Systems and methods for intraocular lens selection
AssigneeAlcon Inc.
InventorsZsolt Bor, Imre Hegedus
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AssigneeAlcon Inc.
InventorsZsolt Bor, Imre Hegedus
Estimating the term…
Systems and methods for intraocular lens selection include receiving, by one or more computing devices implementing a prediction engine, pre-operative multi-dimensional images of an eye; extracting, by the prediction engine, pre-operative measurements of the eye based on the pre-operative images; estimating, by the prediction engine using a prediction model based on a machine learning strategy, a post-operative position of an intraocular lens based on the extracted pre-operative measurements; selecting a power of the intraocular lens based on the estimated post-operative position of the intraocular lens; and selecting the intraocular lens based on the selected power. In some embodiments, the systems and methods further include receiving post-operative multi-dimensional images of the eye after implantation of the selected intraocular lens, extracting post-operative measurements of the eye, and updating the prediction model based on the pre-operative measurements and the post-operative measurements.
A method comprising:
A prediction engine comprising:
A non-transitory machine-readable medium comprising a plurality of machine-readable instructions which when executed by one or more processors are adapted to cause the one or more processors to perform a method comprising:
Dependencies are inferred from the claim text.
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Operational features thereof: characterised by electronic signal processing, e.g. eye models
Computer-aided surgery; Manipulators or robots specially adapted for use in surgery: computer-aided planning, simulation or modelling of surgical…
Eye parts, e.g. lenses or corneal implants; Artificial eyes: intraocular lenses
Architecture, e.g. interconnection topology: combinations of networks
About 12 years 9 months of term left · ends 14 Jul 2039 (estimated)
The present disclosure relates to systems and methods of using multi-dimensional images of an eye to aid in the selection of an intraocular lens to be implanted.
Cataract surgery involves removing the natural lens of an eye and, in most cases, replacing the natural lens with an artificial intraocular lens (IOL). To achieve an optimal post-operative visual outcome, a good pre-operative surgical plan is crucial. Some of the important pre-operative planning decisions are the selection of an appropriate IOL power and an estimate of an effective lens position (ELP) which are determined according to measurements taken of the patient's eye's anatomical and optical characteristics and used in one or more IOL power calculation formulas. See, for example, Cooke, et al., “Comparison of 9 Intraocular Lens Power Calculation Formulas,” J. Cataract Refract. Surg. Vol. 42, pp. 1157-64, 2016; Goto, et al., “Prediction of Postoperative Intraocular Lens Position with Angle-to-Angle Depth Using Anterior Segment Optical Coherence Tomography,” Ophthalmology Vol. 123, pp. 2474-80, 2016; Kane, et al., “Intraocular Lens Power Formula Accuracy: Comparison of 7 Formulas,” J. Cataract Refract. Surg. Vol. 42, pp. 1490-1500, 2016; Martinez-Enriquez, et al. “Estimation of Intraocular Lens Position from Full Crystalline Lens Geometry: Towards a New Generation of Intraocular Lens Power Calculation Formulas,” Nature Scientific Reports Vol. 8:9829, 2018; Melles, et al., “Accuracy of Intraocular Lens Calculation Formulas,” Ophthalmology Vol. 125(2), pp. 1-10; Norrby, et al. “Prediction of the True IOL Position,” Ophthalmology Vol. 101, pp. 1440-46, 2017; and Olsen, “Calculation of Intraocular Lens Power: A Review,” Acta Ophthalmol Scand, Vol. 85, pp. 472-85, 2007, each of which is hereby incorporated by reference in its entirety.
Typically, the measurements used in the IOL prediction formulas are one-dimensional measurements taken on the optical axis using an optical and/or ultrasound biometer. These traditional measurement practices lead to inaccuracy in the ELP which, in turn, leads to the selection of an IOL power that results in a suboptimal vision outcome for the patient.
For a more complete understanding of the present technology, its features, and its advantages, reference is made to the following description, taken in conjunction with the accompanying drawings.
FIG. 1 is a diagram of a system for IOL selection according to some embodiments.
FIG. 2 is a diagram of a method of implanting an IOL using a prediction engine according to some embodiments.
In the figures, elements having the same designations have the same or similar functions.
This description and the accompanying drawings that illustrate inventive aspects, embodiments, implementations, or modules should not be taken as limiting—the claims define the protected invention. Various mechanical, compositional, structural, electrical, and operational changes may be made without departing from the spirit and scope of this description and the claims. In some instances, well-known circuits, structures, or techniques have not been shown or described in detail in order not to obscure the invention. Like numbers in two or more figures represent the same or similar elements.
In this description, specific details are set forth describing some embodiments consistent with the present disclosure. Numerous specific details are set forth in order to provide a thorough understanding of the embodiments. It will be apparent, however, to one skilled in the art that some embodiments may be practiced without some or all of these specific details. The specific embodiments disclosed herein are meant to be illustrative but not limiting. One skilled in the art may realize other elements that, although not specifically described here, are within the scope and the spirit of this disclosure. In addition, to avoid unnecessary repetition, one or more features shown and described in association with one embodiment may be incorporated into other embodiments unless specifically described otherwise or if the one or more features would make an embodiment non-functional.