• DOI:10.1167/iovs.10-6846
• Corpus ID: 24839147

Performance of automated drusen detection by polarization-sensitive optical coherence tomography.

@article{Schlanitz2011PerformanceOA,
  title={Performance of automated drusen detection by polarization-sensitive optical coherence tomography.},
  author={Ferdinand Schlanitz and Bernhard Baumann and Tobias Spalek and Christopher Sch{\"u}tze and Christian Ahlers and Michael Pircher and Erich G{\"o}tzinger and Christoph K. Hitzenberger and Ursula Margarethe Schmidt-Erfurth},
  journal={Investigative ophthalmology \& visual science},
  year={2011},
  volume={52 7},
  pages={
          4571-9
        }
}

• F. Schlanitz, B. Baumann, +6 authors U. Schmidt-Erfurth
• Published 1 June 2011
• Medicine
• Investigative ophthalmology & visual science

PURPOSE
To estimate the potential of polarization-sensitive optical coherence tomography (PS-OCT) for quantitative assessment of drusen in patients with early age-related macular degeneration (AMD).

METHODS
Fifteen eyes from 13 patients presenting drusen consistent with Age-Related Eye Disease Study classifications (grades 2 and 3) were examined ophthalmoscopically, followed by fundus photography, autofluorescence imaging, and three-dimensional scanning using a PS-OCT. For the automated evaluation of drusen location, area, and volume, a novel segmentation algorithm was developed based on the polarization scrambling characteristics of the retinal pigment epithelium (RPE) and applied to each complete data set. Subsequently, the drusen in each individual B-scan were identified by two independent expert graders. Concordance between manual and automated segmentation results was analyzed. Errors in the automated segmentation performance were classified as nonsignificant, moderate, or severe. RESULTS. In all, 2355 individual drusen, with a mean of 157 drusen per eye, were analyzed. Of drusen seen in the individual B-scans, 91.4% were detected manually by both expert graders. The automated segmentation algorithm identified 96.5% of all drusen without significant error. The mean difference in manual and automated drusen area (mean, 4.65 mm(2)) was 0.150. The number of detected drusen was significantly higher with automated than that with manual segmentation. PS-OCT segmentation was generally superior to fundus photography (P < 0.001). Particularly in nondetected drusen, a large variability in drusen morphology was noted.

CONCLUSIONS
Automated drusen detection based on PS-OCT technology allows a fast and accurate determination of drusen location, number, and total area.