Preferred intraocular lens selection based on ray tracing

Abstract

A system and method for selecting a preferred intraocular lens for implantation in an eye includes a controller having a processor and a tangible, non-transitory memory having instructions recorded thereon. The controller is in communication with a diagnostic module adapted to store pre-operative anatomical data of the eye as an eye model. The controller is configured to identify, via a prediction module, respective substitution post-operative variables for each of a plurality of intraocular lenses. Incorporating the respective substitution post-operative variables into the eye model generates a respective pseudophakic eye model for each of the plurality of intraocular lenses. A ray tracing module is run on each pseudophakic eye model to identify at least one respective metric of the plurality of intraocular lenses. A preferred intraocular lens is selected based on a comparison of the respective metrics.

Description

[Technical Field]

[0001] This disclosure relates, in general, to a system and method for selecting an intraocular lens for implantation in the eye. More specifically, this disclosure relates to selecting a preferred intraocular lens from a plurality of intraocular lenses based on ray tracing. Generally, the human lens is transparent, allowing light to pass through easily. However, due to various factors, areas within the lens can become cloudy and opaque, thus negatively affecting the quality of vision. Such a situation can be treated by cataract surgery. In cataract surgery, an artificial lens is selected for implantation in the patient's eye. In fact, cataract surgery is commonly performed worldwide. Today, various types of intraocular lenses are available in terms of both model (e.g., multifocal intraocular lenses that correct different ranges of vision) and refractive power, but it is not always clear what the optimal choice may be for a particular patient. Furthermore, the refractive power calculation formulas for intraocular lenses currently use limited preoperative diagnostic information and relatively simple optical analysis to recommend intraocular implantation prescriptions. [Overview of the Initiative] [Means for solving the problem]

[0002] Disclosed herein is a system and method for selecting a preferred intraocular lens for implantation into a target eye. The system includes a processor and a controller having tangible non-temporary memory on which instructions are stored. The controller communicates with a diagnostic module adapted to store preoperative anatomical data of the eye as an eye model. The system includes a predictive module and a ray tracing module, which can be selectively executed by the controller. The predictive module is adapted to identify each imputed postoperative variable of the eye, based in part on the preoperative anatomical data. The ray tracing module is adapted to calculate the propagation of light through the eye.

[0003] The controller is configured to identify the respective imputed postoperative variables for each of the multiple intraocular lenses via a prediction module. By incorporating each imputed postoperative variable into the eye model, a pseudophakic eye model is generated for each of the multiple intraocular lenses. The controller is configured to run a ray tracing module on each pseudophakic eye model to identify at least one respective metric for each of the multiple intraocular lenses. A preferred intraocular lens is selected from the multiple intraocular lenses at least partially based on a comparison of at least one respective metric. Each metric may be a point diffusion function. Each metric may be a modulation transfer function.

[0004] In some embodiments, performing a ray tracing module involves propagating a ray beam backward through the eye until it reaches a spot on the retina, with the ray beam parallel to the optical axis of the eye before entering the eye from the anterior surface of the cornea. Here, each metric may be based on the spatial distribution of the ray beam at the spot on the retina. The ray tracing module may be adapted to use the respective refractive indices within the eye, applicable to light with a wavelength of 550 nanometers. The ray tracing module may be adapted to use the respective refractive indices within the eye, applicable to multiple wavelengths across the visible portion of the spectrum.

[0005] In some embodiments, performing a ray tracing module involves generating a beam of light with a specific divergence at a spot on the fovea of ​​the eye that fully illuminates the pupil, and propagating the beam forward through the eye until it exits the anterior surface of the cornea, where each metric may be based on the spatial distribution of the beam after it exits the anterior surface of the cornea.

[0006] Preoperative anatomical data may include the axial length of the eye. Preoperative anatomical data may include the location and profile of the anterior and posterior surfaces of the cornea. Preoperative anatomical data may include the location, orientation, and size of the pupil in a three-dimensional coordinate system, with the pupil under light-adapted conditions. Each substituted postoperative variable of the eye may include the location and orientation of multiple intraocular lenses. Each substituted postoperative variable may include the location and orientation of at least one of the pupil and iris.

[0007] Disclosed herein is a method for selecting a preferred intraocular lens for implantation in the eye using a system having a processor and a controller having tangible non-temporary memory on which instructions are recorded. The method includes acquiring preoperative anatomical data of the eye via a diagnostic module and storing the preoperative anatomical data as an eye model. Via a prediction module, each of the respective substituted postoperative variables for a plurality of intraocular lenses is identified, based in part on the preoperative anatomical data.

[0008] The method involves generating a pseudophasic eye model for each of several intraocular lenses by incorporating each substituted postoperative variable into the eye model via a controller. A ray tracing module is adapted to compute the propagation of light through the eye, and the ray tracing module is selectively runnable by the controller. The method involves running the ray tracing module on each pseudophasic eye model to identify at least one respective metric for each of the several intraocular lenses. A preferred intraocular lens is selected from the several intraocular lenses at least partially based on a comparison of at least one respective metric.

[0009] The above-mentioned features and advantages of this disclosure, as well as other features and advantages, will be readily apparent from the following detailed description of the best mode for implementing this disclosure, in conjunction with the accompanying drawings. [Brief explanation of the drawing]

[0010] [Figure 1] Figure 1 is a schematic diagram of a system for selecting a preferred intraocular lens for implantation in the eye, comprising a controller and a ray tracing module. [Figure 2] Figure 2 is a schematic flowchart of the methods that can be performed by the controller in Figure 1. [Figure 3] Figure 3 is a schematic diagram showing an example of one implementation of the ray tracing module shown in Figure 1, according to the first embodiment. [Figure 4] Figure 4 is a schematic diagram showing an example of an implementation of the ray tracing module shown in Figure 1, according to the second embodiment. [Figure 5] Figure 5 is a schematic diagram of the point diffusion function graphs for multiple intraocular lenses. [Figure 6] Figure 6 is a schematic diagram of the point diffusion function graphs for multiple intraocular lenses. [Modes for carrying out the invention]

[0011] Referring to drawings where similar reference numbers point to similar components, Figure 1 schematically illustrates a system 10 for selecting a preferred intraocular lens 12 for implantation into the eye E of subject 14. The preferred intraocular lens 12 is selected from a plurality of intraocular lenses 16. Referring to Figure 1, the system 10 includes a controller C having at least one processor P and at least one memory M (or tangible non-temporary computer-readable storage medium) on which instructions for performing a method 100 for selecting a preferred intraocular lens 12 are recorded. Method 100 is shown in Figure 2 and will be described below with reference to it.

[0012] Referring to Figure 1, system 10 includes a diagnostic module 18 adapted to store preoperative anatomical data of eye E, which is stored as an eye model 20. Preoperative anatomical data may be obtained from at least one imaging device 22. System 10 may include a prediction module 24 and a ray tracing module 26, which can be selectively run by controller C. The prediction module 24 is adapted to infer postoperative anatomical parameters of eye E, at least partially based on the preoperative anatomical data. The ray tracing module 26 is adapted to calculate the propagation of light through eye E.

[0013] Referring to Figure 1, System 10 includes a lens selection module 28 that receives the output of a ray tracing module 26 for a set of intraocular lenses, i.e., multiple intraocular lenses 16, for investigation. This information allows the clinician to select the best model and / or refractive power to optimize visual performance. In outline, System 10 inputs preoperative anatomical data of the eye E about to undergo cataract surgery and identifies each of the multiple intraocular lenses 16 via a prediction module 24. Each of the imposed postoperative variables includes the postoperative location and orientation of each of the multiple intraocular lenses 16 and the iris / pupil complex.

[0014] Referring to Figure 1, each substituted postoperative variable is incorporated into the eye model 20 to generate each pseudophakic eye model 30 for each of the multiple intraocular lenses 16. Controller C is configured to run the ray tracing module 26 to identify at least one respective metric for each pseudophakic eye model 30. The ray tracing module 26 provides an assessment of the focusing ability of the pseudophakic eye. A preferred intraocular lens 12 is selected from the multiple intraocular lenses 16 based at least in part on a comparison of each at least one metric (hereinafter, "at least one"), respectively. System 10 offers the technical advantage of more accurately predicting retinal focus that matches the anatomical structure of the pseudophakic eye, leading to a better selection from the multiple intraocular lenses 16.

[0015] Referring to Figure 1, the system 10 may include a user interface 32 that can be operated by the user. The user interface 32 may include a touchscreen or other input device. The controller C may be configured to process signals to and from the user interface 32 and a display (not shown).

[0016] As shown in Figure 1, various components of system 10 may be configured to communicate via network 34. The diagnostic module 18, predictive module 24, ray tracing module 26, and lens selection module 28 may be integrated into controller C. Alternatively, the diagnostic module 18, predictive module 24, ray tracing module 26, and lens selection module 28 may be part of a remote server or cloud unit accessible to controller C via network 34. Network 34 may be a bus implemented in various ways, such as a serial communication bus in the form of a local area network. The local area network may include, but is not limited to, Controller Area Network (CAN), Flexible Data Rate Controller Area Network (CAN-FD), Ethernet, Wi-Fi, Bluetooth®, and other data connection forms. Other types of connections may be used.

[0017] Here, with reference to Figure 2, a flowchart of method 100 for selecting a preferred intraocular lens 12 is shown. Method 100 may be fully or partially performed by controller C in Figure 1. Method 100 does not need to be applied in the specific order described herein. Furthermore, it is understood that some blocks may be omitted. Method 100 begins in block 110.

[0018] Block 110 in FIG. 2 configures the controller C to obtain preoperative anatomical data of the eye E, which is stored as part of the eye model 20 in the diagnostic module 18. The preoperative anatomical data may include biometric data and may be obtained from at least one imaging device 22. The imaging device 22 may be a topography device, an ultrasonic machine, an optical coherence tomography machine, a magnetic resonance imaging machine, or other imaging devices available to those skilled in the art. The preoperative anatomical data can be obtained from a single image or multiple images.

[0019] An example of the preoperative image 40 is shown in FIG. 1. The preoperative image 40 can be obtained via ultrasound biomicroscopy. Ultrasound biomicroscopy may use a transducer with a relatively high frequency of about 35 MHz to 100 MHz and a tissue penetration depth of about 4 mm to 5 mm. Referring to FIG. 1, the preoperative anatomical data includes the position and orientation of each of the native lens 42 and iris 44. The orientation may include the inclination with respect to the XYZ coordinate system. The preoperative anatomical data includes the position, orientation, and size of the pupil 46 under photopic conditions. Photopic conditions refer to vision under well-illuminated conditions that mainly have functions due to cone cells in the eye. In some embodiments, the photopic conditions may be defined to include an adaptation level of 3 candela per square meter (cd / m 2 ) or more.

[0020] Referring to FIG. 1, the position of each of the native lens 42, iris 44, and pupil 46 can be specified three-dimensionally in the XYZ coordinate system along the X-axis and along the Y-axis and Z-axis. The XYZ coordinate system can be defined such that the X-axis is parallel to the visual axis A. Alternatively, the XYZ coordinate system can be defined such that the X-axis is parallel to another geometric or optical axis (not shown). Here, the eye model 20 includes the position and orientation of the visual axis A.

[0021] The eye model 20 includes a plurality of parameters P1...P NIt can be regarded as a three-dimensional model of a preoperative or phakic (including the natural lens) eye defined by [(representing preoperative anatomical data)]. Referring to FIG. 1, a plurality of parameters (or preoperative anatomical data) may include the lens thickness 48, the anterior chamber depth 50, and the corneal thickness 52. In addition, the eye model 20 within the diagnostic module 18 includes the refractive indices of various parts of the eye E. The diagnostic module 18 can be selectively executed to approximate or parameterize the surface of the eye E based on preoperative anatomical data and algorithms available to those skilled in the art. The eye model 20 of FIG. 1 may include the shape and location of the anterior corneal surface 54A and the posterior corneal surface 54B. The eye model 20 may further include the shape and location of the anterior lens surface 56 and the posterior lens surface 58. The preoperative anatomical data may include the axial length L of the eye E (shown in FIGS. 3 and 4). Since the eyeball typically has a substantially spherical shape, the eye model 20 may approximate the surface of the retina 60 from the axial length 58 (shown in FIG. 2).

[0022] Method 100 continues at block 120, where the controller C is configured to select a plurality of intraocular lenses 16 (see FIG. 1) for investigation for implantation into the subject 14. The plurality of intraocular lenses 16 may include a first IOL 16A and a second IOL 16B that may be single focus or multifocal lenses with varying refractive power. In some embodiments, the first IOL 16A is configured to provide better vision at a first distance range and the second IOL 16B is configured to provide better vision at a second distance range. Alternatively, the first IOL 16A may be an adaptive lens having a fluid-filled internal cavity that is fluid movable, thereby changing the thickness (and refractive power) of the first IOL 16A. It should be understood that the plurality of intraocular lenses 16 can take many different forms and include multiple and / or alternative components.

[0023] Method 100 proceeds from block 120 to block 130. Block 130 in Figure 2 includes identifying the respective substituted postoperative variables for each eye E of the multiple intraocular lenses 16 via the prediction module 24. To reflect the anatomical structure of the postoperative or pseudophakic eye, each substituted postoperative variable is incorporated into the eye model 20, thereby generating each pseudophakic eye model 30 (see Figure 1) for each of the multiple intraocular lenses 16. In other words, the measurement parameters of the congenital lens 42, iris 44, and pupil 46 in the eye model 20 are replaced with the corresponding predicted parameters of the pseudophakic eye to form each pseudophakic eye model 30. For example, referring to Figure 1, the first pseudophakic eye model 30A for the first IOL 16A is generated. The second pseudophakic eye model 30B for the second IOL 16B is generated.

[0024] The substituted postoperative variables are based in part on preoperative anatomical data and the characteristics of multiple intraocular lenses 16. An example of a pseudophakic eye model 230 is shown in Figure 3. The postoperative pupil 246 (see Figure 3) may be displaced or tilted from the visual axis A (see Figure 1). In the preoperative image 40 shown in Figure 1, the iris 44 may be bulging and shifted forward due to the relatively bulky shape of the congenital lens 42. The postoperative iris 244 (see Figure 3) may have a relatively flatter geometry.

[0025] Referring to Figure 4, the substituted postoperative variables include the location and orientation or inclination (relative to the XYZ coordinate system) of the intraocular lens 242, pupil 246, and / or iris 244, respectively. The prediction module 24 uses the measurement parameters P1...P N Using (from block 110), the first function f(P1...P N The prediction module 24 can be adapted to predict the position and tilt of each of the multiple intraocular lenses 16 using the second function g(P1...P N ) and the third function h(P1...P N It can be configured to predict pupil position / inclination and iris position / inclination using a first function f(P1...P N) The second function g(P1...P N ) and the third function h(P1...P N ) are based on intraocular lens refractive power calculation formulas available to those skilled in the art. Examples of such formulas include the SRK / T formula, the Holladay formula, the Hoffer Q formula, the Olsen formula, and the Haigis formula.

[0026] In some embodiments, the prediction module 24 incorporates a machine learning module, such as a neural network, that is trained to identify the surrogate postoperative variables through a training data set of historical pairs of preoperative and postoperative data. A historical pair refers to the preoperative and postoperative data of the same human. The system 10 can be "adaptable" and configured to be periodically updated using a larger training set. The surrogate postoperative variables can be obtained from other estimation methods available to those skilled in the art.

[0027] The method 100 proceeds from block 130 to block 140, and the controller C is configured to execute a ray tracing module 26 to identify each metric of each pseudophakic eye model 30. The ray tracing module 26 provides an assessment of the focusing performance of the pseudophakic eye. The propagation of light through the eye E can be traced through reflection and refraction using Snell's law, which describes the refraction of a ray of light at a surface separating two media with different refractive indices. In other words, when each ray in the light beam faces a surface, the new direction of each ray is determined according to Snell's law using the refractive indices stored in the diagnostic module 18. In some embodiments, the ray tracing module 26 uses refractive indices applicable to light with a wavelength of 550 nanometers (green light). In other embodiments, the ray tracing module 26 uses refractive indices applicable to multiple wavelengths. This helps to account for wavelength dispersion effects, for example, between the diagnostic measurement wavelength and different wavelengths important for human vision or between multiple visible wavelengths, in order to assess the impact of chromatic aberration on retinal image quality and other factors.

[0028] According to the first embodiment, an example of the first implementation form 200 of the ray tracing module 26 is shown in Figure 3. Figure 3 shows a luminous beam 202 propagating through a pseudo-lens eye model 230. The first implementation form 200 is described with reference to subblocks 142, 144, and 146 (of block 140) in Figure 2.

[0029] Subblock 142 allows the ray tracing module 26 (in Figure 1) to be adapted to trace or propagate a luminous beam 202 through a pseudo-lens eye model 230. The luminous beam 202 is parallel to the optical axis O of eye E. The luminous beam 202 may be simulated to be emitted from a light source 204 having a wavelength of, for example, 550 nanometers. A first portion 202A of the luminous beam 202 propagates through the anterior corneal surface 254A and the posterior corneal surface 254B.

[0030] Subblock 144 causes the ray beam 202 in Figure 3 to propagate posteriorly through the intraocular lens 242 until it reaches the spot 206 on the retina 210 (see third portion 202C) (see second portion 202B). The spatial distribution of the ray beam 202 at spot 206 is recorded. Ray tracing can be repeated for pupils 246 of different diameters.

[0031] Subblock 146 derives each metric using the spatial distribution of the luminous flux 202 at spot 206 on retina 210. Each metric may be a distribution of a single parameter or value of interest. Each metric may include, but is not limited to, wavefront grammar, modulation transfer function (MTF), and point diffusion function (PSF). An example of a set 400 point diffusion function graphs is schematically shown in Figure 5. Referring to Figure 5, traces 402, 404, 406, and 408 show point diffusion functions acquired with four different intraocular lenses, respectively. The size of the pupil 246 (or pupil 346 in Figure 4) in set 400 is approximately 5 mm. In Figure 5, the vertical axis represents intensity, while the horizontal axis represents the distance D (positive and negative) to either side of the reference point corresponding to spot 206 on retina 210.

[0032] Here, with reference to Figure 6, a set of 500 modulation transfer functions is schematically shown. A modulation transfer function is formally defined as the magnitude (absolute value) of a complex optical transfer function, specifying how different spatial frequencies are handled by the optical system. Traces 502, 504, and 506 in Figure 6 show the modulation transfer functions acquired with three different intraocular lenses, respectively. In Figure 6, the Y-axis represents the transfer function (magnitude of transmission of incident radiation), while the X-axis represents spatial frequency.

[0033] Here, with reference to Figure 4, a second implementation form 300 of the ray tracing module 26 according to the second embodiment is shown. Figure 4 shows the light beam 302 propagating through the pseudo-lens eye model 330. The second implementation form 300 will be described with reference to subblocks 152, 154, and 156 (of block 140) in Figure 2.

[0034] Subblock 152 causes the luminous beam 302 (see first portion 302A) to originate at a spot 306 on the fovea 308 of the retina 310 and have a specific divergence 312 that fully illuminates the pupil 346 of eye E. The fovea 308 is a depression in the inner surface of the retina, approximately 1.5 mm wide. The fovea 308 is composed entirely of cones and has a photoreceptor layer specialized for maximum visual acuity. The spot 306 can be infinitesimally small. Subblock 154 causes the luminous beam 302 (see second portion 302B) to propagate in front of the intraocular lens 342 until it exits the anterior corneal surface 354A and the posterior corneal surface 354B.

[0035] Subblock 156 configures controller C to identify the respective metrics of multiple intraocular lenses 16 based on the spatial distribution of the luminous beam 302 after it exits the anterior corneal surface 354A (see third subblock 302C). As described above, each metric may be a single parameter, a grammar, and may include a wavefront grammar, modulation transfer function (MTF), and point diffusion function (PSF). The ray tracing module 26 in Figure 1 is configured to simulate wavefront measurement using an aberration device 314 such as a Hartma-Shack aberration meter (see Figure 4). Wavefront measurement analyzes the direction and inclination of the luminous beam 302 exiting the anterior corneal surface 354A after a small virtual light source is created on the retina 310 by a virtual laser beam at the spot 306 where the luminous beam 302 is generated. Each wavefront of each of the multiple intraocular lenses 16 can be transformed by Fourier transform into a set of point diffusion functions 400 (shown in Figure 5). In an ideal eye, the wavefront exiting the corneal surface 354A is a flat wavefront; that is, the luminous beam 302 exiting the corneal surface 354A is perfectly parallel to the optical axis O and has an infinitesimal point diffusion function. In a non-ideal eye, the luminous beam 302 exiting the corneal surface 354A is not perfectly parallel to the optical axis O. Ray tracing can be repeated for pupils 346 of different diameters.

[0036] Block 160 configures controller C to select an intraocular lens 12 that is preferable for implantation and best suited to the desired visual quality of subject 14, based in part on a comparison of the respective metrics obtained in subblocks 146 and 156 of block 140. For example, a trace in set 400 (see Figure 5) representing the minimum width point diffusion function may be selected as the preferred intraocular lens 12.

[0037] Controller C in Figure 1 includes a computer-readable medium (also referred to as a processor-readable medium) which includes a non-temporary (e.g., tangible) medium related to providing data (e.g., instructions) that can be read by a computer (e.g., by the computer's processor). Such a medium can take many forms, including but not limited to non-volatile and volatile media. Examples of non-volatile media include optical or magnetic disks and other persistent memory. Examples of volatile media include dynamic random access memory (DRAM) which can constitute main memory. Such instructions may be transmitted by one or more transmission media, including coaxial cables, copper wires and optical fibers, which include wiring including a system bus coupled to the computer's processor. Some forms of computer-readable media include, for example, floppy disks, flexible disks, hard disks, magnetic tapes, other magnetic media, CD-ROMs, DVDs, other optical media, punch cards, paper tapes, other physical media with perforation patterns, RAM, PROMs, EPROMs, flash EEPROMs, other memory chips or cartridges or other computer-readable media.

[0038] The lookup tables, databases, data repositories, or other data stores described herein may include various types of mechanisms for storing, accessing, and retrieving various types of data, including hierarchical databases, multiple files in a file system, proprietary application databases, and relational database management systems (RDBMS). Each such data store may be contained within a computing device using a computer operating system as described above and may be accessed over a network in one or more different ways. File systems may be accessible from a computer operating system and may contain files stored in various formats. RDBMS may use structured query language (SQL) in addition to languages ​​for creating, saving, editing, and executing stored procedures such as the PL / SQL language described above.

[0039] While the detailed description and drawings or figures support and illustrate this disclosure, the scope of this disclosure is defined solely by the claims. Although several best modes and other embodiments for carrying out the claimed disclosure have been described in detail, various alternative designs and embodiments for carrying out the disclosure as defined in the appended claims exist. Furthermore, the features of the embodiments shown in the drawings or the various embodiments referred to herein should not necessarily be understood as independent embodiments of each other. Rather, each of the characteristics described in one example of an embodiment can be combined with one or more other desirable characteristics from other embodiments, resulting in other embodiments that are not described in words or not described by reference to the drawings. Thus, such other embodiments are included within the framework of the appended claims. According to embodiment (1), a system for selecting a preferred intraocular lens for implantation in the eye, A controller having a processor and tangible non-temporary memory on which instructions are recorded. A diagnostic module that communicates with the controller and is adapted to store preoperative anatomical data of the eye as an eye model, A predictive module that can be selectively executed by the controller and is adapted to identify each of the substituted postoperative variables of the eye, based in part on the preoperative anatomical data. A ray tracing module that can be selectively executed by the controller and is adapted to calculate the propagation of light through the eye. The controller includes, The diagnostic module is used to acquire the preoperative anatomical data of the eye, Through the prediction module, the respective postoperative variables of each of the multiple intraocular lenses are identified, By incorporating each of the aforementioned substituted postoperative variables into the eye model, a pseudophakic eye model is generated for each of the multiple intraocular lenses. The ray tracing module is run on each of the pseudophakic eye models to identify at least one metric for each of the multiple intraocular lenses, Selecting the preferred intraocular lens from the plurality of intraocular lenses based in part on a comparison of each of the at least one of the metrics mentioned above. It is a system configured to perform the following actions. According to embodiment (2), executing the ray tracing module means that The light beam is propagated backward through the eye until it reaches a spot on the retina, wherein the light beam is propagated parallel to the optical axis of the eye before it enters the eye from the anterior surface of the cornea. Based on the spatial distribution of the light beam at the spot on the retina, obtain each of the at least one metrics. Includes. According to embodiment (3), the ray tracing module is adapted to use the respective refractive indices within the eye, which are applicable to light with a wavelength of 550 nanometers. According to embodiment (4), the ray tracing module is adapted to use the respective refractive indices within the eye, which are applicable to multiple wavelengths across the visible portion of the spectrum. According to embodiment (5), executing the ray tracing module means that To generate a beam of light with a specific divergence that sufficiently illuminates the pupil at a spot on the fovea of ​​the eye, The light beam is propagated forward through the eye until it exits the anterior surface of the cornea. Based on the spatial distribution of the light beam after it exits the anterior surface of the cornea, the respective metrics are obtained. Includes. According to embodiment (6), the preoperative anatomical data includes the axial length of the eye. According to embodiment (7), the preoperative anatomical data includes the respective locations and profiles of the anterior and posterior surfaces of the cornea of ​​the eye. According to embodiment (8), the preoperative anatomical data includes the location, orientation, and size of the pupil of the eye in a three-dimensional coordinate system, wherein the pupil is under light-adaptation conditions. According to embodiment (9), each of the substituted postoperative variables of the eye includes the respective locations and orientations of the plurality of intraocular lenses. According to embodiment (10), each of the substitute postoperative variables includes the respective location and orientation of at least one of the pupil and the iris. According to embodiment (11), each of the at least one metrics is a point diffusion function. According to embodiment (12), each of the at least one metrics is a modulation transfer function. According to embodiment (13), a method for selecting a preferred intraocular lens for implantation in the eye, using a system having a processor and a controller having a tangible non-temporary memory on which instructions are recorded, The diagnostic module acquires preoperative anatomical data of the eye and stores the preoperative anatomical data as an eye model. Through the prediction module, the respective substituted postoperative variables for each of the multiple intraocular lenses are identified, based in part on the preoperative anatomical data. By incorporating each of the substituted postoperative variables into the eye model via the controller, a pseudophakic eye model is generated for each of the multiple intraocular lenses. Adapting a ray tracing module to calculate the propagation of light through the aforementioned eye, wherein the ray tracing module is selectively adaptable by the controller. The ray tracing module is run on each of the pseudophakic eye models to identify at least one metric for each of the multiple intraocular lenses, Selecting the preferred intraocular lens from the plurality of intraocular lenses based at least partially on a comparison of each of the at least one of the metrics mentioned above. This method includes [something]. According to embodiment (14), executing the ray tracing module means that The light beam is propagated backward through the eye until it reaches a spot on the retina, wherein the light beam is propagated parallel to the optical axis of the eye before it enters the eye from the anterior surface of the cornea. Based on the spatial distribution of the light beam at the spot on the retina, each metric is obtained. Includes. According to embodiment (15), the ray tracing module further includes using refractive indices applicable to light with a wavelength of 550 nanometers. According to embodiment (16), executing the ray tracing module means that To generate a light beam with a specific divergence that sufficiently illuminates the pupil of the eye at a spot on the fovea of ​​the eye, The light beam is propagated forward through the eye until it exits the anterior surface of the cornea. Based on the spatial distribution of the light beam after it exits the anterior surface of the cornea, the respective metrics are obtained. Includes. According to embodiment (17), the preoperative anatomical data includes the axial length of the eye and the respective locations and profiles of the anterior and posterior surfaces of the cornea of ​​the eye. According to embodiment (18), the preoperative anatomical data includes the location, orientation, and size of the pupil of the eye in a three-dimensional coordinate system, wherein the pupil is under light-adapted conditions. According to embodiment (19), each of the substitute postoperative variables includes at least two respective locations and orientations of the plurality of intraocular lenses, pupils, and irises. According to embodiment (20), the further includes selecting each of the at least one metric such that it is at least one of the point diffusion function and the modulation transfer function.

Claims

1. A system for selecting a suitable intraocular lens for implantation into the eye, A controller having a processor and tangible non-temporary memory on which instructions are recorded. An ophthalmic imaging system that communicates with the controller and is adapted to store preoperative anatomical data of the eye as an eye model, wherein the ophthalmic imaging system includes at least one of a topography device or an optical coherence tomography (OTC) machine, Equipped with, The controller includes a predictive module that is selectively executable by the controller and adapted to identify each of the substituted postoperative variables of the eye, based in part on the preoperative anatomical data. The controller includes a ray tracing module that is selectively executable by the controller and adapted to calculate the propagation of light through the eye. The aforementioned controller, The preoperative anatomical data of the eye is acquired via the topography device or the optical coherence tomography (OTC) machine. Through the prediction module, the respective postoperative variables of each of the multiple intraocular lenses are identified, By incorporating each of the aforementioned substituted postoperative variables into the eye model, a pseudophakic eye model is generated for each of the multiple intraocular lenses. The ray tracing module is run on each of the pseudophakic eye models to identify at least one metric for each of the multiple intraocular lenses, Selecting the preferred intraocular lens from the plurality of intraocular lenses, based in part on a comparison of each of the at least one metrics (including at least one of the wavefront distribution of light rays emanating from the anterior surface of the cornea, modulation transfer function (MTF), or point diffusion function (PSF)), Outputting the recommended values ​​for the best intraocular lens to optimize visual performance. It is configured to do the following: Executing the aforementioned ray tracing module means To generate a beam of light with a specific divergence that sufficiently illuminates the pupil at a spot on the fovea of ​​the eye, The light beam is propagated forward through the eye until it exits the anterior surface of the cornea. Based on the spatial distribution of the light beam after it exits the anterior surface of the cornea, the respective metrics are obtained. The operation of generating, propagating, and acquiring is repeated for pupils of different diameters and the same intraocular lens among the aforementioned multiple intraocular lenses. including, system.

2. Executing the aforementioned ray tracing module means The propagation of the light beam backward through the eye until the light beam reaches a spot on the retina, wherein the light beam is parallel to the optical axis of the eye before entering the eye from the anterior surface of the cornea. Based on the spatial distribution of the light beam at the spot on the retina, obtain each of the at least one metrics. The system according to claim 1, including the following:

3. The system according to claim 1, wherein the ray tracing module is adapted to use the respective refractive indices within the eye, applicable to light with a wavelength of 550 nanometers.

4. The system according to claim 1, wherein the ray tracing module is adapted to use the respective refractive indices within the eye, applicable to a plurality of wavelengths across the visible portion of the spectrum.

5. The system according to claim 1, wherein the preoperative anatomical data includes the axial length of the eye.

6. The system according to claim 1, wherein the preoperative anatomical data includes the respective locations and profiles of the anterior and posterior surfaces of the cornea of ​​the eye.

7. The system according to claim 1, wherein the preoperative anatomical data includes the location, orientation, and size of the pupil of the eye in a three-dimensional coordinate system, and the pupil is under light-adaptation conditions.

8. The system according to claim 1, wherein each of the substituted postoperative variables of the eye includes the respective locations and orientations of the plurality of intraocular lenses.

9. The system according to claim 1, wherein each of the substituted postoperative variables includes the respective location and orientation of at least one of the pupil and the iris.

10. The system according to claim 1, wherein each of the at least one metrics is the point diffusion function.

11. The system according to claim 1, wherein each of the at least one metrics is the modulation transfer function.

Images