Zeyu Li

Background: Corvis ST (CVS) provides dynamic corneal response parameters for biomechanical assessment, but conventional metrics may not uniquely reflect region-specific alterations in corneal material properties. This study investigated how regional changes in corneal material properties influence CVS biomechanical parameters and explored a multi-parameter strategy for regional mechanical interpretation. Methods: An idealized finite element corneal model was divided into central, paracentral, and peripheral zones, and the stiffness of each zone was independently adjusted to 70–130% of baseline to simulate regional softening or stiffening. An air-puff load was applied to the anterior corneal surface, and nodal coordinates were used to calculate conventional CVS parameters and the newly proposed DA Ratio X series. Normalized relative changes and univariate linear regression were used to characterize response direction and sensitivity. Results: Most parameters showed approximately linear responses to regional stiffness alterations, with region-dependent differences in response direction and magnitude. Central material changes produced the largest responses. Similar parameter values or trends could arise from different regional mechanical alterations, indicating that a single parameter may not uniquely identify the underlying regional change. Within this idealized simulation framework, the extended DA Ratio series improved regional differentiation, and the combination of DeflArea, DAR4, and IIR provided a candidate theoretical framework for distinguishing central, paracentral, and peripheral changes. Conclusions: CVS biomechanical parameters were influenced by the spatial location of corneal material alterations, and single-parameter interpretation may not uniquely reflect the underlying regional mechanical changes. Coordinated interpretation of multiple parameters demonstrated distinct response patterns across different modeled regions and may provide ideas for future regional biomechanical assessment. Further validation using patient-specific models and clinical datasets is warranted to evaluate the applicability of this framework.