PMID- 21123769
OWN - NLM
STAT- MEDLINE
DCOM- 20110113
LR  - 20220310
IS  - 1552-5783 (Electronic)
IS  - 0146-0404 (Linking)
VI  - 51
IP  - 12
DP  - 2010 Dec
TI  - Performance of drusen detection by spectral-domain optical coherence tomography.
PG  - 6715-21
LID - 10.1167/iovs.10-5288 [doi]
AB  - PURPOSE: To evaluate the performance of automated analyses integrated in three 
      spectral-domain optical coherence tomography (SD-OCT) devices to identify drusen 
      in eyes with early (i.e., nonatrophic and nonneovascular) age-related macular 
      degeneration (AMD). METHODS: Twelve eyes of 12 AMD patients, classified as AREDS 
      2 and 3 and having a mean count of 113 drusen were examined with three clinical 
      SD-OCT devices (Cirrus [Carl Zeiss Meditec, Dublin CA], 3DOCT-1000 [Topcon, 
      Tokyo, Japan], and Spectralis [Heidelberg Engineering, GmbH, Heidelberg, 
      Germany]) and five different scan patterns. After standard automated segmentation 
      of the RPE was performed, every druse in each B-scan was identified and graded by 
      two independent expert graders. Errors in the segmentation performance were 
      classified as negligible, moderate, or severe. Correlations were based on the 
      diameter and height of the druse and its automated segmentation. The overall 
      drusen pattern identified by experts' detailed delineation was plotted with a 
      custom-made computer program to compare automated to manual identification 
      outcomes. RESULTS: A total of 1356 drusen were analyzed. The automated 
      segmentation of the retinal pigment epithelium (RPE) by Cirrus made significantly 
      fewer errors in detecting drusen than did the 3DOCT-1000 (P < 0.001). The Cirrus 
      200 x 200 scan pattern detected 30% of the drusen with negligible errors. 
      Spectralis did not offer a true RPE segmentation. The drusen counts by expert 
      graders were significantly higher in the scans than in the standard fundus 
      photographs (P < 0.05). CONCLUSIONS: SD-OCT imaging proved an excellent 
      performance in visualizing drusen-related RPE disease. However, the available 
      automated segmentation algorithms showed distinct limitations to reliable 
      identification of the amount of drusen, particularly smaller drusen, and the 
      actual size.
FAU - Schlanitz, Ferdinand G
AU  - Schlanitz FG
AD  - Department of Ophthalmology, Medical University of Vienna, Vienna, Austria.
FAU - Ahlers, Christian
AU  - Ahlers C
FAU - Sacu, Stefan
AU  - Sacu S
FAU - Schutze, Christopher
AU  - Schutze C
FAU - Rodriguez, Marcos
AU  - Rodriguez M
FAU - Schriefl, Sabine
AU  - Schriefl S
FAU - Golbaz, Isabelle
AU  - Golbaz I
FAU - Spalek, Tobias
AU  - Spalek T
FAU - Stock, Geraldine
AU  - Stock G
FAU - Schmidt-Erfurth, Ursula
AU  - Schmidt-Erfurth U
LA  - eng
PT  - Journal Article
PL  - United States
TA  - Invest Ophthalmol Vis Sci
JT  - Investigative ophthalmology & visual science
JID - 7703701
SB  - IM
MH  - Aged
MH  - Aged, 80 and over
MH  - *Diagnostic Techniques, Ophthalmological
MH  - Female
MH  - Humans
MH  - Macular Degeneration/*diagnosis
MH  - Male
MH  - Middle Aged
MH  - Retinal Drusen/*diagnosis
MH  - Retinal Pigment Epithelium/pathology
MH  - Tomography, Optical Coherence/*methods
EDAT- 2010/12/03 06:00
MHDA- 2011/01/14 06:00
CRDT- 2010/12/03 06:00
PHST- 2010/12/03 06:00 [entrez]
PHST- 2010/12/03 06:00 [pubmed]
PHST- 2011/01/14 06:00 [medline]
AID - 51/12/6715 [pii]
AID - 10.1167/iovs.10-5288 [doi]
PST - ppublish
SO  - Invest Ophthalmol Vis Sci. 2010 Dec;51(12):6715-21. doi: 10.1167/iovs.10-5288.