Correlation Between Corneal Biomechanical Indices and the Severity of Keratoconus

Koh, Shizuka; Inoue, Ryota; Ambrósio, Renato; Maeda, Naoyuki; Miki, Atsuya; Nishida, Kohji

doi:10.1097/ico.0000000000002129

Cited by 36 publications

(60 citation statements)

References 39 publications

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“…It was reported that the thinning of the corneal apex is a typical character of the keratoconus eye [ 38 ]. The current results reported that SP-A1 in keratoconus eyes was statistically positively related with TCT, which was consistent with previous studies [ 16 , 21 , 32 ]. Several researchers had proposed that the thinning of the cornea in keratoconus patients would decrease the biomechanical properties, which in turn resulted in the focal weakening of cornea, and the decrease of corneal properties might further thin the cornea [ 15 , 39 , 40 ].…”

Section: Discussionsupporting

confidence: 94%

“…Thus, a multicenter study should be conducted to explore the distribution of SP-A1 in different populations in the future. In addition, the current study found that the SP-A1 value in keratoconus eyes was lower than that in normal eyes, which was similar to other reports [ 3 , 13 , 17 , 21 ]. The differences in SP-A1 values indicated that keratoconus eyes had weaker corneal stiffness than normal eyes, which provide reference for exploring the etiology of keratoconus.…”

Section: Discussionsupporting

confidence: 92%

“…The study showed that the SP-A1 in Chinese normal eyes was lower than previous results reported by Fernandez et al [ 12 ], Sedaghat et al [ 17 ], and Qin et al [ 20 ], and higher than other studies shown in Supplementary Table 1 [ 3 , 11 , 13 , 15 , 16 , 18 , 21 – 32 ]. The SP-A1 value in keratoconus eyes of our study was lower than previous studies conducted by Sedaghat et al [ 33 ], Kataria et al [ 13 ], and Hashemi et al [ 9 ], and higher than other studies shown in Supplementary Table 1 [ 3 , 14 , 15 , 17 , 18 , 21 , 22 , 25 , 32 , 34 , 35 ]. This discrepancy might be attributed to the study population diversity, sample size discrepancy, and the inconsistent inclusion criteria of the study subjects.…”

Section: Discussioncontrasting

confidence: 57%

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Association between Corneal Stiffness Parameter at the First Applanation and Keratoconus Severity

Yang

Fan

et al. 2020

Journal of Ophthalmology

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Objective. The study aimed to evaluate the character of corneal stiffness parameter at the first applanation (SP-A1) in normal and keratoconus eyes and explore the association between SP-A1 and keratoconus severity indicators. Methods. A total of 351 normal and 351 keratoconus eyes were included in the current study. Keratoconus was diagnosed according to the corneal topography map and slit-lamp examination. The severity of keratoconus was classified to mild (steep keratometry (Ks) < 48D), moderate (48 ≤ Ks < 55D), and severe (Ks ≥ 55D). The SP-A1 was measured using the Corvis ST software. The correlation analyses and receiver operating characteristic (ROC) curve were performed in the current analysis. ResultsThe SP-A1 values of keratoconus were lower than that of normal eyes (72.11 (57.02, 83.08) mmHg/mm vs 110.89 (100.45, 122.47) mmHg/mm, P < 0.001 ). With the severity of keratoconus increasing, the SP-A1 decreased and the value of SP-A1 was 79.54 (70.30, 90.93) mmHg/mm, 65.11 (53.14, 77.46) mmHg/mm, and 47.59 (37.50, 62.14) mmHg/mm in mild, moderate, and severe keratoconus eyes, respectively ( P < 0.001 ). The negative association between SP-A1 and Ks was found in mild, moderate, and severe keratoconus eyes (r mild = -0.171, rmoderate = -0.317, rsevere = −0.288, all P < 0.05 ). A positive association between SP-A1 and the thinnest corneal thickness (TCT) was found in all eyes (rnormal = 0.687, rmild = 0.519, rmoderate = 0.488, rsevere = 0.382, all P < 0.05 ). SP-A1 was found to be statistically positively associated with intraocular pressure (IOP), biomechanical corrected IOP (bIOP), time from the initiation of air puff until the first applanation (A1T), corneal velocity at the second applanation (A2V), and negatively associated with deformation amplitude (DA), peak distance (PD), corneal velocity at the first applanation (A1V), time from the initiation of air puff until the second applanation (A2T), and DA Ratio Max [2 mm] both in normal and keratoconus eyes (all P < 0.05 ). The ROC analysis indicated that the AUC (95% CI) of SP-A1 was 0.952 (0.934–0.967) and 0.930 (0.904–0.951) in detecting keratoconus eyes and mild keratoconus eyes from normal eyes, respectively. Conclusions. The SP-A1 value decreased while the keratoconus severity increased. It was lower in keratoconus than that in normal eyes and could be helpful in identifying keratoconus eyes from normal eyes. Further researches would be warranted to expand the clinical utility of SP-A1.

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Section: Discussionsupporting

confidence: 94%

Section: Discussionsupporting

confidence: 92%

Section: Discussioncontrasting

confidence: 57%

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Association between Corneal Stiffness Parameter at the First Applanation and Keratoconus Severity

Yang

Fan

et al. 2020

Journal of Ophthalmology

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“…Koh et al have observed similar results for DAR2, IntInverseR and SPA1 based on anterior and posterior curvature as well as corneal thickness. Steeper corneas (anterior and posterior curvature) have been associated with higher DAR2, higher IntInverseR and lower SPA1 [ 40 ].…”

Section: Discussionmentioning

confidence: 99%

Development of a classification system based on corneal biomechanical properties using artificial intelligence predicting keratoconus severity

2021

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Background To investigate machine-learning (ML) algorithms to differentiate corneal biomechanical properties between different topographical stages of keratoconus (KC) by dynamic Scheimpflug tonometry (CST, Corvis ST, Oculus, Wetzlar, Germany). In the following, ML models were used to predict the severity in a training and validation dataset. Methods Three hundred and eighteen keratoconic and one hundred sixteen healthy eyes were included in this monocentric and cross-sectional pilot study. Dynamic corneal response (DCR) and corneal thickness related (pachymetric) parameters from CST were chosen by appropriated selection techniques to develop a ML algorithm. The stage of KC was determined by the topographical keratoconus classification system (TKC, Pentacam, Oculus). Patients who were classified as TKC 1, TKC 2 and TKC 3 were assigned to subgroup mild, moderate, and advanced KC. If patients were classified as TKC 1–2, TKC 2–3 or TKC 3–4, they were assigned to subgroups according to the normative range of further corneal indices (index of surface variance, keratoconus index and minimum radius). Patients classified as TKC 4 were not included in this study due to the limited amount of cases. Linear discriminant analysis (LDA) and random forest (RF) algorithms were used to develop the classification models. Data were divided into training (70% of cases) and validation (30% of cases) datasets. Results LDA model predicted healthy, mild, moderate, and advanced KC eyes with a sensitivity (Sn)/specificity (Sp) of 82%/97%, 73%/81%, 62%/83% and 68%/95% from a validation dataset, respectively. For the RF model, a Sn/Sp of 91%/94%, 80%/90%, 63%/87%, 72%/95% could be reached for predicting healthy, mild, moderate, and advanced KC eyes, respectively. The overall accuracy of LDA and RF was 71% and 78%, respectively. The accuracy for KC detection including all subgroups of KC severity was 93% in both models. Conclusion The RF model showed good accuracy in predicting healthy eyes and various stages of KC. The accuracy was superior with respect to the LDA model. The clinical importance of the models is that the standalone dynamic Scheimpflug tonometry is able to predict the severity of KC without having the keratometric data. Trial registration NCT04251143 at Clinicaltrials.gov, registered at 12 March 2018 (Retrospectively registered).

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“…Corneal focal biomechanical weakness is considered to play a major role during the pathological changes in KC [2][3][4][5][6][7]. Corneal visualization Scheimpflug technology (Corvis ST, Oculus Optikgeräte GmbH; Wetzlar, Germany) is commonly used to assess corneal biomechanics [8].…”

Section: Introductionmentioning

confidence: 99%

Relationship between corneal biomechanical parameters and corneal sublayer thickness measured by Corvis ST and UHR-OCT in keratoconus and normal eyes

Liu

et al. 2021

Eye and Vis

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Background To explore the relationship between corneal biomechanical parameters and corneal sublayer thickness using corneal visualization Scheimpflug technology (Corvis ST) and ultrahigh-resolution optical coherence tomography (UHR-OCT) in clinical and suspected keratoconus and normal eyes. Methods Cross-sectional prospective study. A total of 94 eyes of 70 participants were recruited. Twenty five eyes of 19 keratoconus patients, 52 eyes of 34 patients showing high risk of developing keratoconus according to the Belin/Ambrosio Enhanced Ectasia Display, and each eye of 17 normal subjects were enrolled. All participants underwent Corvis ST, Pentacam, and UHR-OCT examinations at the same time. Stiffness parameter A1 (SP-A1), deformation amplitude ratio (DA ratio), and other biomechanical parameters were recorded using Corvis ST. The vertical and horizontal thickness profiles of central 3 mm corneal epithelium, Bowman’s layer, and stroma as measured by the perpendicular distance between the neighboring interfaces were generated using UHR-OCT. The flat keratometry and steep keratometry were obtained using Pentacam. Analysis of correlation was applied to explore the association between variables. Results Most of the biomechanical parameters and corneal sublayer thickness profiles showed statistical differences among three groups. A statistically significant linear relationship was noted between SP-A1 and DA ratio in all three groups. SP-A1 was found to be positively correlated with epithelial and Bowman’s layer thickness in the keratoconus (KC) group, and with stromal thickness in all three groups. In the normal and suspected keratoconus (SKC) groups, only stromal thickness was included in the stepwise linear regression to predict SP-A1, whereas in the KC group, steep keratometry and Bowman’s layer thickness were included. Conclusions Significant and different correlations were noted between corneal stiffness and corneal sublayer thickness in different groups, indicating that corneal sublayers may play different roles in maintaining corneal biomechanical stability between keratoconus and normal eyes.

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Correlation Between Corneal Biomechanical Indices and the Severity of Keratoconus

Cited by 36 publications

References 39 publications

Association between Corneal Stiffness Parameter at the First Applanation and Keratoconus Severity

Association between Corneal Stiffness Parameter at the First Applanation and Keratoconus Severity

Development of a classification system based on corneal biomechanical properties using artificial intelligence predicting keratoconus severity

Relationship between corneal biomechanical parameters and corneal sublayer thickness measured by Corvis ST and UHR-OCT in keratoconus and normal eyes

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