Biomechanics in Keratoconus Diagnosis

The Role of Pentacam Random Forest Index in Detecting Subclinical Keratoconus in a Chinese Cohort

Purpose: This study aimed to evaluate the diagnostic accuracy of a novel shape index, the Pentacam Random Forest Index (PRFI), in detecting keratoconus (KC), specifically subclinical keratoconus, in Chinese refractive surgery candidates. Methods: This prospective cohort study included 856 participants who were divided into four groups based on their tomographic outcomes: the KC group (n = 137), the very asymmetric ectasia (VAE) group (n = 73), the normal cornea group (n = 363) and the tomographically suspected KC (TSK) group (n = 283). The diagnostic performance of PRFI and other widely used indices, including the shape index BAD-D and the combined index TBI, was assessed using receiver operating characteristic (ROC) curve analysis and compared using DeLong's test. The area under the curve (AUC), best cutoff values, and Youden index for each parameter are reported. Additionally, the false-positive rates of BAD-D and PRFI were calculated and compared in "normal corneas". Results: All shape and biomechanical parameters collected in this study were found to be significantly different among the four groups (KC, VAE, TSK, and normal groups; p = 0.000). The AUC of PRFI was the highest in detecting any form of KC (including clinical KC eyes and VAE-NT eyes) in Chinese refractive surgery candidates, outperforming the widely used shape index BAD-D (0.919 vs. 0.890, p < 0.001). There was no significant difference in performance between the PRFI and the combined TBI index (0.919 vs. 0.916, p > 0.05). For detecting subclinical KC eyes (i.e., VAE-NT), the AUC of PRFI was 0.774, which was statistically comparable to TBI (0.774 vs. 0.776, p > 0.05), while outperforming BAD-D (0.774 vs. 0.684, p < 0.001). The best cutoff values of PRFI for detecting any KC and VAE-NT eyes were determined to be 0.37 and 0.27, respectively. Additionally, PRFI demonstrated a lower false-positive rate than BAD-D (13.8% vs. 43.8%, p < 0.001). Notably, the relatively high false-positive rate of BAD-D observed in this study might be attributed to the smaller horizontal corneal diameter in tomographically suspected eyes. Conclusions: The PRFI proved to be a superior shape index compared to BAD-D in detecting any form of keratoconus, including subclinical cases, in Chinese refractive surgery candidates. This finding may be attributed to the relatively small corneas commonly observed in Asians.

The KERATO Biomechanics Study 1: A Comparative Evaluation Using Brillouin Microscopy and Dynamic Scheimpflug Imaging

PURPOSE

To assess the corneal biomechanical properties in normal individuals and patients with keratoconus using the Brillouin optical scanning system (Intelon Optics) (BOSS) and compare them with ultra-high-speed Scheimpflug imaging (Corvis ST; Oculus Optikgeräte GmbH).

METHODS

Sixty eyes from 60 patients (30 normal and 30 keratoconus) were included in this prospective, single-center, comparative, non-interventional study. Corneal biomechanics were evaluated using the Corvis ST and the BOSS. With the BOSS, each corneal image was acquired three times, measuring 10 locations within an 8-mm diameter. Parameters extracted included mean, maximum, and minimum Brillouin shift. These 10 points were also grouped into superior, central, and inferior regions. BOSS repeatability was assessed using the coefficient of repeatability and coefficient of variation. Furthermore, normal individuals and patients with keratoconus were compared using the Corvis ST and BOSS.

RESULTS

The BOSS exhibited good repeatability, with coefficient of repeatability ranging from 0.098 to 0.138 GHz for single points in normal individuals and 0.096 to 0.149 GHz for patients with keratoconus. Statistical analysis revealed significant differences between normal individuals and patients with keratoconus, indicating softer corneas in keratoconus, observed with both the Corvis ST and BOSS. Specifically, the BOSS showed significant differences in mean, inferior, and superior mean, maximum, and minimum Brillouin frequency shift (all P < .05), whereas the Corvis ST displayed highly significant differences in stiffness parameter at first applanation, stress strain index, deformation amplitude ratio, and inverse integrated radius (all P < .001).

CONCLUSIONS

Corneal biomechanical measurements proved highly repeatable and effectively demonstrated significant differences between normal individuals and patients with keratoconus using both the BOSS and the Corvis ST. [J Refract Surg. 2024;40(8):e569-e578.].

Biomechanical changes following corneal crosslinking in keratoconus patients

PURPOSE

To evaluate the biomechanical and tomographic outcomes of keratoconus patients up to four years after corneal crosslinking (CXL).

METHODS

In this longitudinal retrospective-prospective single-center case series, the preoperative tomographic and biomechanical results from 200 keratoconus eyes of 161 patients undergoing CXL were compared to follow-up examinations at three-months, six-months, one-year, two-years, three-years, and four-years after CXL. Primary outcomes included the Corvis Biomechanical Factor (CBiF) and five biomechanical response parameters obtained from the Corvis ST. Tomographically, the Belin-Ambrósio deviation index (BAD-D) and the maximal keratometry (Kmax) measured by the Pentacam were analyzed. Additionally, Corvis E-staging, the thinnest corneal thickness (TCT), and the best-corrected visual acuity (BCVA) were obtained. Primary outcomes were compared using a paired t-test.

RESULTS

The CBiF decreased significantly at the six-month (p < 0.001) and one-year (p < 0.001) follow-ups when compared to preoperative values. E-staging behaved accordingly to the CBiF. Within the two- to four-year follow-ups, the biomechanical outcomes showed no significant differences when compared to preoperative. Tomographically, the BAD-D increased significantly during the first year after CXL with a maximum at six-months (p < 0.001), while Kmax decreased significantly (p < 0.001) and continuously up to four years after CXL. The TCT was lower at all postoperative follow-up visits compared to preoperative, and the BCVA improved.

CONCLUSION

In the first year after CXL, there was a temporary progression in both the biomechanical CBiF and E-staging, as well as in the tomographic analysis. CXL contributes to the stabilization of both the tomographic and biomechanical properties of the cornea up to four years postoperatively.

Longitudinal Analysis of Corneal Biomechanics of Suspect Keratoconus: A Prospective Case-Control Study

BACKGROUND

To evaluate the corneal biomechanics of stable keratoconus suspects (Stable-KCS) at 1-year follow-up and compare them with those of subclinical keratoconus (SKC).

METHODS

This prospective case-control study included the eyes of 144 patients. Biomechanical and tomographic parameters were recorded (Corvis ST and Pentacam). Patients without clinical signs of keratoconus in both eyes but suspicious tomography findings were included in the Stable-KCS group (n = 72). Longitudinal follow-up was used to evaluate Stable-KCS changes. Unilateral keratoconus contralateral eyes with suspicious tomography were included in the SKC group (n = 72). T-tests and non-parametric tests were used for comparison. Multivariate general linear models were used to adjust for confounding factors for further analysis. Receiver operating characteristic (ROC) curves were used to analyze the distinguishability.

RESULTS

The biomechanical and tomographic parameters of Stable-KCS showed no progression during the follow-up time (13.19 ± 2.41 months, p > 0.05). Fifteen biomechanical parameters and the Stress-Strain Index (SSI) differed between the two groups (p < 0.016). The A1 dArc length showed the strongest distinguishing ability (area under the ROC = 0.888) between Stable-KCS and SKC, with 90.28% sensitivity and 77.78% specificity at the cut-off value of -0.0175.

CONCLUSIONS

The A1 dArc length could distinguish between Stable-KCS and SKC, indicating the need to focus on changes in the A1 dArc length for keratoconus suspects during the follow-up period. Although both have abnormalities on tomography, the corneal biomechanics and SSI of Stable-KCS were stronger than those of SKC, which may explain the lack of progression of Stable-KCS.

Corneal biomechanics in early diagnosis of keratoconus using artificial intelligence

Keratoconus is a blinding eye disease that affects activities of daily living; therefore, early diagnosis is crucial. Great efforts have been made toward an early diagnosis of keratoconus. Recent studies have shown that corneal biomechanics is associated with the occurrence and progression of keratoconus. Hence, detecting changes in corneal biomechanics may provide a novel strategy for early diagnosis. However, an early keratoconus diagnosis remains challenging due to the subtle and localized nature of its lesions. Artificial intelligence has been used to help address this problem. Herein, we reviewed the literature regarding three aspects of keratoconus (keratoconus, early keratoconus, and keratoconus grading) based on corneal biomechanical properties using artificial intelligence. Furthermore, we summarized the current research progress, limitations, and possible prospects.

Corneal biomechanics and diagnostics: a review

PURPOSE

Corneal biomechanics is an emerging field and the interest into physical and biological interrelations in the anterior part of the eye has significantly increased during the past years. There are many factors that determine corneal biomechanics such as hormonal fluctuations, hydration and environmental factors. Other factors that can affect the corneas are the age, the intraocular pressure and the central corneal thickness. The purpose of this review is to evaluate the factors affecting corneal biomechanics and the recent advancements in non-destructive, in vivo measurement techniques for early detection and improved management of corneal diseases.

METHODS

Until recently, corneal biomechanics could not be directly assessed in humans and were instead inferred from geometrical cornea analysis and ex vivo biomechanical testing. The current research has made strides in studying and creating non-destructive and contactless techniques to measure the biomechanical properties of the cornea in vivo.

RESULTS

Research has indicated that altered corneal biomechanics contribute to diseases such as keratoconus and glaucoma. The identification of pathological corneas through the new measurement techniques is imperative for preventing postoperative complications.

CONCLUSIONS

Identification of pathological corneas is crucial for the prevention of postoperative complications. Therefore, a better understanding of corneal biomechanics will lead to earlier diagnosis of ectatic disorders, improve current refractive surgeries and allow for a better postoperative treatment.

Corneal Biomechanical Properties to Predict Prognosis of Abnormal Tomographic Corneas: A Prospective Cohort Study

PURPOSE

To analyze the corneal biomechanical properties in patients with abnormal corneal tomography (ACT) and predict their stability using the biomechanical stability index (BSI).

DESIGN

Prospective cohort study.

METHODS

Setting: Multicenter study.

STUDY POPULATION

This study included 385 eyes of 278 patients with stable ACT (n = 70), subclinical keratoconus (SKC, n = 65), keratoconus (n = 65), normal controls (NL, n = 142). Forty-three eyes with first-visit ACT were included in a separate cohort (follow-up ACT group).

OBSERVATION PROCEDURE

Tomographical and biomechanical parameters (Pentacam and Corvis ST) were recorded.

MAIN OUTCOME MEASURES

Nonparametric tests were used for comparison. Logistic regression was employed to introduce BSI to separate stable ACT and SKC accurately. An independent dataset of 43 first-visit ACT eyes was followed up for 1 year to validate BSI's accuracy and positive and negative predictive values (PPV, NPV).

RESULTS

The tomographical and biomechanical parameters in patients with Stable ACT remained stable over the follow-up period (12.73 ± 2.57 months, P > .05). Stable ACT had 12/14 biomechanical parameters different (P < .05) from SKC but not different from NL (P > .05). With a cut-off value of 0.585, BSI demonstrated the strongest ability to distinguish between stable ACT and SKC (area under the receiver operating characteristic curve = 0.991), with 93.85% sensitivity and 97.14% specificity. During the 1-year follow-up of 43 eyes (follow-up ACT group), 30 remained stable. The accuracy, PPV, and NPV of the BSI were 95.35%, 100%, and 93.75%, respectively.

CONCLUSIONS

Biomechanical properties of patients with stable abnormal tomography corneas were stronger than SKC and close to normal corneas, which may explain the reason for tomographic stability. The BSI may be useful for predicting disease progression in patients with ACT and the possible management of corneal cross-linking at the first visit.

Accuracy of an Air-Puff Dynamic Tonometry Biomarker to Discriminate the Corneal Biomechanical Response in Patients With Keratoconus

PURPOSE

The aim of this study was to assess accuracy of the mean corneal stiffness ( kc , N/m) parameter to discriminate between patients with keratoconus and age-matched healthy subjects.

METHODS

Dynamic Scheimpflug imaging tonometry was performed with Corvis ST (Oculus Optikgeräte GmbH, Germany) in patients with keratoconus (n = 24; study group) and age-matched healthy subjects (n = 32; control). An image processing algorithm was developed to analyze the video sequence of the Corvis ST air-puff event and to determine the geometric and temporal parameters that correlated with the corneal tissue biomechanical properties. A modified 3-element viscoelastic model was used to derive the kc parameter, which represented the corneal tissue resistance to deformation under load. Receiver operating characteristic curves were used to assess the overall diagnostic performance for determining the area under the curve, sensitivity, and specificity of the kc in assessing the corneal tissue deformation to the Corvis ST air-puff event in keratoconus and control eyes. The Corvis Biomechanical Index ( CBI ) was analyzed for external validation.

RESULTS

The kc parameter was significantly different between keratoconus and controls ( P < 0.001), ranging from 24.9 ±3.0 to 34.2 ±3.5 N/m, respectively. It was highly correlated with CBI (r = -0.69; P < 0.001); however, the kc parameter had greater specificity (94%) than CBI (75%), whereas the 2 biomarkers had similar area under the curve (0.98 vs. 0.94) and sensitivity (96% vs. 92%) in predicting the occurrence of keratoconus.

CONCLUSIONS

The kc parameter extracted by video processing analysis of dynamic Scheimpflug tonometry data was highly accurate in discriminating patients with clinically manifest keratoconus compared with controls.

Mendelian Randomisation Analysis of Causal Association between Lifestyle, Health Factors, and Keratoconus

Keratoconus (KC), a leading cause of vision impairment, has an unclear aetiology. This study used Mendelian randomization (MR) to explore the causal links between various factors (smoking, asthma, Down syndrome, inflammatory bowel disease, atopic dermatitis, and serum 25-hydroxyvitamin D levels) and KC. A two-sample MR design, grounded in genome-wide association study (GWAS) summary statistics, was adopted using data from FinnGen, UK Biobank, and other GWAS-related articles. The inverse-variance weighted (IVW) method was employed, complemented by the Wald ratio method for factors with only one single-nucleotide polymorphism (SNP). Sensitivity and stability were assessed through Cochrane's Q test, the MR-Egger intercept test, MR-PRESSO outlier test, and the leave-one-out analysis. The IVW results for the ORA (Ocular Response Analyzer) biomechanical parameters indicated significant associations between tobacco smoking (CH: p < 0.001; CRF: p = 0.009) and inflammatory bowel disease (CH: p = 0.032; CRF: p = 0.001) and corneal biomechanics. The Wald ratio method showed tobacco smoking was associated with a lower risk of KC (p = 0.024). Conversely, asthma (p = 0.009), atopic dermatitis (p = 0.012), inflammatory bowel disease (p = 0.017), and serum 25-hydroxyvitamin D levels (p = 0.039) were associated with a higher risk of KC by IVW, and the same applied to Down syndrome (p = 0.004) using the Wald ratio. These results underscore the role of corneal biomechanics as potential mediators in KC risk, warranting further investigation using Corvis ST and Brillouin microscopy. The findings emphasise the importance of timely screening for specific populations in KC prevention and management.

Clinical and Morphological in Vivo Confocal Microscopy Findings following a Modified Biphasic Higher Fluence Transepithelial Corneal Crosslinking

Purpose: To compare the refractive efficacy and morphological changes in the cornea following a novel biphasic higher fluence transepithelial corneal crosslinking (BI-TE-CXL) and transepithelial corneal crosslinking (TE-CXL) in adults keratoconus.Methods: Patients with progressive keratoconus who required corneal crosslinking were assigned to the BI-TE-CXL group (32 eyes, phase 1: 7.2 J/cm2 for 5 min and 20 s of pulsed-light exposure, KXL, Glaukos-Avedro; phase 2: 3.6 J/cm2 for 6 min and 40 s of continuous light exposure at the front curvature apex with a 6 mm diameter light spot, UVX-2000, IROC) or the TE-CXL group (32 eyes, uniform 7.2 J/cm2 for 5 min and 20 s of pulsed-light exposure, KXL, Glaukos-Avedro). Uncorrected distance visual acuity (UDVA), corrected distance visual acuity (CDVA), corneal fluorescein staining (CFS), corneal topography, anterior segment optical coherence tomography (AS-OCT), and in vivo corneal confocal microscopy (IVCM) were performed 3, 6, 12 and 24 months after surgery.Results: The CFS scores in the BI-TE-CXL group were significantly higher than those in the TE-CXL group on the first two days after surgery (p < 0.001). The Kmax (at 12 and 24 months) and CDVA (logMAR) were significantly lower in the BI-TE-CXL group than those in the TE-CXL group (p < 0.05). The corneal demarcation line under AS-OCT was visible in 81.3% of patients in the BI-TE-CXL group and 15.6% in the TE-CXL group. The depth of the demarcation line under IVCM was significantly deeper in the BI-TE-CXL group (248.3 ± 25.0 μm) than that of the TE-CXL group (136.5 ± 15.6 μm) in the central cornea (p < 0.001). The cross-linked collagen structures in the central cornea were still present after 12 months in the BI-TE-CXL group. No significant difference in sub-basal nerve density between the two groups (p > 0.05).Conclusions: Following BI-TE-CXL, CDVA was significantly improved, accompanied by deeper demarcation line depth and persistent crosslinked structures in the central corneal stroma.

Machine learning analysis with the comprehensive index of corneal tomographic and biomechanical parameters in detecting pediatric subclinical keratoconus

Background: Keratoconus (KC) occurs at puberty but diagnosis is focused on adults. The early diagnosis of pediatric KC can prevent its progression and improve the quality of life of patients. This study aimed to evaluate the ability of corneal tomographic and biomechanical variables through machine learning analysis to detect subclinical keratoconus (SKC) in a pediatric population. Methods: Fifty-two KC, 52 SKC, and 52 control pediatric eyes matched by age and gender were recruited in a case-control study. The corneal tomographic and biomechanical parameters were measured by professionals. A linear mixed-effects test was used to compare the differences among the three groups and a least significant difference analysis was used to conduct pairwise comparisons. The receiver operating characteristic (ROC) curve and the Delong test were used to evaluate diagnostic ability. Variables were used in a multivariate logistic regression in the machine learning analysis, using a stepwise variable selection to decrease overfitting, and comprehensive indices for detecting pediatric SKC eyes were produced in each step. Results: PE, BAD-D, and TBI had the highest area under the curve (AUC) values in identifying pediatric KC eyes, and the corresponding cutoff values were 12 μm, 2.48, and 0.6, respectively. For discriminating SKC eyes, the highest AUC (95% CI) was found in SP A1 with a value of 0.84 (0.765, 0.915), and BAD-D was the best parameter among the corneal tomographic parameters with an AUC (95% CI) value of 0.817 (0.729, 0.886). Three models were generated in the machine learning analysis, and Model 3 (y = 0.400*PE + 1.982* DA ratio max [2 mm]-0.072 * SP A1-3.245) had the highest AUC (95% CI) value, with 90.4% sensitivity and 76.9% specificity, and the cutoff value providing the best Youden index was 0.19. Conclusion: The criteria of parameters for diagnosing pediatric KC and SKC eyes were inconsistent with the adult population. Combined corneal tomographic and biomechanical parameters could enhance the early diagnosis of young patients and improve the inadequate representation of pediatric KC research.

Corneal biomechanics in normal and subclinical keratoconus eyes

BACKGROUND

The diagnosis of keratoconus, as the most prevalent corneal ectatic disorder, at the subclinical stage gained great attention due to the increased acceptance of refractive surgeries. This study aimed to assess the pattern of the corneal biomechanical properties derived from Corneal Visualization Scheimpflug Technology (Corvis ST) and evaluate the diagnostic value of these parameters in distinguishing subclinical keratoconus (SKC) from normal eyes.

METHODS

This prospective study was conducted on 73 SKC and 69 normal eyes. Subclinical keratoconus eyes were defined as corneas with no clinical evidence of keratoconus and suspicious topographic and tomographic features. Following a complete ophthalmic examination, topographic and tomographic corneal assessment via Pentacam HR, and corneal biomechanical evaluation utilizing Corvis ST were done.

RESULTS

Subclinical keratoconus eyes presented significantly higher Deformation Amplitude (DA) ratio, Tomographic Biomechanical Index (TBI), and Corvis Biomechanical Index (CBI) rates than the control group. Conversely, Ambrósio Relational Thickness to the Horizontal profile (ARTh), and Stiffness Parameter at the first Applanation (SPA1) showed significantly lower rates in SKC eyes. In diagnosing SKC from normal eyes, TBI (AUC: 0.858, Cut-off value: > 0.33, Youden index: 0.55), ARTh (AUC: 0.813, Cut-off value: ≤ 488.1, Youden index: 0.58), and CBI (AUC: 0.804, Cut-off value: > 0.47, Youden index: 0.49) appeared as good indicators.

CONCLUSIONS

TBI, CBI, and ARTh parameters could be valuable in distinguishing SKC eyes from normal ones.

Dynamic topography analysis of the cornea and its application to the diagnosis of keratoconus

PROPOSE

To establish a dynamic topography analysis method which simulates the dynamic biomechanical response of the cornea and reveals the variations of such response within the corneal surface, and thereafter to propose and clinically evaluate new parameters for the definite diagnosis of keratoconus.

METHODS

58 normal (Normal) and 56 keratoconus (KC) subjects were retrospectively included. Personalized corneal air-puff model was established using corneal topography data by Pentacam for each subject, and the dynamic deformation under air-puff loading was simulated using finite element method, which then enabled calculations of corneal biomechanical parameters of the entire corneal surface along any meridian. Variations in these parameters across different meridians and between different groups were explored by two-way repeated measurement analysis of variance. New dynamic topography parameters were proposed as the range of the calculated biomechanical parameters within the entire corneal surface, and the AUC of ROC curve was used to compare the diagnostic efficiency of newly proposed and existing parameters.

RESULTS

Corneal biomechanical parameters measured in different meridians varied significantly which were more pronounced in KC group due to its irregularity in corneal morphology. Considering such between-meridian variations thus led to improved diagnostic efficiency of KC as presented by the proposed dynamic topography parameter rIR with an AUC of 0.992 (sensitivity: 91.1%, specificity: 100%), significantly better than the current topography and biomechanical parameters.

CONCLUSIONS

The diagnosis of keratoconus may be affected by the significant variations of corneal biomechanical parameters due to corneal morphology irregularity. By considering such variations, the current study established the dynamic topography analysis process which benefits from the high accuracy of (static) corneal topography measurement while improving its diagnosis capacity. The proposed dynamic topography parameters, especially the rIR parameter, showed comparable or better diagnostic efficiency for KC than existing topography and biomechanical parameters, which can be of great clinical significance for clinics without access to instrument for biomechanical evaluations.