Apparatus, systems and methods for improving visual outcomes for pseudophakic patients
09823163 · 2017-11-21
Assignee
Inventors
- Aixa Alarcon Heredia (Groningen, NL)
- Carmen Canovas Vidal (Groningen, NL)
- Robert Rosén (Groningen, NL)
- Hendrik A. Weeber (Groningen, NL)
- Patricia Ann Piers (Groningen, NL)
Cpc classification
G16Z99/00
PHYSICS
G01M11/0235
PHYSICS
International classification
Abstract
A system and method of characterizing through-focus visual performance of an IOL using metrics based on an area under the modulation transfer function for different spatial frequencies at different defocus positions of the IOL. Also disclosed is a system and method of characterizing through-focus visual performance of an IOL using a metric based on an area under a cross-correlation coefficient for an image of a target acquired by the IOL at different defocus positions of the IOL.
Claims
1. An optical system configured to predict clinical visual performance of an intraocular lens (IOL), the system comprising: an IOL optical quality measurement device configured to acquire a plurality of images of a target including objects with different spatial frequencies and obtain modulation transfer function (MTF) and/or phase transfer function (PTF) at different spatial frequencies for different defocus positions of the IOL in a vision range from the acquired plurality of images, the measurement device comprising: a processor configured to execute programmable instructions stored in a non-transitory computer storage medium to calculate a metric based on at least one preclinical metric selected from: an area under the MTF (MTFa) obtained by integrating preclinical through focus MTF measurements obtained for different spatial frequencies between 0 cycles per mm and 200 cycles per mm for each of the different defocus positions; a cross correlation coefficient (X-cor) corresponding to a convolution of a reference image and the plurality of images acquired by the IOL optical quality measurement device at each of the different defocus positions; a weighted MTF (wMTF) obtained by integrating a product of a threshold contrast sensitivity (CS.sub.th) and through focus MTF measurements obtained for different spatial frequencies between 0 cycles per mm and 200 cycles per mm for each of the different defocus positions; or a weighted OTF (wOTF) obtained by integrating a product of a threshold contrast sensitivity (CS.sub.th), through focus MTF measurements, and cosine of the PTF obtained for different spatial frequencies between 0 cycles per mm and 200 cycles per mm for each of the different defocus positions; and obtain a correlation between the calculated metric and clinical data that predicts visual acuity (VA) at different defocus positions of the intraocular lens (IOL).
2. The system of claim 1, wherein the measurement device comprises: a reference image illuminated by a light source; and an imaging system including a pupil.
3. The system of claim 2, wherein the light source is a white light source.
4. The system of claim 2, wherein the pupil has a size between 1 mm and 6 mm.
5. The system of claim 1, wherein the objects have spatial frequencies between about 0 cycles per mm (cpmm) and 200 cpmm.
6. The system of claim 1, wherein the target is selected from the group consisting of an optotype, a slit, a 1951 USAF picture chart; and a subset of bars from a 1951 USAF picture chart.
7. The system of claim 1, wherein the measurement device is a computing device including the processor, the computing device configured to simulate the plurality of images using models for the target and the IOL.
8. The system of claim 1, wherein the metric is based on at least two preclinical metrics selected from: the area under the MIT (MTFa) for each of the different defocus positions; the cross correlation coefficient (X-cor) for the acquired plurality of images at each of the different defocus positions; the weighted MIT (wMTF) for each of the different defocus positions; or the weighted OTF (wOTF) for each of the different defocus positions.
9. The system of claim 1, wherein the different defocus positions are between 0 D and −3.0 D.
10. The system of claim 1, wherein the processor is configured to calculate the area under the MTF (MTFa) according to
11. The system of claim 1, wherein the processor is configured to calculate the weighted MTF (wMTF) according to
12. The system of claim 1, wherein the processor is configured to calculate the weighted OTF (wOTF) according to
Description
BRIEF DESCRIPTION OF THE DRAWINGS
(1) Embodiments of the present invention may be better understood from the following detailed description when read in conjunction with the accompanying drawings. Such embodiments, which are for illustrative purposes only, depict novel and non-obvious aspects of the invention. The drawings include the following figures:
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DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENT
(26) Each and every feature described herein, and each and every combination of two or more of such features, is included within the scope of the present invention provided that the features included in such a combination are not mutually inconsistent.
(27) As used herein, the terms “about” or “approximately”, when used in reference to a Diopter value of an optical power, mean within plus or minus 0.25 Diopter of the referenced optical power(s). As used herein, the terms “about” or “approximately”, when used in reference to a percentage (%), mean within plus or minus one percent (±1%). As used herein, the terms “about” or “approximately”, when used in reference to a linear dimension (e.g., length, width, thickness, distance, etc.) mean within plus or minus one percent (1%) of the value of the referenced linear dimension.
(28) Pre-clinical optical performance of IOLs is currently assessed using modulation transfer function (MTF) values at a single spatial frequency between about 0 cycles per mm and about 100 cycles per mm. The Modulation Transfer Function (MTF), describing the resolution and performance of an optical system is the ratio of relative image contrast divided by relative object contrast. In other words MTF=Relative Image Contrast/Relative Object Contrast. Through focus visual acuity is clinically measured using optotypes that can be deconstructed into multiple spatial frequencies. All spatial frequencies contribute to the interpretation of these optotypes. For example, lower spatial frequencies can help characterize the performance of the IOLs in performing visual tasks under conditions of noise or blur. Accordingly, multiple spatial frequencies should be considered when evaluating the pre-clinical optical performance of the IOL so that the pre-clinical estimate matches the visual acuity of the IOL when implanted in the eye.
(29) One such pre-clinical metric is the area under the through focus MTF curve captured for multiple spatial frequencies simultaneously (MTFa). The MTFa can be defined using equation 1 from 0 cycles per mm to 50 cycles per mm, where d determines the sampling size for preclinical measurements at each spatial frequency (f).
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(31) The MTFa can be integrated between 0 cycles per mm and 50 cycles per mm; between 0 cycles per mm and 100 cycles per mm; between 0 cycles per mm and 150 cycles per mm; between 5 cycles per mm and 150 cycles per mm; between 0 cycles per mm and 200 cycles per mm; or there between.
(32) Another example of a pre-clinical metric that can predict the visual performance of an IOL when implanted bilaterally in a patient is the area under the weighted MTF (wMTF). The wMTF can be calculated for each defocus position by the area under the product of the threshold contrast sensitivity (CS.sub.th) (as measured by Campbell and Green in 1965.sup.1) and the MTF measured in the optical bench for a range of spatial frequencies (equation 2) where d determines the sampling size for preclinical measurements at each spatial frequency (f).
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(34) For example, the wMTF can be integrated between 0 cycles per mm and 50 cycles per mm; between 0 cycles per mm and 100 cycles per mm; between 0 cycles per mm and 150 cycles per mm; between 0 cycles per mm and 200 cycles per mm; or there between.
(35) Another example of metric that can predict the visual performance of an IOL when implanted bilaterally in a patient is the area under the weighted optical transfer function (wOTF). The wOTF can be calculated for each defocus position as described in equation 3 where d determines the sampling size of the spatial frequency (f), PTF is the phase transfer function measured in the optical bench and the CS.sub.th the threshold contrast sensitivity as measured by Green and Campbell (1965) Campbell F W, Green D G. Optical and retinal factors affecting visual resolution. J Physiol. 1965; 181(3):576-93.
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(37) The wOTF can be integrated between 0 cycles per mm and 50 cycles per mm; between 0 cycles per mm and 100 cycles per mm; between 0 cycles per mm and 150 cycles per mm; between 0 cycles per mm and 200 cycles per mm; or there between.
(38) Another example of a metric that is capable of predicting the visual performance of an IOL when binocularly implanted in a patient is the cross correlation (X-cor) metric. The X-cor metric can be calculated by performing a convolution of a reference image and the image collected by a bench-top optical system for each defocus position, adjusting parameters of the collected image, such as for example, magnification, average intensity levels and position shifts of the collected images in order to yield the highest cross correlation coefficient. A reference image having a wide range of spatial frequencies and orientations can provide a better estimate of the visual performance. For example, the reference image can include the 1951 USAF resolution test chart, the USAF optical test pattern or other patterns and images used in optometry. In various implementations, the X-cor metric can be obtained by using, as reference image, a 1951 USAF picture chart measured on a bench-top optical system at the best focus for the ISO cornea for a 3 mm pupil at green light in water without IOL.
(39) The MTFa, the wMTF, the wOTF and the X-cor metrics can predict the through focus visual acuity of an IOL when implanted bilaterally with sufficient accuracy. Therefore, and because these metrics correlate to clinical performance, their maximum is a valid best focus position, from which depth of focus can be defined, so that these metrics can be used to define the clinical depth of focus provided for a particular lens design from preclinical data measured in actual IOL samples. Alternatively, to evaluate if the through focus visual acuity provided by an IOL decreases monotonically from the best focus, the MD (monotonic decrease) parameter can be calculated using the visual acuity curves predicted by these metrics. The MD-parameter can be calculated by fitting the predicted visual acuity to a linear function from 0 D to −3 D. Without any loss of generality, the MD-parameter can refer to the product of the slope and the correlation coefficient (R.sup.2) of the linear function. For example, monofocal lenses have a clear monotonic decrease of the visual acuity from the best focus which corresponds to very negative MD parameters.
(40) In another embodiment, the predicted visual acuity can be fitted to a linear function for a smaller defocus range, i.e. between 0 D and −1.5 D or between 0 D and −1.0 D or between 0 D and −0.5 D. The range can also incorporate positive defocus values, so that the fitting can be performed between +0.5 D and −0.5 D. To evaluate if the lens is tolerant to refractive errors, a TRE (tolerance to refractive errors) parameter can be calculated using the through focus visual acuity or contrast sensitivity curves provided by these metrics. The TRE-parameter can be calculated by fitting the predicted visual acuity to a linear function from 0 D to −1.5 D or to −1.0 D or to −0.5 D. Without any loss of generality, the TRE-parameter can refer to the inverse of product of the slope and the correlation coefficient (R.sup.2) of the linear function. In an alternative embodiment, the TRE-parameter can be defined as the inverse of the slope of the linear function. The more tolerant to refractive errors the lens is, the higher the TRE-parameter will be.
(41) Another metric to evaluate the visual acuity over a range of defocus is the area under through focus visual acuity curve (AU Defocus curve) measured clinically in patients implanted with an IOL. The AU Defocus curve provides with a single value to estimate the average visual performance over a defocus range (e.g. from −2 D to −0.5 D to evaluate intermediate vision; from −0.5 D to 0 D to evaluate distance vision; from −3 D to −2 D to evaluate near vision; from −0.5 D to +0.5 D to evaluate tolerance to refractive errors). For a given defocus range, the AU Defocus curve is calculated by integrating the area under the through focus visual acuity measured clinically over that defocus range. The AU Defocus parameter can alternatively be calculated from the clinical through focus contrast sensitivity measured for one particular spatial frequency.
(42) The AU Defocus curve over a defocus range (e.g. from −2 D to −0.5 D to evaluate intermediate vision) can be estimated from preclinical measurements by the area under the through focus MTFa (AU MTFa) for a given spatial frequency range (e.g. from 0 cycles per mm to 50 cycles per mm; from 0 cycles per mm to 100 cycles per mm). The AU MTFa, calculated from the preclinical through focus MTF measurements, provides with a single value to describe the average visual performance of a pseudophakic patient implanted with an IOL over a range of defocus.
(43) Another metric that can predict the average visual performance over a range of defocus is the area under the through focus wMTF (AU wMTF) for that defocus range. The AU wMTF can be calculated by integrating the wMTF over a defocus range (e.g. between −2 D and −0.5 D to evaluate intermediate vision).
(44) Another metric that can predict the average visual performance over a range of defocus is the area under the through focus (AU wOTF) for that defocus range. The AU wOTF can be calculated by integrating the wOTF over a defocus range (e.g. between −2 D and −0.5 D to evaluate intermediate vision).
(45) Another metric that can predict the average visual performance of an IOL for a given defocus range from preclinical data is the area under the through focus X-cor (AU X-cor) for that defocus range. The AU X-cor can be calculated by integrating the X-cor curve over a defocus range (e.g. between −2 D and −0.5 D to evaluate intermediate vision). An implementation of a system and method of obtaining the different metrics discussed above is described below.
(46) The MTFa, the wMTF, the wOTF can predict the distance contrast sensitivity (CS) at 6 and 12 cpd of an IOL when implanted bilaterally. Furthermore, AU MTFa, AU wMTF and AU wOTF can be used to predict the area under the contrast sensitivity through focus curve, providing an estimation of the contrast performance in the intermediate range.
(47) Correlation Between Preclinical Metrics and Clinical Results
(48) The correlation between the various metrics described in the previous section calculated for several different IOL models and the high contrast binocular visual acuity (VA) measured in patients implanted with the same IOL models is described below with reference to
VA(x)=ax^b+c Equation 4
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(50) TABLE-US-00001 TABLE 1 R.sup.2 and coefficients (a, b and c) than best fit the clinical VA with the preclinical metrics MTFa, wMTF, wOTF and X-cor using equation 4. MTFa wMTF wOTF X-cor R.sup.2 0.951 0.959 0.935 0.893 a 0.078414 2.065996 1.0865 0.130328 b −1.00019 −0.75199 −0.3646 −1.42647 c −0.2072 −0.19493 −0.35135 −0.21744
(51) The MTFa was calculated for spatial frequencies up to 50 cpmm. This value was chosen because the correlation coefficient between the clinical VA and the MTFa reaches a plateau (
(52) For comparison,
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(56) The various metrics illustrated in
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(61) The various metrics illustrated in
(62) The correlation between the preclinical metrics MTFa, wMTF, wOTF and X-cor described in the previous section calculated for several different IOL models and the clinical CS at 6 and 12 cycles per degree (cpd) measured in patients implanted with the same IOL models is described below with reference to
CS(x)=ax^b+c Equation 5
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(64) TABLE-US-00002 TABLE 2 R.sup.2 and coefficients (a, b and c) than best fit the clinical CS at 6 cpd with the preclinical metrics MTFa, wMTF and wOTF using equation 5. MTFa wMTF wOTF X-cor R.sup.2 0.747 0.688 0.650 0.629 a −0.03191 −59.7651 −4.9608 4.013639 b −1.90106 −1.75212 −0.93507 0.27834 c 1.720074 1.71499 1.77662 −2.23111
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(69) TABLE-US-00003 TABLE 3 R.sup.2 and coefficients (a, b and c) than best fit the clinical CS at 12 cpd with the preclinical metrics MTFa, wMTF and wOTF using equation 5. MTFa wMTF wOTF X-cor R.sup.2 0.970 0.969 0.974 0.985 a −0.10183 13.89135 2.010493 0.955806 b −1.38586 0.019724 0.096027 3.571574 c 1.31097 −13.8744 −1.79611 0.51569
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(73) It is noted that the correlation between clinical data and preclinical metrics will change if preclinical metrics are performed for different optical conditions (e.g. green/white light, 3 mm/5 mm aperture, etc.).
(74) Example of Characterizing the Optical Performance of IOLs Using the Metrics
(75) In one example of the systems and methods, the performance of two IOLs was compared. One of the IOLs included was aspheric monofocal IOL (referred to herein as IOL1). Another IOL also included was one aspheric multifocal lens, with an add power of +4.00 in the IOL plane (referred to herein IOL2)
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(77) The array of ordered values 508 can measure and/or record and/or include data related to one or more types of available IOL, models of optotypes, one or more models of the eye, etc. In some embodiments, the sequence of instructions 518 can include algorithms to measure the corresponding preclinical data to calculate the metrics for different defocus ranges and analyze the optical performance of the IOLs and relate that to their clinical performance.
(78) The algorithms and/or formulae to calculate the metrics can be implemented as a set of instructions which are stored in a non-transitory computer medium and executed by processing electronics 502. The calculation of the metrics can be performed over the internet. The algorithms and/or formulae to calculate the metrics can be implemented as a mobile application which can be downloaded on a mobile device. The algorithms and/or formulae to calculate the metrics can be implemented as a software program that is a part of an instrument. An instrument to implement the methods described herein can comprise a set of apparatuses, including a set of apparatuses from different manufacturers that are configured to perform the necessary measurements and calculations. Any instrument comprising all needed measurements (MTF, PTF and/or recording the image yielded by the optical system with or without containing the IOL) as well as the needed calculations to implement the methods described herein can be considered as an inventive embodiment. The processing electronics may be embodied in a distributed computing system, general purpose desktop, laptop, tablet or mobile computer, and/or may comprise hardware and/or software.
(79) The processing electronics 502 may be embodied in a general purpose desktop, laptop, tablet or mobile computer. In certain embodiments, the system 500 may be configured to be electronically coupled to another device, such as one or more instruments for obtaining measurements of the optical quality provided by each IOL in a particular physical eye model. Alternatively, the system 500 may be adapted to be electronically and/or wirelessly coupled to one or more other devices.
(80) The system can be implemented as a bench-top optical system. In such implementations, the processing electronics 502 can be connected to an optical bench-top system 501 including an illumination source, an imaging system and one or more targets. Alternately, the system can be implemented on one or more computing devices using models for the target, the various implementations of the IOLs, white light source and the imaging system. In various implementations, the target can be an optotype including a plurality of characters and/or letters. For example, the metrics can be obtained from the evaluation of the images and/or MTF and/or PTF measurements yielded by different IOL designs. In various implementations, the target can include a plurality of objects with a wide range of spatial frequency content (e.g. between about 0 cycles per mm and about 200 cycles per mm). In various implementations, the target can be a 1951 USAF picture chart. In an alternative embodiment, the target can be a slit, oriented in any direction. The analysis of the image provided by the IOL under study once implanted in the particular eye model, allows for calculating the corresponding MTF and PTF at different spatial frequencies.
(81) To obtain the MTFa, wMTF, wOTF and X-cor metrics, the through focus MTF and PTF (both for different spatial frequencies) and USAF pictures can be measured in an optical bench. As a way of example, these measurements can be performed at 3 mm pupil in white light. The optical conditions at which these measurements can be performed may depend on the optical conditions for which the correlation with clinical data as described in the previous sections has been developed. Alternatively, optical bench measurements can be performed in any combination of light conditions and pupil size that fulfill the previous requirement. Without any loss of generality, the pupil sizes referred to herein can represent the exposed central area of the IOL under test, which can differ from the aperture stop of the test system.
(82) To obtain the AU MTFa, AU wMTF, AU wOTF and AU X-cor metrics, the through focus MTF and PTF (both for different spatial frequencies) and USAF pictures can be measured in an optical bench. As a way of example, these measurements can be performed at 3 mm pupil in white light. The optical conditions at which these measurements can be performed may depend on the optical conditions for which the correlation with clinical data as described in the previous sections has been developed. Alternatively, optical bench measurements can be performed in any combination of light conditions and pupil size that fulfill the previous requirement. Without any loss of generality, the pupil sizes referred to herein can represent the exposed central area of the IOL under test, which can differ from the aperture stop of the test system.
(83) The imaging system can be configured to be in communication with processing electronics (e.g., processing electronics 502) that are configured to calculate the area under the MTF (MTFa) curve for a range of spatial frequencies (e.g. between 0 cycles per mm to 50 cycles per mm) for each defocus position (e.g. from −3 D to 0 D in steps of 0.5 D) from the measured through focus MTF and/or PTF obtained for several different spatial frequencies, and/or USAF pictures. Alternatively, the system can be configured to obtained the wMTF and wOTF for a range of spatial frequencies (e.g. between 0 cycles per mm and the maximum spatial frequency measured or between 0 cycles per mm and 150 cycles per mm) for each defocus position (e.g. from about −3.0 D to about 0 D in steps of 0.5 D). The processing electronics can be further configured to calculate the X-cor for each defocus position (e.g., between about −3.0 D and about 0 D in steps of 0.5 D). Furthermore, the simulated VA can be calculated for each of these metrics making use of the regressions shown in the previous section.
(84) As a way of example,
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(86) It is noted that the absolute difference between the simulated VA calculated for an IOL model and the clinical VA measured in patients bilaterally implanted with the same IOL model for different defocus positions between about 0 D and about −3.0 D is lower than 0.1 Log MAR for most of the defocus positions and most of the preclinical metrics. Therefore, any of the metrics can be used to predict the VA measured in patients implanted with these IOLs for which the preclinical metrics have been calculated. Furthermore, the preclinical metrics described above can be used to develop newer correlations when clinical and preclinical data for the other IOL models are available. Alternatively, these preclinical metrics, together with existing correlations to clinical data for other IOL models, can be used to predict the though focus simulated VA for new IOL models or prototypes. In another embodiment, existing correlation to clinical data can serve to determine preclinical levels related to clinical effectiveness and safety requirements.
(87) The MD parameter described above can be also calculated to assess the degree of monotonic decrease that simulated VA shows from distance vision.
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(89) From the slope and correlation coefficient of the linear fit curves, the MD parameter was calculated. Table 4 below shows the corresponding slope, correlation coefficient and resulting MD parameter for the first IOL model (IOL1) and the second IOL model (IOL2). Both the slope (in absolute value) and the correlation coefficient are greater for IOL1 than for IOL2, resulting in a smaller MD parameter for IOL1 than for IOL2. This indicates that simulated VA decreases monotonically from the distance peak for IOL1 than for IOL2. Furthermore, and due to the fact that the slope for IOL1 is greater in absolute value than for IOL2, the decrease in VA is greater for IOL1 than for IOL2, indicating that IOL2 provides a better estimate of VA at intermediate and near vision distances than IOL1. Therefore, the MD parameter can be used to rank the degree of monotonic decrease and the near and/or intermediate performance of existing or new IOLs prototypes.
(90) TABLE-US-00004 TABLE 4 The slope, correlation coefficient and MD parameter calculated from the linear fitting of the simulated VA for two IOL models MTFa wOTF MD MD Slope R2 Parameter Slope R2 Parameter IOL1 −0.248 0.99 −0.25 −0.243 0.99 −0.24 IOL2 −0.003 0.001 −3.2E−6 −0.027 0.13 −0.004
(91) The area under (AU) each particular metric integrated for different defocus positions between about −0.5 D and about −2.0 D and the AU X-cor over the defocus range (e.g. between −2 D to −0.5 D) were calculated for each IOL design. Simulated AU Defocus curve can be calculated along with the correlations described in the previous section.
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(93) Different metrics can be used to evaluate the optical performance of rotationally asymmetric IOLs at intermediate distances. For example, radially averaged MTF (rMTF) can be used instead of MTF to calculate the MTFa. In various implementations, rMTF can be measured for different orientations and averaged. The MTFa can then be calculated by calculating the area under the rMTF for a range of spatial frequencies.
(94) The metrics herein described can be calculated from measured values in in-vitro conditions. In an alternative embodiment, these preclinical metrics and the corresponding correlations with clinical data can be calculated from wavefront aberrations measurements. In an alternative embodiment, these preclinical metrics and the corresponding correlations with clinical data can be calculated from ray tracing simulations. These calculations can retrieve the simulated MTF, PTF and/or simulated USAF pictures, from which the different metrics discussed above can be calculated. These calculations can be used to develop new correlations with clinical results for these IOL models for which these are available. Alternatively, they can be used to assess the intermediate performance or to simulate the clinical VA or the degree of monotonic decrease or tolerance to refractive errors for new IOL models. These correlations can be used to assess the clinical contrast sensitivity at 6 and 12 cpd at distance and/or intermediate and/or near. These simulations can be performed in physical or realistic eye models.
(95) The metrics described herein can be used to develop new correlations with the clinical performance of the IOL models (e.g. driving simulation). The preclinical measurements described herein can be fitted to clinical data or to data obtained from adaptive optics visual simulation. It has been shown that visual acuity and contrast sensitivity measured when inducing the phase profile corresponding to different IOL models using adaptive optics corresponds to visual performance measured in patients implanted with the same IOLs (Schwarz et al ARVO 2014 and Manzanera et al ARVO 2015). Therefore, both, the data obtained in clinical studies involving patients implanted with IOLs and data measured using adaptive optics visual simulation can be used to fit the preclinical information measured in optical bench testing to get the above described preclinical metrics.
(96) The metrics described herein can be calculated for different pupil sizes. The pupil size can be adapted to the light conditions. For example, 4.5 mm pupil size can be used to simulate mesopic conditions in pseudophakic patients.
(97) The metrics described herein can be calculated for different ranges of defocus position. For example, they can be calculated between about −2.0 D and −0.5 D to evaluate intermediate vision, between about −3.5 D and −2.0 D to evaluate near vision or between about −0.5 D and −0 D to evaluate far vision or between +0.5 D and −0.5 D to evaluate tolerance to refractive errors
(98) The metrics described herein can be calculated for different ranges of defocus position. For example, they can be calculated between about −2.0 D and −0.5 D to evaluate intermediate vision, between about −3.5 D and −2.0 D to evaluate near vision or between about −0.5 D and −0 D to evaluate far vision or between +0.5 D and −0.5 D to evaluate tolerance to refractive errors
(99) Although, the above disclosure is related to using metrics to evaluate the clinical performance of intraocular lenses (IOLs), the metrics can be used to evaluate the clinical performance of contact lenses, refractive surgery and/or spectacle lenses.
(100) The above presents a description of the best mode contemplated of carrying out the embodiments described herein, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains to make and use of the embodiments described herein. The embodiments described herein can be modified and alternate constructions from that discussed above which are fully equivalent. Consequently, it is not the intention to limit the disclosure to the particular embodiments disclosed. On the contrary, the intention is to cover modifications and alternate constructions coming within the spirit and scope of the invention as generally expressed by the following claims, which particularly point out and distinctly claim the subject matter of the invention.