The Effect of Axial Length Elongation on Corneal Biomechanical Property

Background: To investigate the correlation between the corneal biomechanical parameter stress-strain index (SSI) and axial length (AL) in moderately elongated eye (MEE) and severely elongated eye (SEE).Methods: This study included 117 eyes from 117 participants. Among them, 59 (50.4%) had MEE (AL<26 mm) and 58 (49.6%) had SEE (AL≥26 mm). AL was measured using Lenstar LS-900, and central corneal thickness (CCT) and anterior chamber volume (ACV) were measured using Pentacam. SSI was measured via corneal visualisation Scheimpflug technology (Corvis ST). Kolmogorov-Smirnov test, Student’s t-test, and Pearson and partial correlation analyses were used for statistical analyses.Results: The mean (±SD) SSI was 1.08 ± 0.15 in the MEE group and 0.92 ± 0.13 in the SEE group (p < 0.01). SSI was positively correlated with age (MEE: r = 0.326, p < 0.05; SEE: r = 0.298, p < 0.05) in both groups; it was negatively correlated with AL (r = −0.476, p < 0.001) in the MEE group but not in the SEE group (p > 0.05). CCT was negatively correlated with AL (r = −0.289, p < 0.05) and ACV positively correlated with AL (r = 0.444, p < 0.001) in the MEE group. Neither CCT nor ACV was correlated with AL (p > 0.05) in the SEE group.Conclusion: Corneal biomechanical parameter SSI, which represents the stiffness of corneal tissue, was lower in the SEE group than in the MEE group. When analyzed separately, SSI was negatively correlated with AL in the MEE group, but not in the SEE group, which may provide insight into different ocular growth patterns between lower myopia and higher myopia.

Age distribution and associated factors of cornea biomechanical parameter stress-strain index in Chinese healthy population

Background To investigate the new cornea biomechanical parameter stress-strain index (SSI) in Chinese healthy people and the factors associated with SSI. Methods A total of 175 eyes from 175 participants were included in this study. Axial length was measured with the Lenstar LS-900. Pentacam measured curvature of the cornea and anterior chamber volume (ACV). Cornea biomechanical properties assessments were performed by corneal visualization Scheimpflug technology (Corvis ST). Student’s t-test, one-way ANOVA, partial least square linear regression (PLSLR) and linear mixed effects (LME) model were used in the statistical analysis. Results The mean (±SD) SSI was 1.14 ± 0.22 (range, 0.66–1.78) in all subjects and affected by age significantly after age of 35 (P < 0.05). In LME models, SSI was significantly associated with age (β = 0.526, P < 0.001), axial length (AL) (β = − 0.541, P < 0.001), intraocular pressure (IOP) (β = 0.326, P < 0.001) and steepest radius of anterior corneal curvature (RsF) (β = 0.229, P < 0.001) but not with ACV, biomechanical corrected intraocular pressure (bIOP), flattest radius of anterior corneal curvature (RfF) or central corneal thickness (CCT) (P > 0.05 for each). Conclusions SSI increased with age after the age of 35. In addition to age, SSI was positively correlated with RsF and IOP, while negatively correlated with AL.

Keratoconus Diagnosis: Validation of a Novel Parameter Set Derived from IOP-Matched Scenario

Purpose. Considering that intraocular pressure (IOP) is an important confounding factor in corneal biomechanical evaluation, the notion of matching IOP should be introduced to eliminate any potential bias. This study aimed to assess the capability of a novel parameter set (NPS) derived from IOP-matched scenario to diagnose keratoconus. Methods. Seventy samples (training set; 35 keratoconus and 35 normal corneas; pairwise matching for IOP) were used to determine NPS by forward logistic regression. A large validation dataset comprising 62 matching samples (31 keratoconus and 31 normal corneas) and 203 unmatching samples (112 keratoconus and 91 normal corneas) was used to evaluate its clinical significance. To further assess its diagnosis capability, NPS was compared with the other two prior biomechanical indexes. Results. NPS was comprised of three biomechanical parameters, namely, DA Ratio Max 1 mm (DRM1), the first applanation time (AT1), and an energy loading parameter (Eload). NPS was successfully applied to the validation dataset, with a higher accuracy of 96.8% and 95.6% in the IOP-matched and -unmatched scenarios, respectively. More surprisingly, accuracy of NPS was 95.5% in the combined validation, an improvement compared to the two prior biomechanical indexes. Conclusions. This is the first study taking IOP bias into consideration to determine a biomechanical parameter set. Our study shows that NPS indeed offers comparable performance in keratoconus diagnosis. Translational Relevance. Determining a parameter set after eliminating the influence from IOP is useful in revealing the essential differences between keratoconus and normal corneas and possibly facilitating further progress in keratoconus diagnosis.

Age Distribution and Associated Factors of Cornea Biomechanical Parameter Stress-Strain Index in Chinese Healthy Population

Background: To investigate the new cornea biomechanical parameter stress-strain index (SSI) in Chinese healthy people and the factors associated with SSI.Methods: A total of 175 eyes from 175 participants were included in this study. Axial length was measured with the Lenstar LS-900. Pentacam measured curvature of the cornea and anterior chamber volume (ACV). Cornea biomechanical properties assessments were performed by corneal visualization Scheimpflug technology (Corvis ST). Student’s t-test, one-way ANOVA, partial least square linear regression (PLSLR) and linear mixed effects (LME) model were used in the statistical analysis.Results: The mean (±SD) SSI was 1.14 ± 0.22 (range, 0.66–1.78) in all subjects and affected by age significantly after age of 35 (P < 0.05). In LME models, SSI was significantly associated with age (β=0.526, P<0.001), axial length (AL) (β=-0.541, P<0.001), intraocular pressure (IOP) (β=0.326, P<0.001) and steepest radius of anterior corneal curvature (RsF) (β=0.229, P<0.001) but not with ACV, biomechanical corrected intraocular pressure (bIOP), flattest radius of anterior corneal curvature (RfF) or central corneal thickness (CCT) (P>0.05 for each).Conclusions: SSI increased with age after the age of 35. In addition to age, SSI was positively correlated with RsF and IOP, while negatively correlated with AL.

Age Distribution and Associated Factors of Cornea Biomechanical Parameter Stress-Strain Index in Chinese Healthy Population

Background: To investigate the new cornea Biomechanical parameter stress-strain index (SSI) in Chinese healthy people and the factors associated with SSI. Methods: A total of 175 eyes from 175 participants were included in this study. Axial length was measured with the Lenstar LS-900. Pentacam measured curvature of the cornea and anterior chamber volume (ACV). Cornea biomechanical properties assessments were performed by corneal visualization Scheimpflug technology (Corvis ST). Student’s t-test, one-way ANOVA, partial least square linear regression (PLSLR) and linear mixed effects (LME) model were used in the statistical analysis. Results: The mean (±SD) SSI was 1.14 ± 0.22 (range, 0.66–1.78) in all subjects and affected by age significantly after age of 35 (P < 0.05). In LME models, SSI was significantly associated with age (β=0.526, P<0.001), axial length (AL) (β=-0.541, P<0.001), intraocular pressure (IOP) (β=0.326, P<0.001) and steepest radius of anterior corneal curvature (RsF) (β=0.229, P<0.001) but not with ACV, biomechanical corrected intraocular pressure (bIOP), flattest radius of anterior corneal curvature (RfF) or central corneal thickness (CCT) (P>0.05 for each). Conclusions: SSI increased with age after the age of 35. In addition to age, SSI was positively correlated with RsF and IOP, while negatively correlated with AL.

The Role of Corneal Biomechanics for the Evaluation of Ectasia Patients

Purpose: To review the role of corneal biomechanics for the clinical evaluation of patients with ectatic corneal diseases. Methods: A total of 1295 eyes were included for analysis in this study. The normal healthy group (group N) included one eye randomly selected from 736 patients with healthy corneas, the keratoconus group (group KC) included one eye randomly selected from 321 patients with keratoconus. The 113 nonoperated ectatic eyes from 125 patients with very asymmetric ectasia (group VAE-E), whose fellow eyes presented relatively normal topography (group VAE-NT), were also included. The parameters from corneal tomography and biomechanics were obtained using the Pentacam HR and Corvis ST (Oculus Optikgeräte GmbH, Wetzlar, Germany). The accuracies of the tested variables for distinguishing all cases (KC, VAE-E, and VAE-NT), for detecting clinical ectasia (KC + VAE-E) and for identifying abnormalities among the VAE-NT, were investigated. A comparison was performed considering the areas under the receiver operating characteristic curve (AUC; DeLong’s method). Results: Considering all cases (KC, VAE-E, and VAE-NT), the AUC of the tomographic-biomechanical parameter (TBI) was 0.992, which was statistically higher than all individual parameters (DeLong’s; p < 0.05): PRFI- Pentacam Random Forest Index (0.982), BAD-D- Belin -Ambrosio D value (0.959), CBI -corneal biomechanical index (0.91), and IS Abs- Inferior-superior value (0.91). The AUC of the TBI for detecting clinical ectasia (KC + VAE-E) was 0.999, and this was again statistically higher than all parameters (DeLong’s; p < 0.05): PRFI (0.996), BAD-D (0.995), CBI (0.949), and IS Abs (0.977). Considering the VAE-NT group, the AUC of the TBI was 0.966, which was also statistically higher than all parameters (DeLong’s; p < 0.05): PRFI (0.934), BAD- D (0.834), CBI (0.774), and IS Abs (0.677). Conclusions: Corneal biomechanical data enhances the evaluation of patients with corneal ectasia and meaningfully adds to the multimodal diagnostic armamentarium. The integration of biomechanical data and corneal tomography with artificial intelligence data augments the sensitivity and specificity for screening and enhancing early diagnosis. Besides, corneal biomechanics may be relevant for determining the prognosis and staging the disease.

Combining Genetic Algorithms and Extended Kalman Filter to Estimate Ankle’s Muscle-Tendon Parameters

This work proposes a set of simulation and experimental measurements to estimate muscle biomechanical parameter during human quiet standing. Understanding the mechanisms involved in postural stability is indispensable to improve the knowledge of how humans can regain balance against possible disturbances. Postural stability requires the ability to compensate the movement of the body’s center of gravity caused by external or internal perturbations. This paper describes the implementation of a hybrid parameter-estimation approach to infer the features of the human neuro-mechanical system during quiet standing and the recovery from a fall. The estimation techniques combines a genetic algorithm with the State-Augmented Extended Kalman Filter. These two algorithms running sequentially are utilized to estimate the musculo-skeletal parameters. This paper shows results of the approach when representing human standing as either a second-order or third order mechanical model. Experimental validation on a human subject is also presented.