July 2019
Volume 60, Issue 8
Open Access
Retina  |   July 2019
Photoreceptor Degeneration is Correlated With the Deterioration of Macular Retinal Sensitivity in High Myopia
Author Affiliations & Notes
  • Yuanyuan Wang
    School of Ophthalmology and Optometry, Wenzhou Medical University, Wenzhou, Zhejiang, China
  • Jie Ye
    School of Ophthalmology and Optometry, Wenzhou Medical University, Wenzhou, Zhejiang, China
  • Meixiao Shen
    School of Ophthalmology and Optometry, Wenzhou Medical University, Wenzhou, Zhejiang, China
  • Aixia Yao
    School of Ophthalmology and Optometry, Wenzhou Medical University, Wenzhou, Zhejiang, China
  • Anquan Xue
    School of Ophthalmology and Optometry, Wenzhou Medical University, Wenzhou, Zhejiang, China
  • Yuchen Fan
    School of Ophthalmology and Optometry, Wenzhou Medical University, Wenzhou, Zhejiang, China
  • Shenghai Huang
    School of Ophthalmology and Optometry, Wenzhou Medical University, Wenzhou, Zhejiang, China
  • Jianhua Wang
    Department of Ophthalmology, Bascom Palmer Eye Institute, University of Miami, Miami, Florida, United States
  • Fan Lu
    School of Ophthalmology and Optometry, Wenzhou Medical University, Wenzhou, Zhejiang, China
  • Yilei Shao
    School of Ophthalmology and Optometry, Wenzhou Medical University, Wenzhou, Zhejiang, China
  • Correspondence: Yilei Shao, School of Ophthalmology and Optometry, Wenzhou Medical University, 270 Xueyuan Road, Wenzhou, Zhejiang 325027, China; magic_shao@163.com
  • Fan Lu, School of Ophthalmology and Optometry, Wenzhou Medical University, 270 Xueyuan Road, Wenzhou, Zhejiang 325027, China; lufan62@mail.eye.ac.cn
  • Footnotes
     YW and JY contributed equally to the work presented here and should therefore be regarded as equivalent authors.
Investigative Ophthalmology & Visual Science July 2019, Vol.60, 2800-2810. doi:10.1167/iovs.18-26085
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      Yuanyuan Wang, Jie Ye, Meixiao Shen, Aixia Yao, Anquan Xue, Yuchen Fan, Shenghai Huang, Jianhua Wang, Fan Lu, Yilei Shao; Photoreceptor Degeneration is Correlated With the Deterioration of Macular Retinal Sensitivity in High Myopia. Invest. Ophthalmol. Vis. Sci. 2019;60(8):2800-2810. doi: 10.1167/iovs.18-26085.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Purpose: To investigate structural changes in the retinal outer layers and choroid using adaptive optics (AO) and optical coherence tomography (OCT) in eyes with myopia, and to correlate the changes with decreased macular light sensitivity (MLS).

Methods: This prospective study included 27 subjects with emmetropia and low myopia (EM/LM), 25 with moderate myopia (MM), and 25 with high myopia (HM). Microperimetry was used to quantify MLS in each subject, while AO and OCT images of fundus were analyzed to quantify cone density and regularity and thickness of outer retinal sublayers and choroid. Differences of MLS, cone distribution, and chorioretinal thicknesses were compared among the three groups, and the associations among photoreceptor morphological alterations, MLS, and other parameters were analyzed.

Results: In HM, the MLS, cone density and regularity, and thicknesses of the myoid and ellipsoid zone (MEZ), Henle fiber layer and outer nuclear layer, interdigitation zone and RPE/Bruch complex, and choroid were lower than in EM/LM. Decreased MLS was correlated with lower cone density and regularity, and thinner MEZ and choroid in the inner region, and with lower cone density, thinner MEZ and choroid, and longer axial length in the outer region. Multivariate regression showed that better MLS was correlated with thicker MEZ in the inner region and with higher cone density in the outer region.

Conclusions: Altered cone distribution and outer retinal thickness, especially cone density and MEZ thickness, were significantly correlated with decline of MLS in HM, which may help to evaluate and monitor visual impairment in HM.

High myopia (HM) is one of the leading causes of visual impairment worldwide, particularly in Asia.13 Holden et al.4 estimated that 49.7% of the world population has myopia, and 9.8% will have HM in 2050. The pathological changes resulting from HM are one of the main causes of serious visual impairment, even blindness, that occurs in 12.2% to 31.3% in East Asian countries, such as China, Singapore, and Japan.5 Therefore, HM is a global health burden that urgently needs to be addressed. 
Photoreceptor morphological and functional degeneration in myopia has been reported in previous studies613 and was hypothesized to be the main reason for visual impairment.6 For instance, ERG examinations have documented decreasing b-wave amplitudes in myopic eyes, indicating photoreceptor dysfunction.7 Histologic studies also have highlighted alterations of photoreceptors in myopia models.8,9 Moreover, significant degeneration of choroidal perfusion occurs in high myopia, causing ischemia and reduced nutrition of the outer retina, which may lead to photoreceptor dysfunction.11,12 However, analyzing the impact of HM on photoreceptors and visual function has remained elusive, mainly because of technical difficulties. 
The development of high-resolution imaging techniques, such as adaptive optics (AO) and optical coherence tomography (OCT), has enabled noninvasive imaging and in vivo analysis of retinal structure.10,1316 In previous studies of HM, decreased cone packing density was assessed with AO,10,15 and thinning of the outer retinal thickness was measured with OCT.13,14,16 In the current study, we used both imaging modalities in myopia eyes to assess photoreceptor morphological alterations. The associations in myopia between macular light sensitivity (MLS), photoreceptor morphology, choroidal thickness, axial length (AL), and other variables were further analyzed to estimate visual function from the fundus structural information acquired by AO and OCT. 
Methods
Subjects
Seventy-seven subjects between the ages of 18 and 35 years were recruited from Wenzhou Medical University from May 2017 to August 2018. This project was approved by the Ethics Committee of Wenzhou Medical University, and written consent was obtained from all subjects after they were informed about the benefits, risks, and possible adverse consequences of the procedures. The research was performed in compliance with the tenets of the Declaration of Helsinki. 
All enrolled subjects underwent a comprehensive ophthalmic examination, including refraction error (noncycloplegic), best corrected visual acuity (BCVA), IOP (by the Full Auto Tonometer TX-F; Topcon, Tokyo, Japan), AL measurement (IOL Master 500; IOLMaster; Carl Zeiss Meditec, Dublin, CA, USA), and fundus photography (Canon EOS 10 SLR backing; Canon, Inc., Tokyo, Japan). Only the right eye of each subject was included for data analysis in this study. None of the subjects had any ocular pathology, history of laser treatment, trauma, or surgery. Subjects who had astigmatism more than −1.00 diopter (D), diabetes, hypertension or other systemic diseases, IOP more than 21 mm Hg, BCVA worse than 20/20, diffuse or severe chorioretinal atrophy, or complications of HM such as retinoschisis and choroidal neovascularization were excluded from the current study. Each subject was assigned to one of three groups based on the spherical equivalent (SE), calculated as the spherical power plus half of the negative cylinder power: (1) the first group served as controls and was composed of eyes with emmetropia and low myopia (EM/LM, SE: +0.50 to −2.75 D); (2) the second group had moderate myopia (MM, SE: −3.00 to −5.75 D); and (3) the third group had HM (SE: ≤ −6.00 D). 
Microperimetry Examination
Microperimetry (Micro Perimeter-1, MP1; Nidek Technologies, Padova, Italy) was used to quantify noncycloplegic MLS in a dark room. All subjects were previously exposed to a quick preliminary test examination to familiarize them with the procedure and to minimize the learning curve before the experiment. During the microperimetry examination, the machine projected a super-threshold stimulus onto the optic disk to monitor false-positive responses. The refraction error of each subject was corrected, and eye movements were corrected by an automated tracking system. A single red cross at the central region was used as the fixation target. The percentage of fixations were calculated automatically by the software. Stable fixation was defined as within 2° > 75%. 
The 4-2 staircase strategy and Goldmann III stimuli were adopted for use in the current study. The fixation stimulus was projected onto a white background with the illumination set at 1.27 cd/m2 (4 asb). The range of the stimulus was from 20 dB (equivalent to 0 asb) to 0 dB (equivalent to 400 asb). The starting examination stimulus was 10 dB with a duration of 200 ms. The perimetry threshold examination was performed within a 12° diameter around the macular center. An 8° diameter around the macula (1° = 0.3 mm, thus 8° = 2.4 mm of diameter, which encompassed the macular area) was selected for further analysis. Eight points were tested at 2° from the center of the fovea as the inner region, and 16 points were tested at 4° from the center as the outer region (Fig. 1A). 
Figure 1
 
Fundus-guided macular microperimetry map and OCT image. (A) Macular microperimetric findings superimposed onto the fundus image. The test procedure included 20 locations in 8° of the macular area. Eight points were tested at 2° from the center of the fovea (inner region, red circle), and 16 points were tested at 4° from the center (outer region, blue circle). (B) Cross-section image along the horizontal meridian acquired from OCT. The boundaries of fundus structure were segmented, and the thickness profiles of the macular outer retinal sublayers and choroid were obtained in the inner (ranging from 0.5 to 1.0 mm of eccentricity) and the outer region (ranging from 1.0 to 1.5 mm of eccentricity).
Figure 1
 
Fundus-guided macular microperimetry map and OCT image. (A) Macular microperimetric findings superimposed onto the fundus image. The test procedure included 20 locations in 8° of the macular area. Eight points were tested at 2° from the center of the fovea (inner region, red circle), and 16 points were tested at 4° from the center (outer region, blue circle). (B) Cross-section image along the horizontal meridian acquired from OCT. The boundaries of fundus structure were segmented, and the thickness profiles of the macular outer retinal sublayers and choroid were obtained in the inner (ranging from 0.5 to 1.0 mm of eccentricity) and the outer region (ranging from 1.0 to 1.5 mm of eccentricity).
OCT Measurement of Outer Retinal and Choroidal Thicknesses
The Optovue RTVue XR Avanti (Optovue, Inc., Fremont, CA, USA) OCT system was used to image the retina and choroid. Three-dimensional maps of the chorioretinal thickness were produced by analysis of OCT images from 18 consecutive transverse B-scans of the fundus captured by 8-mm radial line scans passing through the fovea. A good set of scans with a signal strength index of more than 40 was selected for further analysis. 
Custom-developed software was used to analyze the OCT images.13,16,17 Bennett's formula, t = p × q × s, was used to correct the image magnification before calculating the thickness of outer retina and choroid. Based on the AL, the calculation shows the relationship between the OCT-imaged measurement and the actual scan range, where t indicated the actual scan length, p was the magnification factor of the OCT imaging system camera, q was the magnification factor related to the eye AL, and s indicated the original measurement value from the OCT image. The q factor was calculated by the equation q = 0.01306 × (AL – 1.82). For the eye with an AL of 24.46 mm, the t factor would be equaled to the s factor. Then the real scan length t would be determined as t = (AL − 1.82) / 22.64 × s for eyes with other ALs. 
The measurements of macular sublayer thicknesses (Fig. 1B) were divided into two subfields that covered the locations where retinal function were acquired. The first subfield was the inner region, ranging from 0.5 to 1.0 mm of eccentricity. The second subfield was the outer region, ranging 1.0 to 1.5 mm of eccentricity (Fig. 2B). The thicknesses of the following fundic layers were quantified: outer plexiform layer (OPL), Henle fiber layer and outer nuclear layer (HFL + ONL), myoid and ellipsoid zone (MEZ), outer segment of photoreceptors (OS), interdigitation zone and retinal pigment epithelium/Bruch complex (IZ + RPE), and the choroid. 
Figure 2
 
Fundus-guided macular microperimetry map and AO fundus camera image. (A) Macular microperimetric findings superimposed onto the fundus image. The test procedure included 20 locations in 8° of the macular area. Eight points were tested at 2° from the center of the fovea (inner region, red circle), and 16 points were tested at 4° from the center (outer region, blue circle). (B) AO montage with the window size of 10° × 10° was created centered on the fovea. ROI, 80 × 80 pixels, red square, was selected for analysis at 0.6 mm and 1.2 mm of eccentricity along the horizontal and vertical meridians. (C) Magnified view of ROI that was outlined in white square. (D, E) Detection and boundaries segmentation of cone photoreceptor using automatic software (AO detect 2.0b13, Imaging Eyes). Blue crosses indicate positions of cones used to assess cone distribution. (F, G) Represented the cone density and cone number of closest neighbors. In this single case with AL of 23.00 mm, 118 cone photoreceptors were detected in ROI. The cone density and regularity were 33435/mm2 and 97.5%, respectively. N, number of cone cells.
Figure 2
 
Fundus-guided macular microperimetry map and AO fundus camera image. (A) Macular microperimetric findings superimposed onto the fundus image. The test procedure included 20 locations in 8° of the macular area. Eight points were tested at 2° from the center of the fovea (inner region, red circle), and 16 points were tested at 4° from the center (outer region, blue circle). (B) AO montage with the window size of 10° × 10° was created centered on the fovea. ROI, 80 × 80 pixels, red square, was selected for analysis at 0.6 mm and 1.2 mm of eccentricity along the horizontal and vertical meridians. (C) Magnified view of ROI that was outlined in white square. (D, E) Detection and boundaries segmentation of cone photoreceptor using automatic software (AO detect 2.0b13, Imaging Eyes). Blue crosses indicate positions of cones used to assess cone distribution. (F, G) Represented the cone density and cone number of closest neighbors. In this single case with AL of 23.00 mm, 118 cone photoreceptors were detected in ROI. The cone density and regularity were 33435/mm2 and 97.5%, respectively. N, number of cone cells.
Based on the gradient information and shortest path search, a custom-developed software package was used to automatically segment individual retinal layers, as described in our previous studies.13,16,17 Retinal sublayer definitions proposed by the International OCT Panel18 were used as the standard for image segmentation. Each image was visually inspected after the segmentation algorithm was run. In our previous papers, we reported the criteria for recognizing segmentation errors, including small peaks and curve offsets.19,20 If the automated segmentation was wrong, as occurred occasionally at the posterior boundary of the choroid in emmetropic eyes, manual corrections were made. One masked reader performed all analyses of the image segmentation. 
AO Measurement of Cone Photoreceptor Distribution
High-resolution photoreceptor images were obtained with the rtx1 AO retinal camera (Imagine Eyes, Orsay, France). The apparatus included a Shack-Hartmann wavefront sensor, a deformable mirror, and a high-resolution fundus camera. The lateral resolution was 1.6 μm with an approximately 4.2° × 4.2° field of view. During the imaging, the subjects were asked to gaze at an inbuilt yellow cross target that could be moved by the experimenter to pre-set coordinates within ± 10° horizontally and ± 8° vertically. During acquisition, the images that clearly showed a cone mosaic pattern were recorded. After the acquisition of a video, including a series of 40 frames at each location, a built-in program correlated and averaged the captured frames to produce a final image with a window size of approximately 4.0° × 4.0°. In the current study, a retinal image centered on the fovea was first captured. Then the perifoveal areas were imaged by instructing the subjects to consecutively fixate at 3.0° of eccentricity along the four meridians (temporal, nasal, superior, and inferior). Then, the five images of adjacent regions were stitched together using the i2k Retina software provided by the manufacturer to generate a montage (approximate 10° × 10°, corresponding to 3 × 3 mm) for each subject (Figs. 2A, 2B). 
The density and arrangement of cone photoreceptors was analyzed using image processing and recognition software provided by the manufacturer (AO detect 2.0b13; Imaging Eyes, Orsay, Essonne, France), which was reported by others in previous studies.21,22 After correcting the magnification of the montage that was similar with that used for OCT images, regions of interest (ROIs), 80 × 80 pixels, corresponding to 62 × 62 μm for emmetropic eyes, were manually selected for analysis from the locations of 0.6 mm and 1.2 mm of eccentricity along each meridian (corresponding to the inner and outer regions, respectively, Figs. 2B, 2C). A built-in algorithm corrected the magnification of the size of the ROIs based on the AL. Then algorithms based on segmentation and the Delaunay triangulation automatically identified the cone photoreceptors (Figs. 2D, 2E), from which the cone density and regularity were calculated (Figs. 2F, 2G). The density was defined as the cell number per square millimeter, while the regularity was defined as the percentage of cells that had five to seven cell neighbors. 
Statistical Analysis
Statistical analyses were performed using SPSS (version 22.0; SPSS, Inc., Chicago, IL, USA). One-way ANOVA was performed to compare the differences among the three groups. The different frequency of sexes among the three groups was analyzed by the χ2 test. Pearson's correlation and regression analyses were used to calculate correlations between the photoreceptor morphologic parameters with AL and choroidal thickness. Univariate and multivariate linear regression analyses were performed to evaluate the effect of changes in photoreceptor distribution and thicknesses on the MLS, as well as other parameters such as AL and choroidal thickness. P values less than 0.050 were considered statistically significant. 
Results
Patient Characteristics
A total of 77 eyes were analyzed from a cohort that included 27 EM/LM eyes, 25 MM eyes, and 25 HM eyes. Subjects in the HM group had greater degrees of myopia and longer ALs than those in the EM/LM and MM groups. Astigmatism of the HM group was also larger than that the of EM/LM group (P = 0.001, data not shown), but the difference, 0.31 D, was minor. There were no significant differences in age, sex, or IOP among the three groups (P = 0.066 to 0.679, Table 1). 
Table 1
 
Basic Characteristics of the EM/LM, MM, and HM Groups
Table 1
 
Basic Characteristics of the EM/LM, MM, and HM Groups
Differences of MLS and Fundus Biomorphology Among the Three Groups
Compared with the EM/LM group, the MLS was lower in the HM group (inner region: 19.11 ± 0.81 vs. 19.68 ± 0.44 dB, P = 0.002; outer region: 18.78 ± 0.85 vs. 19.50 ± 0.52 dB, P = 0.001; Table 2, Fig. 3). 
Table 2
 
MLS, Cone Distribution, and Thickness of the Outer Retina and Choroid
Table 2
 
MLS, Cone Distribution, and Thickness of the Outer Retina and Choroid
Figure 3
 
Fundus MLS and biomorphology among the three groups. (A) MLS; (B) density of cone; (C) regularity of cone; (D) OPL; (E) HFL + ONL; (F) MEZ; (G) OS; (H) IZ + RPE; (I) Choroidal layer. *P < 0.050. Bar: SD.
Figure 3
 
Fundus MLS and biomorphology among the three groups. (A) MLS; (B) density of cone; (C) regularity of cone; (D) OPL; (E) HFL + ONL; (F) MEZ; (G) OS; (H) IZ + RPE; (I) Choroidal layer. *P < 0.050. Bar: SD.
The ROIs from the AO retinal camera and OCT images with detailed magnified views were acquired from EM/LM, MM, and HM subjects (Fig. 4). There were significant differences in distribution of cone photoreceptors among the three groups (Supplementary Table S1). The cone photoreceptors of the HM group were less dense than that of the EM/LM and MM groups in the inner and outer regions of all four meridians (Supplementary Table S1; all P < 0.005). Along the horizontal meridian, the packing of cone photoreceptors in the HM group was less regular than in the EM/LM and MM groups (both P < 0.005). For the vertical meridian, the cone packing regularity in HM eyes was less than that of EM/LM eyes in inner region (P < 0.050), but was lower than that of MM eyes only in the outer region along the inferior meridian (P = 0.008). Moreover, the cone density and regularity were significantly correlated with the SE at each location except in the outer region along the inferior meridian (Supplementary Fig. S1). Additionally, the averaged cone density and the averaged regularity at 0.6 mm of eccentricity along the four meridians were used for further analysis of the inner region (Table 2, Fig. 3). Similarly, the averaged cone density and the averaged regularity at 1.2 mm of eccentricity along the four meridians were used for further analysis of the outer region. 
Figure 4
 
Representative images from AO fundus camera and OCT images. ROIs from AO images (AC) and OCT B-scan images with the detailed segmentation (DF) of emmetropia (top row), MM (middle row), and high myopia (bottom row), respectively. The ALs of the eyes were 23.53, 25.67, and 27.27 mm, respectively.
Figure 4
 
Representative images from AO fundus camera and OCT images. ROIs from AO images (AC) and OCT B-scan images with the detailed segmentation (DF) of emmetropia (top row), MM (middle row), and high myopia (bottom row), respectively. The ALs of the eyes were 23.53, 25.67, and 27.27 mm, respectively.
The thicknesses of the HFL + ONL, MEZ, and choroid were thinner in the HM group than in the EM/LM group in the inner region (Table 2, Fig. 3; HM versus EM/LM: HFL + ONL, 75.78 ± 8.78 vs. 82.88 ± 9.07 μm; MEZ, 23.46 ± 1.46 vs. 24.70 ± 1.30 μm; choroid, 122.95 ± 34.46 vs. 255.66 ± 60.19 μm; all P < 0.010) and outer region (HM versus EM/LM: HFL + ONL, 67.06 ± 7.14 vs. 74.68 ± 6.64 μm; MEZ, 23.31 ± 1.64 vs. 24.73 ± 1.27 μm; choroid, 125.25 ± 32.91 vs. 255.93 ± 60.26 μm; all P < 0.005). The IZ + RPE layer of the HM group was thinner only in the outer region compared with EM/LM group (HM versus EM/LM: 25.74 ± 4.19 vs. 29.43 ± 3.65 μm, P = 0.003). Moreover, the HFL + ONL was thinner in the MM group than in the EM/LM group (MM versus EM/LM: inner region, 76.11 ± 9.05 vs. 82.88 ± 9.07 μm; outer region, 69.30 ± 6.84 vs. 74.68 ± 6.64 μm, P = 0.014 and 0.011, respectively), whereas there were no significant differences between the MM and HM groups. In contrast, the MEZ layer was thinner in the HM group than in the MM group (HM versus MM: inner region, 23.46 ± 1.46 vs. 24.43 ± 1.41 μm; outer region, 23.31 ± 1.64 vs. 24.46 ± 1.43 μm, P = 0.019 and 0.008, respectively), whereas there were no significant differences between the EM/LM and MM groups. Thickness differences of the OPL and OS among the three groups were not significant (P = 0.058 to 0.852). 
Associations Between Cone Distribution and Outer Retinal Sublayers Thicknesses With AL and Choroidal Thickness
With axial elongation, the cone distribution and thicknesses of the HFL + ONL, MEZ, and choroid significantly decreased (r = −0.296 to −0.798, all P < 0.050, Fig. 5), whereas the OS layer tended to increase in the outer region (r = 0.263, P = 0.014). The associations between MLS and IZ + RPE thickness with AL were significant only for the outer region (r = −0.291 and −0.295, respectively, P < 0.050). The associations between AL and OPL thickness were not significant. Thinning of the choroid was significantly correlated with cone density and regularity (Figs. 6A, 6B) and with the thicknesses of MEZ and HFL + ONL (Figs. 6C, 6D) in the inner region (r = 0.249 to 0.606, all P < 0.050) and in the outer region (r = 0.252 to 0.615, all P < 0.050). 
Figure 5
 
Correlations of AL with MLS, cone distribution, and thickness of the outer retina and choroid. Scatterplots showing AL versus (A) MLS; (B) density of cone; (C) regularity of cone; (D) OPL; (E) HFL + ONL; (F) MEZ; (G) OS; (H) IZ + RPE; (I) choroidal layer. The solid lines and filled circles represent the results in the inner region. The dashed lines and open circles represent the results in the outer region.
Figure 5
 
Correlations of AL with MLS, cone distribution, and thickness of the outer retina and choroid. Scatterplots showing AL versus (A) MLS; (B) density of cone; (C) regularity of cone; (D) OPL; (E) HFL + ONL; (F) MEZ; (G) OS; (H) IZ + RPE; (I) choroidal layer. The solid lines and filled circles represent the results in the inner region. The dashed lines and open circles represent the results in the outer region.
Figure 6
 
Correlations of choroidal thickness with cone photoreceptor morphorlogy. Scatterplot showing choroidal thickness versus (A) cone density; (B) cone regularity; (C) MEZ; (D) HFL + ONL. The solid lines and filled circles represent the results in the inner region. The dashed lines and circles represent the results in the outer region.
Figure 6
 
Correlations of choroidal thickness with cone photoreceptor morphorlogy. Scatterplot showing choroidal thickness versus (A) cone density; (B) cone regularity; (C) MEZ; (D) HFL + ONL. The solid lines and filled circles represent the results in the inner region. The dashed lines and circles represent the results in the outer region.
Multivariate Regression Model to Predict MLS
In univariate regression models (Fig. 7), better MLS was significantly associated with a higher cone density and packing regularity and with a thicker MEZ and choroid in the inner region (r = 0.249 to 0.403, all P < 0.050, Table 3). For the outer region, better MLS was associated with higher cone density, thicker MEZ and choroid (r = 0.287 to 0.442), and shorter AL (r = −0.291) (all P < 0.050, Table 4). The thicknesses of the OPL, HFL + ONL, OS, and IZ + RPE were not significantly associated with MLS (all P > 0.050). 
Figure 7
 
Correlations of MLS with cone photoreceptor morphorlogy in the inner (AD) and outer (EH) regions. Scatterplot showing MLS versus (A, E) cone density; (B, F) MEZ; (C, G) choroidal thickness; (D) cone regularity; (H) AL.
Figure 7
 
Correlations of MLS with cone photoreceptor morphorlogy in the inner (AD) and outer (EH) regions. Scatterplot showing MLS versus (A, E) cone density; (B, F) MEZ; (C, G) choroidal thickness; (D) cone regularity; (H) AL.
Table 3
 
Linear Regression Analysis of Photoreceptor Biomorphology and Other Variables Associated With MLS in the Inner Region
Table 3
 
Linear Regression Analysis of Photoreceptor Biomorphology and Other Variables Associated With MLS in the Inner Region
Table 4
 
Linear Regression Analysis of Photoreceptor Biomorphology and Other Variables Associated With MLS in the Outer Region
Table 4
 
Linear Regression Analysis of Photoreceptor Biomorphology and Other Variables Associated With MLS in the Outer Region
The multivariate analysis included the MLS as a dependent variable (Tables 3, 4). Independent variables included all parameters that were significantly associated with the MLS as shown by univariate analysis. Thus, the OPL, HFL + ONL, OS, and IZ + RPE were dropped from the list of independent parameters. Moreover, AL was dropped from the list for the inner region and cone regularity was dropped for the outer region. In the final model, better MLS was significantly associated with the thicker MEZ layer in the inner region (R2 = 0.162, P = 0.001) and with higher cone density in the outer region (R2 = 0.182, P < 0.001). 
Discussion
The current study used high-resolution imaging technology, including AO and OCT, to determine if structural alterations of the fundus play an important role in visual impairment in HM eyes in which the BCVA was 20/20 or better and without any complications. The morphologic degeneration of photoreceptors in HM eyes was significantly correlated with deterioration of the MLS. As the decline of MLS has been widely documented in previous studies,6,23,24 early intervention to protect the photoreceptor would be important to maintain visual function. 
The progression of HM and related pathological changes is slow; thus, it has been challenging to detect the visual damage in HM with high sensitivity. Visual acuity might be a poor functional end point as it may be unaffected until the late stages of HM (i.e., when pathological changes or complications occur).13,25,26 In contrast, microperimetry measures the vision function by projecting a localized visual stimulus directly onto exact positions of the macula, and thus it has the potential to monitor HM-related visual damage in the macular area.6,23,24 In the current study, we found a decline of MLS in HM. Moreover, the MLS was reduced by 0.10 dB and 0.17 dB per 1-mm increase in AL in the inner and outer regions, respectively, although the correlation between MLS and AL in the inner region was not significant (P = 0.059). Qin et al.6 first reported that the MLS significantly decreased in HM eyes compared with nonmyopic eyes. Zaben et al.23 also found a reduction of retinal sensitivity that correlated with the degree of myopia. Further longitudinal studies were required to confirm the progression of visual dysfunction in HM with and without pathological changes. 
A key finding of the current study was that the decreased MLS was correlated with chorioretinal degeneration, especially disorder of the photoreceptors. Several studies have shown associations between retinal function and fundus structure in HM.7,13,14 For instance, some studies found that thinning of the choroid was correlated with reduced visual acuity.14 The losses in neural activity due to the thinning of the middle and inner retina were reported to result in delayed multifocal electroretinogram timing.7 However, it was unknown if the outer retina was functionally relevant to the visual impairment, thus necessitating the present study. 
Among the parameters of photoreceptor morphology, the thickness of the MEZ layer was one of the most significant predictors of MLS, especially in the inner region. The MEZ is a specialized region that contains mitochondria, Golgi, and endoplasmic reticulum; thus, it is important in the production of ATP, G-proteins, photopsin, and other chemicals that are necessary to maintain photosensitivity.27,28 MEZ thinning was only found in the HM group rather than MM group. This might explain why decreased MLS mainly occurred in HM. Similarly, our recent study found significant MEZ thinning in pathological myopia and was highly associated with worsening BCVA.13 These findings indicated that the MEZ thickness is an important retinal anatomical biomarker with high functional influence, and alteration of MEZ should be closely examined and monitored in the clinic. 
Cone photoreceptor distribution was another important factor correlated with visual dysfunction. Cone density in the outer region was the most significant predictor of MLS in the final regression model, whereas decreased cone regularity in the inner region was also correlated with MLS decline. Reduction of cone density and packing regularity with increased AL or degree of myopia has been reported in previous studies.10,15 However, it is still unclear if the lower cone distribution is correlated with worse visual function. The current study provides evidence of the correlation between cone distribution and macular sensitivity in myopic eyes. Lower cone packing density and regularity in HM eyes indicates potential sparseness and disordered arrangement of cones within certain areas, which is likely to result in reduced spatial vision function and less effective photosensitivity in the fundus. Further investigation should be performed to estimate what magnitude of decreased cone density is required to cause significant visual impairment. 
The mechanical elongation of the ocular axis plays a critical role in the progression of HM. Several studies have observed the correlation between the visual function and AL.6,29,30 With ocular elongation during myopia progression, the photoreceptor layer would expand due to retinal stretching to cover the larger surface area, leading to the decreases of thickness and density,10,14,15 and consequently causing visual impairment. The slope of the trend line between AL with thicknesses of the outer retinal sublayers and choroid were similar between the inner and outer regions. This indicates that the outer retina and choroid might be stretched evenly by eyeball expansion, thus leading to the sparseness of cone photoreceptors. Moreover, cone regularity also decreased with axial elongation. In this case, sparseness of the cones is unlikely to be due simply to retinal stretching, and cone damage and loss are probably subsistent with myopia, especially in the inner region where the slope of the trend line between AL and cone density was steeper than in the outer region. Therefore, investigating and controlling the axial elongation would be helpful to prevent the further disruption of photoreceptors and finally improve visual function. 
Significant thinning of the choroid in myopia and its relationship with visual function have been widely studied.23,31,32 The choroid provides most of the oxygen demand of the photoreceptors.11,12,33 Thinning of the choroid might result in a lack of oxygen, which is indispensable for photoreceptor metabolism and photosensitivity. This might explain the significant correlation between the thinning choroid and cone distribution, thicknesses of HFL + ONL and MEZ layers, and visual dysfunction. Our previous study further demonstrated that the interaction between MEZ and choroidal thickness was significantly correlated with visual acuity in pathological myopia.13 The data implied that for a given MEZ thickness, more visual impairment occurred in eyes with a thinner choroid. For this reason, improving the microenvironment of the photoreceptors and preventing their degeneration would be a new target in the treatment of visual loss. 
There were some limitations in our current study. First, we only investigated a small field within the macula. Larger field imaging and analysis are required in future studies to further confirm the photoreceptor alterations and dysfunction. Second, the border of the choroid was not always clear in the EM/LM group. However, in our previous article, we confirmed the accuracy and repeatability of the choroidal thickness measurements.13,19 Moreover, the measurements of the MEZ thickness and cone density were not performed on a point-by-point basis. To further confirm the corresponding correlation and comparison in the MEZ and cone density, cone density analysis in the whole measurement area will be required. The stimulus projection during microperimetry experiments might vary in eyes with different ALs due to the different magnifications. The mean AL difference between the HM and EM/LM groups was 3.07 mm in this study. Based on Bennett's formula, compared with EM/LM eyes, the stimulus projections in HM eyes were 0.08 mm farther from the fovea in the inner region and 0.16 mm farther from the fovea in the outer regions. This is an issue that should be addressed in the future by changing the stimulus locations. A long-term study is also required to further confirm the predictive role of photoreceptor density on the visual dysfunction. In our current research, changes in photoreceptor distribution and sublayers thicknesses were observed with increased degrees of myopia; however other optical components such as higher order aberrations might also influence the image collection. Further studies utilizing AO-OCT techniques may be the solution to address this question. 
In conclusion, utilization of the AO fundus camera and OCT enabled us to characterize alterations of photoreceptor morphology that were correlated with reduced MLS. Multivariate regression analysis showed that the photoreceptor density and MEZ thickness were significant predictors of MLS loss in HM. Collectively, our results suggest that early clinical monitoring and intervention will depend on properly assessing changes in axial elongation, in the outer retinal sublayers, in the choroid, and in the MLS. With the understanding of these variables, it may become possible to develop protocols that will help evaluate and prevent further visual impairment in HM. 
Acknowledgments
Supported by research grants from the National Key Research and Development Program of China (2016YFC0102500), the National Nature Science Foundation of China (Grant No. 81570880), the Natural Science Foundation of Zhejiang Province (Grant No. LQ16H120007, Grant No. LY16H120007), and Zhejiang medical and health science and technology project (2019PY009). 
Disclosure: Y. Wang, None; J. Ye, None; M. Shen, None; A. Yao, None; A. Xue, None; Y. Fan, None; S. Huang, None; J. Wang, None; F. Lu, None; Y. Shao, None 
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Figure 1
 
Fundus-guided macular microperimetry map and OCT image. (A) Macular microperimetric findings superimposed onto the fundus image. The test procedure included 20 locations in 8° of the macular area. Eight points were tested at 2° from the center of the fovea (inner region, red circle), and 16 points were tested at 4° from the center (outer region, blue circle). (B) Cross-section image along the horizontal meridian acquired from OCT. The boundaries of fundus structure were segmented, and the thickness profiles of the macular outer retinal sublayers and choroid were obtained in the inner (ranging from 0.5 to 1.0 mm of eccentricity) and the outer region (ranging from 1.0 to 1.5 mm of eccentricity).
Figure 1
 
Fundus-guided macular microperimetry map and OCT image. (A) Macular microperimetric findings superimposed onto the fundus image. The test procedure included 20 locations in 8° of the macular area. Eight points were tested at 2° from the center of the fovea (inner region, red circle), and 16 points were tested at 4° from the center (outer region, blue circle). (B) Cross-section image along the horizontal meridian acquired from OCT. The boundaries of fundus structure were segmented, and the thickness profiles of the macular outer retinal sublayers and choroid were obtained in the inner (ranging from 0.5 to 1.0 mm of eccentricity) and the outer region (ranging from 1.0 to 1.5 mm of eccentricity).
Figure 2
 
Fundus-guided macular microperimetry map and AO fundus camera image. (A) Macular microperimetric findings superimposed onto the fundus image. The test procedure included 20 locations in 8° of the macular area. Eight points were tested at 2° from the center of the fovea (inner region, red circle), and 16 points were tested at 4° from the center (outer region, blue circle). (B) AO montage with the window size of 10° × 10° was created centered on the fovea. ROI, 80 × 80 pixels, red square, was selected for analysis at 0.6 mm and 1.2 mm of eccentricity along the horizontal and vertical meridians. (C) Magnified view of ROI that was outlined in white square. (D, E) Detection and boundaries segmentation of cone photoreceptor using automatic software (AO detect 2.0b13, Imaging Eyes). Blue crosses indicate positions of cones used to assess cone distribution. (F, G) Represented the cone density and cone number of closest neighbors. In this single case with AL of 23.00 mm, 118 cone photoreceptors were detected in ROI. The cone density and regularity were 33435/mm2 and 97.5%, respectively. N, number of cone cells.
Figure 2
 
Fundus-guided macular microperimetry map and AO fundus camera image. (A) Macular microperimetric findings superimposed onto the fundus image. The test procedure included 20 locations in 8° of the macular area. Eight points were tested at 2° from the center of the fovea (inner region, red circle), and 16 points were tested at 4° from the center (outer region, blue circle). (B) AO montage with the window size of 10° × 10° was created centered on the fovea. ROI, 80 × 80 pixels, red square, was selected for analysis at 0.6 mm and 1.2 mm of eccentricity along the horizontal and vertical meridians. (C) Magnified view of ROI that was outlined in white square. (D, E) Detection and boundaries segmentation of cone photoreceptor using automatic software (AO detect 2.0b13, Imaging Eyes). Blue crosses indicate positions of cones used to assess cone distribution. (F, G) Represented the cone density and cone number of closest neighbors. In this single case with AL of 23.00 mm, 118 cone photoreceptors were detected in ROI. The cone density and regularity were 33435/mm2 and 97.5%, respectively. N, number of cone cells.
Figure 3
 
Fundus MLS and biomorphology among the three groups. (A) MLS; (B) density of cone; (C) regularity of cone; (D) OPL; (E) HFL + ONL; (F) MEZ; (G) OS; (H) IZ + RPE; (I) Choroidal layer. *P < 0.050. Bar: SD.
Figure 3
 
Fundus MLS and biomorphology among the three groups. (A) MLS; (B) density of cone; (C) regularity of cone; (D) OPL; (E) HFL + ONL; (F) MEZ; (G) OS; (H) IZ + RPE; (I) Choroidal layer. *P < 0.050. Bar: SD.
Figure 4
 
Representative images from AO fundus camera and OCT images. ROIs from AO images (AC) and OCT B-scan images with the detailed segmentation (DF) of emmetropia (top row), MM (middle row), and high myopia (bottom row), respectively. The ALs of the eyes were 23.53, 25.67, and 27.27 mm, respectively.
Figure 4
 
Representative images from AO fundus camera and OCT images. ROIs from AO images (AC) and OCT B-scan images with the detailed segmentation (DF) of emmetropia (top row), MM (middle row), and high myopia (bottom row), respectively. The ALs of the eyes were 23.53, 25.67, and 27.27 mm, respectively.
Figure 5
 
Correlations of AL with MLS, cone distribution, and thickness of the outer retina and choroid. Scatterplots showing AL versus (A) MLS; (B) density of cone; (C) regularity of cone; (D) OPL; (E) HFL + ONL; (F) MEZ; (G) OS; (H) IZ + RPE; (I) choroidal layer. The solid lines and filled circles represent the results in the inner region. The dashed lines and open circles represent the results in the outer region.
Figure 5
 
Correlations of AL with MLS, cone distribution, and thickness of the outer retina and choroid. Scatterplots showing AL versus (A) MLS; (B) density of cone; (C) regularity of cone; (D) OPL; (E) HFL + ONL; (F) MEZ; (G) OS; (H) IZ + RPE; (I) choroidal layer. The solid lines and filled circles represent the results in the inner region. The dashed lines and open circles represent the results in the outer region.
Figure 6
 
Correlations of choroidal thickness with cone photoreceptor morphorlogy. Scatterplot showing choroidal thickness versus (A) cone density; (B) cone regularity; (C) MEZ; (D) HFL + ONL. The solid lines and filled circles represent the results in the inner region. The dashed lines and circles represent the results in the outer region.
Figure 6
 
Correlations of choroidal thickness with cone photoreceptor morphorlogy. Scatterplot showing choroidal thickness versus (A) cone density; (B) cone regularity; (C) MEZ; (D) HFL + ONL. The solid lines and filled circles represent the results in the inner region. The dashed lines and circles represent the results in the outer region.
Figure 7
 
Correlations of MLS with cone photoreceptor morphorlogy in the inner (AD) and outer (EH) regions. Scatterplot showing MLS versus (A, E) cone density; (B, F) MEZ; (C, G) choroidal thickness; (D) cone regularity; (H) AL.
Figure 7
 
Correlations of MLS with cone photoreceptor morphorlogy in the inner (AD) and outer (EH) regions. Scatterplot showing MLS versus (A, E) cone density; (B, F) MEZ; (C, G) choroidal thickness; (D) cone regularity; (H) AL.
Table 1
 
Basic Characteristics of the EM/LM, MM, and HM Groups
Table 1
 
Basic Characteristics of the EM/LM, MM, and HM Groups
Table 2
 
MLS, Cone Distribution, and Thickness of the Outer Retina and Choroid
Table 2
 
MLS, Cone Distribution, and Thickness of the Outer Retina and Choroid
Table 3
 
Linear Regression Analysis of Photoreceptor Biomorphology and Other Variables Associated With MLS in the Inner Region
Table 3
 
Linear Regression Analysis of Photoreceptor Biomorphology and Other Variables Associated With MLS in the Inner Region
Table 4
 
Linear Regression Analysis of Photoreceptor Biomorphology and Other Variables Associated With MLS in the Outer Region
Table 4
 
Linear Regression Analysis of Photoreceptor Biomorphology and Other Variables Associated With MLS in the Outer Region
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