CN110717884B - Method for expressing corneal irregular change based on ocular surface structure change consistency - Google Patents
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- 230000001788 irregular Effects 0.000 title claims abstract description 20
- 238000000034 method Methods 0.000 title claims abstract description 16
- 210000004087 cornea Anatomy 0.000 claims abstract description 23
- 208000021921 corneal disease Diseases 0.000 claims abstract description 7
- 210000005081 epithelial layer Anatomy 0.000 claims description 15
- 238000012937 correction Methods 0.000 claims description 11
- 230000011218 segmentation Effects 0.000 claims description 7
- 230000000877 morphologic effect Effects 0.000 claims description 6
- 238000004364 calculation method Methods 0.000 claims description 5
- 238000010586 diagram Methods 0.000 claims description 5
- 210000000981 epithelium Anatomy 0.000 claims description 5
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- 230000003511 endothelial effect Effects 0.000 claims description 4
- 210000003560 epithelium corneal Anatomy 0.000 claims description 4
- 206010023365 keratopathy Diseases 0.000 claims description 4
- 239000011159 matrix material Substances 0.000 claims description 4
- 238000007689 inspection Methods 0.000 claims description 3
- 201000009310 astigmatism Diseases 0.000 claims description 2
- 201000002287 Keratoconus Diseases 0.000 abstract description 10
- 238000003325 tomography Methods 0.000 abstract description 5
- 238000005516 engineering process Methods 0.000 abstract description 4
- 238000013399 early diagnosis Methods 0.000 abstract description 2
- 230000004660 morphological change Effects 0.000 abstract description 2
- 238000012014 optical coherence tomography Methods 0.000 description 14
- 238000001356 surgical procedure Methods 0.000 description 8
- 238000003384 imaging method Methods 0.000 description 5
- 238000012216 screening Methods 0.000 description 3
- 238000001514 detection method Methods 0.000 description 2
- 238000003745 diagnosis Methods 0.000 description 2
- 201000010099 disease Diseases 0.000 description 2
- 208000037265 diseases, disorders, signs and symptoms Diseases 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 238000004458 analytical method Methods 0.000 description 1
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- 238000003759 clinical diagnosis Methods 0.000 description 1
- 230000000994 depressogenic effect Effects 0.000 description 1
- 230000010354 integration Effects 0.000 description 1
- 238000004445 quantitative analysis Methods 0.000 description 1
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- 238000000528 statistical test Methods 0.000 description 1
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- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B3/00—Apparatus for testing the eyes; Instruments for examining the eyes
- A61B3/10—Objective types, i.e. instruments for examining the eyes independent of the patients' perceptions or reactions
- A61B3/102—Objective types, i.e. instruments for examining the eyes independent of the patients' perceptions or reactions for optical coherence tomography [OCT]
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- A—HUMAN NECESSITIES
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- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B3/00—Apparatus for testing the eyes; Instruments for examining the eyes
- A61B3/10—Objective types, i.e. instruments for examining the eyes independent of the patients' perceptions or reactions
- A61B3/107—Objective types, i.e. instruments for examining the eyes independent of the patients' perceptions or reactions for determining the shape or measuring the curvature of the cornea
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Abstract
A method for expressing the change of the irregular structure of cornea based on the change consistency parameters of the anterior segment tomography technology provides a method for comprehensively expressing the position of the irregular cornea possibly with morphological change by establishing an objective index of the relative position of parameter change, can theoretically improve the early diagnosis performance of the irregular cornea diseases such as keratoconus and the like, and simultaneously reduces the complexity of jointly reading a large number of parameters in clinical practical work.
Description
Technical Field
The invention particularly relates to the technical field of medical detection, and particularly relates to a method for expressing irregular change of a cornea based on consistency of change of an ocular surface structure.
Background
Corneal ectatic diseases, particularly keratoconus, are the main contraindications of the current corneal refractive surgery. The disease changes uncharacteristically in the early stage and is easy to cause missed diagnosis. Statistically, the annual operation amount of the corneal refractive surgery in China is about 150 ten thousand at present, and is expected to increase at a rate of 12-15%. In the group of myopes who wish to undergo corneal refractive surgery, the incidence of keratoconus, which is a major contraindication for corneal refractive surgery, is relatively high. The missed diagnosis of potential keratoconus patients before operation is an important reason for the concurrent corneal dilatation after the corneal refractive surgery. Therefore, the increasing amount of surgery puts higher demands on accurately identifying patients with keratoconus inclination and improving the early screening efficiency of the keratoconus.
Currently, an examination instrument based on a tomography cornea imaging technology has become a mainstream examination means for preoperative screening of corneal refractive surgery. Representative examination tools include a fissure scanning system and a rotating Scheimpflug camera based anterior ocular segment analyzer. Representative commercial instruments that correspond respectively to are the Obscan system (Bausch & Lomb, inc., Rochester, NY) and the Pentacam anterior ocular segment analyzer (Oculus, gmbh., Wetzlar, Germany). Such techniques provide anterior-posterior surface curvature, anterior-posterior surface height distribution, and corneal thickness distribution, anterior chamber depth, and other relevant parameters by three-dimensional reconstruction of tomographic images. Another type of imaging means is tomographic imaging technology capable of imaging the corneal layered structure, which can describe the corneal layered information, and a main representative examination means is Optical Coherence Tomography (OCT). OCT is the most indispensable inspection tool in ophthalmology clinical diagnosis and treatment, and the most commonly used Anterior Segment OCT (AS-OCT) is mainly second generation Fourier domain OCT (FD-OCT) at present, and the axial resolution can reach 1-10 mu m. The method is divided into Spectral domain OCT (SD-OCT) and Swept source OCT (SS-OCT) according to the difference between the light source and the interference detector. Representative commercial instruments corresponding respectively are: RTVue OCT (Optovue, Inc, Fremont, CA) and Casia OCT (Tomey, Inc., Nagoya, Japan). SD-OCT can image the fine structures of corneal epithelium, anterior elastic layer, even posterior elastic layer, etc., and the value of the SD-OCT in preoperative screening of refractive surgery is gradually accepted.
The imaging means based on the tomographic image can perform quantitative analysis on the image to generate a plurality of parameters, and further generate each parameter distribution map through image registration and reconstruction, such as: corneal curvature, corneal thickness map, etc., that express different angular information originating from the same cornea. However, in practice, if a cornea is actually structurally altered, a corresponding change in one or more of the parameter profiles should occur, and their positions should be similar.
Disclosure of Invention
In order to diagnose irregular cornea diseases such as high keratoconus at an early stage and reduce the complexity of jointly interpreting a large number of parameters in clinical practical work, the invention provides a method for expressing the structural change of corneal irregularity based on the change consistency parameters of anterior segment tomography.
The technical solution adopted by the invention is as follows: a method for expressing corneal irregularity structural changes based on a varying consistency parameter of anterior segment tomography, comprising the steps of:
(1) establishing an image database of normal subjects and early irregular keratopathy subjects;
(2) five main parameters were obtained that were associated with the expression of irregular corneal morphology: thickness, front surface curvature, back surface curvature, front surface height, back surface height;
(3) obtaining the steepest value of the curvature of the front surface and the rear surface, the maximum value of the height of the front surface and the rear surface, the minimum value of the thickness and the corresponding coordinate position through the numerical value matrix corresponding to the distribution diagram of the five parameters;
(4) calculating the relative distance of the 5 coordinate positions, expressing the discrete degree of the relative positions, and changing a position consistency parameter LCI;
(5) and further integrating LCI, extreme values and other morphological related parameters, performing statistical regression calculation on normal samples and irregular cornea disease samples to generate a regression equation, giving coefficients and intercept to each parameter, and acquiring the LCES (location consistency enhancement score) through the equation.
The method for calculating the variable location consistency parameter LCI in the step (4) is as follows: and calculating the relative distance according to the coordinate positions of the thickness, the front surface curvature, the rear surface curvature, the front surface height and the rear surface height, wherein the distance expression adopts Euclidean distance which represents the linear distance between two points in Euclidean space. The expression is as follows:
wherein d is1Is a point (x)1,y1) And a reference point (x)0,y0) The euclidean distance between them. With LPacAs a reference point, the other four extreme position points can generate Euclidean distances d with the reference point1，d2，d3，d4. Then there are:
d＝d1+d2+d3+d4；
here, the sum of the euclidean distances of 5 points is represented, i.e., the change position consistency index LCI.
The thickness, front surface curvature, back surface curvature, front surface height, and back surface height parameters are obtained from image data generated by a Pentacam anterior ocular segment analyzer or an anterior ocular segment OCT system.
The steps of obtaining the extreme value of the distribution diagram of the corneal thickness, the front surface curvature, the back surface curvature, the front surface height and the back surface height and the coordinate position of the extreme value are as follows:
(a) the OCT image is segmented, and the main layers of the SD-OCT anterior segment cornea image comprise a red boundary: cornea/epithelial layer front surface, blue border: corneal epithelial basal layer/anterior elastic layer anterior surface, yellow border: anterior elastic layer posterior surface/corneal stroma anterior surface, green border: corneal endothelial layer/posterior corneal surface;
(b) the corneal layer is automatically probed and manually inspected and corrected using automated segmentation software based on the MATLAB language environment. Then, surface correction is carried out on the segmentation layers, registration and reconstruction are carried out, corresponding pixel point positions are output, and information such as absolute corneal height loss and thickness is output by combining correction of scanning length and width;
(c) after the treatment of the steps (a) and (b), the positions of the front surface and the rear surface of the corneal epithelial layer can be obtained, and the corneal epithelial layer is reconstructed. The cornea thickness distribution map can be obtained through the relative positions of the front surface and the back surface of the epithelium; and generating a curvature distribution map by using the height loss distribution maps of the front surface and the rear surface of the epithelial layer, selecting the data of the front surface and the rear surface of the epithelial layer within a certain range, generating an optimal fitting reference surface, obtaining the height distribution maps of the front surface and the rear surface of the corneal epithelium, and detecting in each distribution map to obtain an extreme value and coordinates thereof.
The invention has the beneficial effects that: the invention provides a method for expressing the change of an irregular cornea structure based on the change consistency parameters of an anterior segment tomography technology, which provides a method for comprehensively expressing the position of the irregular cornea possibly with morphological change by establishing an objective index of the relative position of parameter change, can theoretically improve the early diagnosis performance of irregular cornea diseases such as keratoconus and the like, and simultaneously reduces the complexity of jointly reading a large number of parameters in clinical practical work.
Drawings
Fig. 1 shows an anterior surface curvature distribution map, a posterior surface curvature distribution map, a corneal thickness map, a corneal anterior surface height map, and a corneal posterior surface height map generated by a Pentacam anterior segment analyzer (Oculus, gmbh., Wetzlar, Germany), where Δ is an extreme value of each partial map, and the origin of coordinate axes is a corneal vertex.
Fig. 2 is the main level of the SD-OCT anterior segment cornea image, red border: cornea/epithelial layer front surface, blue border: corneal epithelial basal layer/anterior elastic layer anterior surface, yellow border: anterior elastic layer posterior surface/corneal stroma anterior surface, green border: corneal endothelial layer/posterior corneal surface.
FIG. 3 is an automated segmentation software interface based on the MATLAB language environment that automatically explores the hierarchy depicted in FIG. 2 and allows for manual inspection and correction. And then, performing surface correction on the segmentation level, performing registration and reconstruction, and outputting the position of a corresponding pixel point. And then combines the correction of the scanning length and width to output the information of absolute corneal height loss, thickness and the like. A is an example of automatic detection of posterior surface inaccuracy and B is an example of artificial correction of the posterior surface of the cornea.
Fig. 4 is a diagram illustrating the principle of calculating the corneal height, and the absolute corneal height loss distribution diagram output in fig. 3 is used to select the height loss value within a certain range to fit a best reference surface (here, a best fit spherical surface BFS), and the difference between the absolute corneal height loss and the analysis surface is the corneal height distribution, + is raised and-is depressed.
Detailed Description
Example 1
Application of variation position consistency parameters taking Pentacam anterior segment comprehensive analyzer as example
(a) Establishing a Pentacam image database of normal subjects and early irregular keratopathy subjects.
(b) A numerical matrix of the 5 parameter profiles shown in fig. 1 was derived for each subject, including anterior corneal surface curvature, posterior corneal surface curvature, anterior surface height, posterior corneal surface height, corneal thickness. The matrix is read using the MATLAB language environment and the extreme values of each profile and its coordinate position (x, y, value) are output.
(c) And calculating the relative distance according to the five coordinate positions. The distance expression is an euclidean distance (hereinafter referred to as an "euclidean distance") representing a linear distance between two points in an euclidean space. The expression is as follows:
wherein d is1Is a point (x)1,y1) And a reference point (x)0,y0) The euclidean distance between them. With LPacAs a reference point, the other four extreme position points can generate Euclidean distances d with the reference point1，d2，d3，d4。
d＝d1+d2+d3+d4；
Here, d represents the sum of the euclidean distances of 5 points, i.e., "Location Consistency Index" (LCI). The smaller the LCI, the more concentrated the locations of the changes in the five parametric profiles are at the coordinate locations, and the larger the LCI, the more discrete the locations are.
(d) And further integrating LCI, extreme values and other related parameters, such as the morphological parameters of the average curvature of the front surface of the cornea, the astigmatism of the cornea and the like, generating a regression equation by performing statistical regression calculation on normal samples, early keratoconus and other irregular cornea disease samples, and giving coefficients and intercept to each parameter. A Location Consistency Enhanced Score (LCES) is obtained by this equation. The parameters for inclusion of LCES were determined from statistical results by obtaining statistical tests including, but not limited to, the corneal morphological parameters described above.
Example 2
Application of variable position consistency parameters by taking anterior segment OCT system as example
(a) And establishing an OCT (optical coherence tomography) image database of normal subjects and early irregular keratopathy subjects.
(b) The OCT image is segmented, and fig. 2 shows the main levels of the SD-OCT anterior segment cornea image, red border: cornea/epithelial layer front surface, blue border: corneal epithelial basal layer/anterior elastic layer anterior surface, yellow border: anterior elastic layer posterior surface/corneal stroma anterior surface, green border: corneal endothelial layer/posterior corneal surface.
(c) The corneal layer was automatically probed and allowed to be manually examined and corrected using automated segmentation software based on the MATLAB language environment (fig. 3). And then, performing surface correction on the segmentation level, performing registration and reconstruction, and outputting the position of a corresponding pixel point. And then combines the correction of the scanning length and width to output the information of absolute corneal height loss, thickness and the like.
(d) Taking the corneal epithelial layer as an example, after the treatment of the steps b) and c), the positions of the front surface and the rear surface of the corneal epithelial layer can be obtained, and the corneal epithelial layer can be reconstructed. The cornea thickness distribution map can be obtained through the relative positions of the front surface and the back surface of the epithelium; the profile of elevation of the anterior and posterior surfaces of the epithelium generates a curvature profile. A best-fit reference surface (fig. 4) may be generated by selecting a range of anterior and posterior surface data of the epithelium, exemplified here by best-fit spherical BFS, to obtain a corneal epithelium anterior and posterior surface height profile.
(e) Extreme values and their coordinates are detected in each distribution map, and then LCI, LCES and optimal cutoff values are obtained based on irregular corneal diseases such as normal samples and early keratoconus using the calculation and integration methods of c) and d) in example 1.
In the description of the present invention, it should be noted that the terms "center", "longitudinal", "lateral", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", etc., indicate orientations or positional relationships based on those shown in the drawings, and are only for convenience of description and simplicity of description, but do not indicate or imply that the referred device or element must have a specific orientation, be constructed and operated in a specific orientation, and thus, should not be construed as limiting the present invention. Furthermore, the terms "first" and "second" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance.
In the description of the present invention, it should be noted that, unless otherwise explicitly specified or limited, the terms "mounted," "connected," and "connected" are to be construed broadly, e.g., as meaning either a fixed connection, a removable connection, or an integral connection; can be mechanically or electrically connected; they may be connected directly or indirectly through intervening media, or they may be interconnected between two elements. The specific meanings of the above terms in the present invention can be understood in specific cases to those skilled in the art. In addition, in the description of the present invention, "a plurality" means two or more unless otherwise specified.
The skilled person should understand that: although the invention has been described in terms of the above specific embodiments, the inventive concept is not limited thereto and any modification applying the inventive concept is intended to be included within the scope of the patent claims.
The above description is only a preferred embodiment of the present invention, and the protection scope of the present invention is not limited to the above embodiments, and all technical solutions belonging to the idea of the present invention belong to the protection scope of the present invention. It should be noted that modifications and embellishments within the scope of the invention may occur to those skilled in the art without departing from the principle of the invention, and are considered to be within the scope of the invention.
Claims (3)
1. A method for expressing corneal irregularity changes based on ocular surface structure change consistency, comprising the steps of:
(1) establishing an image database of normal subjects and early irregular keratopathy subjects;
(2) five main parameters were obtained that were associated with the expression of irregular corneal morphology: thickness, front surface curvature, back surface curvature, front surface height, back surface height;
(3) obtaining the steepest value of the front surface curvature and the corresponding coordinate position, the steepest value of the back surface curvature and the corresponding coordinate position, the maximum value of the front surface height and the corresponding coordinate position, the maximum value of the back surface height and the corresponding coordinate position, the minimum value of the thickness and the corresponding coordinate position through the numerical matrix corresponding to the distribution diagram of the five parameters;
(4) the relative distance of the 5 coordinate positions is calculated to express the discrete degree of the relative positions, and the position consistency parameter LCI is changed, wherein the calculation method of the position consistency parameter LCI is as follows: calculating the relative distance according to the coordinate positions of the thickness, the front surface curvature, the rear surface curvature, the front surface height and the rear surface height, wherein the distance expression adopts Euclidean distance which represents the linear distance between two points in Euclidean space, and the expression is as follows:
wherein d is1Is a point (x)1，y1) And a reference point (x)0，y0) Of between, in terms of LpacAs a reference point, the other four extreme position points can generate Euclidean distances d with the reference point1，d2，d3，d4Then, there are:
d＝d1+d2+d3+d4；
here, the sum of the euclidean distances of 5 points is represented, i.e., the change position consistency index LCI;
(5) and further integrating LCI, extremum and other morphological related parameters, wherein the other morphological related parameters are the average curvature of the front surface of the cornea and the astigmatism morphological parameters of the cornea, generating a regression equation by performing statistical regression calculation on normal samples and irregular cornea disease samples, giving coefficients and intercept to each parameter, and acquiring the LCES (location consistency enhancement score) through the equation.
2. The method of claim 1, wherein the thickness, anterior surface curvature, posterior surface curvature, anterior surface height, and posterior surface height parameters are obtained from image data generated by a Pentacam anterior segment analyzer or anterior segment OCT system.
3. The method of claim 1, wherein the image data generated by the anterior segment OCT system is used to obtain the extremum of the distribution of thickness, anterior surface curvature, posterior surface curvature, anterior surface height, posterior surface height and the coordinate location thereof by:
(a) the OCT image is segmented, and the main layers of the SD-OCT anterior segment cornea image comprise a red boundary: cornea/epithelial layer front surface, blue border: corneal epithelial basal layer/anterior elastic layer anterior surface, yellow border: anterior elastic layer posterior surface/corneal stroma anterior surface, green border: corneal endothelial layer/posterior corneal surface;
(b) automatically detecting the corneal layer by using automatic segmentation software based on MATLAB language environment, allowing manual inspection and correction, then performing surface correction on the segmented layer, performing registration and reconstruction, outputting corresponding pixel point positions, and outputting absolute corneal height loss and thickness information by combining with correction of scanning length and width;
(c) after the treatment of the steps (a) and (b), the positions of the front surface and the rear surface of the corneal epithelial layer can be obtained, the corneal epithelial layer is reconstructed, and a corneal thickness distribution map can be obtained through the relative positions of the front surface and the rear surface of the epithelium; and generating a curvature distribution map by using the height loss distribution maps of the front surface and the rear surface of the epithelial layer, selecting the data of the front surface and the rear surface of the epithelial layer within a certain range, generating an optimal fitting reference surface, obtaining the height distribution maps of the front surface and the rear surface of the corneal epithelium, and detecting in each distribution map to obtain an extreme value and coordinates thereof.
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| CN113171172B (en) * | 2021-04-21 | 2022-06-21 | 温州医科大学附属眼视光医院 | Method for simulating postoperative condition of cornea |
| CN113284140B (en) * | 2021-06-28 | 2022-10-14 | 上海美沃精密仪器股份有限公司 | Binocular keratoconus diagnosis method based on multi-modal data |
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