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Updated: Jul 20, 2025
In vivo Structural Assessments of Ocular Disease in Rodent Models using Optical Coherence Tomography
Published on: July 24, 2020
Discrimination between keratoconus, forme fruste keratoconus, and normal eyes using a novel OCT-based tomographer
Alain Saad1, Guillaume Debellemanière, Pierre Zeboulon
1From the Department of Ophthalmology, Rothschild Foundation Hospital, Paris, France (Saad, Debellemanière, Zeboulon, Rizk, Rouger, Mazharian, Grise-Dulac, Panthier, Gatinel); CEROV-Center of Expertise and Research in Visual Optics, Paris, France (Saad, Debellemanière, Zeboulon, Rizk, Rouger, Mazharian, Grise-Dulac, Panthier, Gatinel).
Purpose:
To combine objective machine-derived corneal parameters obtained with new swept-source optical coherence tomography (SS-OCT) tomographer (Anterion) to differentiate between normal (N), keratoconus (KC) and forme fruste KC (FFKC).
Setting:
Laser Center, Hôpital Fondation Adolphe de Rothschild, Paris, France.
Design:
Retrospective study.
Methods:
281 eyes of 281 patients were included and divided into 3 groups: N (n = 156), FFKC (n = 43), and KC (n = 82). Eyes were included in each group based on objective evaluation using Nidek Corneal Navigator, and subjective evaluation by authors. The SS-OCT system provided anterior and posterior corneal surface and pachymetry derived variables. The training set was composed of 143 eyes (95 N, 43 FFKC). Discriminant analysis was used to determine the group of an observation based on a set of variables. The obtained formula was tested in the validation set composed of 61 N and 82 KC.
Results:
Among curvature parameters, the FFKC had significantly higher irregularity index at 3 mm and 5 mm, higher inferior-superior index, higher SteepK-OppositeK index and inferiorly decentered posterior steepest keratometry. Among thickness parameters: central pachymetry, thinnest pachymetry, percentage of thickness increase from center to periphery, and inferior decentration of the thinnest point were statistically different between groups. Combination of multiple variables into a discriminant function (F1) included 5 parameters and reached an area under the receiver operating characteristic curve (AUROC) of 0.95 (sensitivity = 75%, specificity = 98.5%) for detection of FFKC. F1 differentiates N from KC with AUROC = 0.99 (sensitivity = 99%, specificity = 99%).
Conclusions:
Combining anterior and posterior curvatures variables along with pachymetric data obtained from SS-OCT allowed automated detection of early KC and KC with very good accuracy (87% and 99.5% respectively).
