Integration analysis method and device for multi-modal retinal ganglion cell data

Abstract

The invention provides an integrated analysis method and device for multi-mode retinal ganglion cell (RGC) data for marking aging of central nervous system cells, and the method takes RGC aging as a biomarker of the aging of the central nervous system cells. Comprising: applying an ETDRS grid to a reconstructed macular region plan view in an OCT retinal thickness map to divide it into a plurality of regions, where the OCT thickness map comprises data values of thicknesses and volumes of five different retinal layers; grouping the plurality of regions, and determining the average thickness and volume data distribution of each region to detect the abundance of the RGC; using a rear pole module to record the OCTA and finely layering to obtain the retina microvascular change of the OCTA; 103 hexagonal mfERG reports of the pERG and ETDRS grids with the same center at the macular position are obtained. Based on the acquired information, histological and functional analysis of the RGC is combined with precise position distribution and corresponding blood supply capillary changes, and a non-invasive early detection analysis module reflecting RGC health is provided.

Description

Background Art

[0001] In vivo tracing of neuronal cells in the central nervous system (CNS) of mammals can be achieved by anterograde or retrograde delivery of specific dyes through nerve fibers or viral delivery of gene manipulation fluorescent labels, and then observed through micropores through special fluorescent microscope lenses. There has been no report on non-invasive and sustainable tracking of specific categories of CNS neurons to monitor the aging process of the CNS. Studies have shown that there are potential structural changes in the brains of patients with mood disorders. For example, Quiroz and Manji (2002) found that the volume of certain areas of the CNS and the number and / or size of glial cells and neurons were significantly reduced. However, it is still very difficult to directly measure the CNS volume or the abundance of glial cells and neurons in the living human brain. The retina, as an extracranial extension of brain neurons and the only neurovascular tissue that can be directly observed, provides an ideal window for monitoring the characteristics of CNS neurons. Since aging is a natural process of death and decline of human brain neurons, by studying the changes in the characteristics of retinal ganglion cells (RGCs) during the aging of CNS cells, it is hoped that retinal cell biomarkers reflecting the aging of CNS neurons can be discovered, providing a non-invasive early detection analysis method.

[0002] Optical coherence tomography (OCT) is a non-invasive imaging technique that uses light waves to perform cross-sectional scanning of the retina. It is based on the concept of interferometry to create cross-sectional images of the retina with an accuracy of at least 10-15 microns (Costa et al., 2006). OCT-based angiography (OCTA) is a new non-invasive method to visualize the retinal vasculature and is based on the principle of diffraction particle movement of moving red blood cells to determine the location of blood vessels passing through various eye segments without the need for any intravascular dyes (Le & Patel, 2020), analyzing scattering from static background tissue to create high-resolution angiography. The OCTA technique allows imaging of blood flowing in the retina and displays the choroidal vasculature through coronal and depth encoding plates, presented together with structural OCT B scans. OCTA can be performed on the same equipment as OCT. Together, they provide detailed flow imaging of the deep retinal vascular plexus and choriocapillaris, as well as retinal structures at different layers. In order to measure the electrical activity of the retina in response to light stimulation, diagnostic tests such as electroretinograms (ERGs) can be used. There are three main types of ERG tests, namely pattern ERG (pERG), flash ERG (fERG), and multifocal ERG (mfERG). The pERG is often used as a test for conditions that affect ganglion cells and different neurodegenerative conditions; the mfERG shows the state of the retina as a whole; and the mfERG is best used to measure dysfunction in the central retinal area. Using different types of ERG tests, you can fully evaluate the state of a patient's retinal function, reliably monitor changes in retinal function over time, and evaluate the effectiveness of treatment.

[0003] However, these studies on the phenomenon still mainly focus on changes in the retina itself, and lack the analysis of the association with specific neurons of CNS neuronal changes. Currently, no standardized model has been found for comprehensive analysis of OCT, OCTA and ERG results, nor has an effective biomarker been found to objectively and quantitatively evaluate the status of CNS neurons. Summary of the invention

[0004] Embodiments of the present invention relate to methods for the integrated analysis of retinal structural and functional biomarkers for identifying CNS cell senescence.

[0005] According to one embodiment of the present invention, an integrated analysis method for multimodal retinal ganglion cell data for central nervous system marker cell aging is provided, and the method uses RGC aging as a biomarker for central nervous system cell aging. The method includes: applying the Early Treatment of Diabetic Retinopathy Study (ETDRS) grid to the macular plan view reconstructed in the optical coherence tomography (OCT) thickness map, dividing the macular plan view into multiple regions, wherein the OCT thickness map includes data values ​​of thickness and volume of five different retinal layers, wherein the five different retinal layers include nerve fiber layer (NFL), ganglion cell layer (GCL), inner plexiform layer (IPL), nerve fiber layer to inner plexiform layer (NFL-IPL) and ganglion cell layer to inner plexiform layer (GCL-IPL); grouping the multiple regions, and determining the average thickness and volume data distribution of each region of the five different layers to detect the abundance of RGC; using the posterior pole module to record optical tomography angiography (OCTA) and finely stratify to obtain retinal microvascular changes of the OCTA; obtaining pER G reports and analyzes the latency of N35, P50, N95, and the amplitudes of P50 (N35-P50) and N95 (P50-N95); obtains a multifocal electroretinogram (mfERG) report of 103 hexagons with the same center in the ETDRS grid at the macula, the mfERG report includes analysis of the latency of P1 and N1, and the amplitudes of P1 and N1; and identifies whether retinal ganglion cells (RGCs) are aging based on the average thickness and volume data of each area of ​​the five different layers of the OCT thickness map, the retinal microvascular changes of the OCTA, the latency of N35, P50, N95, and the amplitudes of P50 (N35-P50) and N95 (P50-N95) in the pERG report, and the latency of P1 and N1, and the amplitudes of P1 and N1 in the mfERG report, thereby identifying cell aging of the central nervous system. Combining the histological and functional analysis of RGCs with their precise location distribution and corresponding changes in blood supply microvasculature provides a non-invasive early detection analysis module that reflects RGC health.

[0006] According to an embodiment of the present invention, the method further comprises: using the posterior pole module to record a plan view of the macular area reconstructed in the OCT thickness map.

[0007] According to an embodiment of the present invention, dividing the macular area plane view into a plurality of regions comprises: dividing the macular area plane view into eight regions, the eight regions comprising an inner ring upper, an inner ring nasal, an inner ring lower, an inner ring temporal, an outer ring upper, an outer ring nasal, an outer ring lower, and an outer ring temporal region; and

[0008] Grouping the plurality of regions comprises: grouping the macular regions to form three annular regions, including: a fovea within 1 mm in diameter; an inner annular zone between 1 mm and 3 mm in diameter; and an outer annular zone between 3 mm and 6 mm in diameter, or,

[0009] Group the macular areas to form 4 zones including: superior, nasal, inferior, and temporal zones in annular areas between 1 mm and 6 mm, or

[0010] The macular areas were grouped to form 8 regions including: the inner annular superior, inner annular nasal, inner annular inferior, and inner annular temporal regions with diameters between 1 mm and 3 mm and the outer annular superior, outer annular nasal, outer annular inferior, and outer annular temporal regions with diameters between 3 mm and 6 mm.

[0011] According to an embodiment of the present invention, for grouping the macular area to form three areas, determining the thickness and volume data of each area of ​​the five different layers includes: calculating the average thickness and volume of the inner annular zone areas of the five different layers; calculating the average thickness and volume of the outer annular zone areas of the five different layers; and calculating the average thickness and volume of the total annular zone, which is the combined area of ​​the inner annular zone area and the outer annular zone area.

[0012] According to an embodiment of the present invention, for grouping the macular area to form 4 areas, determining the thickness and volume data of each area of ​​the five different layers includes: calculating the average thickness and volume of the total upper area, wherein the total upper area is a combination of the inner annular upper area and the outer annular upper area; calculating the average thickness and volume of the total nasal area, wherein the total nasal area is a combination of the inner annular nasal area and the outer annular nasal area; calculating the average thickness and volume of the total lower area, wherein the total lower area is a combination of the inner annular lower area and the outer annular lower area; and calculating the average thickness and volume of the total temporal area, wherein the total temporal area is a combination of the inner annular temporal area and the outer annular temporal area.

[0013] According to an embodiment of the present invention, for grouping the macular area to form 8 areas, determining the thickness and volume data of each area of ​​the five different layers includes: calculating the average thickness and volume of the inner ring upper area, inner ring nasal area, inner ring lower area, and inner ring temporal area of ​​the five different layers; and calculating the average thickness and volume of the outer ring upper area, outer ring nasal area, outer ring lower area, and outer ring temporal area of ​​the five different layers.

[0014] According to an embodiment of the present invention, the method also includes extracting an area with a thickness greater than 45 μm from the OCT thickness map and calculating the area of ​​the area by an image processing method; extracting an area within a 6 mm circle from the ETDRS grid and calculating the area of ​​the area by an image processing method; determining a parameter Area based on the ratio of the area of ​​the area with a thickness greater than 45 μm in the OCT thickness map to the area within a 6 mm circle of the ETDRS grid, wherein the parameter Area is used as a comprehensive indicator of ganglion cell abundance; and determining whether RGC aging exists based on the parameter Area.

[0015] According to an embodiment of the present invention, using the posterior pole module to record optical tomography angiography (OCTA) and finely stratify to obtain the retinal microvascular changes of the OCTA also includes: acquiring OCTA vascular image data; extracting the area within the circle with a diameter of 2 mm centered on the macula as the region of interest (ROI) and cropping out the area of ​​the image; calculating the vascular abundance, vascular length, vascular diameter and vascular tortuosity by applying the OCTAVA method to the ROI; and calculating the foveal avascular zone (FAZ) parameters, the FAZ parameters including the FAZ area index and the FAZ roundness index; identifying whether RGC is aged based on the retinal microvascular changes of the OCTA also includes: determining whether central nervous system cell aging is present based on the vascular abundance, vascular length, vascular diameter and vascular tortuosity and the foveal avascular zone (FAZ) parameters.

[0016] According to an embodiment of the present invention, the method also includes performing a 48-minute graphic electroretinogram (pERG) test twice and obtaining a pERG report; and extracting N35, P50 and N95 latency and P50 and N95 amplitude data from the pERG report by an OCR Space text extraction method; and determining whether RGC aging exists based on the N35, P50 and N95 latency and P50 and N95 amplitude.

[0017] According to an embodiment of the present invention, obtaining an mfERG report includes: performing an mfERG test and obtaining an mfERG report; dividing the 103 hexagons into four different areas / quadrants with a horizontal line and a vertical line, and calculating the average latency and amplitude of P1 and N1 in the four different quadrants, and / or dividing the 103 hexagons into six equally spaced concentric annular areas around the central disk, and calculating the average latency and amplitude of P1 and N1 in the six different rings.

[0018] According to another embodiment of the present invention, a method for a comprehensive analysis module for effective, quantitative and reliable evaluation, identification, assessment and intervention is provided. The method includes analyzing the OCT thickness and volume data of different areas of the nerve fiber layer (NFL), ganglion cell layer (GCL), inner plexiform layer (IPL), nerve fiber layer to inner plexiform layer (NFL-IPL) and ganglion cell layer to inner plexiform layer (GCL-IPL); analyzing the OCT custom parameter Area of ​​the GCL thickness map; analyzing the OCTA superficial and deep vascular plexus and calculating the vascular abundance, vascular length, vascular diameter, vascular tortuosity and / or foveal avascular zone (FAZ) parameters, including FAZ area index and FAZ roundness index; generating pERG reports and analyzing the implicit latency of N35, P50, N95 time) and amplitudes of P50 (N35-P50) and N95 (P50-N95); obtained mfERG reports and analyzed P1 and N1 latencies and P1 and N1 amplitudes; and performed a comprehensive analysis of retinal structural, vascular, and functional parameters by correlating the Early Treatment of Diabetic Retinopathy Study (ETDRS) grid with 103 hexagons in the mfERG report that had the same center at the macula.

[0019] In another embodiment of the present invention, a method for comprehensive and detailed analysis of OCT thickness and volume by applying three different segmentation methods at the macular area and by effective custom parameters is provided. The method comprises: recording the OCT thickness map using a posterior pole module; applying an ETDRS grid to the OCT thickness map to divide the retina into eight regions, the eight regions comprising an inner superior, inner nasal, inner inferior, inner temporal, outer superior, outer nasal, outer inferior, and outer temporal region; grouping the eight regions based on three different division methods; calculating the average thickness and volume data of each region in different layers; the different layers comprising a nerve fiber layer (NFL), a ganglion cell layer (GCL), an inner plexiform layer (IPL), from the nerve fiber layer to the inner plexiform layer (NFL-IPL), and from the ganglion cell layer to the inner plexiform layer (GCL-IPL); cropping the OCT thickness map output by the software so that only the right half of the numerical data is retained for OCT thickness and volume analysis; and The Space method extracts numerical data from the cropped OCT thickness map. The first of the three different segmentation methods includes calculating the average thickness and volume of the inner Annulus sector in five different layers; calculating the average thickness and volume of the outer Annulus sector in the five different layers; and calculating the average thickness and volume of the total Annulus, which is the combined area of ​​the inner Annulus sector and the outer Annulus sector in the five different layers. The second of the three different segmentation methods includes calculating the average thickness and volume of the total upper region, which is the combined area of ​​the inner upper and outer upper regions in the five different layers; calculating the average thickness and volume of the total nasal region, which is the combined area of ​​the inner nasal and outer nasal regions in the five different layers; calculating the average thickness and volume of the total lower region, which is the combined area of ​​the inner lower and outer lower regions in the five different layers; and calculating the average thickness and volume of the total temporal region, which is the combined area of ​​the inner temporal region and the outer temporal region in the five different layers. The third of the three different division methods includes calculating the average thickness and volume of the inner ring upper region, inner ring nasal region, inner ring lower region, and inner ring temporal region in five different layers; and calculating the average thickness and volume of the outer ring upper region, outer ring nasal region, outer ring lower region, and outer ring temporal region in five different layers. The OCT thickness map output by the cropping software is retained so that only the left half of the numerical data is used to calculate the custom parameter Area.The areas with thickness greater than 45 μm were extracted and their areas were calculated by image processing methods. The areas within the 6 mm circle of the ETDRS grid were extracted and their areas were calculated by image processing methods. The value of Area was the ratio of the area with thickness greater than 45 μm on the OCT thickness map to the area within the 6 mm circle of the ETDRS grid.

[0020] In another embodiment of the present invention, a method for comprehensively and in detail analyzing OCTA superficial and deep vascular plexus images is provided. The method comprises: recording the OCTA vascular image data; extracting the area within a 2 mm circle centered on the macula and cropping the rest of the image as a trade-off for including more vascular areas without losing vascular details; calculating vascular abundance, vascular length, vascular diameter, and vascular tortuosity by applying the OCTAVA method to the cropped vascular image; and calculating foveal avascular zone (FAZ) parameters, the FAZ parameters comprising a FAZ area index and a FAZ circularity index.

[0021] In certain embodiments of the present invention, a method for quantitative analysis of a pERG report comprises recording a 48-minute pERG test twice and obtaining a pERG report; and extracting numerical data of the latencies of N35, P50 and N95 and the amplitudes of P50 and N95 from the pERG report by an OCR Space text extraction method.

[0022] In certain embodiments of the present invention, a method for comprehensively analyzing mfERG reports by dividing the analysis area in two different ways is provided. The method includes recording 103 mfERG tests and obtaining mfERG reports; dividing the 103 hexagonal areas in the test report into four different areas / quadrants with a horizontal line and a vertical line, and calculating the average latency and amplitude of P1 and N1 in the four different quadrants; and dividing the 103 hexagons into six equally spaced concentric eccentricities around a central disk, and calculating the average latency and amplitude of P1 and N1 in six different concentric rings.

[0023] In another embodiment of the present invention, a method for integrated analysis of retinal structure and function biomarkers includes applying the ETDRS grid and 103 hexagons to the macular area, both of which are associated with the fovea as the center; and correlating regional changes in retinal structure and function by correlating the overlapping areas of the two overlays.

[0024] According to another embodiment of the present invention, a computer program product is provided, comprising: a non-transitory computer executable storage device, on which computer readable program instructions are contained, and when the computer readable program instructions are executed by a computer, the computer executes the above method.

[0025] According to another embodiment of the present invention, there is provided an integrated analysis device for multimodal retinal ganglion cell data for marking aging, comprising at least one processor configured to execute the above method. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 The process of applying three different partitioning methods to different layers of the retina at the macular area to analyze OCT thickness and volume changes is shown.

[0027] Figure 2 An image of the Early Treatment Diabetic Retinopathy Study (ETDRS) grid, comprising circles having diameters of 1 mm, 3 mm and 6 mm, respectively, is shown overlaid on an OCT thickness map dividing the OCT thickness map into 9 regions.

[0028] Figure 3 An exemplary OCT thickness map of the ganglion cell layer (GCL) is shown along with software-generated statistics including mean thickness and volume of the corresponding 8 regions.

[0029] Figure 4 An exemplary use of OCR Space to extract text from an image is shown, with the image showing the user interface, input, and output.

[0030] Figure 5A An analysis method is shown in which the macular area is divided into 3 zones, namely the inner annular zone, the outer annular zone, and the inner annular zone plus the outer annular zone (total annular zone); Figure 5B Another analysis method is shown, in which the macular area is divided into 4 regions, namely superior, nasal, inferior, and temporal; Figure 5C Another analysis method is shown, in which the macular area is divided into 9 areas, including inner annular superior, inner annular nasal, inner annular inferior, inner annular temporal, outer annular superior, outer annular nasal, outer annular inferior, and outer annular temporal.

[0031] Figure 6 The original OCT thickness map and the OCT thickness map after image preprocessing to extract regions with a thickness exceeding 45 μm are shown.

[0032] Figure 7 A schematic diagram of vascular parameters is shown, including vascular area abundance, mean / distribution of vascular diameter, total length / distribution of vascular length, vascular tortuosity, vascular branch point abundance, and vascular fractal abundance.

[0033] Figure 8 An exemplary superficial vascular plexus image is shown on the left; an exemplary deep vascular plexus image is shown on the right.

[0034] Fig. 9 An original vascular image and a pre-processed vascular image are shown. The pre-processed vascular image extracts an area within a 2 mm circle centered on the macula as a further analysis area.

[0035] Fig.10 An exemplary use of the OCTAVA toolbox is shown. When a microvascular image is uploaded, the toolbox first performs a binarization process on it to extract the vascular structure from the background, and applies a skeletonization algorithm to further extract the vascular structure. Finally, the distribution information of the vascular parameters is output in Excel format.

[0036] Fig.11 Shown is an exemplary use of OCR Space to extract useful data from an uploaded mfERG report, with the amplitude and latency data of N1 and P1 within 6 rings extracted for subsequent analysis.

[0037] Fig.12 A pERG report of exemplary output from the ERG software is shown.

[0038] Fig.13A shows an analysis method of 103 hexagons at the macular area, the 103 hexagons are divided into 4 quadrants, and for each of the 4 quadrants, the average amplitude and latency of P1 and N1 are analyzed separately; Fig. 13B Another analysis method is shown, in which the 103 hexagons at the macular area are divided into 6 concentric equidistant eccentricities, and for each of the 6 rings, the mean amplitude and latency of P1 and N1 are analyzed separately.

[0039] Fig.14 A schematic with two overlays is shown: one is a 1, 3, 6 mm ETDRS grid overlay and the other is a 103 hexagonal divisions with the same center at the macula shown on the same image.

[0040] Fig.15A The 3 different layers of the retina are shown.

[0041] Fig. 15B Further detailed layers of the retina are shown.

[0042] Fig.16 A basic general scanning protocol for optical coherence tomography angiography (OCTA) is shown.

[0043] Figures 17A-17CSchematic diagrams of pERG, flash ERG and mfERG are shown, respectively.

[0044] Fig.18 A schematic diagram of light stimulation of pERG (left) and a schematic diagram of a sample waveform (right) are shown.

[0045] Fig.19A A schematic diagram of light stimulation of mfERG (left), a schematic diagram of contact electrodes (middle), and a schematic diagram of detected electrical waveforms (right) are shown.

[0046] Fig.19B A schematic diagram showing the distribution of amplitude in mfERG and the relationship between amplitude and latency represented by a topographic map is shown.

[0047] Fig. 20 A schematic diagram showing the comparison of OCT thickness and volume parameters for the young and elderly groups for division method 1.

[0048] Fig.21 A schematic diagram showing the comparison of OCT thickness and volume parameters for the young and elderly groups for division method 2.

[0049] Fig. 22 A schematic diagram showing the comparison of OCT thickness and volume parameters for the young and elderly groups for division method 3.

[0050] Fig.23 A schematic diagram showing the comparison of vascular parameters between the young and old groups is shown. DETAILED DESCRIPTION

[0051] Embodiments of the present invention relate to methods for the integrated analysis of retinal structural and functional biomarkers for identifying CNS cell senescence.

[0052] The terms used herein are only used for the purpose of describing specific embodiments and are not intended to limit the present invention. As used herein, the term "and / or" includes any and all combinations of one or more associated listed items. As used herein, the singular forms "one", "an" and "the" are intended to include plural forms as well as singular forms, unless the context clearly states otherwise. It will be further understood that when used in this specification, the terms "include" and / or "comprise" specify the presence of the features, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, steps, operations, elements, components and / or groups thereof.

[0053] Unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which the invention belongs. It will be further understood that terms such as those defined in commonly used dictionaries should be interpreted as having a meaning consistent with their meaning in the context of the relevant art and the present disclosure, and will not be interpreted in an idealized or overly formal sense unless explicitly so defined herein.

[0054] When the term "about" is used in conjunction with a numerical value herein, it is understood that the value may be within the range of 90% to 110% of the value, i.e., the value may be + / -10% of the value. For example, "about 1 kg" means 0.90 kg to 1.1 kg.

[0055] As the extracranial extension of the brain and the only visualized neurovascular tissue, the human retina is an ideal window for monitoring the properties of CNS neurons. Fig.15A As shown in Figure 1, the human retina can be roughly divided into 3 different layers, the photoreceptor cell layer, the ganglion cell layer, and the bipolar cell layer. They can be further divided into more layers, such as Fig. 15B As shown. Among them, ganglion cells are projection neurons of the vertebrate retina, transmitting information from other retinal neurons to other parts of our brain. In order to thoroughly monitor its changes, we need a comprehensive analysis of the properties of the ganglion cell layer (GCL), including structural, vascular and functional properties.

[0056] However, current studies have two major limitations. First, most OCT instruments used in current studies cannot separate the GCL and IPL. Second, current studies rarely combine retinal ganglion cell characteristics with retinal vascular and functional characteristics for comprehensive analysis.

[0057] Therefore, in order to solve the above problems, the present application proposes the following method.

[0058] refer to Figure 1 A-E3 in Figure 3 shows a comprehensive analysis process of OCT thickness and volume of different layers of the retina at the macular region using three different partitioning methods. A method for providing a comprehensive and detailed analysis of OCT thickness and volume by applying three different partitioning methods to 5 different layers of the retina at the macular region (eg, Figure 1 The method includes: recording an optical tomography angiography (OCT) thickness map using a posterior pole module; applying an Early Treatment Diabetic Retinopathy Study (ETDRS) grid to the OCT thickness map to divide the retina into eight regions (eg, Figure 3 as shown); according to Figure 1The eight regions were grouped by three different methods shown in E1, E2, and E3; the average thickness and volume data of each region including the nerve fiber layer (NFL), ganglion cell layer (GCL), inner plexiform layer (IPL), from the nerve fiber layer to the inner plexiform layer (NFL-IPL), and from the ganglion cell layer to the inner plexiform layer (GCL-IPL) were calculated (see Figure 5). Figure 1 The OCT thickness map output from the software was cropped so that only the right half of the numerical data was retained for OCT thickness and volume analysis (as shown in B in FIG). Figure 3 ); extract numerical data from the cropped OCT thickness map using the OCR Space text extraction method (as shown in Figure 4 shown).

[0059] In addition, the present invention defines a custom parameter named Area, which represents the ratio of the area with a thickness greater than 45 μm on the GCL thickness map to the area of ​​the 6 mm circle of the ETDRS grid. The parameter Area is used as a comprehensive indicator of ganglion cell richness, and combined with the standard ETDRS grid analysis indicators, it helps to more comprehensively evaluate the characteristics and changes of retinal structure. The method for determining Area includes: cropping the OCT thickness map output from the software so that it only retains the left half of the original thermal map image for analyzing Area; extracting areas with a thickness greater than 45 μm and calculating their areas through image processing technology; extracting the area within the 6 mm circle of the ETDRS grid and calculating its area through image processing technology; calculating Area, which is the ratio of the area with a thickness greater than 45 μm on the GCL thickness map to the area within the 6 mm circle of the ETDRS grid. Figure 6 An example of calculating Area is shown in FIG.

[0060] In one embodiment, a method for comprehensive and detailed analysis of OCTA superficial and deep vascular plexus images is provided. The method comprises: recording optical coherence tomography angiography (OCTA) vascular image data; Fig. 9 As shown, the area within a 2 mm circle centered on the macula is extracted and the rest of the image is cropped out as a trade-off for retaining more vascular areas without losing vascular details; vascular abundance, vessel length, vessel diameter, and vessel tortuosity are calculated by uploading the cropped vascular image to a toolbox called OCTAVA; and foveal avascular zone (FAZ) parameters including FAZ area index and FAZ circularity index are calculated. Fig.10 An example of image processing and data analysis using OCTAVA is shown in .

[0061] In another embodiment, a method for dividing the mfERG report analysis area in two different ways is also provided. The method includes: recording 103 mfERG tests and obtaining mfERG reports; dividing 103 hexagons into four different areas / quadrants with a horizontal line and a vertical line, and calculating the average latency and amplitude of P1 and N1 in the four different quadrants; and dividing the 103 hexagons into six concentric equidistant eccentric distances around the central disk, and calculating the average latency and amplitude of P1 and N1 in six different rings. The two division methods are Fig.13A and 13B Shown in.

[0062] In another embodiment, a method for integrated analysis of retinal imaging and functional biomarkers is provided. The method comprises: applying both the ETDRS grid and 103 hexagons to the retina at the macular region, both centered on the fovea; and correlating structural and functional changes in the retinal macular region by correlating the overlapping areas of the two overlays. Fig.14 The 1 mm circle of the ETDRS grid corresponds to the combined ring 1 and ring 2. The 3 mm circle of the ETDRS grid (inner ring band, Fig.14 The yellow area in the figure corresponds to Ring 3, and the 6 mm circle of the ETDRS grid (outer ring, Fig.14 The green area in the figure corresponds to loop 4. The results can be well correlated using this combined analysis.

[0063] The results of the analysis of retinal imaging and examples of functional changes at the macular area with increasing age are also provided. First, the results revealed the trend of thickness changes in five different layers using the three division methods shown above. In order to further analyze the results and understand the results more deeply, the samples were divided into two different age groups, the young group was between 22 and 32 years old, and the elderly group was between 50 and 62 years old. An independent sample t-test (t-test) was then performed to evaluate the differences between the two age groups.

[0064] For OCT thickness map analysis, in order to verify the validity of the defined retinal structural biomarkers, an independent sample t-test was performed between age and structural parameters, including the average thickness / volume of 5 different layers in different areas divided by the 3 partitioning methods as described. For partitioning method 1, the NFL thickness of the elderly group increased significantly in the inner annular zone area, the GCL thickness decreased significantly in the outer annular zone area and the total annular zone area, and the NFL-IPL thickness decreased significantly in the outer annular zone area. For partitioning method 2, the NFL thickness of the elderly group increased significantly in the total temporal area, and the GCL thickness decreased significantly in the total superior area, the total inferior area, and the total temporal area. In addition, the NFL volume of the elderly group increased significantly in the total temporal area, the GCL volume decreased significantly in the total superior and total inferior areas, and the NFL-IPL volume decreased significantly in the total superior area. For division method 3, the NFL thickness of the elderly group increased significantly in the inner annular nasal, inner annular temporal, and outer annular temporal regions, the GCL thickness decreased significantly in the inner annular temporal and outer annular inferior regions, the NFL-IPL thickness decreased significantly in the outer annular inferior region, and the GCL-IPL thickness decreased significantly in the outer annular inferior region. In addition, the NFL volume of the elderly group increased significantly in the inner annular temporal and outer annular temporal regions, and the GCL volume decreased significantly in the inner annular superior and outer annular inferior regions.

[0065] For OCTA vascular image analysis, in order to verify the validity of the defined retinal vascular biomarkers, an independent sample t-test was performed between age and vascular parameters, including general parameters such as vessel area density (VAD) and vessel length density (VLD). In addition, the corresponding total / mean / median / variance of vessel length, diameter and tortuosity were included. For the elderly group, the richness of the vasculature was significantly reduced. In addition, the total vessel length was significantly reduced in the elderly group. In addition, the mean and median of vessel diameter and the mean of vessel tortuosity were significantly increased in the elderly group.

[0066] For the mfERG report analysis, in order to verify the validity of the defined retinal function biomarkers, an independent sample t-test was performed between age and functional parameters, including the average amplitude and latency of P1 and N1 in different areas of 103 hexagons, according to the 2 different division methods (4-quadrant division method and 6-ring division method) as described above. For the elderly group, the latency of P1 was significantly increased in quadrants 3 and 4 (4-quadrant division method) and rings 4 and 5 (6-ring division method) of 103 hexagons, and the latency of N1 was also significantly increased in quadrant 1 (4-quadrant division method) and ring 3 (6-ring division method) of 103 hexagons.

[0067] Combining the results of OCT thickness map analysis and mfERG reporter analysis showed that they can be well correlated. Fig.14 , yellow area), the NFL thickness of the elderly group increased significantly, and the latency of N1 in the elderly group also increased significantly. Fig.14 , green area), the thickness of GCL and NFL-IPL in the elderly group was significantly reduced, and the latency of P1 in the elderly group was also significantly increased.

[0068] One limitation is that, since the embodiments of the present invention of the comprehensive analysis method are different from conventional analysis modules, the method may require very specific data types, which include all OCT scan images, OCTA vascular images, and pERG and mfERG test results. In this case, the comprehensive analysis module cannot adapt to the situation when part of the retinal data is missing. In addition, the comprehensive analysis method of the present invention requires the OCT / OCTA and ERG machines used to be able to properly separate the ganglion cell layer, and also requires the ERG machine to be able to perform 103mfERG tests.

[0069] Another limitation is the relatively small sample size used in the present invention to validate the effectiveness of retinal imaging and functional biomarkers: OCT / OCTA scans were performed on 20 subjects per age group (young and old); pERG and mfERG tests were performed on 10 subjects per age group. However, significant retinal changes could still be observed, especially in the outer ring of the macular region.

[0070] Regarding the first limitation, although the detection capability of the equipment may affect the universality of this analysis module, the goal of this study is to conduct a more comprehensive and detailed analysis of the retina in the macular area from multiple levels such as structure, blood vessels and function. Therefore, this limitation will not be resolved.

[0071] To overcome the second limitation, more participants could be recruited from staff or students in the University of Hong Kong and the local community to further confirm the validity of this comprehensive analysis module.

[0072] In one embodiment, the present invention provides a comprehensive analysis method for evaluating retinal changes from the perspective of retinal structure and function. All optical coherence tomography (OCT) and optical coherence angiography (OCTA) images are collected with a resolution of up to 3 microns, which can provide detailed information at the cellular level. Specifically, the present method uses frequency domain optical coherence tomography (SD-OCT) technology equipped with a vascular imaging module to ensure the accuracy of retinal stratification and vascular system details. With the continuous advancement of computer image processing and analysis technology, in-depth analysis of changes at the retinal cell level can be performed to discover retinal biomarkers related to aging and evaluate the health of CNS neurons. By integrating retinal structure and function analysis at the cellular level, the method of the present invention can discover reliable retinal biomarkers to provide support for evaluating the health of CNS neurons. This cross-scale integrated analysis method helps to more comprehensively reflect the overall status of the visual system and central nervous system, and provides an important basis for the early diagnosis and treatment of neurodegenerative diseases.

[0073] Commercially available machines with specific designs and detection parameters for image acquisition and reconstruction are used. Changes in RGC morphology and functional levels can be used for early detection of CNS neuronal health.

[0074] First, this method obtains retinal structural biomarkers in the macular region, including detailed analysis of the thickness and volume data of each layer from OCT scans. Then, the retinal vasculature in the macular region is analyzed based on the superficial and deep vascular plexuses obtained from OCTA scans. Next, multifocal electrophysiological detection (mfERG) is used to evaluate retinal function in specific areas. Through quantitative and comprehensive analysis of these three aspects, changes in retinal ganglion cells during aging can be evaluated, thereby reflecting the health of CNS neurons.

[0075] The method for comprehensive analysis of retinal ganglion cell properties from a structural, vascular, and functional perspective offers two major advantages. First, the method provides a comprehensive analysis of retinal ganglion cell distribution through OCT thickness maps, a comprehensive analysis of the retinal vasculature through OCTA superficial vascular plexus images, and a comprehensive analysis of retinal function through pERG and mfERG reports. This detailed and comprehensive analysis may reveal potential mechanisms of CNS neuronal aging. The second advantage is that the comprehensive analysis method analyzes ganglion cell layer thickness alone, without combining it with the inner plexiform layer, thereby achieving analysis of ganglion cell properties at the cellular level.

[0076] Using the properties of human retinal ganglion cells, which are projection neurons of the vertebrate retina, to monitor CNS neuronal health is a new approach that has not been fully explored before.

[0077] The present invention has customized retinal structural parameters, which have been shown to be effective for analyzing retinal ganglion cell characteristics and evaluating CNS neuron health. In addition to a detailed analysis of retinal vascular and functional changes, the present invention also includes a comprehensive analysis module. This module can effectively promote the discovery of retinal biomarkers and provide support for reliable monitoring of CNS status. By integrating quantitative analysis of multiple aspects such as retinal structure, blood vessels and function, the present invention constructs a comprehensive evaluation framework. This cross-scale integrated approach helps to more accurately reflect the overall status of the visual system and central nervous system, and provide support for early diagnosis and treatment of neurological diseases.

[0078] Embodiments of the present invention focus on cellular level analysis and can correlate retinal structural and functional changes to reveal the underlying mechanisms of CNS cell aging.

[0079] In one embodiment, the present invention provides in great detail systems and methods for a comprehensive analysis module of retinal structural and functional biomarkers. Retinal biomarkers can facilitate early detection of central nervous system neuronal health by studying retinal neuronal properties at the cellular level based on OCT thickness maps, OCTA vascular images, and mfERG reports. Thus, timely intervention can be performed to slow down the further development of neurons and maintain neuronal health in the CNS.

[0080] The quantitative structural and functional biomarkers of the retina produced by the present invention can be used to develop intervention plans related to or potentially related to retinal aging and central nervous system (CNS) neuron decline. These quantitative indicators help to achieve early detection and timely intervention treatment. In addition, the system and method of the present invention can also be used as a routine clinical examination or a community screening tool based on retinal data to monitor the overall health of CNS neurons. This non-invasive assessment method based on the retina provides a convenient and efficient solution for clinicians and researchers, which is expected to promote the early detection and management of neurological diseases.

[0081] In a preferred embodiment, the system and method define and quantify retinal imaging and functional parameters. Participants were divided into two age groups. The age of the young group was 22 to 32 years old, and the age of the elderly group was 50 to 62 years old. Inclusion criteria for the retina were (1) best corrected visual acuity of 20 / 50 or higher; (2) intraocular pressure less than 21 mmHg. Exclusion criteria were (1) presence of significant refractive error, intraocular pressure>21 mmHg; (2) media opacity; (3) concomitant ocular disease; (4) history of glaucoma or retinal pathology or systemic conditions that may affect the visual system; (5) history or evidence of ocular or neurological disease of any nature; (6) best corrected visual acuity based on the Snellen scale ≤20 / 30 (±0.2, in Log Mar). All subjects were required to undergo a complete ophthalmic evaluation, including pupil, anterior segment and funduscopy.

[0082] OCT thickness map analysis

[0083] In some embodiments, the present invention uses the posterior pole module to obtain OCT thickness maps of different layers. For example, in some embodiments of the system of the present invention, the OCT images of the participant include, but are not limited to, thickness maps of the nerve fiber layer (NFL), ganglion cell layer (GCL), and inner plexiform layer (IPL). All thickness maps were obtained using the OCT (SD-OCT) built-in software through two different applications: Fast Macular Cube (for macular analysis) and Retinal Nerve Fiber Layer (RNFL) Glaucoma (for peripapillary assessment). They were then cropped accordingly Figure 3 OCT thickness map output by the software shown in . For thickness and volume analysis, only the right half is required for numerical data extraction. For custom parameter regional analysis, only the left half is required for image processing.

[0084] In some embodiments, for detailed analysis, an Early Treatment Diabetic Retinopathy Study (ETDRS) grid including circles having diameters of 1 mm, 3 mm, and 6 mm, respectively, is overlaid on the OCT thickness map to divide the OCT thickness map into 9 regions (or referred to as zones), such as Figure 2 As shown, with the following tags:

[0085] 1. C1: foveal area;

[0086] 2. S3, N3, I3, T3: the inner ring superior, inner ring nasal, inner ring inferior, and inner ring temporal regions of the inner ring area between 1 mm and 3 mm, respectively;

[0087] 3. S6, N6, I6, T6: the superior, nasal, inferior and temporal regions of the outer ring area between 3 mm and 6 mm, respectively.

[0088] By adopting the ETDRS (Early Treatment Diabetic Retinopathy Study) analysis method, valuable quantitative data can be extracted from retinal thickness maps obtained by optical coherence tomography (OCT) imaging. The ETDRS grid is a standardized, reliable and reproducible method for analyzing and reporting retinal thickness, which helps to better compare the results of different studies and clinical settings. In general, ETDRS charts are considered more accurate and reproducible in analysis and comparison. This is because the ETDRS grid corresponds to the anatomical and functional areas of the retina and can provide clinically relevant information, reflecting the retinal structure and its potential impact on retinal function. Based on the ETDRS grid, the volume and thickness data of different retinal layers (such as the ganglion cell layer GCL and its adjacent layers NFL and IPL) in different sub-fields can be extracted and analyzed. These quantitative indicators help to more comprehensively evaluate the structural characteristics of the retina and provide valuable basis for the diagnosis and monitoring of various retinal diseases.

[0089] Figure 3 An example of a thickness map of the ganglion cell layer and the statistics generated by the software is shown in Figure 1. The different colors on the thickness map represent different thickness values ​​for that region. The lighter the color, the thicker the region. For each of the 9 regions, the built-in analysis software can provide the average thickness as well as volume information for that specific region.

[0090] In some embodiments, the present invention analyzes and quantifies the thickness map of the ganglion cell layer (GCL) and its adjacent layers, including the nerve fiber layer (NFL) and the inner plexiform layer (IPL), to find signs of neurodegeneration. The average thickness and volume of the NFL-IPL from the nerve fiber layer to the inner plexiform layer and the GCL-IPL from the ganglion cell layer to the inner plexiform layer are also analyzed to gain a deeper understanding.

[0091] In a preferred embodiment, the present invention quantifies retinal imaging parameters including but not limited to the average thickness and volume of different regions of the ETDRS (Early Treatment Diabetic Retinopathy Study) grid of different layers of the NFL, GCL, IPL, GCL-IPL and NFL-IPL.

[0092] In some embodiments, the present invention extracts useful data from the output images of the SD-OCT machine through OCR Space, which is an online image processing method that recognizes and extracts numbers or strings from images and converts them into an analyzable format such as text or JSON (Badwaik, Mahmood, & Raza, 2017). Figure 4An example of the input and output data of OCRSpace is shown in , which correctly extracts all useful data, including the average thickness and volume of 9 regions.

[0093] In a specific embodiment, the present invention divides the 1, 3, and 6 mm ETDRS grids into three different areas, including the fovea, i.e., the area within the 1 mm circle, the inner annulus, i.e., the area between the 1 mm and 3 mm circles, and the outer annulus, i.e., the area between the 3 mm and 6 mm circles. Figure 5A An illustration of the division is shown in FIG. In addition, the total annulus is the combined area of ​​the inner annulus and the outer annulus. For each of the inner annulus, outer annulus, and total annulus areas, average thickness and volume data can be obtained and then analyzed by a two-tailed independent sample t-test to calculate a significance value (P) between the two age groups.

[0094] In a specific embodiment, the present invention divides the 1, 3, 6 mm ETDRS grid into 4 different regions, namely, total superior (S3 and S6), total nasal (N3 and N6), total inferior (I3 and I6), and total temporal (T3 and T6). Figure 5B An illustration of the division is shown in For each of these 4 different regions, volume and thickness data were available and then analyzed by a two-tailed independent sample t-test to calculate the significance value (P) between the two age groups.

[0095] In a specific embodiment, the present invention divides the 1, 3, and 6 mm ETDRS grids into 8 different areas, including the inner ring area between 1 mm and 3 mm: the inner ring upper (IS), inner ring nasal (IN), inner ring lower (II), and inner ring temporal (IT); and the outer ring upper (OS), outer ring nasal (ON), outer ring lower (OI), and outer ring temporal (OT). Figure 5C An illustration of the division is shown in For each of these 8 different regions, volume and thickness data were available and then analyzed by a two-tailed independent sample t-test to calculate a significance value (P) between the two age groups.

[0096] In some embodiments, the present invention defines a parameter called Area, which represents the ratio of the area with a thickness greater than 45 μm on the GCL thickness map to the area of ​​a 6 mm circle of the ETDRS grid. This indicator is based on the fact that the average size of human retinal ganglion cells is about 10 μm, and it is believed that the area greater than 45 μm represents sufficient distribution of ganglion cells in the macula. Figure 6As shown in Figure 1, the calculation process of this parameter includes image processing and extraction of areas with a thickness greater than 45 μm using Python OpenCV and Shapely packages. The relevant code can be found in Example 8. The "Area" parameter is considered as a comprehensive indicator that can reflect the richness of ganglion cells. Since the analysis process only focuses on a certain area of ​​the ETDRS grid, the completeness of the analysis may be lost. Therefore, the introduction of the "Area" parameter can make up for this deficiency and provide a supplementary indicator for the effective evaluation of the status of ganglion cells.

[0097] OCTA vascular image analysis

[0098] In some embodiments, the methods of the present invention will quantify retinal microvascular parameters including, but not limited to, vessel area abundance, vessel diameter, vessel length, vessel tortuosity, vessel branch point abundance, and vessel fractal dimension. Figure 7 All vascular characteristics are shown in the figure, and the present invention will calculate the mean, median, variance, skewness and kurtosis of the distribution of these characteristics. In a further preferred embodiment, the method will quantify the parameters of the foveal avascular zone (FAZ), and the FAZ parameters include but are not limited to the FAZ area, FAZ perimeter and FAZ circularity.

[0099] In certain embodiments, the present invention will acquire OCTA image data.Optical coherence tomography angiography, known as OCTA, is a relatively new non-invasive method for visualizing retinal microvasculature. Fig.16 The basic general scanning protocol of Optical Coherence Tomography Angiography (OCTA) is explained in . (a) Repeated B-scans are performed on the "x" fast axis at each "y" slow scan axis point to detect relative flow signals. (b) is a top view of the same general scanning pattern as (a), with repeated B-scans on the fast axis "x" at each "y" position along the slow axis. OCTA rapidly acquires multiple cross-sectional images from a single location and uses motion contrast to distinguish between moving and static elements. Using this technology, microvessels of the superficial and deep capillary plexuses can be individually visualized and analyzed. For example, in some embodiments of the systems and methods of the present invention, participant OCTA images (including but not limited to two consecutive 3mm×3mm coronal OCTA images of the superficial and deep vascular plexuses) are generated by, for example, SD-OCT with an Angiography Module. Figure 8 The superficial and deep vascular plexus images of exemplary acquisitions are shown. The present invention extracts the area within a 2mm circle of the superficial vascular plexus image centered on the macula as the region of interest, which is a trade-off of including more vascular area while not losing vascular details. Fig. 9 An original image and a processed image are shown, in which a region within a circle centered at the fovea and having a diameter of 2 mm is extracted.

[0100] In some embodiments, the present invention utilizes an open source toolbox called OCTAVA developed using MATLAB and based on image processing functions in ImageJ (Untracht et al., 2021). Quantitative analysis of optical coherence tomography angiography (OCTA) images can be performed in detail by the toolbox. Fig.10 As shown in the figure, after uploading the OCTA image, the toolbox will first binarize and skeletonize the original image. Then, based on the extracted vascular structure, the toolbox can analyze various vascular parameters, such as vascular abundance, diameter, length, and tortuosity, and output their distribution data to an Excel file. Next, the two-tailed independent sample t-test in SPSS software is used to perform statistical analysis on the vascular parameters between different age groups and calculate the significance value (P).

[0101] In some embodiments, the method uses a method defined by a patent of the University of Hong Kong (Chiu, 2020) to calculate the FAZ parameters in the vascular image. The FAZ is defined as the area within the fovea centralis in the center of the human eye retina, which is devoid of retinal blood vessels (Shiihara et al., 2017).

[0102] In some embodiments, the systems and methods calculate the largest polygon in the avascular fovea, i.e., a polygon that does not cover any positive vascular signal in the resulting image. In some embodiments, the indication (0,0) corresponds to the upper left corner of the vascular image, and the center of the foveal region is (x inner ,y inner ), and the side length of the blood vessel image is "s". In some embodiments, Θ = 0, 3, 6, 9, ..., 357, that is, considering the inner ,y inner ) to (x inner +s·sin sinθ,y inner +s·cos cosθ) of all pixels within the image on a directed line segment having a value of θ = θ. In some embodiments, the first pixel with a positive signal, i.e., a portion of a blood vessel, is recorded as one of the endpoints of the FAZ. If the value of all pixels within the image on the directed line segment is zero, the particular θ pixel is skipped. If less than three searches return a positive signal, an error is reported. In a particular embodiment, a polygon is defined by connecting all n=120 endpoints in the order in which they are found in the approximate FAZ. In other embodiments, when less than all endpoints are used (some of which searches do not find any positive pixels), a polygon is defined by connecting less than 120 endpoints to divide the FAZ.

[0103] In some embodiments, the systems and methods of the present invention calculate the FAZ area index (FAI). In some embodiments, the systems and methods divide the vertices of the FAZ polygon into (a1, b1), (a2, b2), ..., (a n ,b n In certain embodiments, the systems and methods use the shoelace formula to calculate the area of ​​a polygon:

[0104]

[0105] In some embodiments, the systems and methods define FAI as the FAZ polygon area divided by the pixel area of ​​the vessel image. In addition, if the vessel image is always focused on a 3×3 area, the FAI is comparable between images of different sizes.

[0106] In some embodiments, the systems and methods of the present invention calculate the FAZ perimeter index (FPI). In some embodiments, the systems and methods calculate the perimeter of the FAZ polygon using the following formula:

[0107]

[0108] In some embodiments, the FPI is defined as the FAZ polygon perimeter divided by the side length of the vessel image in pixels. In addition, if the vessel image is always focused on a 3×3 area, the FPI is comparable between images of different sizes.

[0109] In some embodiments, the systems and methods of the present invention calculate the FAZ roundness index (FACI). In a specific embodiment, the FACI quantifies the irregularity of the shape of the divided FAZ and is calculated by the following formula:

[0110]

[0111] When FACI is equal to 1, the FAZ is a perfect circle. In some embodiments, when the FACI value is greater than 1, the FAZ has a more irregular shape.

[0112] ERG test report analysis

[0113] In some embodiments, the present invention will quantify retinal function parameters, including but not limited to the latency of N35, P50 and N95 tested in the pERG test, and the amplitude of N35 to P50 and P50 to N95. In addition, the parameters include the amplitude of P1 and N1 tested in the mfERG test, and the latency of P1 and N1.

[0114] An electroretinogram (ERG) is a diagnostic test that measures the electrical activity of the retina in response to light stimulation. Fig.17A , 17B As shown in Figure 17C, there are three main types of ERG tests, full-field pattern ERG, flash ERG, and mfERG. Using different types of ERG tests to determine the functional status of the retina allows clinicians and researchers to assess patients' retinal-related conditions, reliably monitor retinal function over time, and evaluate the efficacy of retinal treatments.

[0115] In the pattern ERG (pERG), the light stimulus is an alternating checkerboard pattern that evokes an electrical response from the ganglion cells that make up the inner retina. The pERG is commonly used to detect diseases that affect the ganglion cells, as well as many neurodegenerative diseases.

[0116] Specifically, pattern ERG is a non-invasive technique used to assess the function of the inner retina, especially the retinal ganglion cells. It activates the retinal ganglion cells through reverse checkerboard stimulation, producing electrical responses that can be detected using electrodes placed in the eye or surrounding areas.

[0117] Among them, the macula is mainly stimulated. Fig.18 As shown in the sample waveform, the initial negative response of the retinal ganglion cells to the onset of the stimulus N35 occurs at 35 milliseconds. And P50 is the main parameter used for analysis in the graphic ERG analysis, which is the positive peak component and reflects the activity of the distal ganglion cells. N95 is the negative peak component, reflecting the activity of the inner retina. Graphic ERG is most effective in distinguishing abnormalities at the ganglion cell level from distal lesions. The method of the present application extracts and analyzes the latency of N35, P50, and N95 and the amplitudes of N35-P50 and P50-N95.

[0118] In a full-field ERG (ffERG), electrodes record the total electrical response of retinal cells. The total electrical response is a mixture of results from a range of different cells and regions in the retina, which means that the full-field ERG (ffERG) shows the state of the retina as a whole.

[0119] In mfERG (mfERG), the light stimulus displays a series of hexagons that flash between white and black in a pseudo-random sequence. mfERG is best suited to measure dysfunction in the central area of ​​the retina.

[0120] Specifically, the mfERG test shows visual function across the macula. The test divides the macula into multiple hexagonal areas. The stimulus is a random sequence of black and white hexagons, alternating multiple times per second. Fig.19AThe picture shown on the left is an example of a series of black and white hexagons. These stimuli are then received by the human eye, and contact electrodes placed inside the eye will record the electrical activity in response to the stimuli within each hexagonal area. Finally, the results are shown in the picture on the right, where for each hexagonal area, the response is displayed in the form of an electrical waveform. The built-in software of the mfERG machine can also use the concept of topographic mapping to provide a 3D map indicating the distribution of important measurements of the waveform, such as Fig.19B This application extracts and analyzes the latency and amplitude of N1 and P1.

[0121] In a specific embodiment, the present invention obtains pERG and mfERG test results for analysis. Because the present invention focuses on the macula area, and mfERG divides the central retinal area into 103 hexagons, this provides an overall assessment of retinal electrical activity.

[0122] For example, in some embodiments of the comprehensive analysis of the present invention, the pERG and mfERG test results of the participants include, but are not limited to, using, for example, a RETI-port / scan 21ERG machine to generate a graphic ERG report showing an electrical activity waveform with N35, P50, N95 latency and P50 and N95 amplitudes, and a mfERG report showing the overall retinal electrical activity waveform of different regions of the retina. For accuracy, the graphic ERG 48-minute test is repeated twice for both eyes without mydriasis. And for the mfERG test, both eyes are checked separately, and the resolution level is set to 103 segments, and two 50Hz smoothing filters are applied. Corneal contact electrodes (BA / ERG-Jet) and gold foil electrodes are necessary for both graphic ERG and mfERG tests. In other embodiments, a test report from the output of the ERG machine is generated.

[0123] In some embodiments, the present invention extracts useful data from the output ERG report through OCR Space, which is an online image processing method that can recognize and extract numbers or strings from images and convert them into analyzable formats such as text or JSON (Badwaik, Mahmood, & Raza, 2017). Fig.11 An example use of OCRSpace is shown in , where an mfERG report is uploaded and all useful data is extracted, including the amplitude and latency of the P1 and N1 within each ring.

[0124] In some embodiments, the present invention extracts the latencies of N35, P50 and N95 and the amplitudes of P50 and N95 from the pERG 48-minute test report. Fig.12An example of the output of the pERG report is shown in . To ensure accuracy, the pERG test was repeated twice, and the test data of P-ERG1 and P-ERG2 were recorded and analyzed. For each parameter, a two-tailed independent sample t-test was used to analyze the differences between the groups and calculate the significance value (P) between the two age groups.

[0125] In some embodiments, the systems and methods of the present invention divide the 103 hexagons into 4 quadrants, such as Fig.13A As shown. For each quadrant, the average electrical waveform is generated by the built-in software, and the amplitudes of P1 and N1 and the latency of P1 and N1 will be generated and displayed in the mfERG test report. The first column Amp.P1 has a unit different from the other columns, which is nV divided by the square of the degree. Its value represents the amplitude of P1 of a specific hexagon divided by the area of ​​the hexagonal area to achieve the purpose of standardization. The present invention will use a two-tailed independent sample t-test to analyze the differences between the groups and calculate the significance value (P) between the two age groups for each parameter.

[0126] In some embodiments, the systems and methods of the present invention divide the 103 hexagons into 6 concentric equidistant eccentrics around the central disk, such as Fig. 13B As shown. The range of each ring is shown as: Ring 1, from 0° to 1°; Ring, from 1° to 4°; Ring 3, from 4° to 8°; Ring 4, from 8° to 12°; Ring 5, from 12° to 17°; Ring 6, from 17° to 21°. For each ring, the average electrical waveform is generated by the built-in software, and the amplitudes of P1 and N1 and the latency of P1 and N1 will be generated and displayed in the mfERG test report. For each parameter, the present invention uses a two-tailed independent sample t-test to analyze the differences between the groups and calculate the significance value (P) between the two age groups.

[0127] Comprehensive analysis and application

[0128] In some embodiments, the systems and methods of the present invention overlay the 1, 3, 6 mm ETDRS grids onto the 103 hexagons of the mfERG test report and correlate them for comprehensive analysis. Fig.14 Two superimposed images with the same center at the macula on the same retinal image are shown in FIG. The foveal area is within a 1 mm circular area and corresponds to rings 1 and 2 of the mfERG result (from 0° to 4°, Fig.14 The inner ring zone between 1 mm and 3 mm corresponds to ring 3 of the mfERG result (from 4° to 8°, Fig.14 The outer ring zone between 3 mm and 6 mm corresponds to ring 4 of the mfERG result (from 8° to 12°, Fig.14 The green part in the figure).

[0129] In certain embodiments, the method of the present invention correlates retinal structural and functional changes through comprehensive and detailed analysis of OCT thickness maps, OCTA vascular images, pERG and mfERG test reports. The correspondence is constructed by 1, 3, 6 mm ETDRS grids and 103 hexagonal grids with the fovea as the common center.

[0130] In some embodiments, the method of the present invention can collect a user's retinal images and retinal function reports, and output comprehensive evaluation results from the retinal structure, blood vessels and functions. Parameters from these three aspects can be associated through 1, 3, 6 mm ETDRS grids and 103 hexagonal divisions with the same center at the macula, such as Fig.14 shown.

[0131] In some embodiments, the comprehensive analysis module of the present invention can be incorporated into the SD-OCT clinical equipment, so that clinic staff can use the module more conveniently and improve the depth of analysis of retinal images. In a preferred embodiment, the comprehensive analysis module can directly quantify the structural and vascular parameters of the retina. When the clinic completes retinal imaging, there is no need for tedious image processing and quantification. The module can output quantitative results, which is convenient for clinicians to evaluate and analyze the images.

[0132] The present invention provides a comprehensive analysis system and method for imaging and functional biomarkers of aging retina. The method achieves a comprehensive analysis of the structural, vascular and functional characteristics of retinal ganglion cells by analyzing three different forms of data: a ganglion cell layer thickness map obtained based on optical coherence tomography (OCT), superficial vascular information obtained based on OCTA, and functional information obtained based on mfERG testing. This multimodal data analysis can not only analyze the characteristics of ganglion cells at the cellular level, but also provide non-invasive insights into the assessment of the health status of central nervous system neurons and aging mechanisms.

[0133] In addition, the present invention also provides examples of aging analysis of retinal imaging and functional changes to facilitate the identification of retinal imaging and functional biomarkers to achieve effective, quantitative and reliable evaluation, identification, assessment and intervention recommendations for the aging process.

[0134] Materials and methods

[0135] The following are examples illustrating procedures for practicing the present invention. These examples should not be construed as limiting. Unless otherwise indicated, all percentages are by weight and all solvent mixture ratios are by volume.

[0136] Example 1 - Method for quantitative OCT image analysis of ganglion cell distribution

[0137] The present invention uses the posterior pole module of SD-OCT to obtain OCT thickness maps of five different layers including NFL, GCL, IPL, NFL-IPL and GCL-IPL, and further applies the ETDRS grid to process and analyze the OCT thickness map. ETDRS includes circles with diameters of 1 mm, 3 mm and 6 mm respectively overlaid on the OCT thickness map to divide the map into 9 regions, such as Figure 2 As shown, C1 is the foveal area; S3, N3, I3, T3 are the inner ring upper, inner ring nose, inner ring lower and inner ring temporal areas of the inner ring area between 1mm and 3mm respectively; S6, N6, I6, T6 are the outer ring upper, outer ring nose, outer ring lower and outer ring temporal areas of the outer ring area between 3mm and 6mm respectively. The present invention cuts the original thickness map report output by the software to retain only the right half of the numerical data, as shown in Figure 3 and Figure 4 As shown in the figure, the OCR Space text extraction tool can correctly identify the average thickness and volume data of the 9 partitions on the image, extract and convert them into Excel files that can be used for data analysis. Then three different methods are used to conduct a comprehensive analysis of the extracted data.

[0138] The first analysis method divided the macular area into three zones: the inner circle zone was the foveal area within 1 mm; the inner annular zone was the annular zone between 1 mm and 3 mm circles (IA); and the outer annular zone was the annular zone between 3 mm and 6 mm circles (OA). In addition, the total annular zone was defined as the total area of ​​the inner annular zone and the outer annular zone (TA). Based on this partitioning method, the average thickness and volume data of the IA, OA, and TA zones in five different layers were extracted and analyzed.

[0139] The second analysis method divided the macular area into four areas, including S, N, I and T, which are the superior, nasal, inferior and temporal areas of the annular area between 1mm and 6mm. Based on this partitioning method, the average thickness and volume data of four areas in five different layers were extracted and analyzed.

[0140] The third analysis method divided the macular area into 8 areas: IS, IN, II, IT, which are the inner annular zone (annular zone between 1mm and 3mm circles), inner annular superior, inner annular nasal, inner annular inferior, and inner annular temporal areas; and OS, ON, OI, OT, which are the outer annular zone (annular zone between 3mm and 6mm), outer annular superior, outer annular nasal, outer annular inferior, and outer annular temporal areas. Based on this analysis method, the average thickness and volume data of the 8 areas in 5 different layers were extracted and analyzed.

[0141] The present invention defines a parameter named Area. The Area parameter represents the ratio of the area with a GCL thickness greater than 45 μm to the ETDRS 6 mm circle, which is a comprehensive indicator of the richness of ganglion cells. Figure 6 The process of extracting areas with a thickness greater than 45 μm and calculating the Area ratio is shown in Figure 2. The parameter Area is used as a comprehensive indicator of ganglion cell richness to provide valuable supplementary information for retinal structural analysis.

[0142] Example 2 - Method for quantitative OCTA image analysis of vascular properties

[0143] The present invention collects 3×3mm OCTA coronal superficial vascular plexus (SVP) and deep vascular plexus (DVP) images obtained from a SD-OCT machine with angiography module. As a trade-off strategy, the researchers selected a region of interest (ROI) with the following characteristics:

[0144] 1. The vascular area is larger, that is, it has a wider vascular coverage area.

[0145] 2. No loss of vascular details, that is, the detailed characteristics of the blood vessels can be retained without being over-simplified or blurred due to image processing.

[0146] Fig. 9 The ROI determined under this selection principle is shown, which is the area in a 2mm circle of the superficial vascular plexus image centered on the macula. By balancing the vascular area and detail preservation, this ROI helps to more comprehensively analyze the vascular structure characteristics in OCTA images.

[0147] Next, all vascular parameters, including the number of nodes, branch point abundance, fractal abundance, and length, diameter, and tortuosity of the vessels, were obtained by uploading all SVP and DVP images cropped into 2 mm circles to the OCTAVA toolbox, an OCTA vascular image analysis software developed based on ImageJ functions ( Untracht et al., 2021 ).

[0148] To further quantify the FAZ characteristics, the FAZ area index (FAI), FAZ perimeter index (FPI), and FAZ circularity index (FACI) are calculated based on a method provided by another HKU patent (Chiu, 2020). This method divides the vertices of the FAZ polygon into (a1, b1), (a2, b2), …, (a n ,b n ). This procedure uses the shoelace formula to calculate the area of ​​the polygon:

[0149]

[0150] As explained, the process also defines FAI as the FAZ polygon area divided by the pixel area of ​​the vessel image. The FAI is comparable between images of different sizes, and the vessel image is always focused on a 3×3 area.

[0151] The procedure calculates the FAZ Circumference Index (FPI) using the following formula:

[0152]

[0153] The procedure defines the FPI as the perimeter of the FAZ polygon divided by the side length of the vessel image in pixels. The FPI is comparable between images of different sizes, and the vessel image is always focused on a 3×3 region.

[0154] The present invention also calculates the FAZ roundness index (FACI). FACI is used to quantify the irregularity of the shape of the divided FAZ and is calculated by the following formula:

[0155]

[0156] When FACI is equal to 1, the FAZ is a perfect circle, and when the FACI value is greater than 1, the FAZ has a more irregular shape.

[0157] Example 3 - Methods for quantitative ERG reporter analysis of retinal function

[0158] The present invention uses the Reti-Port / scan 21ERG machine to obtain pERG reports and mfERG reports. To ensure accuracy, the pERG test is repeated twice for 48 minutes for each eye without dilation of the pupil, and the mfERG test is performed on each eye. The test resolution of the mfERG is 103 hexagons, and two 50Hz smoothing filters are applied. During the test, corneal contact electrodes (BA / ERG-Jet) and gold foil electrodes are used for both the pERG test and the mfERG test.

[0159] The present invention uses the text extraction method provided by OCR Space to organize and prepare all useful ERG test data for subsequent analysis and comparison. The text extraction method provided by OCR Space is an online image processing method that can recognize and extract numbers or strings from images and convert them into analyzable formats such as text or JSON. Fig.11An exemplary use of OCR Space is shown in Figure 1, including uploading an mfERG report and extracting all useful data (amplitude and latency of P1 and N1 within 6 rings and amplitude and latency of P1 and N1 in 4 quadrants). The present invention also extracts the latency of N35, P50 and N95 and the amplitude of P50 and N95 from the pERG 48-minute test report. Through the automated OCR Space text extraction method, all useful ERG test data are organized and ready for subsequent analysis and comparison.

[0160] Example 4 - Methods for integrated analysis of both retinal imaging and functional biomarkers

[0161] The present invention associates retinal structure with functional changes through comprehensive analysis of OCT thickness maps, OCTA vascular images, pERG and mfERG test reports. Centered on the macula, 1, 3, 6mm ETDRS grids are used to spatially align OCT and ERG data to establish a corresponding relationship. The process superimposes 1, 3, 6mm ETDRS grids on 103 hexagons of the mfERG test report, and spatially aligns the results for comprehensive analysis. The foveal area is within the 1mm circular area and corresponds to rings 1 and 2 (0° to 4°) of the mfERG result. The inner ring zone of the inner circle area between the 1mm and 3mm circles corresponds to ring 3 (from 4° to 8°) of the mfERG result. The outer ring zone of the outer circle area between the 3mm and 6mm circles corresponds to ring 4 (from 8° to 12°) of the mfERG result. Fig.14 Schematic diagram of two superimposed images on the same macular area.

[0162] Example 5 - Measurement of retinal imaging and integrated analysis modules for functional biomarkers

[0163] By comprehensively utilizing the above methods, the present invention has determined a series of reliable retinal structural and functional biomarkers, including the average thickness and volume of different regions of 5 different layers (NFL, GCL, IPL, NFL-IPL, GCL-IPL); vascular parameters include the number of vascular nodes, vascular area abundance, branch point abundance, fractal abundance, as well as vascular length, vascular diameter and vascular tortuosity; functional parameters include P50 and N95 latency and amplitude in the pERG test report, and P1 and N1 latency and amplitude in different regions in the mfERG test report. In order to verify the effectiveness of these biomarkers, the present invention comprehensively analyzed 42 OCT thickness maps, 42 OCTA vascular images, 44 pERG reports and 20 mfERG report results from 42 healthy subjects. All OCT thickness maps were obtained from OCT structural scans at the macular area using SD-OCT equipped with an angiography module with an 815nm IR laser and a 30-degree lens. All OCT superficial / deep vascular plexuses used were from OCTA scans performed across the macular area within a range of 10°×10° (3mm×3mm). In addition, all ERG tests including pERG tests and mfERG tests were performed using RETI-port / scan 21. The methods of the present invention were used to detect different biomarkers representing the overall retinal neuronal properties at the macular area. The participants were divided into two age groups. The young group was 22 to 32 years old, including data from 22 eyes from 11 participants, with an average age of 25.45 and a standard deviation of 3.52. The elderly group was 50 to 62 years old, including 15 eyes from 9 participants, with an average age of 54.20 and a standard deviation of 3.91. Summary of the Invention Statistics were generated for different retinal biomarkers (for each subject's eye, thickness maps of different layers (NFL, GCL, IPL), SVP images, and pERG and mfERG reports were collected), a two-tailed independent sample t-test was performed between the two age groups, and a Pearson correlation test with a 95% confidence interval level was performed, and a two-tailed p-value was calculated.

[0164] The results of the comprehensive analysis using the systems and methods of the present invention can be seen in the following examples. In Example 6, many of the defined parameters are significantly correlated with age and can be used as biomarkers for assessing the characteristic changes of the retina as a person ages and for analyzing CNS neuronal health. As shown in Example 7, the comprehensive analysis can also facilitate a deeper understanding of the underlying biological mechanisms of retinal aging changes.

[0165] Example 6 - Computational Retinal Imaging and Functional Biomarkers

[0166] In order to evaluate the validity of the defined retinal structures and parameters, the present invention used SPSS to perform a two-tailed independent sample t-test to evaluate the changes in retinal structure and function parameters between the two age groups. For OCT thickness map analysis, Pearson bivariate correlation tests were performed between the age groups and the average thickness and volume data of NFL, GCL, IPL, NFL-IPL, and GCL-IPL, respectively. For detailed analysis, the present invention overlaid ETDRS grids with diameters of 1 mm, 3 mm, and 6 mm on the OCT thickness map and divided it into 9 areas (such as Figure 2 As shown). For the thickness maps of 5 different layers, the method of the present invention provides 3 division methods for the area within the ETDRS grid (refer to Example 1). The analysis results can be seen in the table below. Asterisks (*) indicate significant differences between the two age groups. One star (*) indicates p<0.05, and two stars (**) indicate p<0.01.

[0167] The analysis results of the changes in OCT thickness and volume parameters are shown in Figure 2. Fig. 20 , Fig.21 ,and Fig. 22 The present invention uses three different retinal area division methods to compare the differences in structural parameters between the elderly group and the young group. When using division method 1, from Fig. 20 It can be seen that the NFL thickness of the elderly group increased significantly in the inner annular zone; the GCL thickness of the elderly group decreased significantly in the outer annular zone and the total annular zone; the NFL-IPL thickness of the elderly group decreased significantly in the outer annular zone. Fig.21 It can be seen that the NFL thickness of the elderly group increased significantly in the total temporal area; the GCL thickness of the elderly group decreased significantly in the total upper area, total lower area, and total temporal area; the NFL volume of the elderly group increased significantly in the total temporal area; the GCL volume of the elderly group decreased significantly in the total upper and total lower areas; the NFL-IPL volume of the elderly group decreased significantly in the total upper area. Fig. 22 It can be seen that the NFL thickness of the elderly group increased significantly in the inner annular nasal, inner annular temporal and outer annular temporal areas; the GCL thickness of the elderly group decreased significantly in the inner annular temporal and outer annular inferior areas; the NFL-IPL thickness of the elderly group decreased significantly in the outer annular inferior area; the GCL-IPL thickness of the elderly group decreased significantly in the outer annular inferior area; the NFL volume of the elderly group increased significantly in the inner annular temporal area and the outer annular temporal area; the GCL volume of the elderly group decreased significantly in the inner annular superior area and the outer annular inferior area.

[0168] The analysis results of OCTA vascular parameter changes are as follows Fig.23As shown. In order to verify the validity of the defined retinal vascular parameters, the present invention uses an independent sample t-test to compare the differences in vascular parameters between different age groups. The vascular parameters analyzed include general parameters such as vascular area abundance (VAD) and vascular length abundance (VLD). In addition, the corresponding total / mean / median / variance of vascular length, diameter and tortuosity are included. As can be seen from the figure, VAD and VLD, which represent vascular abundance, are significantly reduced in the elderly group. In addition, the total vascular length of the elderly group was significantly reduced, while the mean and median of vascular diameter and the mean of vascular tortuosity were significantly increased.

[0169] The analysis results of the changes in retinal function parameters are shown in Tables 1A-1C. In order to verify the validity of the defined retinal function parameters, the present invention uses an independent sample t-test to compare the differences in function parameters between different age groups. The analyzed function parameters include the average amplitude and latency of P1 and N1 in different areas obtained according to the two different partitioning methods (4-quadrant partitioning method and 6-ring partitioning method) described in Example 3. It can be seen that the latency of P1 in the elderly group increased significantly in quadrants 3 and 4 (4-quadrant partitioning method) and rings 4 and 5 (6-ring partitioning method), and the latency of N1 also increased significantly in quadrant 1 (4-quadrant partitioning method) and ring 3 (6-ring partitioning method).

[0170] Table 1A Differences in mean values ​​of functional parameters (pERG) between different age groups

[0171]

[0172] Table 1B Differences in mean values ​​of functional parameters (mfERG 4 quadrants) between different age groups

[0173]

[0174]

[0175] Table 1C Differences in mean values ​​of functional parameters (mfERG 6 loops) between different age groups

[0176]

[0177]

[0178]

[0179] The results of the combined OCT thickness map analysis and mfERG report analysis showed that they were well correlated. Fig.14 , yellow area), the NFL thickness of the elderly group increased significantly, and the N1 latency of the elderly group also increased significantly. Fig.14 , green area), the thickness of GCL and NFL-IPL in the elderly group was significantly reduced, and the P1 latency in the elderly group was also significantly increased.

[0180] The present invention also performed a Pearson correlation test on the retinal structure and function parameters and age, and used SPSS to calculate the two-tailed p value with a 95% confidence interval. The retinal structure parameters included the average thickness and volume of the NFL, GCL, IPL, NFL-IPL, and GCL-IPL in different areas obtained using three different division methods.

[0181] Take the third division method (8 regions) as an example. As shown in Tables 2A and 2B, within the inner ring region with a radius of 1 mm and 3 mm, the average thickness of the nasal, lower, and temporal regions of the NFL in the elderly group and the volume of the temporal region of the NFL increased significantly. There were no significant changes in other regions of other layers within the inner ring region. Within the outer ring region between 3 mm and 6 mm, the average thickness and volume of the temporal region of the NFL in the elderly group increased significantly. In addition, the average thickness of the nasal, lower and temporal regions of the GCL in the elderly group and the volume of the lower region were significantly reduced. The average thickness of the upper, nasal and lower regions of the NFL-IPL in the elderly group and the volume of the upper and nasal regions were significantly reduced. The average thickness of the lower region of the GCL-IPL in the elderly group was significantly reduced. There were no significant changes in other regions of other layers within the outer ring region.

[0182] In addition, the present invention defines an Area parameter, which represents the ratio of the area with a thickness greater than 45 μm on the GCL thickness map to the area of ​​the 6 mm circle of the ETDRS grid. A two-tailed independent sample t-test was used to find that there was a significant difference in the Area value between the two age groups (p=0.032*). Further Pearson bivariate correlation test showed that the Area value decreased significantly with age, as shown in Table 2C, which verified the validity of the custom parameter.

[0183] Table 2A Pearson correlation results between structural parameters (inner 3 mm circle) and age

[0184]

[0185]

[0186]

[0187] Table 2B Pearson correlation results between structural parameters (outer 6mm circle) and age

[0188]

[0189]

[0190]

[0191] Table 2 Pearson correlation results between structural parameters (area) and age

[0192]

[0193] In order to verify the validity of the defined retinal vascular biomarkers, Pearson bivariate correlation tests were performed between age and vascular parameters. The vascular parameters include general parameters such as the number of nodes, microvascular area abundance, branch point abundance, and fractal abundance. In addition, the corresponding mean, median, variance, skewness, and kurtosis of vascular length, diameter, and tortuosity are also included. As shown in Table 3, all general parameters representing microvascular abundance decreased significantly with age. Other vascular parameters including total vascular length, vascular length abundance, and average vascular length also decreased significantly with age. In addition, the mean and median of vascular diameter and the mean of vascular tortuosity also increased significantly with age.

[0194] Table 3 Pearson correlation results between vascular parameters and age

[0195]

[0196] In order to evaluate the validity of the defined retinal function biomarkers, the present invention performs a Pearson bivariate correlation test between age and pERG parameters (including N35, P50, N95 latency and N35-P50, P50-N95 amplitude) for pERG report results. As shown in Table 4A, with increasing age, the latency of P50 is significantly reduced, and the amplitude of P50-N95 is significantly reduced. Due to the relatively small sample size, the results may not be accurate.

[0197] However, even with a small number of participants the validity of functional biomarkers has been demonstrated.

[0198] Table 4A Pearson correlation results between functional parameters (pERG) and age

[0199]

[0200] In order to evaluate the validity of the defined retinal functional biomarkers, the present invention performs a Pearson bivariate correlation test between age and mfERG parameters (including the latency and amplitude of P1 and N1) for the 103mfERG report results. The 103mfERG test refers to a test that uses 103 hexagonal stimulation areas in the center of the macula to obtain electrophysiological responses in different areas of the retina. Specifically, the present invention provides 2 analysis methods for the report results of the 103mfERG test, which divide the 103 hexagons into 4 quadrants or 6 concentric rings, respectively.

[0201] The first analysis method divides the 103 hexagons into 4 quadrants, such as Fig.13A As shown. In each quadrant, the average electrical waveform was generated by the software. Based on the waveform, the amplitude of P1 and N1 and the latency data of P1 and N1 were obtained. Pearson bivariate correlation test was performed between age and the latency and amplitude of P1 and N1 in each quadrant. As shown in Table 5A, for quadrant 1, the latency of P1 and N1 increased significantly with increasing age; for quadrants 2 and 4, the latency of P1 increased significantly with increasing age; for quadrants 3, there was no significant change in retinal function parameters with increasing age.

[0202] The second analysis method divides the 103 hexagons into 6 concentric and equidistant rings around the fovea, such as Fig. 13B As shown in Table 5B. The range of each ring is as follows: Ring 1 is 0° to 1°; Ring 2 is 1° to 4°; Ring 3 is 4° to 8°; Ring 4 is 8° to 12°; Ring 5 is 12° to 17°; Ring 6 is 17° to 21°. For each ring, an average electrical waveform was generated by the software. Based on the waveform, the amplitude of P1 and N1 and the latency data of P1 and N1 were obtained. Pearson bivariate correlation test was performed between age and the latency and amplitude of P1 and N1 within each ring. As shown in Table 5B, for rings 1 and 2, there was no significant change in retinal function with increasing age; for ring 3, the latency of P1 and N1 increased significantly with increasing age; for rings 4 and 5, the latency of P1 increased significantly with increasing age; for ring 6, the latency of N1 increased significantly with increasing age.

[0203] Table 5A Pearson correlation results between functional parameters (mfERG 4 quadrants) and age

[0204]

[0205] Table 5B Pearson correlation results between functional parameters (mfERG 6 loops) and age

[0206]

[0207] Example 7 - Methods for explaining comprehensive analysis

[0208] As demonstrated in Example 6, many retinal imaging and functional characteristics have changed significantly with age, especially in the outer circular area of ​​the macula. As discussed in Example 5, a comprehensive analysis can be performed by applying two different grid overlays (ETDRS grid and 103 hexagons) to the same macula area centered on the fovea. The results of Example 6 are discussed below. The area within the innermost 1 mm circle of the EDTRS grid corresponds to 0 to 4 degrees on the mfERG report, i.e., the red area. The inner annulus (the area between the 1 mm and 3 mm circles) corresponds to 4 to 8 degrees, i.e., the yellow area. The outer annulus (the area between the 3 mm and 6 mm circles) corresponds to 8 to 12 degrees, i.e., the green area. The analysis results show that within the inner annulus (ring 3), the NFL thickness increases significantly with age, and it is in this area that the latency of N1 and P1 increases significantly with age. In the outer annulus (ring 4), the GCL thickness decreases significantly with age, and in this area, the latency of P1 increases significantly with age. In the circular area with a diameter of 2 mm centered on the fovea, the vascular abundance decreased significantly with age, and the vascular tortuosity also increased significantly with age. There were no significant age-related retinal changes within the 1 mm circle of the ETDRS grid because there were no vascular structures in this area. Based on the above findings, we proposed the following hypothesis about the potential biological mechanisms of retinal changes that occur during aging: As the central nervous system ages, the vascular abundance of the retina decreases sharply, and the vascular tortuosity values ​​increase sharply, indicating rapid vascular hardening. Due to these vascular changes, the oxygen supply capacity of the blood vessels decreases, and the retinal ganglion cells that rely on vascular nutrition supply begin to apoptosis due to insufficient nutrition. Ultimately, because fewer ganglion cells transmit information from the retina to the brain, retinal function also deteriorates. These findings reveal the potential mechanism of changes in the retina during the aging of the human central nervous system. Among them, ganglion cells, as projection neurons of the vertebrate retina, are responsible for transmitting information from other retinal neurons to the brain. Their loss can be used as an indicator of neuronal loss occurring in the central nervous system, providing a basis for timely intervention.

[0209] Example 8 - Algorithms and methods for image processing using OPENCV and SHAPELY in Python

[0210]

[0211]

[0212]

[0213]

[0214]

[0215]

[0216]

[0217] All patents, patent applications, provisional applications, and publications mentioned or cited herein are incorporated by reference in their entirety, including all figures and tables, to the extent they are not inconsistent with the explicit teachings of this specification.

[0218] It should be understood that the examples and embodiments described herein are for illustrative purposes only, and that those skilled in the art will suggest various modifications or changes thereto, and that these modifications or changes are included within the spirit and scope of the present application. In addition, any element or limitation of any invention or embodiment thereof disclosed herein may be combined with any and / or all other elements or limitations disclosed herein (alone or in any combination) or any other invention or embodiment thereof, and all such combinations are within the scope of the present invention without limitation thereto.

[0219] References

[0220] Quiroz, JA, & Manji, HK (2002). Enhancing synaptic plasticity and cellular resilience to develop novel, improved treatments for mood disorders. Dialogues in Clinical Neuroscience, 4(1), 73-92. https: / / doi.Org / 10.31887 / dcns.2002.4.1 / jquiroz

[0221] Costa,RA,Skaf,M.,Melo Jr,LA,Calucci,D.,Cardillo,JA,Castro,JC,Huang,D.,&Wojtkowski,M.(2006).Retinal assessment using optical coherencetomography.Progress in retinal and eye research,25(3),325-353.https: / / doi.org / 10.1016Zj.preteyeres.2006.03.001

[0222] Le, P.H., Patel, B.C. (2020). Optical Coherence Tomography Angiography. StatPearls Publishing, Treasure Island (FL); PMID: 33085382.

[0223] Fingler, J., Readhead, C., Schwartz, D.M., & Fraser, S.E. (2008). Phase-contrast OCT imaging of transverse flows in the mouse retina and choroid. Investigative ophthalmology & visual science, 49(11), 5055 - 5059. https: / / doi.org / 10.1167 / iovs.07 - 1627

[0224] Why is Electroretinography Important? LKC Technologies. (2023, January 31). Retrieved March 27, 2023, from https: / / lkc.com / applications / electroretinography - erg - explained /

[0225] Marshak, D.W. (2009). Retinal Ganglion Cells: Anatomy. In Squire, L.R. (Ed.), Encyclopedia of Neuroscience (pp. 211 - 218). Academic Press. https: / / doi.org / 10.1016 / B978 - 008045046 - 9.00897 - 4

[0226] Badwaik,K.,Mahmood,K.,&Raza,A.(2017).Towards applying OCR andSemantic Web to achieve optimal learning experience.2017IEEE 13thInternational Symposium on Autonomous Decentralized System(ISADS),262-267.https: / / doi.org / 10.1109 / ISADS.2017.40

[0227] Untracht,G.R.,Matos,R.S.,Dikaios,N.,Bapir,M.,Durrani,A.K.,Butsabong,T.,Campagnolo,P.,Sampson,D.D.,Heiss,C.,Sampson,D.M.(2021).OCTAVA:An open-source toolbox for quantitative analysis of optical coherence tomographyangiography images.PLoS ONE,16(12),e0261052.https: / / doi.org / 10.1371 / journal.pone.0261052

[0228] Chiu,K.(2Q20).Methods for automated cloud-based quantitativeassessment of retinal microvasculature using optical coherence tomographyangiography images(H.K.Patent No.63066568).UHK.264P.

[0229] Shiihara,H.,Terasaki,H.,Sonoda,S.,Kakiuchi,N.,Shinohara,Y.,Tomita,M.,&Sakamoto,T.(2017).Objective evaluation of size and shape of superficialfoveal avascular zone in normal subjects by optical coherence tomographyangiography.Scientific Reports,7(1),9853.https: / / doi.org / 10.1038 / s41598-018-28530-7

[0230] Li,Y.K.,Fung,N.S.-K.,Chan,J.C.H.,Choy,B.N.K.,Chow,L.L.W.,Shih,K.C.,Wong,J.K.W.,&Wong,I.Y.H.(2023).OCTA biomarkers in adults aged 50 and above:Aprospective and cross-sectional community-based study.BMC Ophthalmology,23(1),71.

[0231] https: / / doi.org / 10.1186 / s12886-023-02815-6

[0232] Liu,X.,Lai,S.,Ma,S.,Yang,H.,Liu,L.,Yu,G.,Zhong,S.,Jia,Y.,&Zhong,J.(2022).Development of a Novel Retina-Based Diagnostic Score for EarlyDetection of Major Depressive Disorder:An Interdisciplinary View.Frontiers inpsychiatry,13,897759.https: / / doi.org / 10.3389 / fpsyt.2022.897759

[0233] Hart,N.J.,Koronyo,Y.,Black,K.L.,&Koronyo-Hamaoui,M.(2016).Ocularindicators of Alzheimer's:exploring disease in the retina.Actaneuropathological,132(6), https: / / doi.org / 10.1007 / s00401-016-1613-6

[0234] MacGillivray,T.J.,Trucco,E.,Cameron,J.R.,Dhillon,B.,Houston,J.G.,&vanBeek,E.J.(2014).Retinal imaging as a source of biomarkers for diagnosis,characterization and prognosis of chronic illness or long-term conditions.TheBritish journal of radiology,87(1040),20130832.https: / / doi.org / 10.1259 / bjr.20130832

[0235] Hui,J.,Zhao,Y.,Yu,S.,Liu,J.,Chiu,K.,&Wang,Y.(2021).Detection ofretinal changes with optical coherence tomography angiography in mildcognitive impairment and Alzheimer’s disease patients:A meta-analysis.PLOSONE,

[0236] 16(8).https: / / doi.org / 10.1371 / journal.pone.0255362

[0237] Lopez-de-Eguileta, A., Lopez-Garcia, S., Lage, C., Pozueta, A., Garcia-Martinez, M., Kazimierczak, M., Bravo, M., Irure, J., Lopez-Hoyos, M., Munoz-Cac ho,P.,Rodriguez-Perez,N.,Tordesillas-Gutierrez,D.,Goikoetxea,A.,Nebot,C.,Rodriguez-Rodriguez,E.,Casado,A.,10&Sanchez-Juan,P.(2022).The Retinal ganglion cell layer reflects neurodegenerative changes in cognitively unimpairedindividuals.Alzheimer's Research&Therapy,14(1),1-13

[0238] Yoon,SP,Grewal,DS,Thompson,AC,Polascik,BW,Dunn,C.,Burke,JR,&Fekrat,15 S.(2019).Retinal microvascular and neurodegenerative changesin Alzheimer's disease and mild cognitive impairment compared with controlparticipants.Ophthalmology Retina,3(6), 489-499

[0239] Zhang,M.,Zhong,L.,Han,X.,Xiong,G.,Xu,D.,Zhang,S.,Cheng,H.,Chiu,K.,&Xu,Y.20(2021).Brain and retinal abnormalities in the 5xFAD mouse model ofAlzheimer’s disease at early stages.Frontiers in Neuroscience,15,681831.https: / / doi.org / 10.3389 / fnins.2021.681831

[0240] Georgevsky,D.,Retsas,S.,Raoufi,N.,Shimoni,O.,&Golzan,S.M.(2019).Alongitudinal assessment of retinal function and structure in the APP / PS1transgenic mouse model of 25 Alzheimer’s disease.TranslationalNeurodegeneration,8(30).https: / / doi.org / 10.1186 / s40035-019-0170-z

Claims

1. An integrated analysis method for multimodal retinal ganglion cell (RGC) data for marking central nervous system cell aging, the method comprising: applying an Early Treatment Diabetic Retinopathy Study (ETDRS) grid to a macular plan view reconstructed from an optical coherence tomography (OCT) thickness map to divide the macular plan view into a plurality of regions, wherein the OCT thickness map includes data values ​​for thickness and volume of five different retinal layers, wherein the five different retinal layers include a nerve fiber layer (NFL), a ganglion cell layer (GCL), an inner plexiform layer (IPL), a nerve fiber layer to an inner plexiform layer (NFL-IPL), and a ganglion cell layer to an inner plexiform layer (GCL-IPL); grouping the plurality of regions and determining average thickness and volume data for each region of the five different layers; Optical tomographic angiography (OCTA) was recorded using the posterior pole module and finely sliced ​​to obtain retinal microvascular changes of the OCTA; Obtain a graphic electroretinogram (pERG) report that includes analysis of N35, P50, and N95 latencies and P50 and N95 amplitudes; Obtaining a multifocal electroretinogram (mfERG) report of 103 hexagons of the ETDRS grid with the same center at the macula, the mfERG report includes analysis of the latency of P1 and N1 and the amplitude of P1 and N1; and The presence or absence of RGC aging was identified based on the average thickness and volume data of each area in the five different layers of the OCT thickness map, the retinal microvascular changes of the OCTA, the latencies of N35, P50, and N95 and the amplitudes of P50 and N95 in the pERG report, and the latencies of P1 and N1 and the amplitudes of P1 and N1 in the mfERG report.

2. The method according to claim 1, further comprising: The posterior pole module was used to record the plan view of the macular area reconstructed from the OCT thickness map.

3. The method according to claim 1, wherein: Dividing the macular area plane view into a plurality of regions comprises: dividing the macular area plane view into eight regions, the eight regions comprising an inner ring superior, an inner ring nasal, an inner ring inferior, an inner ring temporal, an outer ring superior, an outer ring nasal, an outer ring inferior, and an outer ring temporal region; and Grouping the plurality of regions comprises: The macular areas are grouped to form 3 annular zones including: the fovea within 1 mm in diameter; an inner annulus between 1 mm and 3 mm in diameter; and an outer annulus between 3 mm and 6 mm in diameter, or, Group the macular areas to form 4 zones including: superior, nasal, inferior, and temporal zones in annular areas between 1 mm and 6 mm, or The macular areas were grouped to form 8 regions including: the inner annular superior, inner annular nasal, inner annular inferior, and inner annular temporal regions with diameters between 1 mm and 3 mm and the outer annular superior, outer annular nasal, outer annular inferior, and outer annular temporal regions with diameters between 3 mm and 6 mm.

4. The method of claim 3, wherein grouping the macular area to form three regions, determining the thickness and volume data of each region of the five different layers comprises: Calculate the average thickness and volume of the inner annular zone area of ​​the five different layers; Calculate the average thickness and volume of the outer annular zone areas of the five different layers; as well as The average thickness and volume of the total annulus, which is the combined area of ​​the inner annulus area and the outer annulus area, is calculated.

5. The method of claim 3, wherein grouping the macular regions to form four regions, determining the thickness and volume data of each region of the five different layers comprises: Calculating the average thickness and volume of the total upper area, the total upper area being the combined area of ​​the inner annular upper area and the outer annular upper area; Calculating the average thickness and volume of the total nose area, the total nose area being the combined area of ​​the inner and outer nose ring areas; Calculating the average thickness and volume of the total lower area, the total lower area being the combined area of ​​the inner lower ring area and the outer lower ring area; as well as The mean thickness and volume of the total temporal area, which is the combined area of ​​the inner and outer annular temporal areas, were calculated.

6. The method of claim 3, wherein grouping the macular regions to form eight regions, determining the thickness and volume data of each region of the five different layers comprises: The average thickness and volume of the inner ring supraregion, inner ring nasal region, inner ring subregion, and inner ring temporal region were calculated in five different layers; as well as The average thickness and volume of the outer annular supraregion, outer annular nasal region, outer annular inferior region, and outer annular temporal region were calculated in five different layers.

7. The method according to claim 1, further comprising: Extracting a region with a thickness greater than 45 μm from the OCT thickness map and calculating the area of ​​the region by an image processing method; Extracting a region within a 6 mm circle from the ETDRS grid and calculating the area of ​​the region by an image processing method; Determining a parameter Area based on the ratio of the area of ​​the region with a thickness greater than 45 μm in the OCT thickness map to the area within a 6 mm circle of the ETDRS grid, wherein the parameter Area is used as a comprehensive indicator of ganglion cell abundance; Whether or not RGC aging exists is determined based on the parameter Area.

8. The method according to claim 1, wherein recording optical tomographic angiography (OCTA) using a posterior pole module and finely stratifying to obtain retinal microvascular changes of the OCTA further comprises: Acquire OCTA vascular image data; The area within the circle with a diameter of 2 mm centered on the macula was extracted as the region of interest (ROI) and this area of ​​the image was cropped; calculating vessel abundance, vessel length, vessel diameter, and vessel tortuosity by applying the OCTAVA method to the ROI; and Calculate the foveal avascular zone (FAZ) parameters, including the FAZ area index and the FAZ circularity index; Identifying whether RGCs are aged based on retinal microvascular changes based on OCTA also includes: The presence or absence of RCG aging was determined based on vessel abundance, vessel length, vessel diameter, and vessel tortuosity as well as foveal avascular zone (FAZ) parameters.

9. The method according to claim 1, wherein: Get a pERG report that also includes: Perform 48-minute pERG test twice and obtain pERG report; and Extracting N35, P50 and N95 latency and P50 and N95 amplitude data from the pERG report by OCR Space text extraction method; The presence or absence of RGC aging was determined based on the latencies of N35, P50, and N95, and the amplitudes of P50 and N95.

10. The method according to claim 1, wherein: Obtaining an mfERG report includes: Perform mfERG test and obtain mfERG report; Divide the 103 hexagons into four different regions / quadrants with one horizontal line and one vertical line, and calculate the average latency and amplitude of P1 and N1 in the four different quadrants, and / or The 103 hexagons were divided into six equally spaced concentric annular regions around the central disk, and the average latency and amplitude of P1 and N1 were calculated for the six different annular regions.

11. A computer program product comprising: A non-transitory computer executable storage device having computer readable program instructions thereon, wherein when the computer readable program instructions are executed by a computer, the computer is caused to perform an integrated analysis method of multimodal retinal ganglion cell (RGC) data for marking central nervous system aging as described in any one of claims 1-10.

12. An integrated analysis device for multimodal retinal ganglion cell (RGC) data for marking central nervous system aging, comprising at least one processor configured to execute the method of any one of claims 1-10.

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