PMID- 24569576
OWN - NLM
STAT- MEDLINE
DCOM- 20140520
LR  - 20211021
IS  - 1552-5783 (Electronic)
IS  - 0146-0404 (Print)
IS  - 0146-0404 (Linking)
VI  - 55
IP  - 4
DP  - 2014 Apr 11
TI  - Quantifying disrupted outer retinal-subretinal layer in SD-OCT images in 
      choroidal neovascularization.
PG  - 2329-35
LID - 10.1167/iovs.13-13048 [doi]
AB  - PURPOSE: We reported a fully automated method to identify and quantify the 
      thickness of the outer retinal-subretinal (ORSR) layer from clinical 
      spectral-domain optical coherence tomography (SD-OCT) scans of choroidal 
      neovascularization (CNV) due to exudative age-related macular degeneration 
      (eAMD). METHODS: A total of 23 subjects with CNV met eligibility. Volumetric 
      SD-OCT scans of 23 eyes were obtained (Zeiss Cirrus, 200 x 200 x 1024 voxels). In 
      a subset of eyes, scans were repeated. The OCT volumes were analyzed using our 
      standard parameters and using a 3-dimensional (3D) graph-search approach with an 
      adaptive cost function. A retinal specialist graded the segmentation as generally 
      accurate, local segmentation inaccuracies, or failure. Reproducibility on repeat 
      scans was analyzed using root mean square coefficient of variation (RMS CV) of 
      the average ORSR thickness. RESULTS: Using a standard segmentation approach, 1/23 
      OCT segmentations was graded generally accurate and 22/23 were failure(s). With 
      the adaptive method 21/23 segmentations were graded generally accurate; 2/23 were 
      local segmentation inaccuracies and none was a failure. The intermethod quality 
      of segmentation was significantly different (P << 0.001). The average ORSR 
      thickness measured on CNV patients (78.0 mum; 95% confidence interval [CI], 
      72.5-83.4 mum) is significantly larger (P << 0.001) than normal average ORSR layer 
      thickness (51.5 +/- 3.3 mum). The RMS CV was 8.1%. CONCLUSIONS: We have developed a 
      fully automated 3D method for segmenting the ORSR layer in SD-OCT of patients 
      with CNV from eAMD. Our method can quantify the ORSR layer thickness in the 
      presence of fluid, which has the potential to augment management accuracy and 
      efficiency of anti-VEGF treatment.
FAU - Zhang, Li
AU  - Zhang L
AD  - Department of Electrical and Computer Engineering, University of Iowa, Iowa City, 
      Iowa, United States.
FAU - Sonka, Milan
AU  - Sonka M
FAU - Folk, James C
AU  - Folk JC
FAU - Russell, Stephen R
AU  - Russell SR
FAU - Abramoff, Michael D
AU  - Abramoff MD
LA  - eng
GR  - R01 EY019112/EY/NEI NIH HHS/United States
GR  - R01 EY018853/EY/NEI NIH HHS/United States
GR  - R01 EY017066/EY/NEI NIH HHS/United States
GR  - R01-EB004640/EB/NIBIB NIH HHS/United States
GR  - R01-EY018853/EY/NEI NIH HHS/United States
GR  - R01-EY017066/EY/NEI NIH HHS/United States
GR  - R01 EB004640/EB/NIBIB NIH HHS/United States
PT  - Journal Article
PT  - Research Support, N.I.H., Extramural
DEP - 20140411
PL  - United States
TA  - Invest Ophthalmol Vis Sci
JT  - Investigative ophthalmology & visual science
JID - 7703701
SB  - IM
CIN - Invest Ophthalmol Vis Sci. 2014 Apr;55(4):2336. PMID: 24729551
MH  - Aged
MH  - Aged, 80 and over
MH  - Choroidal Neovascularization/complications/*diagnosis
MH  - Female
MH  - Humans
MH  - Imaging, Three-Dimensional
MH  - Macular Degeneration/*diagnosis/etiology
MH  - Male
MH  - Reproducibility of Results
MH  - Retinal Photoreceptor Cell Outer Segment/*pathology
MH  - Tomography, Optical Coherence/*methods
PMC - PMC3985574
OTO - NOTNLM
OT  - AMD
OT  - OCT
OT  - choroidal neovascularization
OT  - imaging
OT  - retina
EDAT- 2014/02/27 06:00
MHDA- 2014/05/21 06:00
PMCR- 2014/10/01
CRDT- 2014/02/27 06:00
PHST- 2014/02/27 06:00 [entrez]
PHST- 2014/02/27 06:00 [pubmed]
PHST- 2014/05/21 06:00 [medline]
PHST- 2014/10/01 00:00 [pmc-release]
AID - iovs.13-13048 [pii]
AID - 10.1167/iovs.13-13048 [doi]
PST - epublish
SO  - Invest Ophthalmol Vis Sci. 2014 Apr 11;55(4):2329-35. doi: 10.1167/iovs.13-13048.