WO2023149139A1 - 視野検査装置、および視野検査プログラム - Google Patents

視野検査装置、および視野検査プログラム Download PDF

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Publication number
WO2023149139A1
WO2023149139A1 PCT/JP2022/048228 JP2022048228W WO2023149139A1 WO 2023149139 A1 WO2023149139 A1 WO 2023149139A1 JP 2022048228 W JP2022048228 W JP 2022048228W WO 2023149139 A1 WO2023149139 A1 WO 2023149139A1
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visual field
probability density
density function
oct
fundus
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French (fr)
Japanese (ja)
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祥之 山田
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Nidek Co Ltd
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Nidek Co Ltd
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    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B3/00—Apparatus for testing the eyes; Instruments for examining the eyes
    • A61B3/02—Subjective types, i.e. testing apparatus requiring the active assistance of the patient
    • A61B3/024—Subjective types, i.e. testing apparatus requiring the active assistance of the patient for determining the visual field, e.g. perimeter types
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • 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
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • 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
    • A61B3/12—Objective types, i.e. instruments for examining the eyes independent of the patients' perceptions or reactions for looking at the eye fundus, e.g. ophthalmoscopes

Definitions

  • the present disclosure relates to a visual field inspection device and a visual field inspection program for inspecting the visual field of an eye to be examined.
  • a visual field inspection device (sometimes called a "perimeter") is a device for subjectively inspecting the visual field of the subject's eye.
  • the visual field inspection apparatus inspects the visual field at each measurement point on the fundus of the subject's eye depending on whether or not the subject could visually recognize the test optotype projected onto the fundus of the subject's eye.
  • the result of comparison between the layer thickness information of the fundus tomographic image and the normal eye database is acquired, and based on the position information of the region where the layer thickness information is outside the range of the normal eye, the stimulated vision is detected.
  • a mark presentation area is set.
  • the initial brightness of the stimulus target is set based on the position of the lost area or atrophied area with respect to the retinal layer related to the visual function of the fundus of the subject's eye.
  • a typical object of the present disclosure relates to a visual field inspection device and a visual field inspection program capable of performing visual field inspection in a shorter time and with higher accuracy.
  • a first aspect of a visual field testing apparatus projects a stimulus visual target onto each of a plurality of measurement points on the fundus of a subject's eye, and A visual field testing device for acquiring a sensitivity threshold at each of the measurement points based on the response result of the person, wherein the control unit of the visual field testing device calculates a probability that the sensitivity threshold is a random variable for each of the measurement points.
  • an a priori probability density function setting step of setting a density function in advance an initial intensity setting step of setting an initial intensity, which is a projection intensity of a stimulus visual target first projected onto a measurement point; a response result obtaining step of projecting the stimulus visual target onto the stimulus visual target and obtaining a response result of the subject to the stimulus visual target; If it was visible, reducing the probability density below the projected intensity in the probability density function, while if the response result was invisible, above the projected intensity in the probability density function.
  • a function changing step of changing the probability density function by reducing the probability density of a determining step of determining whether or not the measurement end condition for the measurement point is satisfied; If it is determined that the a sensitivity threshold acquisition step of acquiring a sensitivity threshold at the measurement point based on the modified probability density function when it is determined that the termination condition is satisfied; reflected light of the OCT light from the fundus of the subject eye; and an OCT data acquisition step of acquiring OCT data obtained from interference light with a reference light corresponding to the OCT light, and in the prior probability density function setting step, the OCT data acquired in the OCT data acquisition step
  • the probability density function is preset based on the OCT data about the fundus of the subject's eye.
  • a second aspect of a visual field testing apparatus projects a stimulus target onto each of a plurality of measurement points on the fundus of a subject's eye, and A visual field testing device for obtaining sensitivity thresholds at each of the measurement points based on a response result of the subject, wherein the control unit of the visual field testing device obtains at least An angio data acquisition step of acquiring OCT angio data, which is motion contrast data generated by arithmetically processing two OCT signals; and an initial intensity setting step of setting an intensity based on the OCT angio data.
  • a first aspect of a visual field inspection program is a visual field inspection program executed by a visual field inspection controller for controlling inspection by the visual field inspection device, the visual field inspection device comprising: projecting a stimulus target onto each of a plurality of measurement points on the fundus of the subject's eye, and obtaining a sensitivity threshold at each of the measurement points based on the subject's response to the stimulus target; a prior probability density function for setting in advance a probability density function with a sensitivity threshold as a random variable for each of the measurement points by executing the visual field inspection program by a control unit of the visual field inspection control device.
  • a setting step an initial intensity setting step of setting an initial intensity that is a projection intensity of a stimulus target first projected onto a measurement point, a step of projecting the stimulus target onto the measurement point at the set projection intensity, and a response result acquisition step of acquiring a response result of the subject to the target, and if the response result acquired in the response result acquisition step is visible indicating that the stimulus target was visually recognized , by reducing probability densities below the projected intensity in the probability density function, while reducing probability densities above the projected intensity in the probability density function if the response result was invisible, yielding the probability density function a determination step of determining whether or not the termination condition of the measurement for the measurement point is satisfied; and if it is determined in the determination step that the termination condition is not satisfied, the previous response result
  • a repeating step of repeating the response result acquisition step, the function changing step, and the determining step
  • a sensitivity threshold acquisition step of acquiring a sensitivity threshold at the measurement point based on the changed probability density function
  • a second aspect of a visual field inspection program is a visual field inspection program executed by a visual field inspection controller for controlling inspection by the visual field inspection device, the visual field inspection device comprising: projecting a stimulus target onto each of a plurality of measurement points on the fundus of the subject's eye, and obtaining a sensitivity threshold at each of the measurement points based on the subject's response to the stimulus target;
  • the visual field inspection program is executed by the control unit of the visual field inspection control device, and at least two OCT signals acquired at different times with respect to the same position of the fundus of the subject eye are arithmetically processed.
  • the visual field inspection is performed in a shorter time and with higher accuracy.
  • the control unit includes a prior probability density function setting step, an initial intensity setting step, a response result acquisition step, a function change step, a determination step, a repetition step, a sensitivity threshold acquisition step, and an OCT data acquisition step.
  • a prior probability density function setting step a probability density function having a sensitivity threshold as a random variable is set in advance for each measurement point.
  • the probability density function set before the stimulus target is projected onto the measurement point may be referred to as prior probability density function.
  • an initial intensity is set, which is the projection intensity (for example, contrast intensity) of the stimulus visual target that is first projected onto the measurement point.
  • the stimulus visual target is projected onto the measurement point with the set projection intensity, and the subject's response result to the stimulus visual target is acquired.
  • the function changing step if the response result obtained in the response result obtaining step is visible, which indicates that the stimulus visual target was visually recognized, the probability density less than the projected intensity in the probability density function is reduced. Also, when the response result is invisible, the probability density above the projected intensity in the probability density function is reduced.
  • the determination step it is determined whether or not the measurement end condition for the measurement point is satisfied. In the repeat step, when it is determined in the determination step that the termination condition is not satisfied, the projection intensity is newly set according to the previous response result, and then the response result acquisition step, the function change step, and the determination step are performed. Repeated.
  • the sensitivity threshold acquisition step acquires the sensitivity threshold at the measurement point based on the changed probability density function when it is determined in the determination step that the termination condition is satisfied.
  • OCT data acquisition step OCT data obtained from interference light between the reflected light of the OCT light from the fundus of the subject's eye and the reference light corresponding to the OCT light is acquired.
  • a probability density function is preset based on the OCT data about the fundus of the subject's eye acquired in the OCT data acquisition step.
  • the full-threshold method increases or decreases the projection threshold by a first value each time the same response result (visible or invisible) is repeated. This method searches for the sensitivity threshold by decreasing or increasing the projection threshold by a second value whose sign is opposite to the value of 1.
  • stimulation is performed based on OCT data from which various information regarding the state of the fundus of the eye to be examined (for example, at least one of the structure of the fundus layer and perfusion of blood vessels) can be easily obtained.
  • a prior probability density function before target projection is set. Therefore, the sensitivity threshold at the measurement point is obtained based on the prior probability density function that reflects information about the state of the fundus of the subject's eye that affects visual performance. Therefore, the visual field inspection can be easily performed in a shorter time and with higher accuracy.
  • the perfusion state in the blood vessels of the fundus affects the visual function of the eye to be examined.
  • the OCT angio data contains perfusion information of the retinal layer vascular network. Therefore, by setting the prior probability density function based on the OCT angio data, information on the perfusion state of the retinal blood vessels that affects visual performance is appropriately reflected in the prior probability density function. Therefore, the visual field inspection can be easily performed in a shorter time and with higher accuracy.
  • a specific method for setting the prior probability density function based on OCT angio data can be selected as appropriate.
  • the controller may set the a priori probability density function at each measurement point based on the blood vessel density (eg, area or length of blood vessel per unit area) analyzed from OCT angio data.
  • the control unit aligns the two-dimensional front observation image captured in real time during the examination of the fundus of the eye to be examined, which is the target of the visual field test, with the OCT angio data (in this case, the OCT angio front image),
  • a priori probability density function for each measurement point may be set based on the OCT angio data value (for example, blood vessel density value, etc.) at each measurement point on the fundus.
  • OCT data relating to a tomogram of the fundus of the subject's eye may be used.
  • the OCT data related to the tomography may be, for example, the data of the tomographic image itself, or the data of the thickness distribution of a specific layer obtained by analyzing the tomographic image (sometimes referred to as a "thickness map"). There may be.
  • the OCT data related to the tomography may be normal eye comparison data indicating the difference between the thickness distribution of a specific layer in the eye to be examined and the thickness distribution of the specific layer in a normal eye.
  • a ganglion cell complex consisting of a nerve fiber layer (NFL), a ganglion cell layer (GCL), and an inner plexiform layer (IPL) (Ganglion Cell Complex: GCC) layer thickness and the research etc. which paid attention to the relevance of the visual function of the eye to be examined existed.
  • the perfusion state of the blood vessels near the ganglion cells present in the GCC is more relevant to the visual function of the eye to be examined than the layer thickness of the GCC. has become highly probable.
  • Most of the blood vessels in the vicinity of ganglion cells reside in the ganglion cell layer (GCL) and inner plexiform layer (IPL).
  • the information on the perfusion state of the blood vessels, which is likely to affect the visual function is more appropriately obtained by the prior probability density function. be easily reflected in Therefore, the visual field inspection can be easily performed in a shorter time and with higher accuracy.
  • the two specific boundary surfaces that define the specific region may be located between the boundary of the ganglion cell layer (GCL) on the superficial side of the retina and the boundary of the inner plexiform layer (IPL) on the deep side of the retina. That is, of the two specific boundaries, the boundary on the surface side (upper side) of the retina is set at a position below the boundary on the surface side of the ganglion cell layer, and the boundary on the deep side (lower side) of the retina is set at a position below the boundary on the surface side of the ganglion cell layer. It may be set at a position above the boundary on the deep layer side. In this case, the specific region does not include layers other than the ganglion cell layer and the inner plexiform layer.
  • the specific area may change the specific area.
  • the inner limiting membrane (ILM) and the nerve fiber layer (NFL) may be included in the specific region.
  • the prior probability density functions of the measurement points located within the central region may be set based on the OCT angio data.
  • the central region is a region including the fovea when the fundus of the subject's eye is viewed from the front (direction along the line-of-sight direction of the subject's eye). In the central region, there tends to be a higher correlation between vascular perfusion status and visual performance than in the peripheral region. Therefore, by setting the prior probability density function of at least the measurement points in the central region based on the OCT angio data, information on the perfusion state of blood vessels can be more appropriately reflected in the prior probability density function.
  • the prior probability density functions of the measurement points located in the peripheral region may be set based on OCT data related to a tomogram of the fundus of the subject's eye (for example, retinal layers).
  • the peripheral region is an annular region located outside (for example, adjacent to) the central region so as to surround the central region.
  • the OCT data related to the tomogram of the fundus of the subject's eye may be the data of the tomographic image itself, or the data of the thickness distribution of a specific layer obtained by analyzing the tomographic image. Further, the OCT data related to the tomography may be normal eye comparison data indicating the difference between the thickness distribution of a specific layer in the eye to be examined and the thickness distribution of the specific layer in a normal eye.
  • a specific setting method for the prior probability density function in each of the central region and the peripheral region can be selected as appropriate.
  • the control unit may first set the prior probability density functions of all measurement points based on the OCT data regarding the tomography, regardless of the central region and the peripheral region.
  • the controller may then correct the a priori probability density function of the measurement points within the central region based on the OCT angio data. In this case, prior probability density functions in each of the central region and the peripheral region are appropriately set.
  • the control unit may set the projection intensity of the stimulus visual target projected onto the measurement point based on the probability density function set at that time. For example, the control unit may set the initial intensity of the stimulus target to be projected onto the measurement point based on the prior probability density function. In this case, both the initial intensity of the stimulus target to be projected onto the measurement point and the probability density function for obtaining the sensitivity threshold at the measurement point are appropriately set based on the OCT data. Therefore, visual field inspection can be easily performed in a shorter time and with higher accuracy.
  • a specific method for setting the projection intensity of the stimulus target based on the probability density function can be selected as appropriate.
  • the control unit may set an expected value (average) obtained from the probability density function as the projected intensity.
  • the control unit may set, as the projection intensity, a sensitivity threshold at which the probability density function is maximized.
  • a second aspect of the visual field testing device exemplified in the present disclosure projects a stimulus target onto each of a plurality of measurement points on the fundus of the subject's eye, and based on the subject's response to the stimulus target, Obtain the sensitivity threshold at each measurement point.
  • a control unit of the visual field test apparatus executes an angio data acquisition step and an initial intensity acquisition step.
  • OCT angio data acquisition step OCT angio data of the fundus of the eye to be inspected is acquired.
  • OCT angio data is motion contrast data generated by arithmetically processing at least two OCT signals acquired at different times with respect to the same position of the fundus of the subject's eye.
  • the initial intensity which is the projection intensity (for example, contrast intensity) of the stimulus visual target that is first projected onto each measurement point, is set based on the OCT angio data.
  • the perfusion state in the blood vessels of the fundus affects the visual function of the eye to be examined.
  • the OCT angio data contains perfusion information of the retinal layer vascular network. Therefore, by setting the initial intensity of the stimulus target based on the OCT angio data, information on the perfusion state of blood vessels in the retinal layer, which affects visual function, is appropriately reflected in the initial intensity. In other words, it becomes easier to set an appropriate initial intensity according to the perfusion state of the blood vessel. Therefore, the visual field inspection can be easily performed in a shorter time and with higher accuracy.
  • a specific method for setting the initial intensity based on OCT angio data can be selected as appropriate.
  • the controller may set the initial intensity at each measurement point based on blood vessel density (eg, area or length of blood vessel per unit area) analyzed from OCT angio data.
  • the control unit aligns the two-dimensional front observation image captured in real time during the examination of the fundus of the eye to be examined, which is the target of the visual field test, with the OCT angio data (in this case, the OCT angio front image),
  • the initial intensity of each measurement point may be set based on the OCT angio data value (for example, blood vessel density value, etc.) at each measurement point on the fundus.
  • the information of the desired blood vessel (for example, the blood vessel highly relevant to visual function) among the plurality of blood vessels is the initial intensity.
  • a ganglion cell complex consisting of a nerve fiber layer (NFL), a ganglion cell layer (GCL), and an inner plexiform layer (IPL) (Ganglion Cell Complex: GCC) layer thickness and the research etc. which paid attention to the relevance of the visual function of the eye to be examined existed.
  • the perfusion state of the blood vessels near the ganglion cells present in the GCC is more relevant to the visual function of the eye to be examined than the layer thickness of the GCC. has become highly probable.
  • Most of the blood vessels in the vicinity of ganglion cells reside in the ganglion cell layer (GCL) and inner plexiform layer (IPL).
  • the visual field inspection can be easily performed in a shorter time and with higher accuracy.
  • the two specific boundary surfaces that define the specific region may be located between the boundary of the ganglion cell layer (GCL) on the superficial side of the retina and the boundary of the inner plexiform layer (IPL) on the deep side of the retina. That is, of the two specific boundaries, the superficial (upper) retinal boundary is set below the ganglion cell layer, and the deep (lower) retinal boundary is set above the inner plexiform layer. may In this case, the specific region does not include layers other than the ganglion cell layer and the inner plexiform layer. Therefore, information on blood vessels that are different from blood vessels in the vicinity of ganglion cells is less likely to be reflected in the initial intensity. Therefore, information on the perfusion state of blood vessels, which tends to affect visual performance, is likely to be more appropriately reflected in the initial intensity.
  • the specific area may change the specific area.
  • the inner limiting membrane (ILM) and the nerve fiber layer (NFL) may be included in the specific region.
  • the initial intensity of at least the measurement points located within the central region may be set based on the OCT angio data.
  • the central region is a region including the fovea when the fundus of the subject's eye is viewed from the front (direction along the line-of-sight direction of the subject's eye). In the central region, there tends to be a higher correlation between vascular perfusion status and visual performance than in the peripheral region. Therefore, by setting the initial intensities of at least the measurement points in the central region based on the OCT angio data, information on the perfusion state of the blood vessel can be more appropriately reflected in the initial intensities.
  • At least initial intensities of measurement points located within the peripheral region may be set based on OCT data relating to a tomogram of the fundus of the subject's eye (for example, the retinal layer).
  • the peripheral region is an annular region located outside (for example, adjacent to) the central region so as to surround the central region.
  • the tomographic state of the fundus for example, the thickness of a specific layer, etc.
  • visual performance than in the central region. Therefore, by setting the initial intensities of at least the measurement points in the peripheral region based on the OCT data related to the tomography, the state of the fundus can be more appropriately reflected in the initial intensities.
  • the OCT data related to the tomogram of the fundus of the subject's eye may be the data of the tomographic image itself, or the data of the thickness distribution of a specific layer obtained by analyzing the tomographic image. Further, the OCT data related to the tomography may be normal eye comparison data indicating the difference between the thickness distribution of a specific layer in the eye to be examined and the thickness distribution of the specific layer in a normal eye.
  • a specific method for setting the initial intensity in each of the central region and the peripheral region can be selected as appropriate.
  • the control unit may first set the initial intensities of all the measurement points based on the OCT data regarding the tomogram, regardless of the central region and the peripheral region.
  • the controller may then correct the initial intensities of the measurement points within the central region based on the OCT angio data. In this case, the initial intensity in each of the central region and the peripheral region is appropriately set.
  • the control unit includes, for each of the measurement points, a prior probability density function setting step of presetting a probability density function having a sensitivity threshold as a random variable based on the OCT angio data; a response result obtaining step of projecting the stimulus visual target onto a measurement point and obtaining a response result of the subject to the stimulus visual target; If it was visible indicating that it was visible, reducing the probability density below the projected intensity in the probability density function, while if the response result was invisible, the projection in the probability density function A function changing step of changing the probability density function by reducing the probability density equal to or greater than the intensity; a determining step of determining whether or not a measurement termination condition for the measurement point is satisfied; a repeating step of repeating the response result acquiring step, the function changing step, and the determining step after newly setting the projection intensity according to the previous response result when it is determined that the condition is not satisfied; and a sensitivity threshold acquisition step of acquiring a sensitivity threshold at the measurement point based on the modified probability density function if it is determined
  • both the initial intensity of the stimulus visual target projected onto the measurement point and the probability density function for obtaining the sensitivity threshold at the measurement point are appropriately set based on the OCT angio data. Therefore, visual field inspection can be easily performed in a shorter time and with higher accuracy.
  • a specific method for setting the projection intensity of the stimulus target based on the probability density function can be selected as appropriate.
  • the control unit may set an expected value (average) obtained from the probability density function as the projected intensity.
  • the control unit may set, as the projection intensity, a sensitivity threshold at which the probability density function is maximized.
  • the projection intensity is increased or decreased by a first value each time the same response result (visible or invisible) is repeated, and when the response result changes, the projection intensity is decreased from the first value to the first value.
  • the control unit may change the probability density function by normalizing the probability density function by multiplying it by a likelihood function corresponding to the response result (visible or invisible) of the subject.
  • the probability density function is appropriately changed by simple processing.
  • the likelihood function when the response result is visible may be set such that the probability density decreases as the sensitivity threshold is smaller than the projection intensity.
  • the likelihood function when the response result is invisible may be set such that the probability density decreases as the sensitivity threshold is greater than the projection intensity.
  • the projection intensity may be set to the intersection of the likelihood function when the response result is visible and the likelihood function when the response result is invisible.
  • the probability density function may be modified.
  • the measurement termination condition used in the determination step can also be selected as appropriate.
  • the control unit may set the condition that the changed probability density function falls within a predetermined standard deviation as the measurement end condition for the measurement point.
  • the condition for terminating measurement for a measurement point may be that the number of measurement cycles of projecting stimulus targets, acquiring response results, and changing the probability density function for one measurement point reaches a predetermined number.
  • the end condition may be that one of the condition that the standard deviation is within a predetermined range and the condition that the number of measurement cycles reaches a predetermined number is satisfied.
  • a specific method for obtaining the sensitivity threshold at the measurement point based on the modified (final) probability density function can also be selected as appropriate.
  • the control unit may acquire the final average value of the probability density function as the sensitivity threshold.
  • the control unit may obtain, as the sensitivity threshold, an average value of probability density functions within a range within a predetermined standard deviation among the final probability density functions. Further, the control unit may set the sensitivity threshold at which the final probability density function is maximized as the sensitivity threshold of the measurement point for which the measurement has been completed.
  • the position of the photoreceptor cells (cones) that convert light information into signals and the ganglion cells that receive the signals from the photoreceptor cells are out of alignment.
  • a ganglion cell that receives a signal from a certain photoreceptor is hereinafter referred to as a "ganglion cell corresponding to a certain photoreceptor".
  • the control unit identifies the positions of ganglion cells corresponding to the photoreceptor cells present at the measurement point, and sets at least one of the prior probability density function and the initial intensity at the measurement point based on the OCT data of the identified position. may In this case, the OCT data is appropriately reflected in the visual field test progression algorithm after considering the positional deviation between the photoreceptors and the ganglion cells.
  • a specific method for specifying the position of the ganglion cell corresponding to the photoreceptor existing at the measurement point can be selected as appropriate.
  • the position of the ganglion cell corresponding to the photoreceptor may be specified based on a model that defines the relationship between the position of the photoreceptor and the position of the ganglion cell (for example, the known Drasdo model, Sjostrand model, etc.). good.
  • the position where the fixation target forms an image on the fundus is assumed to be the position of the fovea.
  • a method of setting various positions as a reference is also conceivable.
  • the fixation of the subject's eye becomes unstable, the various positions set with reference to the position of the fixation target also become unstable.
  • the fixation target is visually recognized at a position on the fundus other than the fovea centralis due to disease or the like. As a result, it becomes difficult to perform a visual field test that conforms to the structure of the fundus.
  • the control unit obtains a fundus image of the subject's eye (for example, an observation image captured in real time during an examination, an OCT tomographic image, etc.), and sets morphological feature positions on the fundus image to determine the morphology.
  • Various positions may be set on the basis of the characteristic position. In this case, even when the fixation of the subject's eye becomes unstable, or when the fixation target is viewed at a retinal position different from the fovea, visual field testing that conforms to the structure of the fundus can be easily performed.
  • the morphological feature positions may be set on the fundus image according to instructions input by the user. Further, the morphological feature positions may be specified by image processing on the fundus image.
  • control unit sets the position of the fovea centralis and the position of the optic papilla on the fundus image as morphological feature positions, the straight line passing through both the fovea centralis and the optic papilla on the X axis, and the line passing through the fovea centralis on the X axis.
  • Various positions may be set on the fundus image with a straight line perpendicular to the Y axis as the Y axis. In this case, various positions are easily set appropriately on the coordinates.
  • a retinal region that has come to capture visual objects instead of the fovea due to deterioration of the visual function of the fovea is sometimes called PRL (Preferred Retinal Locus). If the PRL deviates significantly from the fovea, the fixation of the subject's eye tends to be unstable, and therefore the visual field test is likely to be unstable.
  • the control unit can detect the position where the image of the fixation target is formed from the observation image of the fundus.
  • At least one of a warning operation indicating that the examination is highly likely to become unstable and a process of changing the presentation method of the fixation target may be executed.
  • the process of changing the presentation method of the fixation target includes, for example, a process of changing at least one of the shape, size, and brightness of the fixation target, or a process of inverting the luminance of the fixation target and the background. etc. can be adopted.
  • the control unit determines the difference between the expected value (average) obtained from the prior probability density function set before projecting the stimulus visual target to the measurement point and the sensitivity threshold obtained as a result of the examination for the measurement point, If the standard is exceeded, the examiner's attention may be called, or the measurement point may be re-examined. In this case, the accuracy of the visual field test is further improved.
  • the control unit aligns the results of the visual field test obtained for each measurement point with various images (for example, at least one of an OCT analysis map, OCT-A, SLO image, fundus camera image, fundus fluorescence image, etc.). It may be displayed on the In this case, the user (doctor, etc.) can confirm the examination result after appropriately grasping the position of each measurement point on the image.
  • images for example, at least one of an OCT analysis map, OCT-A, SLO image, fundus camera image, fundus fluorescence image, etc.
  • FIG. 2 is an optical system configuration diagram of the visual field inspection device 1.
  • FIG. 2 is a block diagram showing an electrical configuration of the visual field inspection device 1;
  • FIG. 4 is a flowchart of visual field inspection control processing executed by a visual field inspection device (visual field inspection control device) 1;
  • 5 is a diagram showing an example of three-dimensional tomographic image data 51;
  • FIG. 4 is a diagram showing an example of OCT angio data 52.
  • FIG. 5 is a diagram showing an example of thickness comparison data 53;
  • FIG. 6 is a diagram showing an example of a front observation image 60 of the fundus with a plurality of measurement points P set.
  • FIG. It is a figure which shows an example of the prior probability density function which was set.
  • FIG. 1 is a block diagram showing an electrical configuration of the visual field inspection device 1;
  • FIG. 4 is a flowchart of visual field inspection control processing executed by a visual field inspection device (visual field inspection control device) 1;
  • 5 is a diagram showing an example
  • FIG. 10 is a diagram showing an example of a likelihood function for modifying the prior probability density function
  • FIG. 10 shows the result of the probability density function shown in FIG. 8 being modified by the invisible likelihood function shown in FIG. 9
  • FIG. 2 is a diagram schematically showing the layer/boundary structure in the fundus.
  • the illumination light source 11 emits infrared light.
  • a condenser lens 12, a cold mirror 13, a ring slit 14, a relay lens 15, and a perforated mirror 16 are arranged in order from the illumination light source 11 side on the optical axis L1 of the illumination light source 11.
  • FIG. An infrared light flux emitted from illumination light source 11 illuminates ring slit 14 via condenser lens 12 and cold mirror 13 .
  • a light flux from the ring slit 14 forms an intermediate image in the vicinity of the aperture of the perforated mirror 16 via the relay lens 15 .
  • a light flux from the ring slit 14 is reflected by the peripheral surface of the perforated mirror 16 .
  • the perforated mirror 16 is arranged on the optical axis L2. The luminous flux reflected by the perforated mirror 16 once forms an image near the pupil of the subject's eye E by the objective lens 17, and then diffuses to illuminate the subject's eye fundus Ef.
  • the cold mirror 13 has the property of reflecting visible light and transmitting infrared light.
  • a photographing light source 18 emits visible light for photographing a color image of the fundus oculi Ef.
  • a flash lamp, an LED light source, or the like can be used as the imaging light source 18 .
  • the flash light emitted from the photographing light source 18 passes through the condenser lens 19, is reflected by the cold mirror 13, passes through the ring slit 4, the relay lens 15, the perforated mirror 16, and the objective lens 17, and reaches the eye E to be examined. It is emitted to the fundus oculi Ef.
  • the reflected infrared light flux from the fundus oculi Ef is reflected by the beam splitter 23 after passing through the objective lens 17, the perforated mirror 16, and the lenses 20, 21, and 22. After that, the reflected infrared light flux passes through the lens 24 and forms an image on the light receiving surface of the imaging device 25 for observation.
  • the beam splitter 23 has the property of reflecting infrared light and transmitting visible light.
  • the observation imaging element 25 has sensitivity in the infrared region.
  • the observation imaging device 25 photographs a two-dimensional front observation image of the fundus Ef of the eye E to be examined in real time during the visual field test.
  • the hole of the perforated mirror 16 is positioned substantially conjugate with the pupil of the subject's eye E, and constitutes a photographic aperture.
  • Lens 21 is a focusing lens that moves along optical axis L2. By adjusting the position of the lens 11 on the optical axis L2, the fundus oculi Ef and the light-receiving surface of the imaging element 25 for observation have a conjugate relationship.
  • the reflected light flux of visible light from the fundus oculi Ef passes through the beam splitter 23 after passing through the objective lens 17, the perforated mirror 16, and the lenses 20, 21, and 22. After that, the reflected luminous flux of visible light passes through the lens 26 and is reflected by the movable mirror 27 to form an image on the light receiving surface of the color imaging device 28 .
  • the color imaging element 28 has sensitivity in the visible range.
  • the movable mirror 27 is moved along the optical axis L2 when capturing a color image, and is retracted from the optical axis L2 during visual field inspection.
  • the eye target projection optical system 30 projects a stimulus eye target for performing a subjective visual field test onto the subject's eye E.
  • a reduction lens 29 is arranged between the target projection optical system 30 and the lens 26 .
  • the optotype projection optical system 30 of this embodiment includes a scanner that adjusts the projection position of the stimulus optotype on the fundus oculi Ef.
  • the visual field testing apparatus 1 processes the front observation image captured in real time by the imaging device 25 for observation, and drives the scanner according to the processing result, so that each of the plurality of measurement points set on the fundus oculi Ef. Project the stimulus target. As a result, even if the fundus oculi Ef moves, the projected position of the stimulus visual target is tracked to an appropriate position.
  • the projection intensity (contrast intensity in this embodiment) of the stimulus target is adjusted as appropriate.
  • the index projection optical system 30 projects a fixation target, which is the fixation target of the eye E to be examined.
  • the brightness, size and shape of the fixation target can be adjusted.
  • the visual field inspection apparatus 1 includes a control unit 40 that controls various controls of the visual field inspection apparatus 1 .
  • the control unit 40 includes a CPU 41 , RAM 42 , ROM 43 and non-volatile memory (NVM) 44 .
  • a CPU 41 is a controller that performs various controls.
  • the RAM 42 temporarily stores various information.
  • the ROM 43 stores programs executed by the CPU 41 and various initial values.
  • the NVM 44 is a non-transitory storage medium that can retain stored content even when the power supply is interrupted.
  • the visual field inspection apparatus 1 of the present embodiment is controlled by the control unit 40 to perform various operations during the visual field inspection (for example, the imaging operation of the front observation image by the observation imaging device 25 and the projection of the stimulus optotype by the index projection optical system 30). movement, etc.). Furthermore, the visual field inspection apparatus 1 of the present embodiment controls the visual field inspection by setting parameters (eg, initial intensity of the stimulus target, prior probability density function, etc.) that define the progress algorithm of the visual field inspection. That is, the visual field inspection apparatus 1 of this embodiment also serves as a visual field inspection control apparatus for controlling the visual field inspection.
  • parameters eg, initial intensity of the stimulus target, prior probability density function, etc.
  • a device different from the visual field inspection device 1 may function as the visual field inspection control device for controlling the inspection by the visual field inspection device 1.
  • the controllers of a plurality of devices may cooperate to function as the visual field inspection control device.
  • the illumination light source 11, the imaging light source 18, the observation imaging element 25, the color imaging element 28, the index projection optical system 30, the display section 31, the operation section 32, and the response switch 33 are connected to the control unit 40.
  • the display unit 31 displays various images. Various devices capable of displaying images can be used for the display unit 31 .
  • the operation unit 32 is operated by the user to input various instructions to the visual field inspection device 1 . For example, at least one of a keyboard, a mouse, a touch panel, and the like can be used as the operation unit 32 .
  • a microphone or the like for inputting various instructions may be used together with the operation unit 32 or instead of the operation unit 32 .
  • the response switch 33 is operated by the subject during the visual field test.
  • the CPU 41 determines whether or not the subject can visually recognize the stimulus target (that is, "visible” when the subject can visually recognize it, or "invisible” when the subject cannot visually recognize it). Identify by As an example, in this embodiment, the response switch 33 is operated when the subject can visually recognize the stimulus target, and the response switch 33 is not operated when the subject cannot visually recognize the stimulus target. Also, a switch that is operated when it is visible and a switch that is operated when it is not visible may be provided separately.
  • the visual field inspection device 1 acquires OCT data of an eye to be inspected.
  • the visual field inspection device 1 may acquire OCT data from the OCT device 50 via at least one of wired communication, wireless communication, a network (such as the Internet), and the like.
  • the visual field inspection apparatus 1 may acquire OCT data via a detachable memory or the like.
  • the OCT device 50 acquires OCT data on the fundus oculi Ef of the eye E to be examined.
  • the OCT data is obtained from the reflected light of the OCT light from the fundus Ef and the interference light of the reference light corresponding to the OCT light.
  • the OCT apparatus 50 includes an OCT light source, a branching optical element, an irradiation optical system, a light receiving element, and the like.
  • the OCT light source emits OCT light.
  • the branching optical element branches the OCT light emitted from the OCT light source into measurement light and reference light.
  • the irradiation optical system irradiates the fundus Ef of the eye E to be examined with the measurement light.
  • the light receiving element receives the combined light of the light reflected by the fundus oculi Ef and the reference light.
  • Visual field test control process An example of the visual field inspection control process executed by the visual field inspection apparatus (visual field inspection control apparatus) 1 will be described with reference to FIGS. 3 to 11.
  • FIG. In the visual field test control process, parameters that determine the progress algorithm of the visual field test (for example, the initial intensity of the stimulus target, the prior probability density function, etc.) are set, and various operations during the visual field test are controlled according to the set parameters. be done.
  • the visual field inspection control process illustrated in FIG. 3 is executed by the CPU 41 according to the visual field inspection control program stored in the NVM 44 .
  • the CPU 41 acquires OCT data about the fundus oculi Ef of the subject's eye E obtained by the OCT device 50 (S1). Specifically, in S1 of the present embodiment, three-dimensional tomographic image data 51 (see FIG. 4), OCT angio data 52 (see FIG. 5), and thickness comparison data 53 (see FIG. 6) are acquired as OCT data. be done. Details of each OCT data will be described later.
  • the CPU 41 starts real-time photographing of the front observation image of the fundus oculi Ef by the observation imaging device 25 while projecting the fixation target onto the subject's eye E by the optotype projection optical system 30 (see FIG. 1) (S2). At this time, the CPU 41 autofocuses the front observation image of the fundus oculi Ef. Further, the CPU 41 selects a reference observation image from among a plurality of intermittently captured front observation images. The selected reference observation image serves as a reference for various alignment processing including tracking processing (so-called “tracking”) of the projected position of the stimulus target.
  • the CPU 41 executes at least one of a fixation target presentation method change process and a warning process as necessary (S3).
  • a retinal region that has come to capture a visual object instead of the fovea due to deterioration of the visual function of the fovea of the subject's eye E may be referred to as PRL (Preferred Retinal Locus). If the PRL deviates significantly from the fovea, the fixation of the subject's eye tends to be unstable, and therefore the visual field test is likely to be unstable.
  • the CPU 41 detects the position where the image of the fixation target is formed from the front observation image of the fundus oculi Ef.
  • the CPU 41 performs the inspection when the position where the image of the fixation target is formed is out of the allowable range centered on the fovea, or when the position where the image of the fixation target is formed is unstable. at least one of a warning operation indicating that there is a high possibility that the is likely to become unstable, and a process of changing the presentation method of the fixation target.
  • the process of changing the presentation method of the fixation target includes, for example, a process of changing at least one of the shape, size, and brightness of the fixation target, or a process of inverting the luminance of the fixation target and the background. etc. can be adopted.
  • the CPU 41 aligns the OCT data acquired in S1 with the front observation image (in this embodiment, the reference observation image described above) captured by the observation imaging device 25 (S4). That is, registration processing is performed so that the positions of the front observation image and the OCT data match when the fundus oculi Ef is viewed from the front direction.
  • the CPU 41 sets the morphological characteristic positions on the front observation image (the reference observation image in this embodiment), and uses the set morphological characteristic positions as references to set a plurality of measurement points for projecting stimulus targets on the front observation image.
  • Set up (S5).
  • a known image processing is performed on a front observation image 60 to obtain a fovea centralis (fovea centralis) 61 and an optic papilla 62, which are morphological characteristic positions. is located.
  • the CPU 41 sets the straight line passing through the fovea centralis 61 and the optic papilla 62 as the X-axis.
  • the CPU 41 defines a straight line that passes through the fovea centralis 61 and is perpendicular to the X-axis as the Y-axis.
  • the CPU 41 sets a plurality of measurement points P on the front observation image 60 with reference to the set coordinate axes.
  • the measurement point P is appropriately set on coordinates based on the morphological feature position.
  • the CPU 41 may set morphological characteristic positions on the front observation image 60 according to instructions input by the user.
  • the CPU 41 identifies the position of the ganglion cell corresponding to the photoreceptor at the set measurement point P (S6). Based on the OCT data of the specified position (that is, the position of the ganglion cell corresponding to the photoreceptor at the measurement point P), the CPU 41 determines the parameters (in this embodiment, the prior probability density function and initial strength) is set (S7, S10).
  • the positions of the photoreceptor cells (cones) that convert light information into signals and the ganglion cells that receive the signals from the photoreceptor cells are misaligned.
  • the location of the ganglion cell corresponding to the photoreceptor is the location of the ganglion cell that receives the signal from the photoreceptor.
  • Visual performance at a given photoreceptor location is related to the state of the retina at the location of the ganglion cell corresponding to the photoreceptor.
  • the parameters of the visual field test based on the OCT data of the position of the ganglion cell corresponding to the photoreceptor at the measurement point P, it is possible to appropriately The OCT data is reflected in the visual field test progression algorithm.
  • a model for example, the known Drasdo model, Sjostrand model, etc.
  • ganglion cells corresponding to photoreceptors A location is identified.
  • the visual field test method adopted in this embodiment will be described.
  • statistics eg, Bayesian statistics
  • the probability density function is changed based on the subject's response to the stimulus target, and based on the changed probability density function, the sensitivity threshold (in this embodiment, contrast sensitivity threshold) is obtained.
  • the CPU 41 preliminarily sets a probability density function with the sensitivity threshold as a random variable for each measurement point P (S7). Details of the processing of S7 will be described later. According to the probability density function illustrated in FIG. 8, it can be seen that the probability that the sensitivity threshold is 20 dB to 30 dB is high. In the following description, the probability density function set in S7 before projecting the stimulus target onto the measurement point P is referred to as prior probability density function.
  • the CPU 41 sets the initial strength of the N-th (initial value is "1") measurement point P among the plurality of measurement points P (S10).
  • the initial intensity is the projection intensity of the stimulus visual target that is first projected onto the N-th measurement point P.
  • the projection intensity K is set at approximately 23 dB. Details of S10 will be described later.
  • the CPU 41 projects the stimulus visual target to the N-th measurement point P at the set projection intensity K (initially the initial intensity).
  • the subject changes the operation of the response switch 33 depending on whether or not the stimulus visual target was visually recognized (that is, "visible” or “invisible”).
  • the subject operates the response switch 33 when the stimulus target is visually recognized, and does not operate the response switch 33 when the subject is not visually recognized.
  • the CPU 41 obtains the subject's response to the stimulus target (S11).
  • the CPU 41 changes the probability density function according to the response result obtained in S11 (S12). Specifically, when the response result is “visible”, the CPU 41 reduces the probability density below the projection threshold K in the probability density function. Further, when the response result is "invisible”, the CPU 41 reduces the probability density of the projection intensity K or more in the probability density function.
  • the probability density function is changed according to the response result by normalizing the probability density function by multiplying the likelihood function (see FIG. 9) according to the response result.
  • the solid line indicates the likelihood function used when the response result is "invisible”.
  • the likelihood function when the response result is "invisible” is set so that the probability density decreases as the sensitivity threshold is greater than the previous projection intensity K (approximately 23 dB in the examples of FIGS. 8 to 10). ing.
  • the likelihood function when the response result is "visible” is set so that the probability density decreases as the sensitivity threshold becomes smaller than the projection intensity K of the previous time.
  • the probability density function shown in FIG. 8 is multiplied by the “invisible (solid line)” likelihood function shown in FIG.
  • the probability density function is multiplied by the “invisible” likelihood function to reduce the probability density of the previous projected intensity K (approximately 23 dB) or more in the probability density function.
  • the modified probability density function greatly reduces the probability of the sensitivity threshold being greater than 23 dB.
  • the probability density function shown in FIG. 8 is multiplied by the "visible (dotted line)” likelihood function shown in FIG. 9 for normalization.
  • the probability that the sensitivity threshold will be less than the previous projection intensity K is greatly reduced.
  • the CPU 41 determines whether or not the measurement end condition for the Nth measurement point P is satisfied (S14).
  • the end condition of measurement can also be set appropriately. For example, the fact that the changed probability density function (see, for example, FIG. 10) falls within a predetermined standard deviation may be set as the termination condition for the measurement of the N-th measurement point P. Further, when the number of measurement cycles of projecting the stimulus target, obtaining the response result (S11), and changing the probability density function (S12) executed for the N-th measurement point P reaches a predetermined number, the N-th measurement is performed. It may be used as a condition for terminating the measurement of the point P. Alternatively, the end condition may be that one of the condition that the standard deviation is within a predetermined range and the condition that the number of measurement cycles reaches a predetermined number is satisfied.
  • the CPU 41 selects the next stimulus target to be projected to the N-th measurement point P based on the subject's response to the previously projected stimulus visual target.
  • a target projection intensity is set (S15).
  • the CPU 41 calculates the projection intensity of the next stimulus visual target projected onto the N-th measurement point P by the probability density function set at that time (that is, the probability density function changed in S12). ). Specifically, the CPU 41 sets the expected value (average) obtained from the probability density function as the projected intensity. Further, the CPU 41 may set a sensitivity threshold at which the probability density function is maximized as the projection intensity. As a result, the next projection intensity is appropriately determined based on the probability density function. After that, the process returns to S11, and the processes of S11 to S14 for the Nth measurement point P are repeated.
  • the CPU 41 sets the sensitivity threshold at the N-th measurement point P based on the final probability density function changed in S12. (In this embodiment, the contrast sensitivity threshold value) is obtained (S16). As an example, in this embodiment, the final average value of the probability density function is obtained as the sensitivity threshold at the Nth measurement point P. As a result, an appropriate value is obtained according to the probability density function. Further, the CPU 41 may acquire, as the sensitivity threshold at the N-th measurement point P, a sensitivity threshold or the like that maximizes the final probability density function.
  • the CPU 41 determines whether or not all (N) measurement points P have been inspected (S18). If the inspection for all the measurement points P has not been completed (S18: NO), the CPU 41 determines based on the already acquired inspection results (for example, the sensitivity threshold of the N-th measurement point P acquired in S16). to correct the prior probability density function for other measurement points P (S19). For example, the CPU 41 may correct the prior probability density function of the measurement points P located near the Nth measurement point P based on the sensitivity threshold for the Nth measurement point P. In this case, the CPU 41 may increase the correction amount as the distance from the Nth measurement point P is shorter.
  • the visual field test for other measurement points P is performed after appropriately considering the results of measurement points P for which measurement has already been completed. Therefore, it becomes easier to further improve the efficiency of inspection.
  • the CPU 41 adds "1" to the counter N that specifies the measurement point P, and executes measurement for the next measurement point (S10 to S18).
  • the inspection for the Nth measurement point P may be omitted. In other words, the inspection of some measurement points P among the plurality of measurement points P may be omitted based on the inspection results of other measurement points P.
  • the CPU 41 determines the expected value (average) obtained from the prior probability density function for each measurement point P and the inspection result for each measurement point P. It is determined whether or not the difference from the obtained sensitivity threshold exceeds a standard. If the difference exceeds the standard, the CPU 41 calls attention (report) to the examiner, or re-examines the measurement point P whose difference exceeds the standard. As a result, the accuracy of the visual field test is further improved.
  • the CPU 41 aligned the results of the visual field test obtained for each measurement point P with various images (for example, at least one of an OCT analysis map, OCT angiography, SLO image, fundus camera image, fundus fluorescence image, etc.). displayed on the screen. Therefore, the user (doctor, etc.) can confirm the examination result after appropriately grasping the position of each measurement point P on the image.
  • images for example, at least one of an OCT analysis map, OCT angiography, SLO image, fundus camera image, fundus fluorescence image, etc.
  • the CPU 41 may analyze the progressing direction of the visual field disorder by comparing the result of the visual field test performed in the past for the same eye E to be examined and the result of the current visual field test. For example, the CPU 41 may calculate the difference between the past inspection result and the current inspection result for each measurement point P, and perform elliptical analysis on the data of four points around each measurement point P.
  • the intensity of change can be obtained from the length of the major axis and the minor axis
  • the direction of progression of the visual field defect can be obtained from the angle between the major axis and the minor axis. Therefore, by displaying the result of the ellipse analysis on the display unit 31, the user can appropriately diagnose the progress of the visual field disorder.
  • the parameters of the visual field test are set based on the OCT data of the subject's eye E acquired in S1.
  • the OCT data acquired in S1 of the present embodiment includes at least one of three-dimensional tomographic image data 51 (see FIG. 4), OCT angio data 52 (see FIG. 5), and thickness comparison data 53 (see FIG. 6). is included.
  • the three-dimensional tomographic image data 51 shows the three-dimensional tomographic structure of the retinal layer of the fundus oculi Ef.
  • the tomographic structure of the retinal layers for example, the thickness of a specific layer, etc.
  • the visual field inspection can be easily performed in a short time and with high accuracy.
  • the OCT angio data 52 (see FIG. 5) is motion contrast data generated by arithmetically processing at least two OCT signals acquired at different times with respect to the same position of the subject's eye Ef.
  • the OCT angio data 52 shown in FIG. 5 is the motion contrast data in a specific region (sometimes referred to as a “slab”) sandwiched between two specific boundary planes in the retinal layer of the fundus oculi Ef. , along the optical axis of the OCT measurement light)).
  • the OCT angio data 52 includes perfusion information of the retinal layer vascular network in the fundus oculi Ef.
  • the perfusion state of blood vessels in the fundus oculi Ef affects the visual function of the eye E to be examined. Therefore, by controlling the visual field test based on the OCT angio data 52, the visual field test can be easily performed in a short time with high accuracy.
  • the thickness comparison data 53 is a kind of OCT data related to the tomogram of the fundus oculi Ef.
  • the thickness comparison data 53 of the present embodiment is a layer (hereinafter referred to as a "specific layer”) in a specific region (sometimes referred to as a “slab") sandwiched between two specific boundary surfaces among the retinal layers of the fundus oculi Ef. ) thickness distribution and the difference in layer thickness distribution in specific regions of a normal eye.
  • Data indicating the thickness distribution of a specific layer (sometimes referred to as a “thickness map”) is obtained by analyzing the three-dimensional tomographic image data 51, for example.
  • the thickness comparison data 53 illustrated in FIG. 6 is data obtained by comparing the thickness distribution of the ganglion cell complex composed of NFL, GCL, and IPL with the thickness distribution of a normal eye.
  • FIG. 11 schematically shows the layer/boundary structure in the fundus oculi Ef.
  • the upper side of FIG. 11 is the surface side of the retina of the fundus oculi Ef. That is, the depth of the layer/boundary increases toward the bottom of FIG.
  • the names of boundaries between adjacent layers are parenthesized.
  • ILM internal limiting membrane
  • NFL nerve fiber layer
  • GCL ganglion cell layer
  • IPL from the superficial side (upper side in FIG. 6)
  • inner plexiform layer inner plexiform layer
  • INL inner nuclear layer
  • OPL outer plexiform layer
  • ONL outer nuclear layer
  • ELM outer limiting membrane
  • IS/OS junction between photoreceptor inner and outer segments
  • RPE retina pigment epithelium
  • BM Bruch's membrane
  • Choroid Choroid
  • the layer thickness of the ganglion cell complex consisting of NFL, GCL, and IPL
  • the visual function of the subject's eye there is a relationship between the layer thickness of the ganglion cell complex (GCC) consisting of NFL, GCL, and IPL and the visual function of the subject's eye.
  • GCC ganglion cell complex
  • the perfusion state of the blood vessels near the ganglion cells present in the GCC is more relevant to the visual function of the eye to be examined than the layer thickness of the GCC. has become highly probable. Many of the blood vessels in the vicinity of ganglion cells are present in the GCL and IPL.
  • the method of setting the prior probability density function (S7) will be described in detail.
  • the sensitivity threshold at the measurement point P is obtained by changing the probability density function according to the subject's response to the stimulus target. Therefore, the higher the adequacy of the prior probability density function set in S7, the easier it is to perform the visual field test in a short period of time and with a high degree of accuracy.
  • the CPU 41 obtains a variety of information about the state of the fundus oculi Ef (for example, at least one of the structure of the layers of the fundus oculi and the perfusion state of blood vessels) based on the OCT data in advance. A probability density function is set.
  • the sensitivity threshold at the measurement point P is obtained based on the prior probability density function that reflects information about the state of the fundus oculi Ef that affects visual performance. Therefore, the visual field inspection can be easily performed in a shorter time and with higher accuracy.
  • the CPU 41 preliminarily performs Sets the probability density.
  • the CPU 41 of the present embodiment based on the blood vessel (perfusion) density (for example, blood vessel area or length per unit area) of the measurement point P analyzed from the OCT angio data 52, at each measurement point P Set the prior probability density function.
  • OCT angio data OCT angio data in this embodiment.
  • OCT angio data OCT angio data in this embodiment.
  • the number of X dB samples is added to the prior probability density function (for example, a histogram whose horizontal axis is expressed in dB as shown in FIG. 8) when similar OCT angio data is acquired.
  • a prior probability density function corresponding to the OCT angio data may be established by accumulating the number of samples per OCT angio data and normalizing.
  • the retina of the fundus oculi Ef has blood vessels in each of a plurality of regions with different depths.
  • the CPU 41 sets the prior probability density based on the OCT angio data 52 in a specific region sandwiched between two specific boundaries (slabs) in the retinal layer of the fundus oculi Ef.
  • the perfusion information of a desired blood vessel for example, a blood vessel highly relevant to visual function
  • a desired blood vessel for example, a blood vessel highly relevant to visual function
  • the a priori probability density function is set based on the OCT angio data 52 of a specific region including at least part of the GCL and IPL.
  • the two boundaries that define the specific region are the boundary of the GCL on the surface side of the retina (NFL/GCL boundary in FIG. 11) and the boundary on the deep retina side of the IPL (IPL/INL boundary in FIG. 11).
  • the retinal surface side (upper) boundary is set at a position below the NFL/GCL boundary
  • the retinal deep layer side (lower) boundary is set at a position above the IPL/INL boundary.
  • the specific region no longer includes layers other than the GCL and INL. Therefore, information on blood vessels that are different from blood vessels in the vicinity of ganglion cells is less likely to be reflected in the prior probability density function. Therefore, information on the perfusion state of blood vessels, which tends to affect visual performance, can be more appropriately reflected in the prior probability density function.
  • the prior probability density of the measurement point P located within the central region 72 including the fovea 61 is added to the OCT angio data 52. set based on In the central region 72, there tends to be a higher correlation between vascular perfusion status and visual performance than in the peripheral regions. Therefore, by setting at least the prior probability density function of the measurement points in the central region 72 based on the OCT angio data 52, information on the perfusion state of blood vessels can be more appropriately reflected in the prior probability density function.
  • the prior probability density function of the measurement points P located within the peripheral region 73 around the central region 72 is set based on the OCT data regarding the tomography.
  • the peripheral region 73 tends to have a higher relationship between the tomographic state of the fundus oculi Ef (for example, the thickness of a specific layer) and visual performance. Therefore, by setting at least the prior probability density function of the measurement point P in the peripheral region 73 based on the OCT data related to the tomography, the state of the fundus oculi Ef can be more appropriately reflected in the prior probability density function.
  • thickness comparison data comparing the thickness distribution of a specific layer (in this embodiment, the ganglion cell complex) in the fundus oculi Ef with the thickness distribution of a specific layer in a normal eye. 53 (see FIG. 6), the prior probability density function of the measurement points P located within the peripheral region 73 is set. Therefore, the state of the thickness of a specific layer, which tends to affect visual performance, is more likely to be more appropriately reflected in the prior probability density function.
  • the CPU 41 converts the prior probability density functions of all the measurement points P into OCT data (thickness comparison data 53 in this embodiment) on the tomography regardless of the central region 72 and the peripheral region 73. set based on After that, the CPU 41 corrects the prior probability density function of the measurement points P within the central region 72 based on the OCT angio data 52 . As a result, the prior probability density functions in each of the central region 72 and peripheral region 73 are appropriately set.
  • the initial intensity is the projection intensity of the stimulus target that is projected onto each measurement point P first.
  • the CPU 41 sets the initial intensity at each measurement point P based on the OCT angio data 52 (FIG. 52) of the position corresponding to each measurement point P.
  • each measurement is performed based on the blood vessel (perfusion) density (for example, blood vessel area or length per unit area) at the measurement point P analyzed from the OCT angio data 52.
  • An initial intensity at point P is set.
  • the CPU 41 sets the initial intensity at each measurement point P based on the OCT angio data 52 in a specific region sandwiched between two specific boundaries (slabs) in the retinal layer of the fundus oculi Ef. do.
  • perfusion information of a desired blood vessel for example, a blood vessel highly relevant to visual function
  • a desired blood vessel for example, a blood vessel highly relevant to visual function
  • the initial intensity is set based on the OCT angio data 52 of the specific region including at least part of the GCL and IPL.
  • the two boundaries (slabs) delimiting the OCT angio data 52 are from the superficial retinal boundary of the GCL (NFL/GCL boundary in FIG. 11) to the deep retinal boundary of the IPL (FIG. 11 IPL/INL boundary at ). That is, of the two specific boundaries, the retinal surface side (upper) boundary is set at a position below the NFL/GCL boundary, and the retinal deep layer side (lower) boundary is set at a position above the IPL/INL boundary. is set to In this case, perfusion information of blood vessels different from blood vessels in the vicinity of ganglion cells is less likely to be reflected in the initial intensity. Therefore, information on the perfusion state of blood vessels, which tends to affect visual performance, is likely to be more appropriately reflected in the initial intensity.
  • the initial intensity of the measurement point P located within the central region 72 including the fovea 61 is set based on the OCT angio data 52.
  • the central region 72 there tends to be a higher correlation between vascular perfusion status and visual performance than in the peripheral regions. Therefore, by setting the initial intensities of at least the measurement points in the central region 72 based on the OCT angio data 52, information on the perfusion state of the blood vessel can be more appropriately reflected in the initial intensities.
  • the initial intensity of the measurement point P located in the peripheral region 73 around the central region 72 is the OCT data related to the tomography (in this embodiment, the thickness distribution of the ganglion cell complex is compared with that of a normal eye. It is set based on the data 53).
  • the peripheral region 73 tends to have a higher relationship between the tomographic state of the fundus oculi Ef (for example, the thickness of a specific layer) and visual performance. Therefore, by setting the initial intensity of at least the measurement point P in the peripheral region 73 based on the OCT data related to the tomography, the state of the fundus oculi Ef can be more appropriately reflected in the initial intensity.
  • the CPU 41 sets the projection intensity of the stimulus visual target projected onto the measurement point P based on the probability density function set at that time. Therefore, in S10, the CPU 41 sets the initial intensity of the stimulus visual target to be projected on the measurement point P based on the prior probability density function set in S7. As described above, in S7, the prior probability density function is set based on the OCT data. Therefore, by setting the initial intensity based on the prior probability density function set in S7, the OCT data is appropriately reflected in the initial intensity. As an example, in S10 of the present embodiment, the expected value (average) obtained from the probability density function is set as the projection intensity.
  • both the prior probability density function and the initial intensity are set based on OCT data.
  • only one of the prior probability density function and the initial intensity may be set based on OCT data.
  • the initial intensity may be set based on the OCT angio data 52 when a visual field testing method that does not use the prior probability density function is employed.
  • the process of setting the prior probability density function in S7 of FIG. 3 is an example of the "prior probability density function setting step".
  • the process of setting the initial strength in S10 of FIG. 3 is an example of the "initial strength setting step.”
  • the process of acquiring the subject's response results in S11 and S12 of FIG. 3 is an example of the "response result acquisition step.”
  • the process of changing the probability density function in S12 of FIG. 3 is an example of the "function changing step”.
  • the process of determining whether or not the termination condition is satisfied in S14 of FIG. 3 is an example of the "determination step”.
  • the process of repeating S11 to S14 when the end condition is not satisfied in S14 of FIG. 3 is an example of the "repeating step”.
  • the process of acquiring the sensitivity threshold in S16 of FIG. 3 is an example of the "sensitivity threshold acquisition step”.
  • the process of acquiring OCT data in S1 of FIG. 3 is an example of an "OCT data acquisition step” and an “

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