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. 2023 Oct 6:11:1266940.
doi: 10.3389/fbioe.2023.1266940. eCollection 2023.

The application of corneal biomechanical interocular asymmetry for the diagnosis of keratoconus and subclinical keratoconus

Affiliations

The application of corneal biomechanical interocular asymmetry for the diagnosis of keratoconus and subclinical keratoconus

Ruilan Dong et al. Front Bioeng Biotechnol. .

Abstract

Purpose: To evaluate the interocular consistency of biomechanical properties in normal, keratoconus (KC) and subclinical keratoconus (SKC) populations and explore the application of interocular asymmetry values in KC and SKC diagnoses. Methods: This was a retrospective chart-review study of 331 ametropic subjects (control group) and 207 KC patients (KC group, including 94 SKC patients). Interocular consistency was evaluated using the intraclass correlation coefficient (ICC). Interocular asymmetry was compared between the control and KC groups and its correlation with disease severity was analyzed. Three logistic models were constructed using biomechanical monocular parameters and interocular asymmetry values. The diagnostic ability of interocular asymmetry values and the newly established models were evaluated using receiver operating characteristic curves and calibration curves. Net reclassification improvement (NRI) and integrated discrimination improvement (IDI) were also estimated. Results: The interocular consistency significantly decreased and the interocular asymmetry values increased in KC patients compared with those in control individuals. In addition, the interocular asymmetry values increased with respect to the severity of KC. The binocular assisted biomechanical index (BaBI) had an area under the curve (AUC) of 0.998 (97.8% sensitivity, 99.2% specificity; cutoff 0.401), which was statistically higher than that of the Corvis biomechanical index [CBI; AUC = 0.935, p < 0.001 (DeLong's test), 85.6% sensitivity]. The optimized cutoff of 0.163 provided an AUC of 0.996 for SKC with 97.8% sensitivity, which was higher than that of CBI [AUC = 0.925, p < 0.001 (DeLong's test), 82.8% sensitivity]. Conclusion: Biomechanical interocular asymmetry values can reduce the false-negative rate and improve the performance in KC and SKC diagnoses.

Keywords: artificial intelligence; corneal biomechanics; diagnostic model; interocular asymmetry; keratoconus; subclinical keratoconus.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

FIGURE 1
FIGURE 1
The process of dividing the datasets and the composition of each dataset. MBI, monocular biomechanical index; BBI, binocular biomechanical index; BaBI, binocular assisted biomechanical index.
FIGURE 2
FIGURE 2
Boxplots of interocular asymmetry values of (A) Δ HCDeflAmp, (B) Δ DAR1, (C) Δ SSI, (D) Δ A2V, (E) Δ IR and (F) Δ SP-A1 for the control and keratoconus with different KSS grading of the worse keratoconic eye. The asterisks show the result of the Kruskal–Wallis test (NS, not significant; *, significant on a p < 0.05 level; **, significant on a p < 0.01 level; ***, significant on a p < 0.001 level). KSS, keratoconus severity score; Δ HCDeflAmp, asymmetry of the deflection amplitude of the corneal apex at the highest concavity; Δ DAR1, asymmetry of the ratio between the central deformation and the average of the peripheral deformation determined at 1.00 mm; Δ SSI, asymmetry of the stress‒strain index; Δ A2V, asymmetry of the speed of the corneal apex at the second applanation; Δ IR, asymmetry of the integrated radius; Δ SP-A1, asymmetry of the stiffness parameter at the first applanation.
FIGURE 3
FIGURE 3
Receiver operating characteristic curves and area under the curve (AUC) of the newly established models and widely used monocular-based indices in (A) the training dataset, (B) the validation dataset and (C) the SKC subgroup. BBI, binocular biomechanical index; MBI, monocular biomechanical index; BaBI, binocular assisted biomechanical index; CBI, Corvis biomechanical index; TBI, tomographic and biomechanical index; PRFI, Pentacam random forest index.
FIGURE 4
FIGURE 4
Calibration curves of (A) BBI, (B) MBI and (C) BaBI in the training dataset. BBI, binocular biomechanical index; MBI, monocular biomechanical index; BaBI, binocular assisted biomechanical index.
FIGURE 5
FIGURE 5
Nomogram for predicting KC from controls using the binocular-assisted biomechanical index (BaBI). A1V, speed of the corneal apex at the first applanation; A2V, speed of the corneal apex at the second applanation; ARTh, Ambrósio relational thickness to the horizontal profile; IR, integrated radius; SP-A1, stiffness parameter at the first applanation; Δ DAR1, asymmetry of the ratio between the central deformation and the average of the peripheral deformation determined at 1.00 mm; Δ ARTh, asymmetry of the Ambrósio relational thickness to the horizontal profile; Δ IR, asymmetry of the integrated radius.

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