Depth optimization system for multifocal intraocular lens implantation in combination with dynamic ocular pressure monitoring

Abstract

This invention relates to the field of surgical planning technology, specifically to a multifocal intraocular lens (IOL) implantation depth optimization system combined with dynamic intraocular pressure monitoring. This system acquires dynamic parameters such as the suspensory ligament hysteresis ratio and vibration energy transmission coefficient, constructs a dual relaxation mechanical model incorporating macroscopic stiffness attenuation and microscopic wrinkle interlocking, introduces dynamic simulation modulated by the energy transmission coefficient, and uses time-series simulation to model the steady-state settlement distance of the lens after overcoming interlocking resistance driven by physiological fluctuations. The refractive drift is acquired and commands are output through the optical convergence-divergence formula. This invention combines patient-specific rheological parameters with suspensory ligament relaxation dynamics simulation to more accurately quantify the possible steady-state settlement distance of the lens postoperatively, improving the predictive accuracy of postoperative refractive outcomes. It provides a more precise depth optimization scheme for preoperative planning of multifocal IOL implantation under complex ocular conditions, ensuring postoperative refractive correction effects.

Description

Technical Field

[0001] This invention relates to the field of surgical planning technology, and more specifically to a multifocal intraocular lens implantation depth optimization system that incorporates dynamic intraocular pressure monitoring. Background Technology

[0002] In the field of ophthalmic refractive cataract surgery, the visual quality of multifocal intraocular lenses is highly dependent on the stability of the lens's axial position within the eye after surgery. Typically, lens power calculations rely on static anatomical parameters such as axial length and corneal curvature to predict the effective lens position (ELP) after surgery, assuming that the capsular bag environment is relatively stable and the lens position is determined solely by anatomical structures.

[0003] However, in clinical practice, some patients with high myopia or long axial lengths experience unpredictable hyperopic drift post-surgery. This drift is closely related to the rheological properties of ocular tissues at the biomechanical level. In these patients, suspensory ligament laxity reduces the lens's centering tension and causes microscopic folds in the capsular bag equator due to tension loss, forming a mechanical interlock. Simultaneously, transient intraocular pressure fluctuations generated by daily physiological activities such as blinking and eye movements act as an external energy source, conducted through the viscoelastic eyeball walls. When this energy accumulates and overcomes the interlocking resistance, the lens sinks posteriorly. Ignoring this dynamic positional change caused by the coupling of suspensory ligament laxity, microscopic interlocking, and dynamic intraocular pressure fluctuations can lead to refractive prediction errors. Summary of the Invention

[0004] To address the technical problem in existing technologies that neglect dynamic positional changes caused by the coupling of suspensory ligament relaxation, microscopic interlocking, and dynamic intraocular pressure fluctuations, leading to refractive prediction errors, the present invention aims to provide a multifocal intraocular lens implantation depth optimization system combined with dynamic intraocular pressure monitoring. The specific technical solution adopted is as follows: This invention provides a multifocal intraocular lens implantation depth optimization system combined with dynamic intraocular pressure monitoring, the system comprising: The rheological parameter analysis module is used to acquire the video stream of the tested eye under air pulse; determine the suspensory ligament hysteresis ratio by the deviation of corneal and lens responses in the video stream; determine the vibration energy transmission coefficient by the amplitude attenuation characteristics of eyeball wall oscillations in the video stream; and obtain the vitreous cavity dilation factor based on ocular biometric data. The lens settling simulation module is used to define the quantitative impact of suspensory ligament relaxation on elastic constraints and capsular folds by using the suspensory ligament hysteresis ratio, and to obtain the capsular centering stiffness and fold friction work threshold; the module also uses the influence of the vitreous cavity expansion factor on the pressure of the posterior chamber fluid to determine the posterior pressure gradient force. Through time-series simulation, the basic external mechanical energy of physiological fluctuations is modulated by the vibration energy transmission coefficient to generate instantaneous kinetic energy. By comparing the gating mechanism of instantaneous kinetic energy with the threshold of wrinkle friction work, the steady-state settlement distance generated by the lens after overcoming micro-interlocking resistance and being affected by the backward pressure gradient force is iteratively analyzed. The drift output module is used to obtain the drift amount based on the steady-state settlement distance using the optical convergence formula and output optimization instructions.

[0005] Furthermore, the method for obtaining the suspensory ligament hysteresis ratio includes: The dynamic displacement trajectories of the corneal vertex and the center point of the anterior surface of the lens are obtained from the video stream; the time difference between the moment when the corneal vertex and the center point of the anterior surface of the lens reach their maximum displacement in the dynamic displacement trajectory is calculated; the ratio of the time difference to the expected baseline lag time is used as the suspensory ligament lag ratio.

[0006] Furthermore, the method for obtaining the vibration energy conduction coefficient includes: The corneal vertex amplitude sequence during the free oscillation phase of the eyeball after the air pulse is unloaded is extracted; the corneal vertex amplitude sequence is fitted using an exponential decay model to obtain the oscillation decay coefficient; the ratio of the expected baseline decay coefficient to the oscillation decay coefficient is used as the vibration energy transmission coefficient.

[0007] Furthermore, the method for obtaining the vitreous cavity dilation factor includes: The axial length of the examined eye is determined using ocular biometric data. When the axial length is greater than the baseline axial length, the difference between the axial length and the baseline axial length is normalized to obtain the vitreous cavity dilation factor. Otherwise, the preset minimum factor is used as the vitreous cavity dilation factor.

[0008] Furthermore, the method for obtaining the centering stiffness of the bag includes: The centering stiffness of the capsule is obtained by utilizing the inverse negative correlation between the hysteresis ratio of the suspensory ligament and the expected reference capsule stiffness constant.

[0009] Furthermore, the method for obtaining the wrinkle friction work threshold includes: Based on the expected baseline frictional work constant, a power-law positive correlation between the wrinkle frictional work threshold and the suspensory ligament hysteresis ratio is established, and the wrinkle frictional work threshold is calculated.

[0010] Furthermore, the method for obtaining the backward pressure gradient force includes: By using the vitreous cavity dilation factor to linearly modulate the expected baseline posterior chamber pressure constant, a posterior pressure gradient force pointing towards the retina is obtained.

[0011] Furthermore, the method of modulating the basic external mechanical energy to simulate physiological fluctuations using the vibration energy conduction coefficient to generate instantaneous kinetic energy includes: At each sampling moment during the simulation process, the instantaneous kinetic energy at the sampling moment is obtained by combining the reference external mechanical energy and vibration energy transmission coefficient, as well as random disturbance variables that follow a preset distribution.

[0012] Furthermore, the method for obtaining the steady-state settlement distance includes: Set the initial displacement of the lens position during the simulation process; for each sampling moment, when the instantaneous kinetic energy is less than or equal to the wrinkle friction work threshold, use the displacement at the current sampling moment as the displacement at the next sampling moment. When the instantaneous kinetic energy is greater than the threshold of the wrinkle friction work, the product of the displacement at the current sampling moment and the centering stiffness of the bag is used as the elastic restoring force; after calculating the difference between the backward pressure gradient force and the elastic restoring force, the product of the difference and the reference unit slip coefficient is used as the displacement change; combining the displacement at the current sampling moment and the displacement change, the displacement at the next sampling moment is obtained. After completing the simulation for a preset number of iterations, the displacement values ​​at the end of all simulation processes for a continuous number of sampling times are combined to obtain the steady-state settlement distance.

[0013] Furthermore, the step of obtaining the drift amount using the optical convergence-divergence formula based on the steady-state settlement distance and outputting optimization instructions includes: The expected baseline retinal convergence is obtained by substituting the lens geometrically predicted position into the optical convergence formula; the corrected retinal convergence is obtained by substituting the position after correcting the lens geometrically predicted position with the steady-state settling distance into the optical convergence formula; the deviation between the corrected retinal convergence and the expected baseline retinal convergence is used as the drift amount. The reverse compensation degree is generated and output based on the drift amount.

[0014] The present invention has the following beneficial effects: This invention constructs a dual-relaxation mechanical model by acquiring dynamic parameters such as the suspensory ligament hysteresis ratio and vibration energy transmission coefficient. This model incorporates both macroscopic stiffness attenuation and microscopic wrinkle interlocking. By decoupling the competing effects of suspensory ligament relaxation on decreased macroscopic centering ability and increased microscopic interlocking resistance, it avoids the problem of single-trend predictions being unable to adapt to complex relaxation states. Simultaneously, it introduces dynamic simulation modulated by the energy transmission coefficient, using time-series simulation to model the steady-state deposition distance of the lens after overcoming interlocking resistance driven by physiological fluctuations. This transforms the cumulative effect of postoperative random physiological fluctuations on lens position into a quantifiable physical deposition value. Finally, the refractive drift is acquired through the optical convergence-divergence formula, and targeted optimization instructions are output. This allows for more accurate prediction of postoperative hyperopia drift in highly myopic patients, effectively offsetting refractive errors caused by postoperative lens deposition. This invention combines patient-specific rheological parameters with suspensory ligament relaxation dynamics simulation to more accurately quantify the possible steady-state deposition distance of the lens after surgery, improving the prediction accuracy of postoperative refractive results. It provides a more precise depth optimization scheme for preoperative planning of multifocal intraocular lens implantation under complex ocular conditions, ensuring postoperative refractive correction effects. Attached Figure Description

[0015] To more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0016] Figure 1 This is a structural diagram of a multifocal intraocular lens implantation depth optimization system combined with dynamic intraocular pressure monitoring, provided as an embodiment of the present invention. Detailed Implementation

[0017] To further illustrate the technical means and effects adopted by the present invention to achieve its intended purpose, the following, in conjunction with the accompanying drawings and preferred embodiments, details the specific implementation, structure, features, and effects of a multifocal intraocular lens implantation depth optimization system combined with dynamic intraocular pressure monitoring proposed according to the present invention. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.

[0018] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0019] The following description, in conjunction with the accompanying drawings, details a specific scheme for a multifocal intraocular lens implantation depth optimization system combined with dynamic intraocular pressure monitoring provided by the present invention.

[0020] Please see Figure 1 The diagram shows a structural diagram of a multifocal intraocular lens implantation depth optimization system combined with dynamic intraocular pressure monitoring according to an embodiment of the present invention. The system includes: a rheological parameter analysis module 101, a lens settling simulation module 102, and a drift output module 103.

[0021] The rheological parameter analysis module 101 is used to acquire the video stream of the tested eye under an air pulse; determine the suspensory ligament hysteresis ratio by the deviation of the corneal and lens responses in the video stream; determine the vibration energy transmission coefficient by the amplitude attenuation characteristics of the eyeball wall oscillation in the video stream; and obtain the vitreous cavity dilation factor based on ocular biometric data.

[0022] A standardized, fixed-distance air pulse is applied to the examined eye using a non-contact visual ocular biomechanical analyzer. Simultaneously, the device's built-in high-speed camera unit is activated. In one specific embodiment of this invention, throughout the entire process of the air pulse acting on the examined eye, dynamic tomographic imaging of the anterior segment of the eye is performed at a sampling frequency of no less than 4000 frames per second. Continuous dynamic ocular image data is obtained through sampling. The image data undergoes preprocessing such as noise reduction and frame sequence calibration to obtain a video stream suitable for subsequent analysis. It should be noted that the non-contact visual ocular biomechanical analyzer acquisition and the frame synchronization control preprocessing of the high-speed camera are existing conventional technologies and will not be elaborated upon here.

[0023] Since the physiological function of the suspensory ligament is to maintain the tension balance and positional stability of the lens within the capsular bag, when the suspensory ligament becomes loose or ruptured, the mechanical response of the lens to external transient impact forces will lag behind the deformation of the cornea. The degree of loosening of the suspensory ligament determines the lag in the dynamic response of the lens to external disturbances.

[0024] In this embodiment of the invention, the dynamic displacement trajectories of the corneal apex and the center point of the anterior surface of the lens are acquired in the video stream. The horizontal axis of the trajectory represents the sampling time, and the vertical axis represents the posterior displacement of the anatomical structure relative to its initial position. The displacement trajectory of the corneal apex represents the direct effect of external impact force, and the displacement trajectory of the center point of the anterior surface of the lens represents the hysteretic response after transmission through the suspensory ligaments. The time difference between the moment when the corneal apex and the center point of the anterior surface of the lens reach their maximum displacement in the dynamic displacement trajectory is calculated. A larger time difference indicates a weaker constraint of the suspensory ligaments on the lens and a higher degree of relaxation.

[0025] Therefore, the ratio of the time difference to the expected baseline lag time is used as the suspensory ligament lag ratio. The larger the suspensory ligament lag ratio, the more severe the relaxation of the suspensory ligament and the weaker the centering force on the lens. The expected baseline lag time is a constant obtained based on statistical analysis of ocular data from healthy individuals and can be adjusted according to updates in clinical testing data.

[0026] Because the eyeball walls, such as the sclera and cornea, possess bioviscoelasticity, this property causes the eyeball to exhibit damped oscillatory behavior after being subjected to external mechanical stimuli. The damping characteristics of the eyeball walls determine the proportion of externally input kinetic energy, such as the force generated by blinking or eyeball rotation, that is dissipated, and the proportion that can penetrate the eyeball walls and be transmitted to the suspensory ligament-capsule complex, thereby driving the lens to shift. The viscoelasticity of the eyeball walls determines the transmission loss of external mechanical vibrations; the greater the damping, the lower the energy transmission efficiency.

[0027] In this embodiment of the invention, the corneal vertex amplitude sequence during the free oscillation phase of the eyeball after the air pulse is unloaded is extracted. After the air pulse is unloaded during the free oscillation phase, the air pressure applied to the examined eye is stopped. The free oscillation phase is the natural vibration phase of the eyeball wall due to its own viscoelasticity without external excitation. The amplitude is the displacement value of the corneal vertex relative to the equilibrium position in this phase. The amplitude sequence is a continuous data set of corneal vertex amplitude at different sampling times.

[0028] An exponential decay model was used to fit the corneal apex amplitude sequence to obtain the oscillation decay coefficient, which directly characterizes the strength of the eyeball wall's damping energy dissipation capacity. As an example, the expression for the exponential decay model is: In the formula, Represented as Amplitude at time, This is represented as the initial amplitude. It is represented as a negative exponential function with the natural constant as the base. This is represented by the oscillation decay coefficient. The oscillation decay coefficient represents the decay rate of eyeball wall oscillations. The larger the value, the stronger the damping energy dissipation capacity of the eyeball wall, and the greater the transmission loss of external energy.

[0029] Furthermore, the ratio of the expected baseline attenuation coefficient to the oscillation attenuation coefficient is used as the vibration energy transmission coefficient. A larger ratio indicates higher energy transfer efficiency. Since the eyeball wall always exhibits damping energy dissipation characteristics, the oscillation attenuation coefficient is always greater than 0; therefore, the denominator of the ratio cannot be zero to ensure the validity of the calculation results. In this embodiment of the invention, the expected baseline attenuation coefficient is statistically obtained from the average oscillation attenuation coefficient of the eyeball wall in healthy individuals and can be adjusted according to updates in clinical testing data.

[0030] Elongation of the axial length of the eye due to pathological factors such as high myopia is mainly manifested as axial expansion of the vitreous cavity. This change in anatomical structure not only stretches the suspensory ligaments but also creates a larger fluid volume in the posterior chamber region, thus forming a potential pressure gradient, or anatomical bias, pointing towards the retina from a biomechanical perspective. The axial length of the vitreous cavity determines the distribution of pressure in the posterior chamber.

[0031] In one specific embodiment of the present invention, an optical biometric instrument based on optical coherence tomography (OCT) technology is used to acquire ocular biometric data and determine the axial length of the examined eye. This device can achieve non-invasive and accurate measurement, directly outputting the measured axial length data of the examined eye. The baseline standard axial length is a reference value for axial length under normal physiological conditions, which can be set to 24.0 mm in this embodiment. This value can be clinically adjusted according to group characteristics such as race and age, and is not limited here.

[0032] When the axial length is greater than the baseline axial length, it indicates that the examined eye has the characteristic of axial dilation of the vitreous cavity. The degree of dilation is positively correlated with the difference between the axial length and the baseline value. The difference between the axial length and the baseline axial length is normalized to obtain the vitreous cavity dilation factor. Specifically, the ratio of the difference to the baseline axial length is used as the vitreous cavity dilation factor. Normalization is achieved by dividing by the baseline axial length, thereby eliminating the influence of dimensions.

[0033] Otherwise, if the axial length is less than or equal to the baseline standard axial length, it indicates that the examined eye has no pathological vitreous cavity dilation and no additional pressure gradient pointing towards the retina is formed in the posterior chamber region. The preset minimum factor is used as the vitreous cavity dilation factor, which is used to characterize the posterior chamber pressure distribution characteristics in the non-dilation state. In the embodiments of the present invention, the preset minimum factor is set to 0, which can prevent the generation of no additional posterior pressure gradient force in the subsequent model. The implementer can adjust it according to the specific implementation scenario, and there is no restriction here.

[0034] At this point, the extraction of three rheological parameters of the examined eye is complete. The obtained suspensory ligament hysteresis ratio, vibration energy transmission coefficient, and vitreous cavity expansion factor will serve as the core input parameters for subsequent lens sedimentation simulation.

[0035] The lens settling simulation module 102 is used to define the quantitative impact of suspensory ligament relaxation on elastic constraints and capsular folds by using the suspensory ligament hysteresis ratio, thereby obtaining the capsular centering stiffness and the fold friction work threshold; it uses the influence of the vitreous cavity expansion factor on the pressure of the posterior chamber fluid to determine the posterior pressure gradient force; through time-series simulation, it uses the vibration energy transmission coefficient to modulate the basic external mechanical energy simulating physiological fluctuations to generate instantaneous kinetic energy; by comparing the gating mechanism of instantaneous kinetic energy and fold friction work threshold, iteratively analyzes the steady-state settling distance of the lens after overcoming microscopic interlocking resistance under the influence of the posterior pressure gradient force.

[0036] Because the relaxation of the suspensory ligaments macroscopically leads to a decrease in the central stiffness of the capsule, but microscopically causes capsule wrinkling due to the lack of tension, thus generating a frictional work threshold, the degree of change of both is positively correlated with the degree of relaxation of the suspensory ligaments. The suspensory ligament hysteresis ratio can accurately characterize this degree of relaxation. Therefore, the suspensory ligament hysteresis ratio can be used to quantitatively define the central stiffness of the capsule and the wrinkle frictional work threshold, so as to realize the construction of patient-specific mechanical parameters.

[0037] In this embodiment of the invention, since the higher the degree of relaxation of the suspensory ligaments, the weaker their elastic constraint on the lens, the capsular bag centering stiffness changes inversely. The capsular bag centering stiffness is obtained by utilizing the inverse negative correlation between the suspensory ligament hysteresis ratio and the expected baseline capsular bag stiffness constant. The capsular bag centering stiffness characterizes the capsular bag's ability to maintain the lens at its geometric center. Specifically, the capsular bag centering stiffness is obtained by calculating the ratio of the expected baseline capsular bag stiffness constant to the suspensory ligament hysteresis ratio. The expected baseline capsular bag stiffness constant can be set to 0.8 N / m, which is the average centering stiffness value of the capsular bag in a healthy eye and can be adjusted according to updates in clinical testing data.

[0038] In this embodiment of the invention, since the higher the degree of relaxation of the suspensory ligament, the more obvious the capsule wrinkles, the frictional work threshold required to overcome interlocking increases non-linearly. Based on the expected benchmark frictional work constant, a power-law positive correlation between the wrinkle frictional work threshold and the suspensory ligament hysteresis ratio is established, and the wrinkle frictional work threshold is calculated. The wrinkle frictional work threshold can characterize the energy barrier required to trap the lens after the capsule relaxes and wrinkles. Here, the power law is an exponential relationship that characterizes the non-linear growth characteristics. The power law exponent can be set to 1.5, and the value is usually in the range of 1.2 to 2.0 to reflect the rapid increase of the frictional work threshold.

[0039] In one specific embodiment of the present invention, the expected reference friction work constant is multiplied by a power of the suspensory ligament hysteresis ratio, and the resulting product is used as the wrinkle friction work threshold. The expected reference friction work constant can be set to 1.2 × 10⁻⁶. -6 J, obtained based on statistical data from a healthy eye population, characterizes the basic surface frictional energy of the standard capsule material in a wrinkle-free state. As an example, the expression for the wrinkle frictional work threshold is: In the formula, This is expressed as the threshold of wrinkle friction work. This is expressed as the expected reference frictional work constant. Expressed as the hysteresis ratio of the suspensory ligaments. It is represented as the power-law exponent.

[0040] Furthermore, considering that an increase in the vitreous dilatation factor implies an increase in the posterior chamber fluid volume, thereby generating a pressure gradient pointing towards the retina, in this embodiment of the invention, the expected baseline posterior chamber pressure constant is linearly modulated using the vitreous dilatation factor to obtain a backward pressure gradient force pointing towards the retina, simulating the continuous thrust on the lens caused by anatomical structural bias due to axial elongation. Specifically, the sum of the value 1 and the vitreous dilatation factor is used as the gain coefficient, and the product of the expected baseline posterior chamber pressure constant and the gain coefficient is used as the backward pressure gradient force.

[0041] In this embodiment of the invention, the expected baseline posterior chamber pressure constant is obtained based on statistics from healthy eyes, representing the baseline of posterior chamber hydrostatic pressure under standard axial length, and is not limited thereto. As an example, the expression for the posterior pressure gradient force is: In the formula, Represented as the backward pressure gradient force, Expressed as the expected baseline atrial pressure constant, It is expressed as the vitreous cavity expansion factor. It is represented as the gain coefficient.

[0042] The discretized time-iteration method of time-series simulation can simulate the lens dynamics evolution driven by physiological fluctuations, reconstructing the lens deposition process from its initial position to its steady-state position after surgery. The simulation process involves discretizing the postoperative lens deposition window into several consecutive sampling times, and iteratively calculating the lens position change at each time point. In one specific embodiment of this invention, the postoperative lens deposition window is set to 30 days, and then the window is evenly divided into several sampling times, with a time interval of 1 hour. It should be noted that the number of divisions can be adjusted according to the simulation accuracy requirements; the duration of the deposition window and the number of sampling times can be flexibly set and are not limited here.

[0043] Since the axial displacement of the lens is driven by external mechanical energy transmitted through the eyeball wall, the basic external mechanical energy simulating physiological fluctuations is modulated using the vibration energy transmission coefficient to generate instantaneous kinetic energy, reflecting the effective driving energy actually acting on the lens at each sampling moment. In this embodiment of the invention, at each sampling moment during the simulation process, the instantaneous kinetic energy at the sampling moment is obtained by combining the baseline external mechanical energy and the vibration energy transmission coefficient, as well as random perturbation variables that follow a preset distribution. The instantaneous kinetic energy can dynamically change with the sampling moment, closely reflecting the randomness of physiological activities.

[0044] Among them, the random perturbation variable represents the energy fluctuation characteristics of physiological activities such as blinking and eye movement, follows a standard normal distribution, and its value can be normalized to the interval of 0 to 1. Specifically, it is a dimensionless coefficient randomly generated at each sampling time, and the baseline external mechanical energy is set to 2.0 × 10⁻⁶. -6 J represents the average mechanical energy input level generated by normal physiological activities. Therefore, in this embodiment of the invention, the product of the reference external mechanical energy, the vibration energy transmission coefficient, and the random disturbance variable is taken as the instantaneous kinetic energy.

[0045] Instantaneous kinetic energy can be used for interlocking gating. The gating mechanism determines whether the lens breaks through the interlocking resistance of the capsule folds at the current sampling moment. This determination result is used to decide whether the lens has shifted at that moment. In this embodiment of the invention, the initial displacement of the lens position during the simulation process is set. With the geometrically predicted position of the lens as the origin, the initial displacement is set to 0 mm, representing the initial state in which the lens has not settled.

[0046] For each sampling moment, when the instantaneous kinetic energy is less than or equal to the wrinkle friction work threshold, it indicates that the input kinetic energy is insufficient to overcome the mechanical interlock barrier of the capsule wrinkles. The lens remains in the same position, and the displacement at the current sampling moment is used as the displacement at the next sampling moment, so as to achieve a changeless update of the lens position in this iteration step.

[0047] When the instantaneous kinetic energy exceeds the threshold of the wrinkle friction work, it indicates that the capsular bag interlocking state is released, the lens enters the sliding mode, and is driven by the net force to sink backward. First, the product of the displacement at the current sampling moment and the capsular bag centering stiffness is taken as the elastic restoring force. The elastic restoring force is the reaction force of the capsular bag attempting to pull the lens back to the geometric center, and it has a linear variation characteristic that the larger the displacement, the stronger the elastic restoring force.

[0048] Next, after calculating the difference between the backward pressure gradient force and the elastic restoring force, the product of this difference and the reference unit slip coefficient is used as the displacement change. By subtracting the difference, the net force driving the lens slip is measured, and finally, the single-time displacement value of the lens under the current net force is obtained. The reference unit slip coefficient can be taken as 0.02 mm / N, which represents the single-time displacement of the lens under a unit net force and is determined by the viscous resistance of the fluid within the capsule.

[0049] Finally, by combining the displacement and displacement change at the current sampling time, the displacement at the next sampling time is obtained, and the sedimentation position of the lens is updated. In this embodiment of the invention, the sum of the displacement and displacement change at the current sampling time is used as the displacement at the next sampling time.

[0050] The simulation process involves iterative calculations at all sampling times sequentially according to the aforementioned rules. Therefore, after completing the simulation for the preset number of iterations, a sequence of lens displacement evolution at each sampling time can be obtained, reflecting the dynamic sedimentation process of the lens. In this embodiment of the invention, the preset number of iterations can be determined based on the duration of the postoperative healing window and the simulation step size, consistent with the number of sampling times. For example, it can be set to the number of iterations corresponding to one sampling time per hour for 30 days post-surgery. The specific value is not limited here.

[0051] In this embodiment of the invention, the steady-state settlement distance is obtained by fusing the displacement values ​​at a consecutive number of sampling moments at the end of all simulation processes, thus eliminating the end-position jitter caused by random disturbances and ensuring the stability of the results. For example, the consecutive number can be 24, in which case the displacement values ​​at the last 24 consecutive sampling moments in the evolution sequence are selected as the end data. The displacement value at the end has tended to be stable, with minimal fluctuation.

[0052] Understandably, the simulated displacement needs to conform to the actual anatomical space limitations of the eyeball. Therefore, based on the statistical characteristics of the anterior chamber depth of healthy eyeballs through anatomical analysis, a preset limit displacement value is set. When the cumulative displacement reaches the limit displacement value during the simulation, the preset limit displacement value is used as a cutoff value to constrain the displacement and ensure the authenticity of the simulated displacement.

[0053] In this embodiment of the invention, the arithmetic mean of the displacements at a consecutive number of sampling moments at the end of all simulation processes can be used as the steady-state settlement distance. In other embodiments of the invention, the steady-state settlement distance can also be obtained by statistically averaging the displacement values ​​corresponding to the last 10% of sampling moments at the end of the evolution sequence. The selection process can be adjusted by the implementer according to the specific implementation scenario, and is not limited here.

[0054] This completes the time-series simulation of the entire lens deposition process, and the obtained steady-state deposition distance will serve as the core physical parameter for subsequent refractive drift analysis and compensation.

[0055] The drift output module 103 is used to obtain the drift amount based on the steady-state settlement distance using the optical convergence formula and output optimization instructions.

[0056] Since the lens settling distance changes the actual optical focal length of the intraocular lens relative to the retina, resulting in hyperopic drift not included in conventional geometric formulas, the Gaussian optical convergence formula is used to map the lens settling distance into the amount of settling-induced refractive drift, thereby providing optimized suggestions for preoperative intraocular lens selection.

[0057] In this embodiment of the invention, the expected baseline retinal convergence is obtained by substituting the lens geometric prediction position into the optical convergence formula. The lens geometric prediction position refers to the effective lens position calculated using conventional third- or fourth-generation IOL calculation formulas, such as SRK / T and Barrett Universal II, based on static parameters such as axial length and corneal curvature. It should be noted that the specific method for obtaining the geometric prediction position can be chosen by those skilled in the art based on common knowledge, and will not be elaborated here.

[0058] An optional optical convergence formula is based on the Gaussian thin lens model, which correlates parameters such as axial length, lens position, corneal refractive power, and intraocular lens refractive power to calculate the convergence of light rays after refraction through the cornea and intraocular lens onto the retina. Its expression is: In the formula, Represented as aggregation degree, It is expressed as the refractive index of aqueous humor, usually taken as 1.336, which is a commonly used constant in ophthalmology. This is expressed as the axial length of the examined eye. This is represented as the predicted geometric location of the lens. This represents the refractive power of the intraocular lens to be implanted.

[0059] The corrected retinal convergence is then obtained by substituting the steady-state settling distance into the formula for the corrected lens geometric prediction position. This corrected position is the sum of the steady-state settling distance and the lens geometric prediction position, representing the actual axial position of the lens relative to the retina after postoperative biomechanical settling. This corrected position is then used to calculate the corresponding retinal convergence. It should be noted that because the posterior settling of the lens shortens the distance between it and the retina, the corrected convergence will be greater than the expected baseline retinal convergence, clinically manifesting as hyperopia.

[0060] The deviation between the corrected retinal convergence and the expected baseline retinal convergence is used as the drift amount. Specifically, the difference between the corrected retinal convergence and the expected baseline retinal convergence is used as the drift amount. The drift amount is the refractive drift amplitude caused by lens deposition, which characterizes the hyperopia drift caused by the lens deposition causing the image focus to fall behind the retina. The larger the value, the more significant the hyperopia deviation.

[0061] Finally, a reverse compensation value is generated and output based on the drift amount. In this embodiment of the invention, the sedimentation-induced refractive drift amount can be inverted to obtain a preoperative myopia reserve power that is equal in value but opposite in sign to the drift amount. For example, if the drift amount is +0.50D, indicating hyperopia drift, a negative reverse compensation power of -0.50D is generated. By outputting the reverse compensation power, it is suggested that doctors use this negative reserve power as the target refractive power when selecting the intraocular lens power. This means that immediately after surgery, the patient will be in a state of mild myopia. As the lens gradually sinks backward under biomechanical action after surgery, the patient's actual refractive power will automatically drift to emmetropia, thereby achieving long-term precise vision correction.

[0062] In summary, this invention constructs a dual relaxation mechanical model that incorporates macroscopic stiffness attenuation and microscopic wrinkle interlocking by acquiring dynamic parameters such as the suspensory ligament hysteresis ratio and vibration energy transmission coefficient. This model decouples the competing effects of suspensory ligament relaxation on decreased macroscopic centering ability and increased microscopic interlocking resistance, avoiding the problem of single-trend prediction being unable to adapt to complex relaxation states. Simultaneously, dynamic simulation modulated by the energy transmission coefficient is introduced, using time-series simulation to model the steady-state deposition distance of the lens after overcoming interlocking resistance driven by physiological fluctuations. This transforms the cumulative effect of postoperative random physiological fluctuations on lens position into a quantifiable physical deposition value. Finally, the refractive drift is obtained through the optical convergence-divergence formula, and targeted optimization instructions are output, enabling more accurate prediction of postoperative hyperopia drift in highly myopic patients and effectively offsetting refractive errors caused by postoperative lens deposition. This invention combines patient-specific rheological parameters with suspensory ligament relaxation dynamics simulation to more accurately quantify the possible steady-state deposition distance of the lens after surgery, improving the prediction accuracy of postoperative refractive results. It provides a more precise depth optimization scheme for preoperative planning of multifocal intraocular lens implantation under complex ocular conditions, ensuring postoperative refractive correction effects.

[0063] It should be noted that the order of the above embodiments of the present invention is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. The processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0064] The various embodiments in this specification are described in a progressive manner. The same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on describing the differences from other embodiments.

Claims

1. A multifocal intraocular lens implantation depth optimization system combined with dynamic intraocular pressure monitoring, characterized in that, The system includes: The rheological parameter analysis module is used to acquire the video stream of the tested eye under air pulse; determine the suspensory ligament hysteresis ratio by the deviation of corneal and lens responses in the video stream; determine the vibration energy transmission coefficient by the amplitude attenuation characteristics of eyeball wall oscillations in the video stream; and obtain the vitreous cavity dilation factor based on ocular biometric data. The lens settling simulation module is used to define the quantitative impact of suspensory ligament relaxation on elastic constraints and capsular folds by using the suspensory ligament hysteresis ratio, and to obtain the capsular centering stiffness and fold friction work threshold; the module also uses the influence of the vitreous cavity expansion factor on the pressure of the posterior chamber fluid to determine the posterior pressure gradient force. Through time-series simulation, the basic external mechanical energy of physiological fluctuations is modulated by the vibration energy transmission coefficient to generate instantaneous kinetic energy. By comparing the gating mechanism of instantaneous kinetic energy with the threshold of wrinkle friction work, the steady-state settlement distance generated by the lens after overcoming micro-interlocking resistance and being affected by the backward pressure gradient force is iteratively analyzed. The drift output module is used to obtain the drift amount based on the steady-state settlement distance using the optical convergence formula and output optimization instructions.

2. The multifocal intraocular lens implantation depth optimization system combined with dynamic intraocular pressure monitoring according to claim 1, characterized in that, The method for obtaining the suspensory ligament hysteresis ratio includes: The dynamic displacement trajectories of the corneal vertex and the center point of the anterior surface of the lens are obtained from the video stream; the time difference between the moment when the corneal vertex and the center point of the anterior surface of the lens reach their maximum displacement in the dynamic displacement trajectory is calculated; the ratio of the time difference to the expected baseline lag time is used as the suspensory ligament lag ratio.

3. The multifocal intraocular lens implantation depth optimization system combined with dynamic intraocular pressure monitoring according to claim 1, characterized in that, The method for obtaining the vibration energy conduction coefficient includes: The corneal vertex amplitude sequence during the free oscillation phase of the eyeball after the air pulse is unloaded is extracted; the corneal vertex amplitude sequence is fitted using an exponential decay model to obtain the oscillation decay coefficient; the ratio of the expected baseline decay coefficient to the oscillation decay coefficient is used as the vibration energy transmission coefficient.

4. The multifocal intraocular lens implantation depth optimization system combined with dynamic intraocular pressure monitoring according to claim 1, characterized in that, The method for obtaining the vitreous cavity expansion factor includes: The axial length of the examined eye is determined using ocular biometric data. When the axial length is greater than the baseline axial length, the difference between the axial length and the baseline axial length is normalized to obtain the vitreous cavity dilation factor. Otherwise, the preset minimum factor is used as the vitreous cavity dilation factor.

5. The multifocal intraocular lens implantation depth optimization system combined with dynamic intraocular pressure monitoring according to claim 1, characterized in that, The method for obtaining the centering stiffness of the bag includes: The centering stiffness of the capsule is obtained by utilizing the inverse negative correlation between the hysteresis ratio of the suspensory ligament and the expected reference capsule stiffness constant.

6. The multifocal intraocular lens implantation depth optimization system combined with dynamic intraocular pressure monitoring according to claim 1, characterized in that, The method for obtaining the wrinkle friction work threshold includes: Based on the expected baseline frictional work constant, a power-law positive correlation between the wrinkle frictional work threshold and the suspensory ligament hysteresis ratio is established, and the wrinkle frictional work threshold is calculated.

7. The multifocal intraocular lens implantation depth optimization system combined with dynamic intraocular pressure monitoring according to claim 1, characterized in that, The method for obtaining the backward pressure gradient force includes: By using the vitreous cavity dilation factor to linearly modulate the expected baseline posterior chamber pressure constant, a posterior pressure gradient force pointing towards the retina is obtained.

8. The multifocal intraocular lens implantation depth optimization system combined with dynamic intraocular pressure monitoring according to claim 1, characterized in that, The method of modulating the basic external mechanical energy to simulate physiological fluctuations using the vibration energy conduction coefficient to generate instantaneous kinetic energy includes: At each sampling moment during the simulation process, the instantaneous kinetic energy at the sampling moment is obtained by combining the reference external mechanical energy and vibration energy transmission coefficient, as well as random disturbance variables that follow a preset distribution.

9. The multifocal intraocular lens implantation depth optimization system combined with dynamic intraocular pressure monitoring according to claim 1, characterized in that, The method for obtaining the steady-state settlement distance includes: Set the initial displacement of the lens position during the simulation process; for each sampling moment, when the instantaneous kinetic energy is less than or equal to the wrinkle friction work threshold, use the displacement at the current sampling moment as the displacement at the next sampling moment. When the instantaneous kinetic energy is greater than the threshold of the wrinkle friction work, the product of the displacement at the current sampling moment and the centering stiffness of the bag is used as the elastic restoring force; after calculating the difference between the backward pressure gradient force and the elastic restoring force, the product of the difference and the reference unit slip coefficient is used as the displacement change; combining the displacement at the current sampling moment and the displacement change, the displacement at the next sampling moment is obtained. After completing the simulation for a preset number of iterations, the displacement values ​​at the end of all simulation processes for a continuous number of sampling times are combined to obtain the steady-state settlement distance.

10. The multifocal intraocular lens implantation depth optimization system combined with dynamic intraocular pressure monitoring according to claim 1, characterized in that, The process of obtaining drift amount using the optical convergence-divergence formula based on steady-state settlement distance and outputting optimization instructions includes: The expected baseline retinal convergence is obtained by substituting the lens geometrically predicted position into the optical convergence formula; the corrected retinal convergence is obtained by substituting the position after correcting the lens geometrically predicted position with the steady-state settling distance into the optical convergence formula; the deviation between the corrected retinal convergence and the expected baseline retinal convergence is used as the drift amount. The reverse compensation degree is generated and output based on the drift amount.

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