Purpose: To measure the deformation of the human optic nerve head (ONH) and peripapillary tissue (PPT) in response to acute intraocular pressure (IOP) elevation. Methods: The ONH and PPT of 14 human donor globes were imaged with high-frequency ultrasonography during inflation testing from 5 to 30 mm Hg. A correlation-based speckle tracking algorithm was used to compute tissue displacements, and the through-thickness, in-plane, and shear strains were calculated by using least-squares strain estimation methods. The ONH and PPT were segmented along the anterior-posterior direction and the nasal-temporal direction. Regional displacements and strains were analyzed and compared. Results: The ONH displaced more posteriorly than the PPT in response to an acute IOP increase. Scleral canal expansion was minimal but correlated with ONH posterior displacement at all IOP levels. Through-thickness compression was concentrated in the anterior of both the ONH and the PPT. Shear was concentrated in the vicinity of the canal with higher shear in the peripheral ONH than the central ONH and higher shear in the PPT near the scleral canal than that further away from the canal. Conclusions: High-resolution ultrasound speckle tracking showed a displacement mismatch between the ONH and the PPT, larger compressive strains in the direction of IOP loading in the anterior ONH and PPT, and higher shear strains in the periphery of ONH in response to acute IOP elevation in the human eye. These findings delineate the deformation patterns within and around the ONH and may help understand IOP-associated optic nerve damage.

Purpose: To measure the deformation of the porcine optic nerve head (ONH) and peripapillary sclera (PPS) in response to intraocular pressure (IOP) elevation. Methods: High-frequency ultrasound was used to image the ONH and PPS of 12 porcine eyes during ex vivo inflation testing from 5 to 30 mm Hg. A speckle tracking algorithm was used to compute tissue displacements in the anterior-posterior direction and expansion of the scleral canal. Through-thickness, in-plane, and shear strains were calculated within the ONH. Regional displacements and strains were analyzed and compared. Results: The ONH and PPS showed overall posterior displacement in response to IOP elevation. Posterior displacement of the ONH was larger than and strongly correlated with the posterior displacement of the PPS throughout inflation testing. Scleral canal expansion was much smaller and leveled off quicker than ONH posterior displacement as IOP increased. Through-thickness compression was concentrated in the anterior ONH, which also experienced larger in-plane and shear strains than the posterior ONH. Within the anterior ONH, all three strains were significantly higher in the periphery compared with the center, with the shear strain exhibiting the greatest difference between the two regions. Conclusions: High-resolution ultrasound speckle tracking revealed the full-thickness mechanical response of the posterior eye to IOP elevation. A mismatch in posterior displacement was found between the ONH and PPS, and regional analyses showed a concentration of strains within the periphery of the anterior porcine ONH. These deformation patterns may help in understanding IOP-associated optic nerve damage and glaucoma susceptibility.

Characterization of the biomechanical behavior of the optic nerve head (ONH) in response to intraocular pressure (IOP) elevation is important for understanding glaucoma susceptibility. In this study, we aimed to develop and validate a three-dimensional (3D) ultrasound elastographic technique to obtain mapping and visualization of the 3D distributive displacements and strains of the ONH and surrounding peripapillary tissue (PPT) during whole globe inflation from 15 to 30 mmHg. 3D scans of the posterior eye around the ONH were acquired through full tissue thickness with a high-frequency ultrasound system (50 MHz). A 3D cross-correlation-based speckle-tracking algorithm was used to compute tissue displacements at ∼30,000 kernels distributed within the region of interest (ROI), and the components of the strain tensors were calculated at each kernel by using least square estimation of the displacement gradients. The accuracy of displacement calculation was evaluated using simulated rigid-body translation on ultrasound radiofrequency (RF) data obtained from a porcine posterior eye. The accuracy of strain calculation was evaluated using finite element (FE) models. Three porcine eyes were tested showing that ONH deformation was heterogeneous with localized high strains. Substantial radial (i.e., through-thickness) compression was observed in the anterior ONH and out-of-plane (i.e., perpendicular to the surface of the shell) shear was shown to concentrate in the vicinity of ONH/PPT border. These preliminary results demonstrated the feasibility of this technique to achieve comprehensive 3D evaluation of the mechanical responses of the posterior eye, which may provide mechanistic insights into the regional susceptibility in glaucoma.

Purpose: In vivo evaluation of corneal biomechanics holds the potential for improving diagnosis and management of ocular diseases. We aimed to develop an ocular pulse elastography (OPE) technique to quantify corneal strains generated by naturally occurring pulsations of the intraocular pressure (IOP) using high-frequency ultrasound. Methods: Simulated ocular pulses were induced in whole porcine and human donor globes to investigate the effects of physiologic variations in baseline IOP, ocular pulse amplitude, and frequency on corneal strains. Ocular pulse–induced strains were measured in additional globes before and after UVA-riboflavin–induced corneal crosslinking. The central cornea in each eye was imaged with a 50-MHz ultrasound imaging system and correlation-based speckle tracking of radiofrequency data was used to calculate tissue displacements and strains. Results: Ocular pulse–induced corneal strains followed the cyclic changes of IOP. Both baseline IOP and ocular pulse amplitude had a significant influence on strain magnitude. Variations in pulse frequency within the normal human heart rate range did not introduce detectable changes in corneal strains. A significant decrease of corneal strain, as quantified by the OPE technique, was observed after corneal crosslinking. The extent of corneal stiffening (i.e., strain reduction) seemed to correlate with the initial strain magnitude. Conclusions: This ex vivo study demonstrated the feasibility of the OPE method to quantify corneal strains generated by IOP pulsation and detect changes associated with corneal crosslinking treatment. Translational Relevance: Integrating in vivo measurement of IOP and ocular pulse amplitude, the OPE method may lead to a new clinical tool for safe and quick biomechanical evaluations of the cornea.

Cells migrate by adapting their leading-edge behaviors to heterogeneous extracellular microenvironments (ECMs) during cancer invasions and immune responses. Yet it remains poorly understood how such complicated dynamic behaviors emerge from millisecond-scale assembling activities of protein molecules, which are hard to probe experimentally. To address this gap, we establish a spatiotemporal “resistance-adaptive propulsion” theory based on the interactions between Arp2/3 complexes and polymerizing actin filaments and a multiscale dynamic modeling system spanning from molecular proteins to the cell. We quantitatively find that cells can accurately self-adapt propulsive forces to overcome heterogeneous ECMs via a resistance-triggered positive feedback mechanism, dominated by polymerization-induced actin filament bending and the bending-regulated actin-Arp2/3 binding. However, for high resistance regions, resistance triggers a negative feedback, hindering branched filament assembly, which adapts cellular morphologies to circumnavigate the obstacles. Strikingly, the synergy of the two opposite feedbacks not only empowers the cell with both powerful and flexible migratory capabilities to deal with complex ECMs but also enables efficient utilization of intracellular proteins by the cell. In addition, we identify that the nature of cell migration velocity depending on ECM history stems from the inherent temporal hysteresis of cytoskeleton remodeling. We also show that directional cell migration is dictated by the competition between the local stiffness of ECMs and the local polymerizing rate of actin network caused by chemotactic cues. Our results reveal that it is the polymerization force–regulated actin filament–Arp2/3 complex binding interaction that dominates self-adaptive cell migrations in complex ECMs, and we provide a predictive theory and a spatiotemporal multiscale modeling system at the protein level.

Purpose: To assess ocular rigidity using dynamic optical coherence tomography (OCT) videos in glaucomatous and healthy subjects, and to evaluate how ocular rigidity correlates with biomechanical and morphological characteristics of the human eye.Methods: Ocular rigidity was calculated using Friedenwald's empirical equation which estimates the change in intraocular pressure (IOP) produced by volumetric changes of the eye due to choroidal pulsations with each heartbeat. High-speed OCT video was utilized to non-invasively measure changes in choroidal volume through time-series analysis. A control-case study design was based on 23 healthy controls and 6 glaucoma cases. Multiple diagnostic modalities were performed during the same visit including Spectralis OCT for nerve head video, Pascal Dynamic Contour Tonometry for IOP and ocular pulse amplitude (OPA) measurement, Corvis ST for measuring dynamic biomechanical response, and Pentacam for morphological characterization.Results: Combining glaucoma and healthy cohorts (n = 29), there were negative correlations between ocular rigidity and axial length (Pearson R = −0.53, p = 0.003), and between ocular rigidity and anterior chamber volume (R = −0.64, p = 0.0002). There was a stronger positive correlation of ocular rigidity and scleral stiffness (i.e., stiffness parameter at the highest concavity [SP-HC]) (R = 0.62, p = 0.0005) compared to ocular rigidity and corneal stiffness (i.e., stiffness parameter at the first applanation [SP-A1]) (R = 0.41, p = 0.033). In addition, there was a positive correlation between ocular rigidity and the static pressure-volume ratio (P/V ratio) (R = 0.72, p < 0.0001).Conclusions: Ocular rigidity was non-invasively assessed using OCT video and OPA in a clinic setting. The significant correlation of ocular rigidity with biomechanical parameters, SP-HC and P/V ratio, demonstrated the validity of the ocular rigidity measurement. Ocular rigidity is driven to a greater extent by scleral stiffness than corneal stiffness. These in vivo methods offer an important approach to investigate the role of ocular biomechanics in glaucoma.