Cloud based system cataract treatment database and algorithm system

Abstract

To provide systems, devices and methods that provide assistance in selecting appropriate interventions for treatment of disease of and injury to the eye.SOLUTION: Systems 100 provide cloud-based processing 140 and storage of clinical data and patient-specific data, which can provide treatment recommendations and projected outcomes to a practitioner using a local device. Systems, devices and methods can generate interactive physiomechanical models of the eye of a specified individual, which are derived from measurements of mechanical properties of structures of the eye. The physiomechanical model is interactive, and can be used to emulate effects of one or more medical interventions in the eye in order to implement an optimized treatment plan for the individual.SELECTED DRAWING: Figure 1

Description

Technical Field

[0001] This application claims the benefit of U.S. Provisional Patent Application No. 62 / 850,876, filed May 21, 2019, and U.S. Provisional Patent Application No. 62 / 842,850, filed May 3, 2019. All of these and all other referenced materials are hereby incorporated by reference in their entirety. In the event that the definition or use of a term in those incorporated materials conflicts with or is contrary to the definition of a term herein, the definition of the term herein shall control.

[0002] The field of the invention is computer-assisted surgery, particularly ophthalmic surgery.

Background Art

[0003] In this background art, it is intended to introduce various aspects of the art related to embodiments of the present invention. Accordingly, the description herein provides a framework for better understanding the present invention and should not be construed as an admission of prior art.

[0004] The use of headings in this specification is for purposes of clarification of description and is in no way limiting. Accordingly, the processes and disclosures described under the headings need to be read in the context of the entire specification, which includes various examples. The use of headings in this specification does not limit the scope of protection of the present invention.

[0005] Currently, the success of surgical interventions on the eye, such as LASIK, PRK, cataract removal, and intraocular lens placement, depends mainly on the skill and experience of the individual surgeon and the ability to adapt the ongoing procedure as normal variations within the eye and surgical complications become apparent. Less-than-optimal results and the need for additional “refinement” procedures occur at a higher rate than desired.

[0006] Computer-based systems have been developed to improve patient outcomes by facilitating patient tracking among practitioners and enabling consultation among practitioners. For example, U.S. Patent No. 9,700,292 to Nawana et al. describes a computerized system for tracking patients from initial onset through diagnosis, treatment, recovery, and outcome. This system is primarily focused on orthopedics but can provide recommendations regarding diagnosis and treatment based on stored patient data and information provided by practitioners. These recommendations are based on historical data. Therefore, the accuracy of the predicted results is necessarily limited by the breadth of the data being stored.

[0007] One approach to address the lack of relevant past clinical data is to provide a realistic model that emulates (imitates) the natural workings of the human body well enough to accurately predict the impact of medical interventions. U.S. Patent Application Publication No. US2003 / 0208190 (Roberts et al.) describes evaluating measurement results taken before and after creation of a corneal flap to generate a biomechanical model of the eye and then using this to generate ablation algorithms and predictions of surgical outcomes. However, with this approach, some degree of surgical intervention on the eye is required before generating the prediction model.

[0008] U.S. Patent Application Publication No. US2011 / 0208172 (Youssefi et al.) describes a system that makes continuous measurements of corneal shape / thickness at multiple locations during laser ablation and warns the surgeon if the desired shape is not achieved. The surgeon can then adjust the ablation there. However, such an approach relies on the individual experience of the surgeon to provide predictions of the effects of such adjustments. All publications identified herein are incorporated by reference to the same extent as if each individual publication or patent application was specifically and individually indicated to be incorporated by reference. In the event that the definition or use of a term in an incorporated reference conflicts with or is contrary to the definition of that term provided herein, the definition of the term provided herein applies and the definition of the term in the reference does not apply.

[0009] European Patent EP1613253 (Matthaus et al.) describes an expert system that uses input patient-specific information to recommend the most suitable one among a number of stored ophthalmic treatment plans for an individual patient. Surgeons select from among these treatment plans based on their individual experience and preferences. However, such a system does not truly predict the outcome.

[0010] U.S. Patent Application Publication No. 2007 / 0073905 (Roberts et al.) each describe a trained expert system for making recommendations to ophthalmic surgeons based on similar measurements from a patient, using the stored correlation between preoperative and intraoperative measurements of various features including the patient's previous eye treatment results. However, the results of such expert systems strongly depend on the available dataset. Such a system may not be able to appropriately predict a patient if the patient's measured values are outside the range included in the dataset where the patient's measurements are stored.

[0011] Recently, attempts have been made to generate several mathematical biomechanical models of parts of the body that can simulate specific functional aspects. For example, International Patent Application Publication No. WO2019 / 072875 (Deleu et al.) describes the generation of such models of the foot and ankle based on measurements of bone and soft tissue. This model is used to emulate the foot and ankle at rest and during dynamic movement. The data obtained from this emulation is used as a guide when orthopedic surgeons consider and determine appropriate treatment strategies, and to emulate the effects of the simulated treatment applied to the model. Similar mathematical biomechanical models have also been proposed for elements of the cardiovascular system (e.g., International Patent Application Publications WO2018 / 108276 by Dahl et al. and WO2018 / 057529 by Sanders et al.), and for vascular elements of the brain (e.g., U.S. Patent Application Publication No. US2018 / 0098814 by Avisar).

[0012] U.S. Patent No. 10,181,007 describes generating a "biomechanical" model of the cornea for use in optimizing refractive treatment using a finite element model. This method derives a finite element model based on individual corneal and intraocular pressure measurements and assigns permeability values to various regions of the cornea based on these measurements. These permeability values represent the ability of fluid to enter and exit the cornea as a result of intraocular pressure. Simulation of corneal changes involves changing these permeability values and resulting in computational results of the corneal configuration changed under the influence of intraocular pressure. However, using a sigmoid function to model changes in the mechanical properties of the cornea in such a model cannot easily accommodate steep gradients or sudden transitions between physical properties that are general characteristics of anatomical structures. Studer et al., Journal of Refractive Surgery 31(7):480 - 486 (2015), points out the lack of predictive value of this algorithmic approach for several procedures. This is thought to be due, at least in part, to the inability to account for specific anatomical features of the eye. SUMMARY OF THE INVENTION PROBLEM TO BE SOLVED BY THE INVENTION

[0013] Accordingly, there remains a need for a biomechanical or physical - mechanical model of the human eye that is useful for accurate emulation of surgical ophthalmic interventions. MEANS FOR SOLVING THE PROBLEM

[0014] The subject matter of the present invention provides a system, device, and method for a cloud-based collaborative computer-aided treatment method for use in optimizing surgery using femtosecond laser incisions and / or phacoemulsification for the removal of the natural lens, for example, in the treatment of cataracts. Such systems and methods utilize one or more physical mechanical models based on the mechanical properties of the eye and / or the structure of the patient's eye to model the effects of a medical intervention on a particular patient. This modeling enables the user to create an optimized treatment plan and evaluate the likelihood of subsequent complications.

[0015] One embodiment of the present invention is a system for assisting a user in performing an ophthalmic surgery on a patient's eye, which includes a user interface communicatively connected to an input / output interface (e.g., a web page) and configured to communicate with a user device; a database including a patient database, a clinical database, and a treatment database, communicatively connected to the input / output interface; and a processor communicatively connected to the input / output interface and the database. The processor includes an algorithm that provides a physical mechanical model of the eye or a part of the eye, and at least one of the input / output interface, the database, and the processor is cloud-based.

[0016] In some embodiments, the input / output interface includes a planning module and / or a treatment module. The database can also include a practitioner database and / or a device database. The processor can include a machine learning algorithm configured to correlate data from the clinical database with data from the patient database and provide a recommended treatment via the input / output interface. In a preferred embodiment, the input / output interface, the database, and the processor are cloud-based.

[0017] Another embodiment of the present invention is a method for assisting a user in performing an ophthalmic surgery on a patient, the method comprising the steps of accessing a planning module of an input / output interface (e.g., a web page) communicatively connected to a database and a processor, the input / output interface including algorithm assistance, the database including a patient database, a clinical database, and a treatment database; inputting a desired result in an ophthalmic surgery via the input / output interface; determining a recommended treatment using a machine learning algorithm of the processor and data from the patient database, the clinical database, and the treatment database; and transmitting the recommended treatment to the input / output interface. At least one of the input / output interface, the database, and the processor is cloud-based. In some embodiments, a physical mechanical model of an eye or part of an eye can be generated and used to input a desired result and / or display a recommended treatment to the user. The database can include a surgeon database and / or a device database, and the recommended treatment can be determined, at least in part, by data from the surgeon database and / or the device database.

[0018] In some embodiments, an expected result of the recommended treatment is transmitted to the input / output interface. If this expected result is accepted, the recommended treatment can be transmitted to a processing module of the input / output interface. If the expected result is not accepted, a change to the recommended treatment is input and a changed treatment and a changed result are generated. The changed result is transmitted to the input / output interface, and if it is accepted, the changed treatment can be transmitted to the input / output interface.

[0019] One embodiment of the present invention is a method for assisting a user in performing an ophthalmic surgery on a patient, the method comprising: physically characterizing the eye to determine at least a first density and at least a first dimension of the eye structure; applying the determined density and dimension to derive a physical model representing the eye structure or its anatomical structure; receiving from the user a selection of a selected ophthalmic procedure; applying the selected ophthalmic procedure to the physical model to predict the effect of applying the selected ophthalmic procedure to the eye structure; and providing to the user (e.g., a surgeon or a medical technician) a display of the predicted effect of the selected ophthalmic procedure when applied to the eye structure. The display can be at least one of one or more tabular data, a three-dimensional display, the probability of a successful or satisfactory result, and a recommendation of an alternative procedure. In some embodiments, the method includes applying the selected procedure to the patient's eye. Suitable procedures include femtosecond laser procedures, YAG laser procedures, phacoemulsification, application of a vitreous cutter, intraocular aspiration, placement of an intraocular lens, and corneal flap incision.

[0020] The physical model is derived from the mechanical properties of the eye. The mechanical properties are one or more of Young's modulus, stress / strain modulus, Poisson's ratio, density, hardness, ductility, and the results of finite element analysis of the eye structure under compression, tension, torsion, and shear.

[0021] The display of the predicted effect of the applied procedure can be derived from a structural analysis of the change in mechanical properties due to the selected procedure. Alternatively, the display of the predicted effect can be derived from the minimization of the calculated strain or static energy after application of the selected procedure, where the calculated strain or static energy is derived from the above mechanical properties. In other embodiments, the display of the predicted effect of the applied procedure is derived from a combination of these.

[0022] In some embodiments of the present invention, additional data is collected and used for generating a physical mechanical model, so that the physical mechanical model can be generated. Appropriate data includes corneal acoustic response or ultrasonic data, topography data, pachymetry data, height data, corneal thickness data, corneal curvature data, wavefront data, intraocular pressure data, peripheral stromal thickness data, patient age, patient gender, contact lens wearing time, previous surgical intervention, response to previous surgical intervention, and / or yield point of the cornea.

[0023] In some embodiments, a selected treatment is adjusted to generate a modified treatment, and the physical mechanical model is used to predict the effect of applying the modified treatment to the eye. Such adjustments can include one or more of (a) the amount of laser energy applied, (b) the depth of penetration of the resection or incision, and (c) the pattern of resection or incision applied to the eye. In some embodiments, a series of candidate treatments are applied to the physical mechanical model to identify the optimal treatment.

[0024] In some embodiments, a predicted effect on the eye structure provides a modified eye structure, and a second physical mechanical model representing the modified eye structure can be generated using the calculated physical properties of the modified eye structure. This second physical mechanical model can be utilized to evaluate the effect of additional selected treatments on the modified eye structure.

[0025] Another embodiment of the present invention is a method of phacoemulsification of the eye's lens, comprising physically characterizing the eye to determine at least a first density and at least a first dimension of the lens structure; applying the determined density and dimension to derive a first physical-mechanical model of the lens structure; identifying for the user a set of phacoemulsification procedures; receiving from the user a selection of a phacoemulsification procedure selected from the set; predicting, using the first physical-mechanical model, one or more effects of applying the selected phacoemulsification procedure to the eye; and applying the selected phacoemulsification procedure to the eye. The first physical-mechanical model is derived from the mechanical properties of the lens. Such an embodiment may provide an intraocular lens having at least a first haptic, and using the physical-mechanical model, identify a preferred location of the first haptic within a cavity formed at least in part by phacoemulsification, and include the additional step of positioning the intraocular lens in the cavity such that the first haptic approaches the preferred location. In some embodiments, following the selected phacoemulsification procedure, the eye is re-scanned to determine a second density and a second dimension. The first physical-mechanical model is then modified using the second density and the second dimension to generate a second physical-mechanical model. This is then used to determine the probability of any complications, either of phacoemulsification (such as rupture of the lens capsule) or of positioning of the intraocular lens (such an inaccurate postoperative position of the lens).

[0026] Another embodiment of the concept of the present invention is a method for femtosecond laser treatment of the eye, comprising physically characterizing the eye to determine at least a first density and at least a first dimension of the eye structure; applying the determined density and dimension to derive a first physical model of the eye structure; identifying a set of femtosecond laser treatments for the user; receiving from the user a selection of a femtosecond laser treatment selected from the set; predicting the effect of applying the selected femtosecond laser treatment to the eye using the first physical model; applying the selected femtosecond laser surgery to the eye; re-characterizing the eye to determine the changed density and changed dimension; modifying the first physical model using the changed density and changed dimension to generate a second physical model; determining the amount of lens segmentation using the second physical model; and proposing a preferred phacoemulsification using the amount of lens segmentation.

[0027] Another embodiment of the present invention is a laser system including a femtosecond laser configured and operable to deliver a femtosecond laser beam to the eye, and a modeling system having a modeling engine and / or a patient database. The patient database is configured to receive density characteristics of the eye structure and dimension characteristics of the eye structure. Such a system can include a graphical user interface (GUI) configured to receive input from the user and display output from the modeling system. Such input includes the selected treatment.

[0028] In some embodiments of these systems, the modeling system is configured to derive a physical model representation of the eye structure based on the density characteristics of the eye structure received from the patient database, the determined dimensional characteristics of the eye structure received from the patient database, or both. Such a system receives a treatment selected from the GUI and applies the selected treatment to the physical model representation of at least a portion of the eye structure, thereby deriving the predicted effect of the selected treatment on the eye structure. In some embodiments, the modeling system provides a display of the predicted effect to the GUI.

[0029] In embodiments of such a system, the system can include a phacoemulsification aspiration system. In embodiments of these systems, the system is configured to perform one or more of the methods, treatments, or derivation operations described in this "Means for Solving the Problem".

[0030] Various objects, features, aspects, and advantages of the subject matter of the present invention will become more apparent from the following detailed description of the preferred embodiments and the accompanying drawings (where like numerals represent like components).

Brief Description of the Drawings

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MODE FOR CARRYING OUT THE INVENTION

[0042] The following description includes information that may be useful for understanding the present invention. None of the information provided in this specification is admitted to be prior art or related to the claimed invention, nor is it admitted that any specifically or implicitly referenced publications are prior art.

[0043] Throughout the following discussion, numerous references will be made to servers, services, interfaces, portals, platforms, or other systems formed from computing devices. The use of such terms is understood to represent one or more computing devices having at least one processor configured to execute software instructions stored on a computer-readable tangible non-transitory medium. For example, a server can include one or more computers operating as a web server, a database server, or other type of computer server in a manner that performs the described roles, responsibilities, or functions.

[0044] As used herein, unless otherwise specified, the terms "femtosecond laser", "femtosecond laser beam", "femtosecond pulse", and similar such terms are used to refer to the pulse duration, and thus the pulse length (also called the pulse width) of the laser beam, where the pulse duration is from about 10 picoseconds (about 10×10 -12 seconds or less) to about 1 femtosecond (fs) (1×10 -15 seconds), and mean all lasers and laser beams therebetween.

[0045] As used herein, unless otherwise specified, room temperature is about 25°C. Similarly, standard ambient temperature and pressure are about 25°C and about 1 atmosphere. Unless otherwise specified, all values that are temperature-dependent, pressure-dependent, or both, including all tests, test results, physical properties, and viscosities, are provided at standard ambient temperature and pressure.

[0046] Generally, the term "about" and the symbol "~" as used herein, unless otherwise specified, mean a variance or range of ±10%, errors of experiments or equipment associated with obtaining the recited values, preferably the greater of these.

[0047] As used herein, unless otherwise specified, recitations of ranges of values, ranges from about "x" to about "y", and similar listings of such terms and quantifications function merely as shorthand references to the individual values within the range. Thus, they include each item, feature, value, amount, or quantity that is within the range. As used herein, unless otherwise specified, all individual points within a range are incorporated herein and are part of this specification as if individually set forth herein.

[0048] As used herein, terms such as "at least", "greater than", etc., unless otherwise specified, also mean "or more", i.e., such terms do not exclude lower values unless otherwise specified.

[0049] It should be noted that it is not necessary to provide or discuss the theory underlying the novel and groundbreaking processes, materials, performances, or other beneficial features and characteristics related to or of the subject matter of embodiments of the present invention. Nevertheless, various theories are presented herein to further the art. The theories described herein do not limit, restrict, or narrow the scope of protection afforded to the invention recited in the claims, unless otherwise specifically stated. These theories may not be required or practiced for the use of the present invention. Further, it should be understood that the present invention may lead to new theories not previously known for explaining the functional features of embodiments of the methods, articles, materials, devices, and systems of the present invention. And such later-developed theories do not limit the scope of protection afforded to the present invention.

[0050] The various embodiments of the systems, therapies, processes, compositions, uses, and materials described herein can be used in various other fields, as well as in various other activities, uses, and embodiments. Further, these embodiments can be used, for example, with existing systems, therapies, processes, compositions, uses, and materials, as well as with systems, therapies, processes, compositions, uses, and materials that may be developed in the future, and with systems, therapies, processes, compositions, uses, and materials that may be modified, in part, based on the teachings herein. Additionally, the various embodiments and examples described herein can be used with each other, in whole or in part, and in various different combinations. Thus, for example, the configurations provided in the various embodiments herein can be used with each other. For example, the components of an embodiment having A, A' and B, and the components of an embodiment having A", C and D can be used with each other in various combinations, such as A, C, D or A, A", C and D. The scope of protection given to the present invention should not be limited to a particular embodiment, example, configuration, or arrangement described or shown in a particular embodiment.

[0051] The system and method of the present invention provide a user with cloud-based interactive software that assists in ophthalmic procedures, including incision and phacoemulsification of the lens (e.g., using a femtosecond laser). For the purposes of this application, a femtosecond laser and / or a femtosecond laser beam is about 10 picoseconds (10×10 -12 seconds) or less, about 1 picosecond (10 -12 seconds) or less, and 1 femtosecond (fs) (10 -15It means a laser beam having a pulse duration including (seconds). Such procedures include the insertion and placement of an intraocular lens. The implementation of such systems and software can include the use of a three-dimensional physical model of the eye or part of the eye. Such physical models (described in more detail below) can provide the user with predictions or predicted responses to proposed or actual changes to the structure of the eye (e.g., incisions, lens removal, etc.).

[0052] In the following, many exemplary embodiments of the subject matter of the present invention are provided. Each embodiment represents a single combination of elements of the present invention, but the subject matter of the present invention is considered to include all possible combinations of the disclosed elements. Thus, if one embodiment includes elements A, B, and C and a second embodiment includes elements B and D, the subject matter of the present invention can also include other combinations of A, B, C, or D, even if not explicitly disclosed.

[0053] The grouping of alternative elements or embodiments of the present invention disclosed herein should not be construed as limiting. Each group element can be referenced and claimed individually or in any combination with other members of the group or other elements found herein. One or more elements of the group can be included in or deleted from the group for reasons of convenience and / or patentability. If such inclusion or deletion occurs, this specification is considered to include the modified group and thus to satisfy the description of all Markush groups used in the appended claims.

[0054] An example of the system of the present invention is shown in FIG. 1. Such a system (100) can include a local interface (110) for the operator to input and receive information. Such a local interface can communicate with an information network (e.g., the Internet) that provides access to an input / output interface (130) via an Internet interface (120) such as a website. Such an input / output interface can provide communication with the data storage and processing functions of the system. In a preferred embodiment of the present invention, the input / output interface (130), processing (140), and data storage (150) are cloud-based, but one or more of these components or parts thereof can be embodied in system components that are local to the user. The storage component can include one or more databases used by the processing (processing) function of the system, and the user can directly access it via the input / output interface. Cloud-based storage of such databases permits all users to update and add information stored therein. The processing component of the system can incorporate one or more algorithms, such as receiving input from the user, providing assistance in determining an optical treatment plan, and generating an interactive physical model of the eye and / or eye structures, as detailed below. It should be understood that using cloud-based processing, updates and improvements are distributed to all users.

[0055] The Internet interface in the present invention can be arranged as two or more modules, as shown in FIG. 2. In the illustrated Internet interface (200), three different modules are provided. The planning module (210) provides an interface useful for planning a treatment course to the operator. The planning module can access the database (220) directly or via algorithm support (215). The database can include sub-databases that are information useful for the operator and / or algorithm to support. Typical sub-databases include an information database (225) containing patient-specific information; a clinical database (230) containing aggregated data related to medical conditions / injuries, treatment modes, outcomes, physical parameters of the eye and eye structures (for use in generating, for example, physical models of mechanical devices); an operator database (235) containing operator-specific information such as specialized training / skills, experience in various treatment modes, treatment preferences; a treatment database (240) containing information related to various medical intervention procedures, effects of medications, etc.; and / or a device database (245) containing information related to the use and performance characteristics of various medical devices, availability of devices in various treatment facilities, etc.

[0056] During use, the operator can utilize the planning module to explore different treatment options for a specific patient and / or plan a treatment protocol. In some embodiments, the operator can use the planning module to conveniently and directly access information from a database (e.g., by means of line commands, icon-based navigation, etc.) to determine a treatment protocol based on personal experience. In a preferred embodiment, the operator can utilize algorithmic assistance (215) to determine an optimal treatment plan. Such algorithmic assistance includes providing the operator with a three-dimensional interactive physical model of the eye (or a part thereof), which can be used to input trial treatments and display the expected results. Alternatively, or additionally, in some embodiments, the operator can provide information regarding the condition or injury to be treated to an assistance algorithm, which can apply a machine learning approach to data from a patient database and a clinical database to propose one or more likely successful treatment plans. In some embodiments, the assistance algorithm can utilize information from an operator database to adjust the proposal to match the operator's skills or preferences, and similarly, utilize information from an equipment database to adjust the proposal to utilize the equipment and facilities available at the operator's location.

[0057] If the practitioner is satisfied with the proposed treatment plan, it can be transferred to the treatment module (250) of the Internet interface, for example, by storing it in the patient database (225) for retrieval. The treatment module can be used to assist the practitioner during the course of treatment, such as by providing guidance during a surgical procedure. In some embodiments, the treatment module can be used by the practitioner to practice the medical procedure as it will be performed, using an interactive physical model based on the patient's anatomical structure. In a preferred embodiment, the treatment module can access a database (220) similar to, identical to, or the same as the database accessed by the planning module (210). The treatment module can provide the practitioner with direct access to the information in the database or provide access via algorithmic assistance (255). In a preferred embodiment, the algorithmic assistance provides the practitioner with an interactive physical model of the patient's eye (or part thereof), allows the practitioner to enter the steps of the treatment plan using this model, and displays the predicted results of those steps. In some embodiments, they can be provided as augmented reality that is overlaid on the patient's anatomical structure during treatment. In some embodiments, deviations from the expected results are entered during surgery and the system is used to propose alternative procedures.

[0058] The Internet interface can also include a training module (260). Such a training module can be used when educating future practitioners, provide training for current practitioners to update or expand their skills, and / or be used for discussions among practitioners. In a preferred embodiment, the training module can access a database (220) similar to, identical to, or the same as the database accessed by the planning module (210). The training module can utilize a stored and idealized physical model of a typical eye presenting one or more disease / injury states and display the results of various interventions. When used for discussion purposes, one or more consulting practitioners can directly access the patient-specific data and the proposed treatment plan and then provide feedback to the primary practitioner.

[0059] The system and method of the present invention include one or more data processing devices, one or more data storage devices, and one or more interactive algorithms. These can be implemented or accessed via a wired network, a wireless network, or a data / processing cloud system. This advantageously provides portability and a degree of device independence, enabling the system and method of the present invention to be widely implemented with a minimal local investment in computing hardware. The use of cloud-based data and / or processing also provides for the simultaneous distribution of data and updated software and local access to patient data throughout the system. Such patient data can then be utilized by the algorithms of the system to generate proposed treatment protocols and / or improve the physical model. Thus, accessing patient data throughout the system via a cloud-based system can improve the accuracy of diagnosing and treating eye conditions.

[0060] The system and method of the present invention can utilize and / or incorporate a wide range of computing and display devices that can function as a local interface. Such devices include smartphones, tablet computers, wearable devices (such as smartwatches, smart glasses, etc.), laptop computers, and household appliances such as desktop / tower computers. In some embodiments, the device can include medical-grade electronic devices such as binocular head-up displays, microscope head-up displays (e.g., for phacoemulsification), and monitors / displays housed and configured for use in an operating room. Such devices can provide either fully computer-generated working images or augmented reality displays that overlay computer-generated images on acquired images of the eye being treated.

[0061] Embodiments of the present invention include one or more databases that can be used for storing patient-specific data, clinical data related to eye diseases, clinical data related to treatment protocols and outcomes, treatment plans, user (e.g., physician) preferences, the experience of individual practitioners with different optical conditions and / or treatment methods, algorithms for selecting treatment plans, algorithms for generating physical and mechanical models of a patient's eye (or a part thereof), etc. All or part of such databases can be implemented in cloud storage and accessed to upload and / or download via a wired or wireless internet connection (e.g., via a website or similar interface).

[0062] In some embodiments of the present invention, algorithms can be used to assist a user (e.g., a physician) in selecting and / or optimizing an ophthalmic surgical procedure for a particular patient based on patient-specific characteristics and desired outcomes input by the user. In preferred embodiments, such algorithms can be based on machine learning and can correlate patient-specific characteristics and desired outcomes with clinical data (which may include patient data related to eye condition, age, gender, ethnicity, presence or absence of genetic markers, underlying diseases, current medications, previous interventions), applied procedures and / or techniques, and observed objective and / or subjective outcomes. Other inputs can include physician preferences, the scope of the physician's experience or training in various treatment modalities, and the physician's success rate in various procedures. All or part of such algorithms can be implemented on a cloud computing platform. Using cloud computing not only enables implementation on various platforms but also provides a larger and more diverse dataset that facilitates accurate machine learning.

[0063] In addition to providing a support algorithm for treatment optimization, the system and method of the present invention can provide an interface for the practitioner (e.g., an ophthalmologist) to input their individual preferences. Examples of such preferences can include the use of a particular femtosecond laser available in the immediate clinical setting, the preferred depth and / or length of the incision, the brand and model of the intraocular lens, etc. These settings can be input, for example, using a web-based checklist. In preferred embodiments, the support algorithm incorporates these preferences into the proposed treatment plan.

[0064] In some embodiments of the present invention, a treatment plan can include two or more types of surgical interventions. For example, the treatment of cataracts includes making an incision in the cornea using a femtosecond laser and destroying and removing the cloudy lens using phacoemulsification. In such embodiments, the algorithm according to the present invention can be instructed to optimize one surgical intervention of a procedure preferentially over another surgical intervention of that procedure. For example, in the treatment of a cataract patient with significant astigmatism but no other complications, the placement and size of the corneal incision can be used to reduce the degree of postoperative astigmatism. In such a situation, the algorithm can be instructed to prioritize the optimization of the femtosecond laser incision portion over phacoemulsification. Alternatively, if the patient has particularly problematic cataracts, the operator can choose to optimize phacoemulsification over the first femtosecond laser incision step. Such weighting of optimizations in a procedure is performed by the algorithm based on individual patient data. Alternatively, such weighting can be determined and input by the operator.

[0065] As described above, the system of the present invention can include a database that records the experience of individual operators using various tools and techniques in the treatment of various eye conditions. These can be used to complement or replace the treatment optimization algorithm with the results of clinical data input and / or physical machine modeling simulations, thereby introducing practical elements of actual practice into the optimization. In some embodiments, the operator can selectively access the record of a particular operator's experience, and in some embodiments, can communicate in real time with one or more selected operators for discussion. Implementing such functions in a cloud-based system advantageously provides a consistent interface that supports effective collaboration and community interaction among a large number of people.

[0066] In the devices and methods of the subject of the present invention, patient-specific information is used to generate a dynamic and interactive three-dimensional model of all or part of an individual's eye. As used herein, a three-dimensional model includes a two-dimensional display provided on a computer display that provides perspective, shading, color cues, is rotatable, or includes other visual cues indicating length, width, and height. The construction of this three-dimensional model is based at least in part on measurements of physical parameters related to an individual's eye and is a physical-mechanical model that reflects its mechanical properties (such as stiffness, elasticity, density, thickness, etc.). In some embodiments, the physical-mechanical model is based on the patient's natural, unaltered eye. In other embodiments, the physical-mechanical model is based on an eye that has undergone a medical intervention (e.g., LASIK, PRK, cataract removal, intraocular lens placement, vitrectomy, scleral buckle, etc.) that affects the physical, mechanical, and / or optical properties of the patient's eye. In such embodiments, the physical properties of the modified tissue and / or artificial device can be included as inputs to the physical-mechanical model. In other embodiments, a dynamic physical-mechanical model (i.e., one that shows the transition from a baseline state to a changed state) is used, and the predicted effect of a medical intervention on the eye or a part thereof can be shown using a physical-mechanical model of the eye obtained from measurements taken prior to the medical intervention and the changes to those measurements predicted from the medical intervention (i.e., before and after the change, respectively).

[0067] The physical mechanical model is dynamic and can respond to inputs from a user (e.g., a physician) representing changes to the eye of interest. Examples of such changes include medical interventions such as incisions made to a particular part of the eye, excision of parts of the eye, removal or replacement of an eye structure (e.g., a lens with a cataract), addition of a material or substance to the eye (e.g., a tissue graft, an intraocular lens, etc.), and administration of drugs (e.g., drugs that change intraocular pressure). When such an input is received, the physical mechanical model is modified to generate a modified physical mechanical model that represents the overall or partial configuration of the eye after the change input by the user. In some embodiments, a transitional physical mechanical model can be derived that can provide an animated or other dynamic display of the movement and / or configuration changes that occur during the transition between the pre-change and post-change configurations to facilitate understanding and interpretation of the effects of the input changes. In some embodiments, an overlay between the pre-change and post-change configurations can be provided to facilitate understanding and interpretation of the effects of the input changes.

[0068] In addition to displaying changes in the shape, orientation, and / or configuration of all or part of the eye of interest, the physical mechanical model can provide an enhanced physical mechanical model that provides visual cues useful for explicitly or implicitly highlighting specific results or values for all or part of the model. For example, color coding can be used to highlight characteristics of the surface topography (e.g., characteristics of the cornea after excision) and / or mechanical strains that may not be easily observable in an unenhanced physical mechanical model. FIG. 3 is an exemplary three-dimensional display of a physical mechanical model of a lens within the lens capsule of a human eye. The shading represents the degree of mechanical strain within the structure, and the arrows represent the direction of the strain. Similarly, ray tracing showing the refraction of one or more wavelengths of light passing through the eye structure can be used to show the location where an optimal focus occurs to evaluate the effect of implanting an intraocular lens. In some embodiments, such enhancements can be combined, for example, to evaluate the effect of laser ablation for correcting a corneal defect in an eye that has received an intraocular lens.

[0069] The physical and mechanical model according to the present invention can be used for an operator to evaluate the results of different interventions and / or treatments on a patient's eye and create a treatment plan that best addresses the patient's individual condition. In this way, the physical and mechanical model provides a tool that utilizes the operator's training and experience in combination with a virtual model that reflects the results of the intervention applied to a specific eye, enabling the operator to use freely available techniques and tools to create an effective treatment plan with the highest degree of familiarity and comfort. Using such an interactive physical and mechanical model, it is also possible to create a treatment plan that utilizes combinations of familiar treatment modes (such as ablation, lens exchange, medication, etc.) that would not be considered otherwise.

[0070] In some embodiments, an initial physical and mechanical model can be utilized to determine an optimal treatment (e.g., an incision into the cornea using a femtosecond laser as an initial step in lens removal) that functions as one step of a multi-step treatment. Subsequently, a second physical and mechanical model that reflects the change in the mechanical properties of the eye or a part of the eye (e.g., as a result of the first treatment) can be used to determine the optimal treatment for the next step (e.g., phacoemulsification, intraocular lens placement, etc.). In some embodiments, the second physical and mechanical model is based on the predicted mechanical properties derived from the calculated effect of the first treatment on the first physical and mechanical model. In other embodiments, such a second physical and mechanical model is derived using the mechanical properties of the eye or the eye structure determined by measurements taken subsequent to the first treatment.

[0071] An example of a general workflow of the system of the present invention is shown in FIG. 4. As shown, such a system can include a database that can store patient-specific data obtained from measurements made on a patient's eye, the patient's medical history, etc., as detailed below. Such a database can also include statistical data obtained from population surveys, including recorded results of specific interventions and / or treatments, and characteristics of specific subpopulations. Information from the patient-specific database (and in some implementations, the statistical database) is provided to a modeling engine. The modeling engine utilizes this data to generate a patient-specific mathematical-physical model of the eye or a part thereof based on the patient-specific data. For example, the modeling engine can apply basic mechanical principles to measurements and known characteristics of a part of the eye to estimate characteristics such as curvature, surface topography, probability of loss of integrity, etc. Alternatively, the modeling engine can use patient-specific data along with calculated and / or known characteristics of the eye's structure to calculate the strain energy of the eye or a part thereof, and then repeatedly apply different configurations and / or dimensions (within an acceptable range) to generate a low-strain energy configuration. In some embodiments, such approaches can be combined. In some embodiments, what is calculated with such a mathematical model can be compared with and / or used to modify information obtained from statistical data.

[0072] Such a mathematical model provided by the modeling engine can be provided to a graphics engine as display data, and the graphics engine provides an output perceptible to humans on a display. In a preferred embodiment, this mathematical model is in a format of output suitable for a three-dimensional display or a functional two-dimensional display (of the three-dimensional model). Other display formats are also contemplated, such as tabular output, written or verbal recommendations, graphical or color-key displays of the probability of desired results, etc.

[0073] As shown in FIG. 5, in some embodiments, an initial pre-modification mathematical model of a particular patient's eye or a part thereof can be generated by a modeling engine using patient-specific data obtained from measurements, history, etc. This provides display data that describes the patient's eye prior to intervention to the graphics engine, and the graphics engine provides an input to a display that can provide a display of the patient's eye or a part thereof observable by a human prior to medical intervention. This serves as a baseline or starting point for a dynamic physical model that provides a "before and after" view of the effect of the proposed medical treatment. Similarly, FIG. 6 shows a workflow of a similar process, where the graphics can provide an input to a display, which can then provide an observable display of the patient's eye (or a part thereof) after medical intervention. This can serve as an endpoint of the proposed medical treatment or as a result at an intermediate point of a complex / multi-step medical treatment.

[0074] As shown in FIG. 8, in some embodiments, a modified mathematical model of a particular patient's eye or a part thereof can be generated by entering one or more proposed interventions that will change the values of patient-specific data. In some embodiments, the effect of such an intervention on the particular data before the change is determined by a modeling engine, which uses these modified values to derive the modified mathematical model. In other embodiments, the modification of the values of the particular data before the change is performed in a separate operation that generates a modified patient-specific data set within the database. This modified patient-specific data set is made accessible to the modeling engine and can be used to generate the modified mathematical model. Similar to the generation of the mathematical model before the change, the data from the statistical data set can be used to determine the optimal model generation method or to modify the model after the change based on the historical data of the group. Once the modified mathematical model is determined, a set of data representing the modification is determined to be provided to the graphics engine, and then the graphics engine provides an observable output (e.g., via a display) representing the result after the proposed intervention.

[0075] In some embodiments, the modified particular data derived from the mathematical model can be input into the database. Such modified particular data can then be used as a starting point for calculating the effect of subsequent proposed interventions, thereby generating a second modified physical model. Through such a sequential approach, an optimal treatment plan for a complex procedure involving many different steps can be derived. For example, the optimal size and placement of a corneal incision can be determined using the first modified model, and the optimal selection and placement of an intraocular lens in the treatment of cataracts can be determined using the subsequent modified model.

[0076] The generation of a physical mechanical model can include inputting patient-specific data that includes various characteristics of the individual eye to be treated into a specific patient-specific database. Such data can include corneal acoustic response and / or ultrasonic data, topography data, pachymetric data, height data, corneal thickness data, corneal curvature data, wavefront data, intraocular pressure data, peripheral stromal thickness data, patient age, patient gender, contact lens wearing period, previous surgical interventions, and / or response to previous surgical interventions. Such data can be obtained by corneal topography, optical coherence tomography, wavefront analysis, ultrasound, and / or patient interviews.

[0077] The data collected in this way can be used to determine or infer various mechanical properties that can be used to derive a physical mechanical model of the eye or eye structure. Such mechanical properties can include Young's modulus, stress / strain elastic modulus, Poisson's ratio, density, hardness, ductility, and / or the results of finite element analysis of the eye structure under compression, tension, torsion, and shear. These can be affected by temperature, which can change to some extent during treatment.

[0078] Such patient-specific data can be obtained and input for any relevant eye structure. Relevant eye structures can include the lens, lens capsule, zonular sclera, cornea, iris, epithelium, cilia and muscles, anterior chamber with aqueous humor, posterior chamber with vitreous humor, suspensory ligament, pupil, Schlemm's canal, fibrociliary band, and / or retina.

[0079] Embodiments of the present invention can also include a statistical database that includes data obtained from a population of patients who have received ophthalmic treatment. Such a statistical database can include data related to a particular population segment (age range, gender, ethnicity, presence or absence of a particular genetic marker, etc.), eye condition, applied intervention / treatment, and outcome. Such a statistical database can also include information related to the correlation between the characteristics of a particular population segment, the applied intervention and / or treatment, and the outcome. In some embodiments, access to such data and / or correlations can be used to derive the characteristics of the modified physical machine model. Using such a statistical database can improve the accuracy of the modified physical machine model by providing statistically appropriate estimates of values not provided in the patient-specific database. For example, patient-specific factors such as age, gender, past treatment, etc. can be used to define a population segment within the statistical database that can provide statistically appropriate estimates of patient-specific values that do not exist in the patient-specific database.

[0080] Shape changes associated with an intervention directed to one or more parts of the eye can be calculated using one or more mechanical models that provide estimates such as curvature based on the mechanical properties of the eye's structure. Such mechanical properties are derived from the individual data stored in the database and recalculated after their properties have been changed by a medical intervention. Examples of such mechanical properties include Young's modulus (E), which provides a measure of the elasticity of the structure, and Poisson's ratio, which is the ratio of the transverse contraction strain to the longitudinal extension strain in the direction of the stretching force. These can be estimated from appropriate measurement results. For example, (1 - v2)P·-(1)E = 2aK(a / h, v)w, where: ·E is Young's modulus ·P is the pushing force ·v is Poisson's ratio ·w is the depth of indentation (dimple) ·a is the radius of the indenter ·h is the thickness of the tissue ·K is a magnification factor that depends on the aspect ratio a / h and Poisson's ratio. Solutions can be obtained based on the assumption of minute deformation of the indentation. Changing the components of the eye may change the parameters that affect the mechanical properties (such as Young's modulus) of such components. For example, changing the thickness of a part of the cornea by laser ablation directly affects the thickness of the tissue in that area. The modeling engine is used to estimate the impact of the eye structure parameters changed by the proposed medical intervention on such mechanical properties, and forces (such as intraocular pressure) can be applied to the eye to estimate the impact on the composition of such a structure in order to generate a physical mechanical model of the eye after the change. Similarly, the impact of such a change in configuration in a specific eye structure on adjacent or connected eye structures can be calculated and made available for use in the physical mechanical model after the change. By combining the physical mechanical models before and after the change of an individual eye or a part thereof, a dynamic physical mechanical model of the eye can be generated based on mechanical estimation.

[0081] Alternatively, an energy minimization approach can be utilized that provides a modeling engine with a mathematical model of the relationship between the forces existing within an eye or part of an eye and the characteristics of the eye or part of the eye, where the values from the patient-specific database are derived from the mechanical relationships as described above. This mathematical model provides a set of coordinates used in the generation of a three-dimensional physical mechanical model that can represent a low-energy solution or a minimized-energy solution of the mathematical model. In some embodiments, this mathematical model is applied as a whole to the eye or a specific part of the eye. In other embodiments, a series of mathematical models are applied to segments of the eye or a specific part of the eye to generate a set of mathematical models, and each member of this set provides a correlation between the forces existing within each respective segment and the characteristics of that segment. In such embodiments, an additional integration model is derived that characterizes the interactions between such segments.

[0082] The modeling engine can further output one or more sets of display data used to derive coordinates for the display of a physical machine model based on the mechanical relationship between the stored physical parameters (e.g., density, thickness, elasticity, rigidity, etc.) and the applied and / or inherent forces in the eye. By applying such mechanical relationships, display data can be generated that represents a set of coordinates that provides the minimum static energy solution of the physical machine model determined by the calculation of strain and stress within the structure.

[0083] For example, using well-known mechanical relationships, baseline strain or static energy can be derived from applying stored physical parameters (which may be the result of measurements from an individual) to a stored baseline or general physical machine model that includes a set of baseline spatial coordinates for a general eye or a desired portion of the eye. Next, the modeling engine applies a static energy reduction algorithm to change the spatial coordinates of this modified baseline physical machine model and reduce or minimize the baseline static energy. Such an algorithm can, for example, iteratively calculate and rank various possible dimensional strains or static energies limited by known characteristics of the eye or eye structure. The final physical machine model is realized when this static energy is minimized (i.e., when further changes would result in an increase in the calculated static energy or strain).

[0084] In another embodiment of the present invention, the eye or a part thereof (e.g., the cornea) can be modeled as a flexible laminate structure. Such a layered model can include two or more layers adhered to each other, with one surface of a layer contacting and continuously adhering to the corresponding surface of an adjacent layer. By doing so, the layered physical model can more fully represent the actual eye and / or eye structure within the naturally occurring anatomical context than a strict mechanical and / or energetic approach. In such a layered model, adjacent layers can have different thicknesses, compositions, and mechanical properties, and can be selected and arranged to at least partially replicate the anatomical structure of the eye and its different tissue layers. Such a layered physical model can provide, for example, a relatively thin and flexible epithelial layer adhered to a non-flexible Bowman layer adhered to a relatively thick and flexible stroma with varying density within a physical model of the cornea, and can account for changes in any or all of these layers.

[0085] An example of such a layered model is shown in FIG. 9, which shows an exemplary layered model of a portion of the cornea. The layered model (900) incorporates three layers (910, 920, 930), which are modeled as having individual mechanical / physical properties corresponding to the epithelial layer (910), Bowman layer (920), and stroma (930). The layered physical model (900) is generated by treating the entire structure as a flexible laminate where layer (910) continuously adheres to layer (920) and layer (920) continuously adheres to layer (930).

[0086] The basic mechanical properties of various parts of the cornea are available (see Masterson and Ahearne, Experimental Eye Research, 177:122-129 (2018); Last et al., Journal of Structural Biology, 167(1):19-24 (2009)), and can be further improved based on patient-specific data (e.g., measurements, age, medical history, etc.). A resulting layered model of the eye or part thereof, its response to stress (e.g., intraocular pressure), its response to changes in thickness (e.g., by photoablation) or stiffness (e.g., by crosslinking) of all or part of one or more layers, etc., can be mathematically generated by any suitable method. For example, a predictive physical-mechanical model of the layered structure can be generated using an artificial neural network trained using previously recorded data. The multi-continuum theory has been applied to predict the behavior of flexible laminated composites and can be applied in a similar way to generate a layered physical-mechanical model. Tools such as ANSYS Workbench TM have been used to provide 3D CAD models of synthetic laminated composites and can be applied to generate a layered physical-mechanical model.

[0087] In some embodiments of the present invention, a model of a part of the eye can be generated by a first method, and the resulting part is incorporated into a larger structure modeled by a second method. For example, if an energy minimization approach is found to provide suitable results for a part of the cornea, a first model representing such a part can be generated in that way. Once such a first model is generated, it can be incorporated as a layer within a more complex layered model of the cornea incorporating additional layers with different mechanical properties. Such a combined approach can advantageously reduce the computational load.

[0088] In some embodiments, the modeling engine can provide results obtained in a single operation. In other embodiments, a series of trial solutions can be repeatedly applied until a low static energy, appropriate mechanical estimation, or solution of an appropriate layered model is identified. If a single mathematical model is derived for an eye or a part thereof, a single set of display data can be used. For example, if it is necessary to model only the lens of an individual's eye, a single mathematical model may be sufficient to describe the relationship between the forces applied to a part of the lens (defining the shape of the lens represented as display data) and the physical properties of the lens.

[0089] Alternatively, if a physical mechanical model of a wider or more complex structure is desired, a set of mathematical models of segments or parts of the desired structure can be used to derive the respective coordinates of a specified eye or segment or part of the eye. Thus, known mechanical relationships can be applied to patient-specific data related to the segment to derive the baseline static energy value of the segment, for application to the segments of the corresponding baseline physical mechanical model of the general eye or part of the eye. The integrated static energy of the whole eye or part thereof by applying the spatial coordinates from the static energy minimization physical mechanical model of each segment to the integrated model defines the spatial relationship between the individual segments. Next, the spatial coordinates of the individual segments can be iteratively adjusted to generate an integrated physical mechanical model with minimized static energy. In some embodiments, it is desirable to only partially minimize the static energy of each segment before minimizing the static energy of the integrated physical mechanical model.

[0090] In some embodiments of the present invention, the results of mechanical estimation models, energy minimization, and / or layered models can be combined to provide a mixed physical-mechanical model of the eye. In such a combined approach, weights can be applied to the results of mechanical estimation, energy minimization, and / or layered models to adjust their respective relative contributions to the final physical-mechanical model. In some embodiments, the results of the physical-mechanical models of mechanical estimation before and after a change and the physical-mechanical models of energy minimization can be compared with data from a statistical database obtained from patients having characteristics similar to those of a particular patient and treatments corresponding to a proposed medical intervention. If such a comparison shows that any of the mechanical estimation approach, energy minimization approach, layered model, or their combined approach matches the data in the statistical database more closely than the individual models, the physical-mechanical modeling approach that provides the best match can be preferentially utilized for emulation and treatment planning for a particular patient.

[0091] In some embodiments of the present invention, the static energy minimization physical-mechanical models, mechanical estimation models, and / or layered models of the eye or eye part can be further modified by data from a statistical database. Such modifications can provide more accurate results when the patient's eye is incompletely characterized prior to generating the physical-mechanical model and / or when the phenomenon is recorded but the understanding of the underlying mechanism is incomplete. For example, if the statistical database contains data indicating that the use of a particular configuration of a corneal ring is associated with a greater flattening of the corneal surface than expected in a particular patient population to which the patient belongs, the spatial coordinates used to generate the three-dimensional physical-mechanical model of the corneal surface can be adjusted to reflect this.

[0092] As described above, the output of the modeling engine can be a set of spatial coordinates representing the configuration of a three-dimensional physical machine model. Such spatial coordinates are provided to the graphics engine, which then generates a three-dimensional display. A dynamic physical machine model showing the predicted results of a proposed medical intervention from a baseline state can be presented as a dynamic or animated three-dimensional display based on an appropriate set of such spatial coordinates. Such three-dimensional displays can be surface or sets of surfaces, three-dimensional displays with some parts removed to reveal internal structures, partially translucent or transparent structures, or displayed as cross-sections. Similarly, while the solution for the whole eye or a desired part of the eye is being derived, the modeling engine can be used to generate a three-dimensional display of a part of the whole. For example, while a physical machine model of the whole eye is being generated, the user may want to display only a part of the physical machine model representing the lens or the corneal surface. However, the characteristics of the displayed part are derived from calculations performed on data related to the whole eye or a part thereof.

[0093] The graphics engine can provide output for any suitable display. As described above, herein, a 3D display can include an image that uses a conventional 2D computer display to display perspective, shading, color cues, rotation capabilities, etc. that exhibit 3D properties. Alternatively, the graphics engine can provide output for holographic, stereoscopic displays, virtual reality sets, or other 3D display technologies. In some embodiments of the present invention, the output of the graphics engine can be incorporated into an augmented reality system in combination with an image of a patient's eye. In some embodiments, the graphics engine can provide output to a 3D printer to generate a physical representation of the predicted results of treatment. Such a physical representation can include differences in color, density, and / or flexibility to display features of the eye tissue or portions thereof as so displayed. Such 3D displays can be particularly valuable as an aid in preparing for ophthalmic surgery and / or as an educational aid for both the patient undergoing treatment and the practitioner.

[0094] In some embodiments, the graphics engine is not used to provide graphical feedback to the user. In such embodiments, the feedback can be provided in the form of a tabular representation of the results, or a summary document of the potential positive and / or negative results. In some embodiments, such a summary can include recommendations for alternative treatments. In yet other embodiments, the feedback can be provided to the user in a non-display visual form, such as color-coded icons or displays indicating positive or negative results.

[0095] As described above, the physical mechanical model of the present invention can be used in an interactive system that enables a medical practitioner to determine the results of various medical interventions in an individual's diseased or abnormal eye. For that purpose, an emulation system incorporating the physical mechanical modeling system described above can include a mechanism for inputting data related to a planned intervention. Such data can be obtained from a treatment database containing data related to a particular intervention, such as a laser ablation pattern, a PRK incision pattern, a known phacoemulsification process, a particular model of an intraocular lens, etc. Such information can be selected by the user and applied to the pre-modification physical mechanical model of the eye to generate a modified physical mechanical model. Such pre-modification and post-modification physical mechanical models can be combined to generate a dynamic physical mechanical model that shows the effect of one or a series of proposed medical treatments to be performed on the eye. Such a dynamic physical mechanical model can be used for emulation to design or plan a treatment method for an individual patient that can be expected to be more successful compared to the case where it depends only on the training and experience of individual physicians.

[0096] In some embodiments, data related to a planned intervention can be input by a user in a dynamic manner, such as via an appropriate interface, where the user selects an appropriate intervention tool and applies it to the physical machine model before the change. For example, in some embodiments, the user can use a mouse or a similar pointing device to draw a LASIK resection or PRK incision pattern on the cornea of the physical machine model of the patient's eye displayed on a computer screen, and then enter the specified resection parameters or incision depth before generating the physical machine model after the change. Alternatively, a user wearing a VR (virtual reality) set can virtually select and operate virtual tools within a virtual environment that includes the physical machine model of the eye before the change. In some embodiments, the sensor glove can include a haptic feedback or other tactile feedback device to more closely emulate the physical reality. In such embodiments, a series of physical machine models after the change can be derived and displayed when the proposed intervention is applied to provide at least an approximately real-time emulation of the effect of the eye intervention. This enables changes within the emulated treatment, which in turn leads to the development of a more efficient and effective intervention procedure.

[0097] A method for generating a physical mechanical model of an eye, and the effect of a medical treatment on a specific patient's eye can be implemented as part of a treatment system. Such a treatment system can include a memory for storing and retrieving database information as described above, a user interface, and a display. Throughout the following description, numerous references are made to other systems formed from servers, services, interfaces, portals, platforms, or computing devices. Such computing devices are assumed to have at least one processor configured to execute software instructions stored on a computer-readable tangible non-transitory medium. For example, such a system can be implemented on a server and include one or more computers that operate as a web server, a database server, or other type of computer server to perform the described roles, responsibilities, or functions. Alternatively, such a system can be realized as a stand-alone device. In some embodiments, such a treatment system can communicate with or be connected to a device used for eye treatment (e.g., a LASIK system) and can be used to provide guidance during the treatment. Example

[0098] In an example of generating and using a physical mechanical model of a part of an eye, when an operator opens the lens capsule surrounding the lens of a specific patient, the operator desires to open it without causing significant damage that would prevent subsequent positioning of the intraocular lens. A cross-section of the eye is shown in FIG. 7. As shown, the lens capsule surrounding the lens is surrounded and connected to various structures of the eye that can affect its shape and position.

[0099] Physical and mechanical data related to various parts of the eye can be derived from measurements of an individual patient's eye, such as intraocular pressure, density, wavefront scan, or changes can be made to statistical data using such measurements to individualize it. Such data can be represented, for example, using a lookup table that can be stored in a patient-specific database. This information can be used to generate a physical and mechanical model of the patient's eye or eye structure before the change. Similarly, changes added to such values as a result of a medical intervention are provided in a similar tabular format and can then be used to generate a physical and mechanical model of the eye or eye structure after the change. Combining such models can form a dynamic physical and mechanical model of the patient's eye or eye structure.

[0100] An example of a typical lookup table of the physical and mechanical characteristics of an individual patient's lens is as follows. Scan data of the patient's eye Population mean Value of the individual lens a.p = density (Scheimpflug TM Lens densitometer; Oculus Pentacam TM ) i. Periphery 1.070 gm / cm 3 1.087 gm / cm 3 ii. Center 1.056 gm / cm 3 1.081 gm / cm 3 iii. Surface 1.072 gm / cm 3 1.090 gm / cm 3 b. Diameter (Scheimpflug TM Lens densitometer; Oculus Pentacam TM ) c. Diameter - transverse 9.5 mm 9.58 mm Aberration variation 0%mm 0.1%mm d. Diameter - sagittal 9.5 mm 8.380 mm Non - spherical aberration variation 0%mm - 20%mm e. Thickness (axial length) 4.000mm - 4.178mm ((Scheimpflug TM Lens densitometer; Oculus Pentacam TM )) f. Anterior IOP 16mm / hg - 20mm / hg (Applamatton TM Tonometer; Air puff) g. Surface shape data CAD model - actual vector (Optical coherence tomography, X - section and 3D image) Itrace TM Aberrometer / Topographer, Stratus OCT TM Instrument model 3000 (Carl Zeiss Meditec), Ultrasonic thickness gauge, lateral, sagittal or axial length, Periphery, center from ultrasound) h. Surface hardness (Shore) SD48 - SD50 (Calculated based on OCT pixel unit density)

[0101] An example of a typical lookup table of the physical - mechanical characteristics of the lens capsule for individual patients is as follows. Patient's eye scan data - average - individual lens capsule bag value a. p = density (Scheimpflug TM Lens densitometer; Oculus Pentacam TM ) i. Peripheral length 1.125gm / cm 3 1.100gm / cm 3 ii. Central top 1.100gm / cm 3 1.001gm / cm 3 iii. Central bottom 1.172gm / cm 3 1.190gm / cm 3 b. Diameter (Scheimpflug TM Lens densitometer; OculusPentacam TM ) c. Diameter - horizontal ellipse 10.1mm 10.2mm Aberration variation 0%mm 0.2%mm d. Diameter - sagittal ellipse 9.3mm 8.780mm Aberration variation 0%mm 10%mm e. Wall thickness 6.2um 5.2um ((Scheimpflug TM Lens densitometer; OculusPentacam TM ) f. Anterior IOP 16mm / hg 20mm / hg (Applamatton TM Tonometer; Air puff) g. Shape CAD model actual vector (Optical coherence tomography, X - section and 3D image, Itrace TM Aberrometer / Topographer, StratusOCT TM Instrument model 3000 (Carl Zeiss Meditec) , Ultrasonic thickness gauge, horizontal, sagittal or axial length, perimeter, center from ultrasonic)

[0102] An example of a typical lookup table of the mechanical characteristics of the zonular fibers of individual patients is as follows. Patient's eye scan data average individual zonular fiber value a. p = density (Scheimpflug TM Lens densitometer; OculusPentacam TM ) Inner 0.910gm / cm 3 0.887gm / cm 3 Outer 1.000gm / cm 3 1.20gm / cm3 b. Diameter (Scheimpflug TM Lens densitometer; OculusPentacam TM , ultrasound biomicroscope)) Diameter - transverse 10.5mm 9.68mm Aberration variation 0%mm 0.1%mm Diameter - sagittal direction 11.5mm 11.380mm Aberration variation 0%mm 20%mm c. Thickness 0.240mm 0.211mm (Scheimpflug TM Lens densitometer; OculusPentacam TM ) d. Anterior IOP 16mm / hg 20mm / hg (Applamatton TM Tonometer; air puff) e. Shape CAD model actual vector (Optical coherence tomography, X - section and 3D images, Itrace TM Aberrometer / topographer, StratusOCT TM Instrument model 3000 (Carl Zeiss Meditec) 、ultrasonic thickness gauge, transverse, sagittal or axial length, perimeter, center from ultrasound) f. Surface hardness (Shore) SD48 SD50 (Calculated based on OCT pixel unit density)

[0103] As described above, to generate a predictive three-dimensional physical machine model using known mechanical principles, the known mechanical principles are applied to such patient-specific values. For example, the Young's modulus with respect to stress and strain can be estimated for various eye structures based on the recorded patient-specific values. Normal eye structures include the lens, lens capsule, zonular sclera, cornea, iris, epithelium, cilia and associated muscles, the anterior chamber with aqueous humor, the posterior chamber with vitreous humor, suspensory ligaments, pupil, Schlemm's canal, fibrociliary band, conjunctiva, limbus, and retina.

[0104] The application of the method and apparatus of the concepts of the present invention is extensive. Examples include the use of a physical machine model in optimizing LASIK results to determine the pattern and depth of keratectomy prior to cutting a corneal flap. This is particularly applicable when the natural properties of the cornea have been altered, for example, by crosslinking (which increases rigidity) and / or previous LASIK or PRK procedures. The physical machine model of the eye can also be applied to procedures performed by a femtosecond laser that produces incisions that are much narrower than those previously made using a blade and result in different mechanical properties in the incised structure. Using the physical machine model of an individual's cornea, various RF intensities, durations, and targeting results in Conductive Keratoplasty (registered trademark) for changing the hardness of the cornea and improving the results of monovision correction for presbyopia can be evaluated. Using the physical machine models of an individual's cornea and lens, the waveform, time, intensity, and incision placement of phacoemulsification can be optimized. Similarly, using the physical machine model of an individual's eye, the selection and placement of an intraocular lens can be optimized to obtain optimal visual acuity results, particularly when the patient has previously undergone LASIK or PRK (refractive correction) of the cornea and / or has extreme myopia or hyperopia that changes the shape of the eyeball.

[0105] In another embodiment of the present invention, the modeling engine communicates with a femtosecond laser system to perform treatments on the lens and / or cornea (including those related to cataract removal / replacement), and refractive treatments (such as limbal relaxing incisions and micro-incisions of the cornea). The femtosecond laser, and the femtosecond laser beam, as these terms are used herein, have a pulse duration of less than about 10 picoseconds (less than about 10×10 -12 seconds) to about 1 femtosecond (fs) (about 1×10 -15 seconds).

[0106] An example of an integrated system according to the present invention is shown in FIG. 10. As shown, the integrated system 1000 includes a femtosecond laser 1001, a first GUI 1004, a second GUI 1003, and a modeling engine 1002 (which can include an integrated phacoemulsification system in some embodiments). The first GUI 1004 and / or the second GUI 1003 can receive and display information and data. Examples of such information and data include control information, information regarding the operation of the system, user selections, user inputs, patient data, modeling information, modeled information, predicted effects, displays, data, tables, and displays, images, information, and data derived or generated from the modeling engine 1002.

[0107] An example of communication and workflow between the modeling engine of the present invention and the laser system is shown in FIG. 11. As shown, there is a femtosecond laser system 1100 (in some embodiments, including an integrated phacoemulsification and aspiration system), and a modeling system 1101 having a modeling engine and one or more patient databases, where the patient databases can include pre-treatment and post-treatment information and / or statistical databases, and each patient database communicates with the modeling engine. The modeling system 1101 communicates with the femtosecond laser, as indicated by arrows 1103 and 1104, and in some embodiments, controls the communication. An example of communication and workflow inside and between systems 1100 and 1101 is shown by workflow chart 1102.

[0108] At least some or all of the components of the modeling system 1101 can be integrated with the laser system 1100 (e.g., included within a common housing). In some embodiments, at least some or all of the components of the modeling system 1101 can be arranged in a stand-alone unit that communicates with the laser system 1100 via a wireless, network, or wired communication system. In some embodiments of the present invention, at least some or all of the components of the modeling system 1101 can be arranged in the cloud. Combinations and variations of these configurations are also contemplated.

[0109] The workflow charts and physical machine models of FIGS. 1 and 2, and combinations and variations thereof, can be used in the embodiments shown in FIGS. 10 and 11. Embodiments of such laser systems can include a phacoemulsification system that is partially or fully integrated with the laser system, including integration and communication with the modeling engine.

[0110] It should be apparent to those skilled in the art that many more changes other than those already described are possible without departing from the present invention. Accordingly, the subject matter of the present invention should not be limited except within the spirit of the appended claims. Further, when interpreting both the specification and the claims, all terms should be interpreted as broadly as possible in accordance with the context. In particular, the term "comprising" should be interpreted as referring to elements, components, or steps in a non-exclusive manner, such that the referenced elements, components, or steps may be present, utilized, or combined with other elements, components, or steps not explicitly referenced. When a claim refers to at least one selected from a group consisting of A, B, C... N, it should be interpreted as requiring only one element from this group, rather than, for example, A and N, or B and N.

Claims

1. 1. A system for assisting a user in performing ophthalmic surgery on an eye of a patient, comprising: a user interface communicatively coupled to the input / output interface and configured to communicate with a user device; databases communicatively connected to the input / output interface, the databases including a patient specific database, a clinical database, and a treatment database; a processor communicatively connected to the input / output interface and to the database, the processor including an algorithm for providing a physical-mechanical model of the eye or a portion of the eye; Including, The system, wherein at least one of the input / output interface, the database, and the processor are cloud-based.

2. The system of claim 1 , wherein the input / output interface includes a planning module that provides an interface useful for planning a course of treatment.

3. The system of claim 1 or 2, wherein the input / output interface includes a treatment module that provides guidance during a surgical procedure.

4. The system of claim 1 , wherein the database includes a practitioner database.

5. 5. A system according to any preceding claim, wherein the database comprises an equipment database.

6. 6. The system of claim 1 , wherein the processor comprises a machine learning algorithm configured to correlate data from the clinical database with data from the patient-specific database and provide a treatment recommendation via the input / output interface.

7. 1. A method for planning eye surgery on a patient, comprising: accessing a planning module in an input / output interface communicatively coupled to a database and a processor, the input / output interface including an algorithmic support, the database including a patient-specific database, a clinical database, and a treatment database; inputting a desired outcome of the eye surgery via the input / output interface; determining a recommended treatment using a machine learning algorithm of the processor and data from the patient-specific database, the clinical database, and the treatment database; Including, The method, wherein at least one of the input / output interface, the database, and the processor are cloud-based.

8. The method of claim 7 , comprising generating a physical-mechanical model of the eye or a portion of an eye.

9. The method of claim 8 , wherein the desired outcome is input by a user's interaction with the physical machine model.

10. The method of claim 8 , wherein the recommended action is communicated to the user by the physical machine model.

11. 11. The method of any one of claims 7 to 10, wherein the database includes a practitioner database, and the recommended treatment is determined in part by data from the practitioner database.

12. 12. The method of any one of claims 7 to 11, wherein the database includes an equipment database, and the recommended action is determined in part by data from the equipment database.

13. 13. The method of any one of claims 7 to 12, comprising the step of transmitting the predicted outcome of the recommended treatment to the input / output interface.

14. 1. A method for planning eye surgery on a patient, comprising: physically characterizing the eye to determine at least a first density and at least a first dimension of the ocular structure; applying the determined densities and dimensions to derive a physical-mechanical model representative of the eye structure or anatomical structure; receiving a selection of a selected ophthalmic procedure from a user; applying the selected ophthalmic treatment to the physical-mechanical model to predict an effect of applying the selected ophthalmic treatment to the ocular structure; providing the user with an indication of a predicted effect of the selected ophthalmic treatment when applied to the ocular structure; Including, the physical-mechanical model is derived from anatomical mechanical properties of the eye or a portion thereof; The method of claim 1, wherein the physical-mechanical model includes a layered model of a cornea of ​​the eye, the layered model incorporating a first model representing a portion of the cornea as a layer of the layered model, the first model being generated using an energy minimization approach, and the layered model incorporating additional layers with different mechanical properties.

15. The method of claim 14, wherein the indication of predicted efficacy is derived from a structural analysis of the change in the mechanical property due to the selected treatment.

16. 16. The method of any one of claims 14 or 15, wherein the indication of predicted effect is derived from minimization of calculated strain or static energy following application of the selected treatment, the calculated strain or static energy being derived from the mechanical properties.

17. 17. The method of any one of claims 14 to 16, wherein the indication of predicted efficacy is derived from analysis of the eye or part of the eye as a flexible laminate structure following application of the selected treatment.

18. 18. The method of any one of claims 14 to 17, comprising acquiring additional ophthalmic data for use in generating the physical-mechanical model, the additional ophthalmic data being selected from the group consisting of corneal acoustic response or ultrasound data, topography data, pachymetry data, height data, corneal thickness data, corneal curvature data, wavefront data, intraocular pressure data, peripheral stromal thickness data, patient age, patient gender, duration of contact lens use, previous surgical intervention, response to previous surgical intervention, and corneal yield point.

19. modifying the selected ophthalmic procedure to generate a modified ophthalmic procedure; using the physical-mechanical model to predict a second predicted effect resulting from application of the altered ophthalmic treatment to the eye; 19. The method of any one of claims 14 to 18, further comprising:

20. 20. The method of claim 19, wherein the second predicted effect on the ocular structure provides a modified ocular structure, and further comprising the step of utilizing the calculated physical properties of the modified ocular structure to generate a second physical-mechanical model representing the modified ocular structure.

21. a femtosecond laser for delivering a femtosecond laser beam to the eye; a modeling system including a modeling engine and a patient database, the patient database configured to receive the determined density characteristic of the ocular structure and the determined dimensional characteristic of the ocular structure; and a graphic user interface (GUI) configured to receive input from a user including a selected action and to display output from the modeling system; Including, The modeling system comprises: deriving a representation of a physical-mechanical model of the ocular structure based on the determined density characteristics of the ocular structure received by the patient database, the determined dimensional characteristics of the ocular structure received by the patient database, or both; receiving the selected action from the GUI; applying the selected treatment to a representation of the physical-mechanical model, thereby deriving a predicted effect of the selected treatment on the ocular structure; providing an indication of the predicted effect in the GUI; and It is designed to carry out the following: The physical-mechanical model includes a layered model of a cornea of ​​the eye, wherein a first model representing a portion of the cornea is incorporated as a layer of the layered model, the first model being generated using an energy minimization approach, and wherein the layered model incorporates additional layers with different mechanical properties.

22. 22. The laser system of claim 21 comprising a phacoemulsification system.

23. 23. The system of claim 21 or 22, wherein the selected procedure is a limbal relaxing incision.

24. 23. The system of claim 21 or 22, wherein the selected procedure is a corneal microincision.

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