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Aushim Kokroo, Alauddin Bhuiyan, Akter Hussain, Rao Kotagiri, Meleha Ahmad, Theodore Smith; Validation of an Automated Software for Choroidal Thickness (CTh) Measurement. Invest. Ophthalmol. Vis. Sci. 2016;57(12):5954.
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© ARVO (1962-2015); The Authors (2016-present)
The growing interest in choroidal pathology as a biomarker for systemic and retinal diseases has increased the need for automated CTh measurement. Here, we assess the accuracy of such an algorithm applied to Enhanced Depth Imaging Spectral Domain Optical Coherence Tomography (EDI SD-OCT) images.
Following B-scan cropping, the top boundary of Retinal Nerve Fiber Layer (RNFL) was detected by applying Canny edge detection, intensity profiling and Dijkstra’s shortest path algorithm; we approximately identified the Retinal Nerve Fiber Layer, Outer Nuclear Layer and Retinal Pigment Epithelium to make the search space smaller. We subsequently tracked the Bruch’s Membrane boundary (BMB) using the same approach. Using BMB as a reference, we identified the choroidal vessel boundaries through an active contour method, thereby identifying a potential choroidal region. Finally, the choroidal boundary was identified from the choroidal vessel demarcations, intensity and boundary gradient information. The software was run on foveal slice EDI SD-OCT images of 15 eyes from 14 patients, generating a continuous CTh measurement curve (Figure 1). Two masked graders also manually demarcated both choroidal boundaries using Adobe Photoshop, allowing automatic A-Scan CTh measurements across the manually graded B-scan. The accuracy of the CTh computed by our software was tested against CTh determined by expert graders using the Spearman rank correlation (ρ). We also computed the mean square error (MSE) between manually graded and automatically detected boundaries through direct pixel-by-pixel matching within the boundaries of the choroid.
Spearman rank correlations (ρ) of 0.735 and 0.729, respectively, were obtained between the two expert graders’ measurements and the automatically measured thicknesses (p<0.01 for both). The MSE for boundary matching between the automatic software and first grader was 0.113 pixels2 and for the second grader 0.079 pixels2.
Our novel automated system for CTh quantification demonstrated strong agreement with manual CTh measurement. In the future, this method can be used to rapidly quantify CTh in various ophthalmological and systemic diseases.
This is an abstract that was submitted for the 2016 ARVO Annual Meeting, held in Seattle, Wash., May 1-5, 2016.
Figure 1: Top, automated choroidal boundaries at foveal slice. Outer RPE (blue), outer choroid (red). Bottom, detailed choroidal thickness measurements (blue), range 245 to 285 microns
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