研究目的
To evaluate a manual region-of-interest (ROI) approach for detecting progressive macular ganglion cell complex (GCC) changes on optical coherence tomography (OCT) imaging.
研究成果
Progressive glaucomatous macular GCC changes were optimally detected with a manual ROI approach. These findings suggest that an approach based on a qualitative evaluation of OCT imaging information and consideration of known patterns of damage can improve the detection of progressive glaucomatous macular damage.
研究不足
1. Eyes in the longitudinal cohort had a relatively short duration of follow-up (average of 1.7 6 0.6 years) and were evaluated over only two visits. 2. Short-term within-session estimates of variability were used rather than short-term between-session estimates. 3. It remains to be determined whether other definitions of automatically identified ROIs could improve the automatic ROI approach.
1:Experimental Design and Method Selection:
The study evaluated changes in the GCC thickness using a manual ROI approach (ROIM), global GCC thickness, and an automatic ROI approach (ROIA). Longitudinal signal-to-noise ratios (SNRs) were calculated for progressive changes detected by each method.
2:Sample Selection and Data Sources:
146 eyes with a clinical diagnosis of glaucoma or suspected glaucoma with macular OCT scans obtained at least 1 year apart were evaluated. Estimates of test–retest variability and age-related changes were obtained from 303 glaucoma and 394 healthy eyes, respectively.
3:List of Experimental Equipment and Materials:
Spectral-domain OCT device (3D OCT-2000; Topcon, Inc., Tokyo, Japan) and a customized program written in MATLAB (MathWorks Inc., Natick, MA) for manual co-registration of volume scans.
4:Experimental Procedures and Operational Workflow:
Changes in the GCC thickness were identified using ROIM, ROIA, and global GCC thickness methods. Longitudinal SNRs were calculated for each method.
5:Data Analysis Methods:
A random intercept model was used to determine the SD of the test–retest differences for a given ROI. The difference in the average longitudinal SNR between the methods was compared using a linear mixed model.
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