scholarly journals Glaucoma Progression Detection by Retinal Nerve Fiber Layer Measurement Using Scanning Laser Polarimetry: Event and Trend Analysis

2012 ◽  
Vol 26 (3) ◽  
pp. 174 ◽  
Author(s):  
Byung Gil Moon ◽  
Kyung Rim Sung ◽  
Jung Woo Cho ◽  
Sung Yong Kang ◽  
Sung-Cheol Yun ◽  
...  
2015 ◽  
Vol 2015 ◽  
pp. 1-6
Author(s):  
Mirian Ara ◽  
Antonio Ferreras ◽  
Ana B. Pajarin ◽  
Pilar Calvo ◽  
Michele Figus ◽  
...  

Objective. To assess the intrasession repeatability and intersession reproducibility of peripapillary retinal nerve fiber layer (RNFL) thickness parameters measured by scanning laser polarimetry (SLP) with enhanced corneal compensation (ECC) in healthy and glaucomatous eyes.Methods. One randomly selected eye of 82 healthy individuals and 60 glaucoma subjects was evaluated. Three scans were acquired during the first visit to evaluate intravisit repeatability. A different operator obtained two additional scans within 2 months after the first session to determine intervisit reproducibility. The intraclass correlation coefficient (ICC), coefficient of variation (COV), and test-retest variability (TRT) were calculated for all SLP parameters in both groups.Results. ICCs ranged from 0.920 to 0.982 for intravisit measurements and from 0.910 to 0.978 for intervisit measurements. The temporal-superior-nasal-inferior-temporal (TSNIT) average was the highest (0.967 and 0.946) in normal eyes, while nerve fiber indicator (NFI; 0.982) and inferior average (0.978) yielded the best ICC in glaucomatous eyes for intravisit and intervisit measurements, respectively. All COVs were under 10% in both groups, except NFI. TSNIT average had the lowest COV (2.43%) in either type of measurement. Intervisit TRT ranged from 6.48 to 12.84.Conclusions. The reproducibility of peripapillary RNFL measurements obtained with SLP-ECC was excellent, indicating that SLP-ECC is sufficiently accurate for monitoring glaucoma progression.


1998 ◽  
Author(s):  
Slawomir Janiec ◽  
Marek Rzendkowski ◽  
Stanislawa Gierek-Ciaciura ◽  
Monika Szymkowiak ◽  
Barbara Momot-Kawalska

Sign in / Sign up

Export Citation Format

Share Document