Keratoconus is a localized corneal ectasia disease that can cause a serious drop in corneal optical performance and a slow decline in visual asymmetry. Keratoconus is an absolute contraindication to corneal refractive surgery; thus, accurate preoperative diagnosis is particularly important. Although the diagnosis of keratoconus in clinical maturity and progression is not difficult, the diagnosis of keratoconus in the subclinical stage is still challenging . At present, the auxiliary methods for diagnosing keratoconus are mainly corneal topography and corneal tomography, but these two methods are susceptible to tear film, ocular surface diseases, and contact lens wear. The diagnosis of subclinical keratoconus has some limitations . Subclinical keratoconus has long been regarded as one of the most important independent risk factors for the occurrence of iatrogenic keratopathy. Studies have shown that changes in corneal biomechanics may occur before changes in typical corneal morphology . In recent years, the biomechanical research of early keratoconus has become a hot topic. In this study, we comparatively analyzed the corneal morphological and biomechanical characteristics of keratoconus, forme fruste keratoconus, and normal corneas, and further analyzed the diagnostic efficiency of various morphological and biomechanical parameters for keratoconus and forme fruste keratoconus.
Wahba et al.  found that corneal morphological parameters have significant statistical differences between normal corneas and keratoconus. In this study, there was a statistically significant difference in all corneal morphological parameters between the normal cornea and keratoconus groups. The corneal curvature, astigmatism, and corneal index of the keratoconus group were significantly higher than those of the normal cornea group, while corneal thickness was significantly smaller than that of the normal cornea group.
Many studies have found that the corneal morphological parameters have a higher ability to distinguish keratoconus from normal corneas, and the BAD-D parameter has higher efficiency, sensitivity, and specificity in distinguishing between normal corneas and keratoconus [22–24]. In a study of 21 cases of keratoconus and 78 cases of the normal cornea, Wang YM et al.  found that BAD-D distinguishes between normal and keratoconus with an AUC of 1.00, cut-off point of 1.54, sensitivity of 1.00, and specificity of 0.803. In this study, all corneal morphological parameters had higher efficiency in distinguishing between normal corneas and keratoconus, with an AUC greater than 0.81. Furthermore, BAD-D had the highest diagnostic efficiency for distinguishing between keratoconus and normal corneas with an AUC of 0.989, cut-off point of 1.595, as well as a sensitivity and specificity of 0.959 and 1.00, respectively.
Scarcelli et al.  suggested that keratoconus is initially caused by the local weakening of corneal biomechanical properties. Over time, under the same IOP, the mechanical strength of the cornea weakens, the mechanical strength of the local area of soft tissue becomes stronger than the surrounding area, and the ability to resist IOP worsens, resulting in an increase in the curvature and thinning of the softer corneal area. Based on these findings, keratoconus may be identified during the biomechanical change stage, before the cornea becomes thinner and more curved.
Earlier studies on keratoconus biomechanics found that the differences in biomechanical parameters between the the normal cornea group and keratoconus group were statistically significant, and the AUC of the parameters overlapped between 0.673 and 0.852 [10, 26, 27]. With the introduction of new Corvis ST parameters, more related studies have appeared. Research by Vinciguerra et al.  found that CBI has the highest efficiency in distinguishing keratoconus and normal cornea in biomechanical parameters, with a sensitivity and specificity of 1.00 and 0.984, respectively. Our previous study found that , among the biomechanical parameters, DA had the highest efficiency in diagnosing keratoconus, with an AUC of 0.882. However, this parameter has significant overlap in the keratoconus group and the control group. In this study, when comparing the normal group with the keratoconus group, most of the biomechanical parameters were significantly different, and most biomechanical parameters could effectively diagnose keratoconus. The parameters proposed by the new version of the software, such as DA Ratio2, Integrated Radius, ARTh, SPA1, and CBI, had higher diagnostic efficiency for keratoconus, with an AUC greater than 0.90, among which SPA1 had the largest AUC (0.94), and a sensitivity and specificity of 0.802 and 0.981, respectively. Although CBI had an AUC value of 0.916 (the cut-off point: 0.516) for distinguishing between keratoconus and normal cornea, its sensitivity and specificity were the highest (0.845 and 1.00, respectively). This is similar to previous research results .
In the past two years, Ambrosio et al.  have developed a new parameter, TBI, and applied it to the keratoconus study. They found that TBI was more efficient than previously analyzed parameters in detecting corneal ectasia diseases, with an AUC of 1.00. When the TBI value was 0.79, the sensitivity and specificity values were both equal to 1.00. In this study, the AUC for TBI to distinguish between keratoconus and normal corneas was 0.993; and, when the value was 0.515, the sensitivity and specificity values were 0.967 and 1.00, respectively. The difference between the AUCs of TBI and BAD-D was not statistically significant; therefore, these two parameters are the most efficient in diagnosing keratoconus.
Keratoconus is typically a binocular disease. When a patient suffers the onset of keratoconus in one eye, the other eye may develop the same disease within a few years [17, 29]. Forme fruste keratoconus in a relatively healthy eye may represent an earlier stage of the disease, and is currently undetectable by topography and tomography . With the development of biomechanical instruments and the development of new parameters, many researchers have analyzed eyes affected by forme fruste keratoconus. Ambrosio et al.  reported that BAD-D, CBI, and TBI can effectively distinguish normal eyes from forme fruste keratoconus, and TBI has the highest diagnostic efficiency, with an AUC of 0.985, sensitivity of 0.904, and specificity of 0.96. Studies by Mingyue et al.  found that BAD-D, CBI, and TBI can effectively distinguish normal eyes from forme fruste keratoconus, and the diagnostic efficiency of CBI is the highest, with an AUC of 0.909, sensitivity of 0.903, and specificity of 0.917. In this study, the ability of BAD-D, CBI, and TBI to distinguish between normal corneas and forme fruste keratoconus was low, with an AUC of 0.684, 0.667, and 0.722, respectively. This is different from some previous reports [11, 13, 30], but similar to the report by Peng Song et al. . Our analysis shows that the parameters in this study have a low ability to diagnose forme fruste keratoconus, mainly because the inclusion criteria for forme fruste keratoconus are different and this study excludes eyes with a BAD-D value greater than 1.6, unlike the study of Mingyue et al. . In their study, the average BAD-D value of the forme fruste keratoconus group was 2.409. This is also different from the study by Pratik Kataria et al. , where the BAD-D value of the forme fruste keratoconus group ranged from − 0.82–3.35. Additionally, in this study, there may be some forme fruste keratoconus patients with normal eyes. These eyes may not have been diseased, or there may have been some true monocular keratoconus. Although studies have shown that true unilateral keratoconus does not exist . However, Imbornoni et al.  reported five cases that may be true unilateral keratoconus, and the healthy eyes of these patients remained normal during 3 to 7 years of follow-up. Therefore, whether there is also true monocular keratoconus needs to be further investigated.
This study has a relatively large sample size and a large number of corneal morphological and biomechanical parameters are included, including some new parameters. Furthermore, this study also analyzed patients with forme fruste keratoconus, which may represent an earlier stage of the disease. The limitation of the study is that this is a cross-sectional study, and there is a lack of follow-up for patients with forme fruste keratoconus. Furthermore, there are relatively few cases of forme fruste keratoconus. In future studies, the sample size will be further increased and we will continue to follow-up the disease progression of patients with forme fruste keratoconus.