Alcon, Inc.

Alcon Refractivehorizons, Inc.

Novartis Ag

Alcon Universal Ltd.

Alcon Refractiveshorizons, Inc.

George H Pettit

John Alfred Campin

Mark Andrew Zielke

Martin Gründig

Peter Zieger

Gary Paul Gray

Daniil Nekrassov

Horia Grecu

Daniel S Durrie

Kevin Liedel

John W Sheets, Jr

Philip Matthew McCulloch

Victor Manuel Hernandez

Martin Gruendig

Daniel W Stanley

Armin Haupt

Robert Moore

William T Lefebvre

Christopher Sean Mudd

Kevin K Liedel

Brant Gillen

John W Sheets

Certain aspects of the present disclosure provide techniques for performing surgical ophthalmic procedures, such as cataract surgeries. An example method generally includes generating, using one or more measurement devices, one or more data points associated with measurements of one or more anatomical parameters for an eye to be treated. Using one or more trained machine learning models, one or more recommendations are generated including one or more IOL parameters for the IOL to be used in the cataract surgery based, at least in part, on the one or more data points. The machine learning models are trained based on at least one historical data set of data points associated with measurements of anatomical parameters mapped to treatment data and treatment result data associated with each historical patient. The one or more IOL parameters comprise one or more of an IOL type, an IOL power, or IOL placement information for implanting the IOL in the eye.

Methods and systems for determining intraocular lens (IOL) parameters for cataract surgery

In certain embodiments, an ophthalmic system for assessing a tear film of an eye comprises measuring devices and a computer. The measuring devices detect light reflected from the eye, where an ocular surface of the eye comprises the tear film, and generate data from the reflected light that describes the eye. The computer aligns the data corresponding to the same location for a plurality of locations, assesses the data at the locations to detect one or more abnormalities of the tear film, and determines a tear film description from the assessment of the data at the locations.

Multi-detector analysis of the tear film of an eye

A system and method for selecting an intraocular lens, for implantation into an eye, includes a controller having a processor and a tangible, non-transitory memory on which instructions are recorded. The controller is configured to selectively execute a machine learning model trained with a training dataset. Execution of the instructions by the processor causes the controller to obtain pre-operative objective data for the patient, including one or more anatomic eye measurements. The controller is configured to obtain pre-operative questionnaire data for the patient, including at least one personality trait. The pre-operative objective data and the pre-operative questionnaire data are entered as respective inputs to the machine learning model. A predicted subjective outcome score for the patient is generated as an output of the machine learning model. The intraocular lens is selected based in part on the predicted subjective outcome score.

Selection of intraocular lens based on a predicted subjective outcome score

An ophthalmic system for measuring an eye comprises measuring devices and a computer. The measuring devices comprise an optical coherence tomography (OCT) device and an aberrometer. The OCT device directs OCT light towards the eye, and detects the OCT light reflected from the eye to measure the eye. The aberrometer directs aberrometer light towards the eye, and detects the aberrometer light reflected from the eye to measure the eye. The computer generates an ocular model of the eye according to the reflected OCT light. The ocular model comprises parameters for the eye, where each parameter is assigned a value. The computer determines an OCT-based wavefront according to the ocular model, determines an aberrometer-based wavefront according to the reflected aberrometer light, ascertains a deviation between the OCT-based wavefront and the aberrometer-based wavefront, and evaluates measurements from one or more of the measuring devices according to the deviation.

Evaluating measurements using information from multiple measuring devices

An ophthalmic system for generating an ocular model of an eye includes an optical coherence tomography (OCT) device, an aberrometer, and a computer. The OCT device detects OCT light reflected from the eye. The aberrometer detects aberrometer light reflected from the eye. The computer generates the ocular model of the eye according to the reflected OCT light. The ocular model includes parameters describing the eye. The parameters include lens parameters that describe the lens of the eye. The computer determines an OCT-based wavefront according to the ocular model, determines an aberrometer-based wavefront according to the reflected aberrometer light, and compares the OCT-based and the aberrometer-based wavefronts. If the wavefronts differ beyond a predefined tolerance, the computer adjusts one or more values assigned to the parameters until the wavefronts satisfy the predefined tolerance. At least one adjusted value is assigned to a lens parameter.

Refining lens parameters of an ocular model

Systems and methods for non-invasively assessing ciliary muscle accommodative potential in phakic eyes may include receiving a plurality of signals generated by a plurality of bipolar electrodes during a ciliary muscle assessment procedure, each of the plurality of signals indicating an electrical field associated with a patient's ciliary muscle, and analyzing the signals to evaluate the patient's ciliary muscle accommodative potential.

Systems and methods for measuring ciliary muscle activity

A system for predicting post-operative vignetting in an eye of a subject includes a controller having a processor and a tangible, non-transitory memory on which instructions are recorded. The controller is in communication with a diagnostic module adapted to store pre-operative anatomic data of the eye as an eye model. The system includes a projection module and a ray tracing module selectively executable by the controller. The projection module is adapted to determine imputed post-operative variables of the eye based at least partially on the pre-operative anatomic data and the intraocular lens. The ray tracing module is adapted to calculate propagation of light through the eye. The ray tracing module is executed to determine a light distribution for respective visual field angles across a predefined field of view. The controller is configured to determine one or more post-operative vignetting parameters based at least partially on the light distribution.

Prediction of post-operative vignetting in a pseudophakic eye

A method of verifying ophthalmic measurements includes obtaining, via an ophthalmic measurement device, a first measurement of at least one ophthalmic parameter over a first measurement area. The first measurement area corresponds to an unassisted visible area of a patient's eye. A second measurement of the at least one ophthalmic parameter over a second measurement area is obtained via the measurement device. The second measurement area corresponds to an assisted visible area of the patient's eye. The first measurement is compared to the second measurement. It is determined if the second measurement diverges from the first measurement. Responsive to a determination that the second measurement diverges from the first measurement, an alert that the second measurement is inaccurate is generated. Responsive to a determination that the second measurement does not diverge from the first measurement, the second measurement is accepted as accurate.

Method and system for measuring optical parameters

A method for assessing a lens capsule stability condition in an eye of a human patient includes directing electromagnetic energy in a predetermined spectrum onto a pupil of the eye, via an energy source, concurrently subsequent to a movement of the eye causing eye saccades to occur therein. The method also includes acquiring images of the eye indicative of the eye saccades using an image capture device, and computing, via the ECU, a motion curve of the lens capsule using the images. Additionally, the method includes extracting time-normalized lens capsule oscillation traces based on the motion curve via the ECU, and then model-fitting the lens capsule oscillation traces via the ECU to thereby assess the lens capsule instability condition. An automated system for performing an embodiment of the method is also disclosed herein, including the energy source, image capture device, and ECU.

Automated assessment of human lens capsule stability

A method for performing wavefront-guided laser surgery on a cornea includes the step of calculating a corneal flap configuration based upon collected anatomical information on an eye and wavefront data on a cornea of the eye. Such data may be collected by, for example, an aberrometer, although this is not intended as a limitation. The calculated configuration is transmitted to a processor in controlling relation to a corneal flap-cutting device. The flap-cutting device is used to create a corneal flap based upon the calculated configuration. A system for performing wavefront-guided laser surgery on a cornea includes a processor for receiving the anatomical information and wavefront data. A software package is adapted to calculate the corneal flap configuration and to control a conical flap-cutting device to cut a corneal flap commensurate with the calculated corneal flap configuration.

Laser corneal flap cutting system and associated methods

A system for determining an accommodative force in a patient includes a sensor adapted to detect motion of a lens of the patient relative to a globe of the patient's eye, a controller configured to determine an accommodative force in the patient based on the relative motion and to determine at least one parameter for an intraocular lens based on the accommodative force, and an interface adapted to output the at least one parameter for the intraocular lens.

Method for assessing residual accommodation in presbyopic eyes

An electro-active ophthalmic lens includes an electromyography sensor, a processor, and an electro-active optical element. The electromyography sensor is configured to detect an electric field in a ciliary muscle of the eye that is proportional to a force exerted by the ciliary muscle and to generate a sensor signal indicative of the electric field. The processor is operable to receive the signal from the electromyography sensor and to determine, based on the sensor signal, an adjustment to optical power for an electro-active optical element and to generate a control signal for the electro-active optical element. The electro-active optical element is operable to receive the control signal and to change an optical power of the electro-active optical element in response to the control signal.

Sensors for triggering electro-active ophthalmic lenses

A method for performing wavefront-guided laser surgery on a cornea includes the step of calculating a corneal flap configuration based upon collected anatomical information on an eye and wavefront data on a cornea of the eye. Such data may be collected by, for example, an aberrometer, although this is not intended as a limitation. The calculated configuration is transmitted to a processor in controlling relation to a corneal flap-cutting device. The flap-cutting device is used to create a corneal flap based upon the calculated configuration. A system for performing wavefront-guided laser surgery on a cornea includes a processor for receiving the anatomical information and wavefront data. A software package is adapted to calculate the corneal flap configuration and to control a corneal flap-cutting device to cut a corneal flap commensurate with the calculated corneal flap configuration.

A method for optimizing a prescription for laser-ablation corneal treatment includes receiving a measured correction prescription for a current patient. Next a database of treatment outcomes on a plurality of previously treated patients is accessed. The database contains a desired correction, and an actual correction. A difference between the desired correction and the actual correction represents an over- or undercorrection resulting from surgery. From the difference data is calculated a distribution of data points as a function of correction level. From the data-point distribution is calculated a statistically based offset applicable to the correction prescription for matching actual corrections with desired corrections. From the data-point distribution is calculated a confidence interval of the data using a predetermined confidence level. The statistically based offset is then adjusted based upon the confidence interval to provide an optimized prescription. The adjusted offset is then output for use in performing a refractive procedure.

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Maitland, FL, United States of America

George H Pettit