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. 2024 Aug 13;103(1):e49–e57. doi: 10.1111/aos.16747

Differentiating optic neuropathies using laser speckle flowgraphy: Evaluating blood flow patterns in the optic nerve head and peripapillary choroid

Chiaki Yamaguchi 1, Naoki Kiyota 1, Noriko Himori 1,2, Kazuko Omodaka 1, Satoru Tsuda 1, Toru Nakazawa 1,3,4,5,✉
PMCID: PMC11704823  PMID: 39136108

Abstract

Purpose

To compare blood flow (BF) impairment patterns in different optic neuropathies using laser speckle flowgraphy (LSFG).

Methods

This retrospective study enrolled 24 eyes of 24 patients with non‐arteritic anterior ischemic optic neuropathy (NAAION), 59 eyes of 59 patients with optic neuritis (ON), 677 eyes of 677 patients with open‐angle glaucoma (OAG), and 110 eyes of 110 controls. The patient backgrounds of all groups were compared. Ophthalmologic findings were evaluated, adjusting for age, sex, blood pressure, pulse rate, and underlying systemic diseases with 1:1 optimal propensity score matching. We used LSFG to obtain optic nerve head (ONH) vessel‐area mean blur rate (MBR; ONH‐MV), ONH tissue‐area MBR (ONH‐MT), and choroidal MBR. The NAAION and ON groups were compared with the control and OAG groups.

Results

Best‐corrected visual acuity was worse in the NAAION, ON, and OAG groups than in controls (p < 0.001). Circumpapillary retinal nerve fibre layer thickness was higher in the NAAION and ON groups and lower in the OAG group than in controls (p < 0.001). Compared to controls, the NAAION and OAG groups had significantly lower ONH‐MV, ONH‐MT, and choroidal MBR (p < 0.05). Additionally, the NAAION group had lower ONH‐MV and choroidal MBR than the OAG group (p = 0.003 and p < 0.001, respectively) but no difference in ONH‐MT (p = 0.857). The ON group had significantly lower ONH‐MV and choroidal MBR compared to the controls (p < 0.001 and p = 0.022, respectively) but no difference in ONH‐MT (p = 0.773).

Conclusion

Optic neuropathies showed different patterns of ocular BF impairment. Therefore, LSFG can be a useful tool for differentiating optic neuropathies.

Keywords: glaucoma, ischemic optic neuropathy, laser speckle flowgraphy, optic neuritis

1. INTRODUCTION

Optic neuropathies have a range of pathological mechanisms, including inflammation, ischemia, and degeneration, and they can profoundly affect the quality of life due to the irreversible impairment of visual function (Behbehani, 2007). These neuropathies often exhibit overlapping clinical features (Biousse & Newman, 2016; Rizzo & Lessell, 1991). To differentiate them, a combination of ocular and systemic subjective examinations is critical, encompassing visual acuity and visual field testing, information on disease onset, and background factors, such as age, sex, and the history of systemic diseases (Behbehani, 2007; Biousse & Newman, 2016). However, certain groups, notably the elderly or those with cognitive disorders, may struggle to provide this information accurately or to succeed in subjective visual tests, underscoring the importance of objective examinations.

In addition to blood tests, the most pivotal objective tests for distinguishing between optic neuropathies might be contrast‐enhanced magnetic resonance imaging (MRI) and fluorescein angiography (FA) (Arnold & Hepler, 1994; Behbehani, 2007; He et al., 2010; Rizzo et al., 2002). However, these tests are time‐consuming and invasive due to the need for dye injections, carrying associated risks like anaphylaxis and potential liver or kidney damage (Hao et al., 2012; Kornblau & El‐Annan, 2019). This landscape underscores the growing demand for non‐invasive diagnostic modalities.

Laser speckle flowgraphy (LSFG) measures mean blur rate (MBR), a parameter aligned with blood flow (BF) velocity, by capitalizing on the speckle pattern triggered by laser light scattering from moving red blood cells (Sugiyama et al., 2010; Tamaki et al., 1994). LSFG is a non‐contact method, requires no dye, and can produce images within a capture time of only 4 s, rendering it both non‐invasive and efficient (Luft et al., 2016; Sugiyama et al., 2010; Tamaki et al., 1994). One of LSFG's strengths lies in the device's capability to designate a region of interest (ROI) on the optic nerve head (ONH) and obtain specific measurements of vessel‐area MBR (MV), which originates in the large vessels rooted in the central retinal artery (CRA), and tissue‐area MBR (MT), which is sourced from the short posterior ciliary arteries (SPCAs) (Aizawa et al., 2011; Aizawa, Nitta, et al., 2014; Wang et al., 2012). When positioning the ROI outside the ONH, LSFG can measure choroidal BF (Isono et al., 2003). Given that the affected BF region can vary based on the specific pathology of a disease, this LSFG feature is advantageous.

In light of these considerations, we employed LSFG in this study to discern patterns of BF disruption in optic neuropathies such as non‐arteritic anterior ischemic optic neuropathy (NAAION), anterior optic neuritis (ON), and open‐angle glaucoma (OAG).

2. MATERIALS AND METHODS

This retrospective, cross‐sectional study was conducted at Tohoku University Hospital in Sendai, Miyagi, Japan. The institutional review board of the Tohoku University Graduate School of Medicine approved the study. All procedures were approved by the ethics committee of Tohoku University Graduate School of Medicine and conformed with the Declaration of Helsinki and its later amendments or comparable ethical standards. We reviewed medical records from July 2011 to March 2023, evaluating 24 162 eyes of 12 458 patients who underwent 69 210 LSFG imaging sessions. From this, we identified 29 eyes of 24 patients with NAAION, and 67 eyes of 59 patients with anterior ON who underwent LSFG imaging, and 1089 eyes of 677 OAG patients (normal‐tension glaucoma: 791 eyes; primary open‐angle glaucoma: 298 eyes). The glaucoma diagnoses were confirmed by a specialist (T.N.). Patients with OAG were included in this study if they met the following criteria: (1) glaucomatous changes to the ONH at baseline with corresponding visual field defects in line with the Anderson‐Patella criteria (Anderson & Patella, 1999); (2) a normal, open angle on gonioscopic examination; (3) intraocular pressure (IOP) of 21 mmHg or less, either with or without medication during the follow‐up period; (4) lens nucleus grade of 2 or less in the Emery‐Little classification; and (5) no presence of vitreoretinal or optic nerve diseases other than glaucoma.

NAAION and anterior ON were diagnosed by a neuro‐ophthalmology expert (N.H.). Patients with NAAION and anterior ON included in this study were limited to those with initial onset, those with the acute‐phase fundus findings described below, and those who had not yet started treatment. Cases of anterior ON included idiopathic ON and ON associated with myelin‐oligodendrocyte glycoprotein antibody‐related disease (MOGAD), neuromyelitis optica spectrum disorder (NMOSD), and multiple sclerosis (MS). More detailed criteria for including NAAION patients are as follows: (1) acute visual disturbance or visual field defect; (2) the presence of a relative afferent pupillary defect; (3) reduced critical flicker fusion frequency; (4) ONH swelling and/or redness present at the initial visit, acute‐phase fundus findings; (5) observed spontaneous resolution of ONH swelling during the follow‐up; (6) ONH‐related visual field defects; and (7) no evidence of any other neurologic, systemic, or ocular disorder that could be responsible for ONH swelling and visual impairment. Patients with anterior ON were included based on the following criteria: (1) acute visual disturbance or visual field defect; (2) presence of a relative afferent pupillary defect; (3) reduced critical flicker fusion frequency; (4) presence of ONH swelling and/or redness at the initial visit, acute‐phase fundus findings; (5) presence of contrast effects along the optic nerve in contrast‐enhanced MRI; and (6) no evidence of any other neoplastic or inflammatory disease that could be responsible for ONH swelling and visual impairment.

We interviewed each patient at the initial visit for a detailed medical history; details recorded included the presence of hypertension (HT), diabetes mellitus (DM), dyslipidemia (DL), heart disease (HD), and sleep apnea syndrome (SAS). Baseline data were collected, including visual acuity, IOP, slit lamp findings, and a dilated funduscopic examination. The control group included 110 fellow eyes of patients with cataract, glaucoma, or retinal diseases (e.g., epiretinal membrane and branch retinal vein occlusion). We did not observe evident thinning of circumpapillary retinal nerve fibre layer thickness (cpRNFLT) (103.70 ± 2.90 μm) or glaucomatous visual field defects (mean deviation [MD] value: −0.61 ± 0.16 dB) in the fellow control eyes of the patients with OAG. One eye was randomly selected per subject. Figure 1 presents a flow chart detailing the eye selection process for analysis. Our analysis in this study included (1) a comparison of clinical characteristics in the NAAION, ON, OAG, and control groups and (2) a comparison of ocular parameters, including LSFG parameters, adjusted for age, sex, systolic BP (SBP), diastolic BP (DBP), pulse rate (PR), HT, DM, DL, HD, and SAS using 1:1 optimal propensity score matching. For the NAAION and ON groups, due to significant differences in background factors and low sample size, we did not perform propensity score matching.

FIGURE 1.

FIGURE 1

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Criteria for eye selection in this study.

2.1. Measurement of clinical variables and BF parameters

IOP was measured with non‐contact tonometry. Visual field testing in the NAAION and ON groups was performed with Goldmann kinetic perimetry (GP). In the glaucoma patients, visual field testing was conducted using the SITA standard 24–2 program of the Humphrey Field Analyser (HFA; Carl Zeiss Meditec, Dublin, CA, USA); only reliable measurements of the visual field were used (fixation errors <20%, false positives <33%, and false negatives <33%) (Cascairo et al., 1991; Newkirk et al., 2006). In certain cases, additional testing with GP was also performed, as deemed appropriate by the attending doctor. ONH and choroid BF were assessed with the LSFG‐NAVI device (Softcare Co., Ltd., Fukutsu, Japan), which measures MBR in arbitrary units (AU). First, an ellipsoid band was manually drawn around the ONH to define the ROI in composite MBR colour maps. The accompanying LSFG software (LSFG analyser, version 3.1.59.0) then automatically divided the large‐vessel and tissue (i.e., capillary) areas of the ONH and determined MV and MT separately in a cross‐sectional analysis. ONH‐MT has been reported to be a good indicator of BF in the deep capillaries of the ONH (Aizawa, Nitta, et al., 2014; Wang et al., 2012). A same‐sized ROI was then set on the temporal side of the ONH in the same image to mark the choroid region, as we described previously (Kiyota, Shiga, et al., 2018). Before the LSFG measurements, the patient's pupils were dilated with 0.4% tropicamide, a muscarinic antagonist (Mydrin M; Santen Pharmaceutical Co., Ltd). After the instillation, the patients sat in a dark, quiet room for 15 min to stabilize pupil dilation, BP, and PR. Then, BP and PR were measured (HBP‐1300; Omron), and LSFG was performed. The LSFG parameter “vascular cloud” (VC) is a parameter that represents the clarity of the vascular network in the ONH (Hashimoto et al., 2018).

2.2. Statistical analysis

All data are shown as the mean value ± standard deviation. The Shapiro–Wilk and Levene tests were performed to confirm the normality of continuous variables in all analyses. Based on these results, the Kruskal‐Wallis test was used for overall group analysis, and the Dunn pairwise comparison test was used for post hoc analyses. For comparisons of continuous variables between the two groups after propensity score matching, the t‐test was used for parametric variables, and the Wilcoxon rank sum test was used for nonparametric variables. For nominal variables, the chi‐squared and Fisher exact tests were used. The significance level for overall group comparisons was set at p < 0.05. The significance level was adjusted to p < 0.008 using Bonferroni correction when performing multiple pairwise comparisons among the overall groups. All statistical analyses were performed with R software version 4.3.0 (available at https://www.R‐project.org/).

3. RESULTS

A comparison of clinical characteristics among the NAAION, ON, OAG, and control groups is presented in Table 1. The age difference between all groups was statistically significant (p < 0.001). The NAAION group had the oldest age (73.29 ± 9.20 years), while the ON group had the youngest (43.44 ± 17.49 years). In the ON group, 79.7% were women, which was significantly higher compared to the NAAION group (29.2%), the OAG group (52.7%), and the control group (45.5%) (p < 0.001). The NAAION group had higher SBP and DBP than the ON, OAG, and control groups (p < 0.05). In the NAAION group, the prevalence rates for HT (83.3%), HD (37.5%), and SAS (33.3%) were higher than in the ON, OAG, and control groups (p < 0.05). In cases where the onset date was clear, the duration from onset to LSFG imaging was 7.43 ± 1.11 days in the NAAION group (n = 21 patients) and 5.07 ± 0.68 days in the ON group (n = 56 patients), indicating that most cases were in their acute phase. Erythrocyte sedimentation rate (ESR) tended to be higher (p = 0.051); however, after adjustments for age and sex, this was not statistically significant (p = 0.992). There was no significant discrepancy between the normal ESR values calculated based on the age and gender (Miller et al., 1983) of our study participants and the actual measured ESR values (NAAION: 38.10 ± 1.7 vs. 33.96 ± 25.15 mm/h and ON: 25.70 ± 1.10 vs. 21.91 ± 21.63 mm/h, respectively). Additionally, no significant difference in C‐reactive protein was observed after age and sex adjustment (p = 0.122).

TABLE 1.

Comparison of clinical characteristics among AION, ON, glaucoma, and control group.

Variable Groups p‐Value Significant pair p‐value
NAAION, n = 24 ON, n = 59 OAG, n = 677 Control, n = 110
Age, years 73.29 ± 9.20 43.44 ± 17.49 58.60 ± 12.28 53.10 ± 17.45 <0.001‡,* A–E < 0.001b, F = 0.002b
Male to female ratio 17:7 12:47 320:357 60:50 <0.001* A, D, E < 0.001a
Systolic BP, mmHg 140.00 ± 17.01 121.78 ± 18.30 126.66 ± 19.28 123.09 ± 18.04 <0.001‡,* A–C < 0.001b
Diastolic BP, mmHg 82.50 ± 19.04 73.93 ± 13.34 76.27 ± 13.31 73.25 ± 11.64 0.005‡,* A = 0.003b, B = 0.008b, C = 0.001b
Pulse rate, bpm 79.67 ± 13.68 78.90 ± 13.54 72.62 ± 11.98 73.90 ± 13.37 0.001‡,* B = 0.005b, D < 0.001b, E = 0.005b
Hypertension, (n %) 20, (83.3%) 6, (10.2%) 178, (26.3%) 31, (28.2%) <0.001* A–C < 0.001a, D = 0.005a, E = 0.007a
Diabetes mellitus, (n %) 7, (29.2%) 1, (1.7%) 54, (8.0%) 16, (14.5%) <0.001* A < 0.001a, B = 0.003a, E = 0.007a
Dyslipidemia, (n %) 9, (37.5%) 4, (6.8%) 148, (21.9%) 31, (28.2%) 0.005* A = 0.001a, D = 0.004a, E = 0.001a
Heart disease, (n %) 9, (37.5%) 1, (1.7%) 63, (9.3%) 10, (9.1%) <0.001* A and B < 0.001§, C = 0.001§
Sleep apnea syndrome, (n %) 8, (33.3%) 1, (1.7%) 45, (6.6%) 7, (6.4%) <0.001* A and B < 0.001§, C = 0.004§
Erythrocyte sedimentation rate, mm/h 33.96 ± 25.15 21.91 ± 21.63 – – 0.051†
C‐reactive protein, mg/dL 0.54 ± 1.02 0.35 ± 1.30 – – 0.485†
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Note: A: NAAION vs. ON, B: NAAION vs. OAG, C: NAAION vs. control, D: ON vs. OAG, E: ON vs. control, F: OAG vs. control. p‐Value indications: * indicates statistical significance after appropriate corrections. Unmarked p values: chi‐square test; † indicates t‐test, ‡ indicates Kruskal‐Wallis test, and § indicates Wilcoxon rank sum test. For pairwise comparisons using Fisher's exact test (indicated by a) and Dunn's test (indicated by b), the significance level was set at p < 0.008 after Bonferroni correction.

Abbreviations: BP, blood pressure; LSFG, laser speckle flowgraphy; NAAION, non‐arteritic anterior ischemic optic neuropathy; OAG, open‐angle glaucoma; ON, optic neuritis.

As shown in Table S1, after optimal propensity score matching, no significant differences in systemic background factors were observed between the groups (p > 0.05). The number of subjects in each group and the results of group comparisons of ocular parameters after the optimal propensity score matching are presented in Table 2. Figure 2 shows the boxplots of LSFG‐derived parameters in the groups. Representative cases of each disease are shown in Figure 3. Compared to the control group, the NAAION group demonstrated significantly worse best‐corrected visual acuity (BCVA) (p < 0.001) and higher cpRNFLT (p < 0.001), but no significant differences in IOP or VC (p = 0.880 and p = 0.119, respectively). The NAAION group, compared to the control group, showed a 26.81% decrease in ONH‐MV (41.35 ± 6.37 vs. 30.26 ± 7.74 AU, p < 0.001), a 20.86% decrease in ONH‐MT (12.46 ± 2.25 vs. 9.86 ± 3.12 AU, p = 0.002), and a 35.04% decrease in choroidal MBR (7.42 ± 1.69 vs. 4.82 ± 1.91 AU, p < 0.001). In comparison to the OAG group, the NAAION group had significantly deteriorated BCVA (p < 0.001) and increased cpRNFLT (p < 0.001), but there was no significant difference in IOP (p = 0.992). The NAAION group had lower VC than the OAG group (p = 0.005). The NAAION group showed a 21.44% decrease in ONH‐MV (38.52 ± 10.39 vs. 30.26 ± 7.74 AU, p = 0.003) and a 36.31% decrease in choroidal MBR (7.63 ± 2.91 vs. 4.82 ± 1.91 AU, p < 0.001) compared to the OAG group, while ONH‐MT did not show any significant difference (9.70 ± 2.32 vs. 9.86 ± 3.12 AU, p = 0.838). In the NAAION group, there was no significant correlation between LSFG parameters and cpRNFLT in the multivariable linear mixed‐effects model after adjusting for age and sex (ONH‐MV: β = −0.06, p = 0.751; ONH‐MT: β = −0.11, p = 0.560; and choroidal MBR: β = −0.10, p = 0.662, respectively). The OAG group had worse BCVA (p < 0.001), lower IOP (p = 0.013), and reduced cpRNFLT (p < 0.001) compared to the control group. The OAG group showed 10.93% lower ONH‐MV (42.56 ± 6.63 vs. 37.91 ± 9.02 AU, p < 0.001), 20.39% lower ONH‐MT (12.31 ± 2.01 vs. 9.80 ± 2.45 AU, p < 0.001), and 9.89% lower choroidal MBR (7.99 ± 2.19 vs. 7.20 ± 2.88 AU, p < 0.001) compared to the control group. The ON group, compared to the control group, had worse BCVA (p < 0.001), significantly increased cpRNFLT (p < 0.001), and no significant difference in IOP (p = 0.766). The ON group showed 11.94% lower ONH‐MV (43.71 ± 6.73 vs. 38.49 ± 7.63 AU, p < 0.001) and 10.32% lower choroidal MBR (8.04 ± 2.13 vs. 7.21 ± 2.49 AU, p = 0.022) compared to the control group, but there was no significant difference in ONH‐MT (12.17 ± 2.34 vs. 12.28 ± 2.34 AU, p = 0.773). The ON group had worse BCVA (p < 0.001), higher IOP (p = 0.022), and higher cpRNFLT (p < 0.001) compared to the OAG group. The ON group had lower VC than the OAG group (p < 0.001). The ON group did not show significant differences in ONH‐MV (39.78 ± 8.01 vs. 38.49 ± 7.63 AU, p = 0.372) or choroidal MBR (7.69 ± 3.12 vs. 7.21 ± 2.49 AU, p = 0.524) compared to the OAG group. In contrast, ONH‐MT was significantly lower in the OAG group, showing a 12.94% decrease (12.28 ± 2.34 vs. 10.69 ± 2.92 AU, p < 0.001) compared to the ON group. In the ON group, there was a positive correlation between choroidal MBR and cpRNFLT (β = 0.48, p < 0.001) and no correlation between ONH‐MV and ONH‐MT in the multivariable linear mixed‐effects model after adjusting for age and sex (ONH‐MV: β = −0.22, p = 0.132 and ONH‐MT: β = 0.21, p = 0.144, respectively). Table S2 shows our findings for cpRNFLT and choroidal MBR in patients with different causes of ON.

TABLE 2.

Comparison of ophthalmological findings after propensity score matching.

Groups Variable Values p‐Value

Control vs. NAAION

n = 24 vs. n = 24

 BCVA, logMAR −0.06 ± 0.10 vs. 1.14 ± 1.05 <0.001*
IOP, mmHg 14.05 ± 2.82 vs. 14.20 ± 3.76 0.880
CpRNFLT, μm 97.92 ± 10.14 vs. 179.33 ± 79.03 <0.001
Vascular cloud, AU 0.32 ± 0.07 vs. 0.28 ± 0.09 0.119 a

Control vs. ON

n = 59 vs. n = 59

 BCVA, logMAR −0.12 ± 0.08 vs. 1.13 ± 1.05 <0.001*
IOP, mmHg 15.61 ± 2.92 vs. 15.78 ± 3.04 0.766 a
CpRNFLT, μm 105.66 ± 11.13 vs. 148.82 ± 72.59 <0.001*
Vascular cloud, AU 0.34 ± 0.06 vs. 0.30 ± 0.07 0.002 a , *

Control vs. OAG

n = 110 vs. n = 110

 BCVA, logMAR −0.12 ± 0.09 vs. −0.06 ± 0.13 <0.001*
IOP, mmHg 15.13 ± 2.86 vs. 14.25 ± 3.14 0.013*
CpRNFLT, μm 103.70 ± 11.71 vs. 61.56 ± 20.84 <0.001*
Mean deviation, dB −0.61 ± 1.59 vs. −8.32 ± 6.64 <0.001*
Vascular cloud, AU 0.36 ± 0.07 vs. 0.33 ± 0.06 <0.001*

OAG vs. NAAION

n = 24 vs. n = 24

 BCVA, logMAR −0.02 ± 0.13 vs. 1.14 ± 1.05 <0.001*
IOP, mmHg 14.21 ± 2.84 vs. 14.20 ± 3.76 0.992 a
CpRNFLT, μm 58.16 ± 19.56 vs. 179.33 ± 79.03 <0.001*
Mean deviation, dB −7.77 ± 6.16 vs. – –
Vascular cloud, AU 0.35 ± 0.09 vs. 0.28 ± 0.09 0.005 a , *

OAG vs. ON

n = 59 vs. n = 59

 BCVA, logMAR −0.07 ± 0.11 vs. 1.13 ± 1.05 <0.001*
IOP, mmHg 14.68 ± 3.72 vs. 15.78 ± 3.04 0.022*
CpRNFLT, μm 66.01 ± 23.29 vs. 148.82 ± 72.59 <0.001*
Mean deviation, dB −8.42 ± 6.23 vs. – –
Vascular cloud, AU 0.37 ± 0.07 vs. 0.30 ± 0.07 <0.001 a , *
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Note: Propensity score matching was performed using age, sex, systolic blood pressure, diastolic blood pressure, pulse rate, hypertension, diabetes mellitus, dyslipidemia, heart disease, and sleep apnea syndrome as covariates.

Abbreviations: AU, arbitrary units; BCVA, best‐corrected visual acuity; cpRNFLT, circumpapillary retinal nerve fibre layer thickness; IOP, intraocular pressure; NAAION, non‐arteritic anterior ischemic optic neuropathy; OAG, open angle glaucoma; ON, optic neuritis.

a

t‐test.

*

Indicates statistical significance. Unmarked p values: Wilcoxon rank sum test.

FIGURE 2.

FIGURE 2

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Boxplots of LSFG parameters in the control, NAAION, ON, and OAG groups. The x‐axis shows the diagnosis, and the y‐axis shows the mean blur rate (MBR) value. The white boxes indicate the optic nerve head (ONH) vessel‐area MBR (MV), the light grey boxes indicate the ONH tissue‐area MBR (MT), and the grey boxes indicate the choroidal MBR. (a) Control vs. NAAION. The NAAION group, compared to the control group, shows a decrease in ONH‐MV (41.35 ± 6.37 vs. 30.26 ± 7.74 AU, p < 0.001), a decrease in ONH‐MT (12.46 ± 2.25 vs. 9.86 ± 3.12 AU, p = 0.002), and a decrease in choroidal MBR (7.42 ± 1.69 vs. 4.82 ± 1.91 AU, p < 0.001). (b) Control vs. ON. The ON group shows lower ONH‐MV (43.71 ± 6.73 vs. 38.49 ± 7.63 AU, p < 0.001) and lower choroidal MBR (8.04 ± 2.13 vs. 7.21 ± 2.49 AU, p = 0.022) compared to the control group, but no significant difference in ONH‐MT (12.17 ± 2.34 vs. 12.28 ± 2.34 AU, p = 0.773). (c) Control vs. OAG. The OAG group shows lower ONH‐MV (42.56 ± 6.63 vs. 37.91 ± 9.02 AU, p < 0.001), lower ONH‐MT (12.31 ± 2.01 vs. 9.80 ± 2.45 AU, p < 0.001), and lower choroidal MBR (7.99 ± 2.19 vs. 7.20 ± 2.88 AU, p < 0.001) compared to the control group. (d) OAG vs. NAAION. The NAAION group shows a decrease in ONH‐MV (38.52 ± 10.39 vs. 30.26 ± 7.74 AU, p = 0.003) and a decrease in choroidal MBR (7.63 ± 2.91 vs. 4.82 ± 1.91 AU, p < 0.001) compared to the OAG group, but no significant difference in ONH‐MT (9.70 ± 2.32 vs. 9.86 ± 3.12 AU, p = 0.838). (e) OAG vs. ON. The ON group does not show significant differences in ONH‐MV (39.78 ± 8.01 vs. 38.49 ± 7.63 AU, p = 0.372) or choroidal MBR (7.69 ± 3.12 vs. 7.21 ± 2.49 AU, p = 0.524) compared to the OAG group. In contrast, ONH‐MT is significantly lower in the OAG group, showing a decrease (12.28 ± 2.34 vs. 10.69 ± 2.92 AU, p < 0.001) compared to the ON group. *p < 0.05, **p < 0.01, ***p < 0.001.

FIGURE 3.

FIGURE 3

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Ocular examination data from representative cases. The examinations include, from left to right: Fundus photographs, optical coherence tomography (OCT) images, laser speckle flowgraphy (LSFG) colour map images, and Goldmann kinetic perimetry (GP) data. Control (72‐year‐old male): The fellow eye of a patient with secondary glaucoma caused by uveitis. Decimal best corrected visual acuity (BCVA) is 1.2, and intraocular pressure (IOP) is 14.3 mmHg. The fundus photograph, OCT image, LSFG colour map, and GP data are all normal. NAAION patient (80‐year‐old female): BCVA is 30 cm (counting fingers), and IOP is 8.0 mmHg. ONH swelling and soft exudates are observed in the fundus photograph and OCT image. Blood flow (BF) in the ONH large vessels, ONH tissue, and choroid are all greatly impaired. Almost complete visual field loss is observed in the GP data. ON patient (74‐year‐old male): Decimal BCVA is 0.6, IOP is 14.7 mmHg. ONH swelling is observed in the fundus photograph and OCT image. BF in the ONH large vessels and choroid is reduced, while BF in the ONH tissue is relatively preserved. The GP data show a parafoveal scotoma and enlargement of Marriott's scotoma. OAG patient (69‐year‐old female): Decimal BCVA is 1.5, IOP is 13.5 mmHg. There is cupping of the disc and loss of cpRNFLT. BF predominantly decreased in the temporal ONH tissue and peripapillary choroid. There is a corresponding nasal step defect in the visual field.

4. DISCUSSION

We used LSFG to measure ocular BF in the NAAION, ON, OAG, and control groups. The NAAION and OAG groups had lower BF in the ONH large vessels, ONH capillaries, and peripapillary choroid comapred to the control group. Additionally, the NAAION group had lower BF in the ONH large vessels and peripapillary choroid comapred to the OAG group. The ON group also showed lower BF in the ONH large vessels and choroid compared to the control group.

In this study, the NAAION group was older, had higher BP, and had a higher prevalence of systemic diseases such as HT, DM, DL, HD, and SAS, while the ON group primarily consisted of younger women. Previous reports have indicated that NAAION is more commonly observed in men over 50 years of age (Hattenhauer et al., 1997). Additionally, associations with systemic diseases have also been acknowledged (Deramo et al., 2003; Hayreh, 2009). Conversely, the ON group in this study predominantly included younger women, which consistent with prior reports (Beck et al., 1992). Since younger women are generally less likely to suffer from atherosclerotic diseases compared to older men, the lower occurrence of these diseases in this study is reasonable. The consistencies with previous reports suggest that we were able to recruit a suitable population.

In the NAAION group, BF was reduced in the ONH large vessels, ONH capillaries, and peripapillary choroid compared to the control group. The NAAION group also showed decreased BF in the ONH large vessels and peripapillary choroid compared to the OAG group. ONH‐MV reflects BF velocity in the ONH large vessels originating from the CRA, while ONH‐MT and choroidal MBR originate in the SPCAs (Aizawa, Nitta, et al., 2014; Wang et al., 2012). Despite ongoing debates around the exact pathophysiological mechanisms of NAAION, there is a consensus that, in addition to systemic background factors such as arteriosclerosis, ocular hypoperfusion during nocturnal hypotension is implicated in the disease onset (Hayreh, Joos, et al., 1994; Hayreh, Zimmerman, et al., 1994). LSFG might be a powerful tool to identify BF reduction in both the ONH and choroid that is potentially caused by upstream BF disturbance due to systemic conditions.

The OAG group showed lower values for all LSFG parameters compared to the control group, with BF in the ONH capillaries showing the most notable reduction, comparable to the NAAION group. Kawasaki et al. (2013) previously reported that narrowing of the retinal vessels may be a predictive factor for the onset of glaucoma. Furthermore, we have reported that BF in the ONH large vessels is reduced in eyes with glaucoma and that this reduction correlates with the severity of glaucoma, as represented by cpRNFLT and MD (Aizawa, Kunikata, et al., 2014; Chiba et al., 2011; Kiyota et al., 2019; Kiyota, Kunikata, et al., 2018). Additionally, we have noted that peripapillary choroidal BF has poor autoregulatory capacity and that lower peripapillary choroidal BF is associated with the progression of glaucoma (Kiyota et al., 2022; Kiyota, Shiga, et al., 2018). Nevertheless, we have already demonstrated that BF in the ONH capillaries most closely correlates with the severity of glaucoma (Aizawa, Kunikata, et al., 2014; Kiyota et al., 2022), which is consistent with our current findings. The site of lesion in glaucoma is believed to be at the level of the axons passing through the lamina cribrosa. Hence, while reductions in BF in the ONH large vessels and peripapillary choroid are also significant, monitoring BF in the ONH capillaries around the lamina cribrosa may provide more valuable insights for detecting glaucoma.

In the ON group, BF in the ONH capillaries was similar to the control group, but BF was reduced in the ONH large vessels and peripapillary choroid. BF in the ONH capillaries was higher than in the OAG group, while the ONH large vessels and peripapillary choroid showed no difference. In ON eyes, increased vascular resistance has previously been observed in the CRA and SPCA, and this aligns with the findings of reduced retinal and choroidal BF in the current study (Akarsu et al., 2004; Sebag et al., 1986). Interestingly, BF in the ONH capillaries, which are also supplied by the SPCA, did not show a notable decrease, even though the capillaries share their origin with the choroid. One potential explanation for this result may be the differences in autoregulatory capacity between the BF in the ONH and the choroid. Specifically, the ONH may possess stronger autoregulatory capabilities than the choroid (Kiyota, Shiga, et al., 2018; Luo et al., 2015), which could explain the lack of a significant decrease in ONH‐MT in eyes with ON in this study. Prior studies have noted a decrease in VC in paediatric ON (Hashimoto et al., 2018), manifesting as a blurred boundary between ONH‐MV and ONH‐MT, a pattern also observed in the ON group in this study. This suggests that segmenting the ONH large vessel area and the ONH tissue area might prevent a significant drop in measured ONH‐MT values.

In the ON group, cpRNFLT and choroidal BF were positively correlated. Interestingly, as shown in Table S2, the NMOSD group showed no or mild ONH swelling and mostly reduced choroidal MBR, which might be due to vasculitis (Takeshita et al., 2021). The MOGAD group showed the most severe ONH swelling, which is consistent with previous reports (Chen et al., 2022), and choroidal MBR showed no or mild decrease compared to the control group. The characteristics of these groups might have contributed to the observed positive correlation between choroidal MBR and cpRNFLT. Although it is challenging to make definitive statements from this data due to the small sample size, we believe it is a very interesting topic for future research.

This study has several limitations. First, we were unable to compare the NAAION and ON groups directly. In the future, we aim to increase the number of cases to compare them directly. Second, although the patients' medical history was retrospectively obtained from their medical charts, it was difficult to collect their treatment history and disease control status, which are also important factors for detailed adjustment. For example, a history of HT has been suggested to be associated with glaucoma (Bae et al., 2014), and treatment with calcium channel blockers might exacerbate glaucoma (Kastner et al., 2023). Nevertheless, as we had BP and PR data and used it for background adjustment in addition to a past history of disease, we believe that we were able to mitigate this limitation. Third, acute diseases like NAAION and ON may exhibit varying patterns of BF impairment between their acute and late stages. Various optic neuropathies can ultimately lead to optic nerve atrophy accompanied by vascular dropout in the late stage. Therefore, the timing of LSFG to study pathophysiology is crucial, yet adjusting it sufficiently can be challenging due to the retrospective nature of the data and the sometimes‐ambiguous onset of symptoms. In this study, we only included LSFG data when there were fundus findings that were typical of the acute phase to minimize this limitation. Fourth, the depth of the area where BF velocity is reflected by LSFG is not fully understood. MT, which is reported to reflect deep‐tissue‐area BF (Aizawa, Nitta, et al., 2014; Wang et al., 2012), may also include more superficial BF, and MV may reflect some deeper BF. It would be ideal if an LSFG device with depth information is developed in the future. Fifth, the impact of optic disc swelling on MBR values remains to be determined. Optic disc inflammation can obscure the boundary between the large vessel and tissue areas, potentially affecting ONH MBR values. Nonetheless, we also set the ROI outside the ONH and observed a decrease in choroidal BF in NAAION and ON, thus reinforcing the validity of our findings regarding BF impairment. Sixth, since this is a cross‐sectional study, it is unclear whether LSFG parameters can be used as disease state markers or for making prognoses. This is an important future direction that should be clarified in future longitudinal studies.

In conclusion, LSFG can be a useful noninvasive tool to differentiate NAAION, ON, and OAG by observing differences in the pattern of ocular BF impairment in the ONH large vessels, ONH capillaries, and choroid.

FUNDING INFORMATION

The authors declare no conflicts of interest related to this study. Financial support for this research was provided in part by the Japan Society for the Promotion of Science (JSPS) KAKENHI Grants‐in‐Aid for Scientific Research (B) (grant number: 17H04349; recipient: T.N.) and grants from the Center of Innovation Program (COI‐NEXT) by the Japan Science and Technology Agency (JST) (grant number: JPMJPF2201). The funders had no role in the design or conduct of the study, collection, management, analysis, or interpretation of the data, preparation, review, or approval of the manuscript, or the decision to submit the manuscript for publication.

Supporting information

Table S1

AOS-103-e49-s001.docx (27.4KB, docx)

Table S2

AOS-103-e49-s002.docx (18.1KB, docx)

ACKNOWLEDGEMENTS

The authors thank Mr. Tim Hilts for reviewing and editing the manuscript's language. We thank Kenji Okamoto of Softcare Co., Ltd. for his valuable comments on the manuscript. This work was presented at the 39th Meeting of the Japanese Society for Ocular Circulation on September 7, 2023, at the 77th Congress of Japan Clinical Ophthalmology on September 10, 2023, and at the 2024 ARVO Annual Meeting.

Yamaguchi, C. , Kiyota, N. , Himori, N. , Omodaka, K. , Tsuda, S. & Nakazawa, T. (2025) Differentiating optic neuropathies using laser speckle flowgraphy: Evaluating blood flow patterns in the optic nerve head and peripapillary choroid. Acta Ophthalmologica, 103, e49–e57. Available from: 10.1111/aos.16747

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Table S1

AOS-103-e49-s001.docx (27.4KB, docx)

Table S2

AOS-103-e49-s002.docx (18.1KB, docx)

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