey; Rebecca L Armour; Beth Edmunds; Martin F Kraus; James G Fujimoto; David Huang Journal: Ophthalmology Date: 2014-03-12 Impact factor: 12.079
Authors: Yali Jia; John C Morrison; Jason Tokayer; Ou Tan; Lorinna Lombardi; Bernhard Baumann; Chen D Lu; Woojhon Choi; James G Fujimoto; David Huang Journal: Biomed Opt Express Date: 2012-11-07 Impact factor: 3.732
Authors: Miao Zhang; Jie Wang; Alex D Pechauer; Thomas S Hwang; Simon S Gao; Liang Liu; Li Liu; Steven T Bailey; David J Wilson; David Huang; Yali Jia Journal: Biomed Opt Express Date: 2015-11-02 Impact factor: 3.732
Authors: Johnny P Su; Rahul Chandwani; Simon S Gao; Alex D Pechauer; Miao Zhang; Jie Wang; Yali Jia; David Huang; Gangjun Liu Journal: J Biomed Opt Date: 2016-08-01 Impact factor: 3.170
Authors: Elena Ávila-Marrón; John P Liscombe-Sepúlveda; Laura Manfreda-Dominguez; Prudencia Rochina-Pérez; Antonio Duch-Samper Journal: Int Ophthalmol Date: 2019-03-09 Impact factor: 2.031