Detection of keratoconus (KC) and especially subclinical keratoconus (SKC) plays a crucial role in preoperative screening of refractive surgeries, considering that 88% of postsurgery corneal ectasia was attributed to keratoconic eyes that failed to be ascertained before surgery (Rand et al., 2003). With the assistance of artificial intelligence (AI), the diagnostic ability of KC has indeed improved greatly in this decade (Vinciguerra et al., 2016; Ambrósio et al., 2017; Lopes et al., 2018). However, the established AI diagnostic models seem to have stepped into a bottleneck period with high but unsatisfactory sensitivity and specificity (Cao et al., 2022). There is still a need to mine more characteristic features of the disease and refine the current diagnostic models.

Corneal morphology has been indicated to have good symmetry in normal individuals in terms of keratometry, pachymetry and elevation (Durr et al., 2015; Xu et al., 2021). Keratoconus is regarded as a binocularly affected but generally asymmetrically developed disease (Gomes et al., 2015). Some research found that the interocular asymmetry of keratoconic eyes is not only greater than that of normal eyes but also increases with the severity of the worse eye (Naderan et al., 2017; Eppig et al., 2018). Then, several studies managed to construct diagnostic models for KC and very early keratoconus (VEKS) or keratoconus suspect (KCS) using the interocular asymmetry in corneal morphology, which presented the inspiring potential of morphological interocular asymmetry to assist the diagnosis of KC and SKC (Saad et al., 2014; Galletti et al., 2015a; Mehlan et al., 2022).

Furthermore, studies have confirmed that the reduction in biomechanical stability occurs prior to the change in morphology and that biomechanical weakening could be the initiating event of the disease (Scarcelli et al., 2014). However, the distribution range of most biomechanical parameters overlaps in normal individuals and SKC patients. Therefore, the effect of applying biomechanical parameters to the diagnosis of SKC is not ideal. There might be asymmetric changes in biomechanical properties first, which then lead to asymmetric morphological changes. We hypothesize that it may be beneficial to improve the sensitivity of diagnosing SKC by introducing biomechanical interocular asymmetry assessment.

In this study, we compared the interocular asymmetry between keratoconic and normal eyes and clarified the normal range of interocular asymmetry in biomechanical properties. In addition, we attempted to construct an asymmetry index based on binocular data and evaluate its auxiliary effect on monocular models for the diagnosis of KC and SKC.

This is a retrospective case–control study. The protocol followed the tenets of the Declaration of Helsinki and was approved by the institutional review board of Peking University Third Hospital. The records of patients with ametropia or keratoconus referred to the Peking University Institute of Laser Medicine were reviewed after informed consent was obtained.

The composition and demographic characteristics of the analyzed datasets are shown in Table 2. A total of 331 myopia patients in the control group and 207 patients in the KC group were recruited in this study. The mean ages were 28.01 ± 7.16 and 25.17 ± 6.01 in the two groups, respectively (p < 0.001). There were more males in the KC group than in the control group (70.0% vs. 38.9%, p < 0.001). The SKC subgroup consisted of 94 patients with an average age of 24.68 ± 5.83 (p < 0.001, compared with the control group), of whom 67.0% were male.

Although AI diagnostic models for distinguishing KC and SKC based on morphological parameters or images have been developed conspicuously over the decade, models based on biomechanical parameters are conversely rare (Vinciguerra et al., 2016; Steinberg et al., 2017). To improve the diagnostic ability for KC and especially SKC, the emphasis should be placed on utilizing biomechanical properties, which represent more intrinsic and subtle changes than morphology. In view of the asymmetric clinical manifestations of keratoconus, this study analyzed and compared the interocular asymmetry in biomechanical properties between normal subjects and patients with keratoconus and evaluated the potential to establish diagnostic models for KC and SKC based on this interocular feature.

We found that biomechanical parameters generally exhibit good interocular consistency in the eyes of normal individuals. However, the consistency is reduced and the interocular asymmetry values increase in keratoconic eyes, especially in parameters including A1V, A2V, HCT, MaxIR, DAR2 and DAR1, etc. Eppig et al. (2018) analyzed biomechanical parameters measured by the Ocular Response Analyzer (Reichert Inc., Depew, United States) and drew the same conclusion that interocular asymmetry is larger in keratoconus than in normal eyes. In contrast to the biomechanical parameters, the biomechanically corrected intraocular pressure (bIOP) has good interocular consistency in patients with KC. We suppose this suggests that although intraocular pressure affects the measurement of biomechanical parameters, it should not be the initial factor that causes the biomechanical changes in KC.

Eppig and others also reported that the interocular asymmetry of corneal hysteresis (CH) and corneal resistance factor (CRF) increased with the severity of KC, but reversal occurred in the severest patients classified as TKC stage 4 (Eppig et al., 2018). In this study, not only were similar close correlations of interocular asymmetry and severity observed, but the similar inverse behavior in severe keratoconus was also found. The inverse might be attributed to the relatively small sample in KSS grade 5. However, this does not affect the promising prospect of applying interocular asymmetry in the diagnosis of SKC.

It is worth noting that corneal biomechanical properties are influenced by some factors. Considerable corneal sclerosis and reduction of corneal viscoelastic properties with age were observed, which could be affected by age-related nonenzymatic cross-linking (Kotecha et al., 2006; Elsheikh et al., 2007; Matalia et al., 2016). The stress‒strain behavior of biological tissue is nonlinear, which means that the stress and strain of the cornea and sclera increase with intraocular pressure, causing a rise in the tangent modulus and influencing immediate corneal stiffness (Ethier et al., 2004; Eliasy et al., 2019). In addition, bIOP is an integral component of other Corvis ST parameters, such as SP-A1. Thus, bIOP also has an impact on the calculation of the classic biomechanical diagnostic parameter CBI (Vinciguerra et al., 2016; Roberts et al., 2017). Corneal thickness may cause differences in biomechanical parameters as well, with thicker corneas having greater dampening properties (Kotecha et al., 2006). To eliminate the influence of these factors, they were all included in the modeling in this study.

Individual interocular asymmetry values perform poorly in diagnosing keratoconus, while combined models perform well. Xian et al. (2023) reported that the AUC of the individual interocular asymmetry values did not exceed 0.9, but the logistic model combining ΔDAR2, ΔIR, and age reached a high AUC of 0.922 in identifying keratoconus. Similar results were achieved in the present study. Although inspiring outcomes were observed, we still have an objective view that the significance of interocular asymmetry lies in assisting monocular model diagnosis rather than replacing it. Therefore, an additional monocular parameter model, MBI, was established, and the classic monocular-based models were adopted as references. When comparing the interocular asymmetry model with the monocular models, no significant advantage was observed. However, the joint model that combined interocular asymmetry values and monocular descriptors had a better AUC than the monocular models, including the MBI, CBI, TBI, and PRFI. The NRI and IDI analysis proved that the interocular asymmetry values indeed bring gain to the monocular parameters in KC diagnosis. Furthermore, we attempted to evaluate the possibility of applying the interocular features in SKC diagnosis.

The difficulty lies in identifying the true population with binocular subclinical keratoconus, since the most popular criterion for SKC is the normal eye with a confirmed keratoconic fellow eye (Henriquez et al., 2020). However, the progression of the keratoconic fellow eye in this population may far exceed that of SKC to the point where it does not meet the diagnosis of bilateral SKC. It is difficult to verify the auxiliary diagnostic value of the biomechanical interocular asymmetry values without a properly allocated SKC group. Due to limited research on interocular asymmetry, there are few reference criteria for grouping binocular SKC. Naderan and others defined the KCS group as consisting of patients suspected of bilateral KC (60 < KISA% < 100 in both eyes) or a combination of KCS and normal eyes (60 < KISA% < 100 in one eye and KISA% < 60 in the other eye) and revealed that the intereye asymmetry of anterior corneal astigmatism had the highest accuracy of 0.923 (Naderan et al., 2017). Henriquez et al. (2015) classified KC patients with binocular Kmax equal to or less than 48 D as the VEKC group and constructed a logistic regression model using the asymmetry of morphological descriptors that reached an AUC value of 0.9957. We ultimately referred to Galleti and others’ research and designated keratoconic patients with KSS grades of 0–2 as the SKC subgroup for model validation alone (Ruiseñor Vázquez et al., 2014; Galletti et al., 2015a).

In distinguishing SKC from normal individuals, BaBI maintained its advantage over the monocular-based models. The additive benefit of interocular asymmetry values to the monocular parameters was also remarkable. Due to the insignificant clinical changes in SKC, the performance of the monocular-based models applied to the SKC population is often worse than that in the KC population, with relatively low sensitivity (Ambrósio et al., 2017; Lopes et al., 2018). However, the sensitivity of the BaBI is apparently higher than that of all other models, which means that the joint model can contribute to reducing the false-negative rate and improving the screening ability of SKC before the refractive surgery.

Although the Corvis ST is currently a widely used corneal biomechanical measurement device, its evaluation of in vivo biomechanics is not perfect. Corvis ST measures tissue responses to global deformation forces; therefore, it is not possible to assess regional differences in biomechanical properties. In addition, air puff results in not only corneal displacement but also motion of the entire ocular tissue and aqueous fluid (Boszczyk et al., 2017; Maczynska et al., 2019), which makes it difficult to detect minute variations in spatial stiffness in cases of SKC where local weakness occurs (Pahuja et al., 2016). However, emerging biomechanical measurements might be a promising supplement to solve this challenge. Brillouin microscopy does not require any stimulation or corneal deformation but relies on optical resolution. Shao et al. reported a distinction between early-stage KC and normal groups in the analysis of regional differences between cone and outside-cone regions and greater interocular differences of Brillouin shifts in stage-I KC patients than in normal controls (Shao et al., 2019). Optical coherence elastography (OCE) has high dynamic spatial and temporal resolution and can achieve flexible submicron stimulation using micro air pulses (Lan et al., 2021). OCE is expected to be able to image small amplitude and high-speed processes related to the propagation of elastic waves in the local cornea, thereby further evaluating the regional distribution characteristics of biomechanical interocular features (e.g., mirror symmetry) and providing a theoretical basis for assisting in the diagnosis of SKC.

There are limitations in this study. We relied on only one high-quality examination per eye to conduct the statistical analysis. There may be concerns about the repeatability of biomechanical measurements, but studies have shown that most biomechanical parameters have good stability in repeated measurements (Herber et al., 2020; Serbecic et al., 2020; Wang et al., 2021). Second, this is a single-center study with a relatively small sample size and a lack of ethnic diversity. We hypothesize that calculating the interocular asymmetry may help reduce the bias caused by the system in comparison to monocular descriptors. Despite this, the normal range of biomechanical interocular asymmetry values proposed in this article and the diagnostic ability of newly constructed models need further clinical testing in different regions and races. Thirdly, this study lacks long-term follow-up and longitudinal data. Considering that secondary corneal ectasia may occur within more than 10 years after refractive surgery, the 2-year follow-up of the control group is relatively short. The limited follow-up time and lack of longitudinal data in the keratoconus group also limit the application of the conclusions obtained in this study—biomechanical interocular asymmetry values increase with the severity of keratoconus—in the assessment of keratoconus progression. After obtaining longer-term follow-up and longitudinal data, the conclusions of this study can be further validated and improved.

In conclusion, there is currently a lack of research on biomechanical interocular asymmetry. In this study, we observed that the biomechanical interocular consistency in patients with keratoconus was lower than that in normal people and clarified the normal scope of interocular asymmetry values of biomechanical descriptors. We found that most interocular biomechanical asymmetry values increase along with the severity of the disease, but the inverse exists in a minority of descriptors in severe KC grading KSS 5. The interocular asymmetry of corneal biomechanical properties performs well in the diagnosis of KC and SKC and has an exact auxiliary value for monocular parameters.