July 2015
Volume 56, Issue 8
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Retina  |   July 2015
Sex-Related Differences in Ocular Blood Flow of Healthy Subjects Using Laser Speckle Flowgraphy
Author Affiliations & Notes
  • Kosei Yanagida
    Department of Ophthalmology Nagoya University Graduate School of Medicine, Nagoya, Japan
  • Takeshi Iwase
    Department of Ophthalmology Nagoya University Graduate School of Medicine, Nagoya, Japan
  • Kentaro Yamamoto
    Department of Ophthalmology Nagoya University Graduate School of Medicine, Nagoya, Japan
  • Eimei Ra
    Department of Ophthalmology Nagoya University Graduate School of Medicine, Nagoya, Japan
  • Hiroki Kaneko
    Department of Ophthalmology Nagoya University Graduate School of Medicine, Nagoya, Japan
  • Kenta Murotani
    Center for Advanced Medicine and Clinical Research, Nagoya University Hospital, Nagoya, Japan
  • Shigeyuki Matsui
    Department of Biostatistics, Nagoya University Graduate School of Medicine, Nagoya, Showa-ku, Japan
  • Hiroko Terasaki
    Department of Ophthalmology Nagoya University Graduate School of Medicine, Nagoya, Japan
  • Correspondence: Takeshi Iwase, Department of Ophthalmology, Nagoya University Graduate School of Medicine, 65 Tsurumai-cho, Showa-ku, Nagoya 466-8560, Japan; TsuyoshiIwase@aol.com
Investigative Ophthalmology & Visual Science July 2015, Vol.56, 4880-4890. doi:10.1167/iovs.15-16567
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      Kosei Yanagida, Takeshi Iwase, Kentaro Yamamoto, Eimei Ra, Hiroki Kaneko, Kenta Murotani, Shigeyuki Matsui, Hiroko Terasaki; Sex-Related Differences in Ocular Blood Flow of Healthy Subjects Using Laser Speckle Flowgraphy. Invest. Ophthalmol. Vis. Sci. 2015;56(8):4880-4890. doi: 10.1167/iovs.15-16567.

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

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Abstract

Purpose: To evaluate sex-related differences in ocular blood flow of healthy subjects using laser speckle flowgraphy (LSFG).

Methods: In this prospective cross-sectional study, we examined 103 healthy volunteers (47 males, 56 females; mean age: 39.3 ± 15.6 years and 42.1 ± 18.7 years, respectively). The blood flow to the optic nerve head (ONH) and choroid was assessed with LSFG, including mean blur rate (MBR) and pulse waveform variables. We evaluated sex-related differences in these variables and compared them with those in other clinical parameters.

Results: A linear single regression showed that the ONH-MBR (r = −0.402, P < 0.001) and five ONH pulse waveforms were significantly correlated with sex. A multiple stepwise regression analysis revealed that sex (β = 0.389, P < 0.001) and age (β = −0.290, P = 0.002) were independent factors, indicating the ONH-MBR, age (β = −0.394, P < 0.001), and subfoveal choroidal thickness (β = 0.221, P = 0.016) were independent factors indicating the choroidal MBR. Moreover, sex was an independent factor indicating the five ONH pulse waveform parameters that were consistent with results of the linear single regression. The optic nerve head MBR in the female group was significantly higher than that in the male group (P < 0.001), but no differences were observed in the choroid between the groups (P > 0.05).

Conclusions: Sex-related differences are present in ocular blood flow in the ONH, but not in the choroid in healthy subjects. We believe that these differences should be considered when interpreting blood flow data in ocular diseases.

Knowledge about ocular blood flow is essential for understanding the pathological conditions associated with and the treatment of various ocular diseases. The blood flow in the optic nerve head (ONH) has been reported to be reduced in some ocular diseases such as glaucoma,1 and impaired choroidal blood flow has been associated with various ocular diseases such as choroidal neovascularization,2 retinitis pigmentosa,3,4 and glaucoma.5,6 
Females have significantly lower mortality and morbidity from ischemic heart disease than males until after the age of menopause.7 However, the extent of symptomatic heart failure after myocardial infarction is higher in females in spite of smaller infarctions or better maintained left ventricular ejection fractions compared with similarly aged males.8,9 Hayward et al.10 reported that the central arterial pressure waveforms in females differed significantly from those in males as assessed by carotid artery tonometry. Sex differences in stroke have been observed across epidemiologic studies, pathophysiological findings, treatment approaches, and outcomes.11 These data raise the possibility that ocular blood flow also have sex-related differences. However, only a few reports have evaluated sex-related differences in choroidal blood flow1214 and none have evaluated ocular blood flow in the ONH or retina. 
Aging is associated with various changes in the vascular system at different structural and functional levels. At the macroscopic level, an increase in the arterial lumen size and arterial wall thickening, particularly of the intima, may be observed.15 These changes can cause arterial stiffening and are important risk factors for a broad range of cardiovascular and retinal vascular diseases, such as retinal artery occlusion, vein occlusion, and macular degeneration.1620 However, these age-related changes can obscure any sex-related differences. 
A variety of techniques for measuring retinal blood flow have been developed, including fluorescein angiography,21 radioactive microspheres,22 and hydrogen clearance.23 With many of the measurement techniques, time intensiveness or problems with reproducibility have hampered their widespread use. Scanning laser Doppler flowmetry (LDF)24 and color Doppler imaging can enable the quantification of the ocular circulation,25,26 but it is difficult to capture the same place and reproduce the same image because of the small capture area. One sophisticated approach is the measurement of blood velocities using laser Doppler velocimetry in addition to vessel diameters.27,28 For a long time, this was the only approach suitable for the measurement of retinal blood flow. However, clinical use of this technique is hampered by the time-intensive nature of the procedure. More recently, Doppler optical coherence tomography (OCT) technique,29 OCT angiography,30 and optical microangiography (OMAG)31,32 have been developed and can measure the blood flow on the ONH and retina using high-resolution depth-resolved imaging with high reproducibility. However, these techniques still have inherent limitations due to the time intensiveness of the procedure in clinical use, particularly in large-scale trials. 
Laser speckle flowgraphy (LSFG) is a noninvasive, real-time method used to measure the relative blood flow velocity in the ONH, retina, and choroid for 4 seconds.3335 Laser speckle flowgraphy can detect the pattern of the speckle contrast produced by the interference of illuminating laser light scattered by the movement of erythrocytes in the blood vessels and can measure the relative blood flow velocity as the mean blur rate (MBR) in the vessels3335; LSFG has been well correlated with actual blood flow values determined using the hydrogen gas clearance and microsphere methods,23,36 meaning the variables determined with LSFG would be comparable between individuals. The analysis software can separately calculate MBRs in the blood vessels and tissues (capillaries) of an entire ONH, and the measurements have excellent reproducibility,37 especially for the ONH.38 The reproducibility of MBR as assessed by the coefficient of variation (COV) was 3.4 on the ONH and 4.7 on choroid.39 
A recent update of the software embedded in the most recent LSFG (LSFG Analyzer, v. 3.1.6; Softcare Co., Ltd., Fukutsu, Japan) enables capturing of synchronized images from each cardiac cycle and derives various heartbeat waveform parameters. The mean blur rate pulse waveform may be a new target biomarker for the detection and evaluation of vascular and capillary aging in the retina. Several reports have described the relationship between these waveform parameters and age.4042 
If the variables determined with LSFG have sex-related differences even in healthy subjects, those from males and females should be separately considered. Therefore, understanding sex-related differences in healthy eyes is essential for the accurate analysis of retinal and choroidal diseases. The purpose of this study was to investigate the correlation of the variables determined using LSFG with sex in healthy subjects within a broad age range. 
Methods
Subjects and Testing Protocol
This was a prospective study, and the procedures used were approved by the Ethics Committee of Nagoya University Hospital. The procedures conformed to the tenets of the Declaration of Helsinki, and an informed consent was obtained from each subject after an explanation of the nature and possible consequences of the study. 
A total of 103 healthy Japanese volunteers with no ophthalmic or systemic diseases were studied. Only one eye per volunteer was randomly used for the measurements. All of the subjects had a best-corrected visual acuity of ≥20/20 and underwent a standard ophthalmic examination to confirm the absence of ocular diseases. Slit-lamp examinations and indirect ophthalmoscopy were used to examine the anterior and posterior segments of the eye. Subjects were also screened for any medical conditions that could influence the hemodynamics of the eye such as diabetes, hypertension, arrhythmia, and vascular diseases. The exclusion criteria included a history of ophthalmic or general disorders, ocular laser or incisional surgery in the experimental eye, topical, or systemic medications including hormonal medications, systolic blood pressure (SBP) > 130 mm Hg, diastolic blood pressure (DBP) > 85 mm Hg, and axial length (AL) > 26.5 mm.43 
All participants were asked to abstain from alcoholic and caffeinated beverages on the morning of the day of the examination because the intake of alcohol and caffeine can influence the intraocular pressure (IOP)44,45 and blood pressure.46,47 Thirty minutes before the examinations, 0.4% tropicamide/phenylephrine (Mydrin P; Santen Pharmaceutical Co., Ltd., Osaka, Japan) was used to dilate the pupil. The subjects rested for 10 to 15 minutes in a quiet dark room before the examination. All examinations were performed in the sitting position. The refractive error (spherical equivalent) was measured with an autorefractometer (KR8900; Topcon, Tokyo, Japan), and the axial lengths were measured with partial optical coherence interferometry (IOLMaster; Carl Zeiss Meditec, La Jolla, CA, USA). The intraocular pressure was measured with a handheld tonometer (Icare; Tiolat Oy, Helsinki, Finland). The systolic and diastolic blood pressures were measured at the left brachial artery at the height of the heart in a sitting position with an automatic sphygmomanometer (CH-483C; Citizen, Tokyo, Japan). The mean arterial blood pressure (MAP); mean ocular perfusion pressure (MOPP); and ocular diastolic perfusion pressure (ODPP) were calculated as follows: MAP = DBP + 1/3(SBP-DBP), MOPP = 2/3 MAP − IOP,48 and ODPP = SBP − IOP.49 
Laser Speckle Flowgraphy
The principles of LSFG have been described in detail.5053 Briefly, this instrument consists of a fundus camera equipped with an 830-nm diode laser as the light source and a standard charge-coupled device sensor (750 width × 360 height pixels) as the detector. After switching on the laser, a speckle pattern appears due to the interference of the light scattered by the movements of the erythrocytes. The mean blur rate is a measure of the relative blood flow velocity, and it is determined by examining the pattern of the speckle contrast produced by the erythrocytes in the ocular blood vessels. The mean blur rate images are acquired at a rate of 30 frames/s over a 4-second period. To evaluate the ONH and choroidal blood flow, a circle was set surrounding the ONH (Fig. 1A), and the center of a rectangle (250 × 250 pixels, degree: 6.31 × 6.31°) was placed at the fovea (Fig. 1B). The “vessel extraction” function of the software then identified the vessel and tissue areas on the ONH so that the MBR could be assessed separately. We evaluated the MBR in the three parts: overall, vessels, and tissue areas on the ONH. The software in the instrument was able to track the eye movements during the measurement period. The laser speckle flowgraphy was measured two times at each time point in all eyes. The average of the variables derived with LSFG was calculated. 
Figure 1
 
Representative composite color maps using the MBR as measured by LSFG. The red color indicates a high MBR and the blue color indicates a low MBR. To measure the MBR on the ONH blood flow and choroidal blood flow, a circle was set around the ONH (A) and the center of a rectangle was set at the fovea (250 × 250 pixels, degree: 6.31 × 6.31°) (B). Change in the MBR on the ONH in a pulse. White arrow indicates one pulse (C). Pulse waves showing changes in the MBR, which is tuned to cardiac cycle for 4 seconds. The total number of frames is 118 in a scan (D).
Figure 1
 
Representative composite color maps using the MBR as measured by LSFG. The red color indicates a high MBR and the blue color indicates a low MBR. To measure the MBR on the ONH blood flow and choroidal blood flow, a circle was set around the ONH (A) and the center of a rectangle was set at the fovea (250 × 250 pixels, degree: 6.31 × 6.31°) (B). Change in the MBR on the ONH in a pulse. White arrow indicates one pulse (C). Pulse waves showing changes in the MBR, which is tuned to cardiac cycle for 4 seconds. The total number of frames is 118 in a scan (D).
The laser speckle flowgraphy analyzer software enables capturing of synchronized images from each cardiac cycle and derives various heartbeat waveform parameters (Figs. 1C, 1D). The mean blur rate for the overall area of the ONH was used for the pulse waveform analysis. All eight parameters of the pulse waveform analysis of LSFG were included in this study (Fig. 2). The first skew, quantified the asymmetry of the waveform distribution and varied with the bias of the waveform shape (Fig. 2A). C is the constant of proportion. Skew is calculated in Equation 1: 
Figure 2
 
The characteristics of the pulse-waveform analysis. The pulse waves showed changes in the MBR. Skew quantified the asymmetry of the waveform's distribution (A). The skew became zero if the shape of the wave was completely symmetrical, whereas the skew became positive or negative if the waveform was distributed leftward or rightward of the center point of the waveform, respectively. The blowout score functioned as an indicator of the strength of the blood flow that was maintained in the vessel between heartbeats (B). The blowout time represented the time that the wave maintained more than half of the mean of the maximum and minimum MBR during a beat (C). The rising rate was derived from the rising area of the waveform (D). It was the ratio between the rising area (S1) and the entire area (Sall) before the peak. The falling rate was derived from the falling area of the waveform (E). It was the ratio between the falling area (S2) and the entire area (Sall) after the peak. The acceleration time index was derived from the ratio of the length of time before reaching the peak to the length of time over the entire heartbeat (F).
Figure 2
 
The characteristics of the pulse-waveform analysis. The pulse waves showed changes in the MBR. Skew quantified the asymmetry of the waveform's distribution (A). The skew became zero if the shape of the wave was completely symmetrical, whereas the skew became positive or negative if the waveform was distributed leftward or rightward of the center point of the waveform, respectively. The blowout score functioned as an indicator of the strength of the blood flow that was maintained in the vessel between heartbeats (B). The blowout time represented the time that the wave maintained more than half of the mean of the maximum and minimum MBR during a beat (C). The rising rate was derived from the rising area of the waveform (D). It was the ratio between the rising area (S1) and the entire area (Sall) before the peak. The falling rate was derived from the falling area of the waveform (E). It was the ratio between the falling area (S2) and the entire area (Sall) after the peak. The acceleration time index was derived from the ratio of the length of time before reaching the peak to the length of time over the entire heartbeat (F).
where the variable N represents the frame number, and the changing MBR waveform of a beat is divided into N frames. The variable m(k) is the average of MBR in the k-th frame. Max represents the maximum MBR value and min is the minimum MBR value in Equation 4. 
The blowout score (BOS) indicates the blood flow volume that is maintained in the vessel between each heartbeat (Fig. 2B); BOS is calculated in Equation 4:    
The blowout time (BOT) is an indicator that represents the length of time that the wave maintained more than half of the mean of the maximum and minimum MBR during a beat. A high BOT indicated that the blood flow remained at a high level for a long time between heartbeats and that the peripheral area received sufficient amounts of blood (Fig. 2C). Blowout time is calculated in Equation 5:     
The rising rates and falling rates are determined using the increasing and decreasing sections of the MBR waveform for a beat, respectively. The rising rate is defined as the ratio between the waveform area before the peak (S1) and the entire area before the peak (Fig. 2D). The falling rate is defined as the ratio after the peak between S2 and Sall (Fig. 2E). The rising rates and falling rates are calculated in Equations 7 and 8:   The flow acceleration index (FAI) is calculated from the maximum change among all frames (1/30 s) in a rising curve (Fig. 2F); FAI is calculated in Equation 9:  
The acceleration time index (ATI) is derived from a ratio of the duration of time taken before reaching the peak to the duration of time for the entire heartbeat (Fig. 2G); ATI is calculated in Equation 10:    
Finally, the resistivity index is calculated by dividing the difference of the maximum and minimum MBR by the maximum MBR (Fig. 2H). The resistivity index is calculated in Equation 11:    
Statistical Analysis
The values of each parameter were presented as the mean ± SD. Independent t-tests were used to compare normally distributed data. Spearman's rank test was used to determine the correlation coefficients between the variables. Stepwise multiple regression analyses were used to determine independent factors affecting the parameters of the pulse waveform analyses. Multiple logistic regression analysis was used to determine the association between sex and the parameters of the pulse waveform analyses. All statistical analyses were performed using statistical software (SPSS Statistics for Windows, Version 22.0; IBM Corp., Armonk, NY, USA). The significance level was set at P < 0.05. 
Results
The demographic data of all of the subjects are shown in Table 1. Forty-seven males (mean age, 39.3 ± 15.6 years) and 56 females (mean age, 42.1 ± 18.7 years) were examined. No significant differences were observed between the groups in the ocular and systemic parameters, except for SBP, which was significantly higher in the male group than in the female group (P = 0.044). 
Table 1
 
Clinical Characteristics of all Subjects
Table 1
 
Clinical Characteristics of all Subjects
Table 2 shows the linear single regression results. The various parameters, in particular, the ONH-MBR in the overall area, were correlated with sex (r = −0.402, P < 0.001). Although the MBRs in the vessel and tissue areas on the ONH were significantly different between the male group and the female group (P < 0.01, P < 0.001, respectively), similar to the MBR in the overall area of the ONH, the difference in the latter was most significant. Accordingly, only the MBR in the overall area on the ONH was used for multiple regression analysis and the pulse waveform analysis in this study. In all, five ONH pulse waveform parameters were correlated with sex (Table 2). In particular, BOS (r = 0.394, P < 0.001); FAI (r = −0.345, P < 0.001); ATI (r = −0.387, P < 0.001); and resistivity index (r = −0.393, P < 0.001) were strongly correlated with sex. 
Table 2
 
Result of Spearman's Rank Correlation Coefficient Between the MBRs and Clinical Parameters
Table 2
 
Result of Spearman's Rank Correlation Coefficient Between the MBRs and Clinical Parameters
The mean blur rates of the overall area on the ONH (r = −0.257, P < 0.001) and choroid (r = −0.299, P < 0.001) were correlated with age. In addition, six of the ONH pulse waveform parameters were correlated with age. Particularly, the BOS (r = −0.426, P < 0.001), BOT (r = −0.549, P < 0.001), falling rate (r = 0.527, P < 0.001), ATI (r = 0.532, P < 0.001), and resistivity index (r = 0.406, P < 0.001) were strongly correlated with age. The parameters of the pulse waveform analysis also correlated with the circulation factors (e.g., BP and heart rate [HR]), but none were correlated with IOP or subfoveal choroidal thickness (SFCT). 
The multiple stepwise regression analysis revealed that sex (β = 0.389, P < 0.001) and age (β = −0.290, P = 0.002) were independent factors indicating the ONH-MBR (Table 3), and that age (β = −0.394, P < 0.001) and SFCT (β = 0.221, P = 0.016) were independent factors indicating choroidal MBR (Table 4). 
Table 3
 
Results of Multiple Stepwise Regression Analysis for Independence of Factors Contributing to ONH-MBR
Table 3
 
Results of Multiple Stepwise Regression Analysis for Independence of Factors Contributing to ONH-MBR
Table 4
 
Results of Multiple Stepwise Regression Analysis for Independence of Factors Contributing to Choroid MBR
Table 4
 
Results of Multiple Stepwise Regression Analysis for Independence of Factors Contributing to Choroid MBR
Table 5 shows only the significant independent factors indicating each ONH pulse waveform parameter in the stepwise multiple regression analysis. The analysis revealed that heart rate (β = −0.461, P < 0.001) and age (β = 0.249, P = 0.005) were independent factors indicating skew, and that age (β = −0.514, P < 0.001); MAP (β = 0.321, P < 0.001); sex (β = −0.296, P < 0.001); and heart rate (β = 0.275, P = 0.001) were independent factors indicating the BOS. The analysis also determined that age (β = −0.550, P < 0.001) and heart rate (β = 0.210, P = 0.012) were independent factors indicating the BOT, that heart rate (β = −0.461, P < 0.001) and sex (β = 0.249, P < 0.001) were independent factors indicating the rising rate, and that age (β = −0.461, P < 0.001) was an independent factor indicating the falling rate. The regression also found that MAP (β = −0.440, P < 0.001); sex (β = 0.220, P = 0.011); age (β = −0.183, P = 0.038); and heart rate (β = 0.179, P = 0.039) were independent factors indicating the FAI, that age (β = 0.432, P < 0.001); sex (β = 0.416, P < 0.001); heart rate (β = 0.224, P = 0.001); and MAP (β = 0.204, P = 0.006) were independent factors indicating the ATI, and that age (β = 0.494, P < 0.001); MAP (β = −0.314, P < 0.001); heart rate (β = −0.342, P < 0.001); and sex (β = 0.306, P < 0.001) were independent factors indicating the resistivity index. 
Table 5
 
Results of Multiple Stepwise Regression Analysis for Independence of Factors Contributing to Pulse Waveform Para
Table 5
 
Results of Multiple Stepwise Regression Analysis for Independence of Factors Contributing to Pulse Waveform Para
Figure 3 demonstrates that the intercept of the regression line of the MBR in the older age group (>45 years) was steeper than that in the younger age group (≤45 years) in the female group (A), and the intercept of the regression line of the MBR was very similar between the males and females in the older age group (>45 years; [B]). 
Figure 3
 
Relationship between the age and ONH-MBR in male and female groups. The intercept of the regression line of the ONH-MBR in the older age group (>45 years) was steeper than that in the younger age group (≤45 years) in the female group (A), and the intercept of the regression line of the MBR was similar between the males and females in the older age groups (>45 years) (B).
Figure 3
 
Relationship between the age and ONH-MBR in male and female groups. The intercept of the regression line of the ONH-MBR in the older age group (>45 years) was steeper than that in the younger age group (≤45 years) in the female group (A), and the intercept of the regression line of the MBR was similar between the males and females in the older age groups (>45 years) (B).
Figure 4 shows that the MBR on the ONH in the female group was significantly higher than that in the male group (P < 0.001), though there were no differences in the choroid between the groups (P > 0.05). 
Figure 4
 
Differences between sexes in the MBR determined by LSFG. The mean blur rate of the ONH in the female group was significantly higher than that in the male group (P < 0.001). No significant differences were observed in the choroidal MBR. NS, no significant difference.
Figure 4
 
Differences between sexes in the MBR determined by LSFG. The mean blur rate of the ONH in the female group was significantly higher than that in the male group (P < 0.001). No significant differences were observed in the choroidal MBR. NS, no significant difference.
Figure 5 shows that the BOS was significantly higher in the male group than in the female group (P < 0.001). The rising rate (P = 0.016), the FAI (P < 0.001), the ATI (P < 0.001) and the resistivity index (P < 0.001) were significantly higher in the female group than in the male group. 
Figure 5
 
Differences between sexes in pulse waveform parameters determined by LSFG. The blowout score was significantly higher in the male group than in the female group. The rising rate, the FAI, the ATI, and the resistivity index (P < 0.001) were significantly higher in the female group than in the males group.
Figure 5
 
Differences between sexes in pulse waveform parameters determined by LSFG. The blowout score was significantly higher in the male group than in the female group. The rising rate, the FAI, the ATI, and the resistivity index (P < 0.001) were significantly higher in the female group than in the males group.
Discussion
A linear single regression showed that the ONH-MBR, the BOS, the rising rate, the FAI, the ATI, and the resistivity index were correlated with sex. The multiple stepwise regression analysis revealed that sex was an independent factor indicating the ONH-MBR and the five ONH pulse waveform parameters, and the results are consistent with that in the linear single regression model. The optic nerve head–mean blur rate was significantly higher in the female group than that in the male group, but no significant differences were observed in the choroidal MBR between males and females. The blowout score was significantly higher in the male group than in the female group, and the rising rate, the FAI, the ATI, and the resistivity index were significantly higher in the female group than in the male group. To the best of our knowledge, this is the first report demonstrating sex-related differences in the blood flow of the ONH. 
Females had significantly lower SBP in the present study. In general, females have lower brachial and ankle SBPs and a lower ankle–arm pressure index than age-matched males.54 Our stepwise multiple regression analysis revealed sex-related differences, meaning that the difference was present, even if the influence of the lower SBP and age was excluded. 
Figure 6 shows representative ONH-MBR waveforms from male (A) and female (B) volunteers, and a comparison that highlighted the changes to it over a beat (C). The maximum and minimum MBRs were higher in the female group, and a greater increment of the MBR to the peak was observed in the female group. In addition, the peak time of the MBR was not very different between the groups, although the number of frames was smaller in the female group because the heart rate was relatively higher; this caused lower numbers of MBR frames per beat in the female group. In general, the heart rates in females are higher than in males.10 Taken together, the female group had an exponential increment in MBR, which resulted in steeper and higher peaks than in the males group. Those differences may have caused the significant differences in the sex-related differences in the pulse waveforms. 
Figure 6
 
Representative ONH-MBR waveforms from in male (A) and female (B) volunteers, and a comparison highlighting the changes to it over a beat (C). The maximum and minimum MBRs were higher in the female group, and a greater increment of the MBR to the peak was observed in the female group. In addition, the peak time of the MBR was almost same between the groups, although the number of frames was lower in the female group (B) because the heart rate was higher in the female group.
Figure 6
 
Representative ONH-MBR waveforms from in male (A) and female (B) volunteers, and a comparison highlighting the changes to it over a beat (C). The maximum and minimum MBRs were higher in the female group, and a greater increment of the MBR to the peak was observed in the female group. In addition, the peak time of the MBR was almost same between the groups, although the number of frames was lower in the female group (B) because the heart rate was higher in the female group.
The flow acceleration index described the maximum change among all frames in a rising curve, and the rising rate is defined as the ratio between the waveform area before the peak (S1) and the entire area before the peak (Fig. 2F). Those parameters were significantly higher in the female group than in the male group. As the representative figure shows, the MBR increased exponentially to a higher peak in the female group, causing the significantly higher FAI and rising rates. 
The blowout score was calculated from the difference in the maximum and minimum MBR and the mean ONH-MBR (Fig. 2B). The mean ONH-MBR was greater in the female group, which meant that the BOS should be higher in the female group if the differences in the maximum and minimum MBRs were the same between sexes. However, the BOS was significantly lower in the female group, because the increment in the MBR was much higher in the female group. Also, the greater increment in the MBR resulted in a higher resistivity index in the female group, because the resistivity index was calculated by dividing the difference of the maximum and minimum MBR by the maximum MBR. 
The acceleration time index was derived from a ratio of the length of time before reaching the peak to the length of time for the entire heartbeat. In the present study, the heart rate was relatively higher in the female group. As a result, the higher heart rate caused fewer MBR frames per beat in the female group. On the other hand, the peak time of the MBR was not very different between the groups. Consequently, the ATI was higher in the female group. 
The pulse waveform should be related to several factors (e.g., perfusion pressure, peripheral vessel resistance, and blood features). The perfusion pressure is closely associated with the SBP. In general, patients with hypertension have steeper and higher peaks in the pulse wave velocity.55 Despite having volunteers who were taking medicines for hypertension, SBP values of >130 mm Hg or DBP values of >85 mm Hg were excluded from this study; the peak was steeper and higher in the female group. Even the SBP was significant lower and MOPP was lower in the female group. The mean blur rate and the pulse waveform parameters were based on the movement of erythrocytes in the ocular blood vessels. Taken together, erythrocytes can move faster in the ocular vessels in females, at least on the ONH, although the perfusion pressures were not higher. Accordingly, females should have different blood features than the males. 
In other organs, especially in the brain, a higher blood flow velocity has been reportedly observed in females. Males had lower cerebral blood flow velocity compared with females up to the age of 80 years.56 Vavilala et al.57 reported that females had higher flow velocities in both the basilar and middle cerebral arteries. Azhim et al.58 reported significant sex-related differences in the blood flow velocity in the common carotid artery. 
The specific features of blood flow in females, such as a faster erythrocyte flow with a higher heart rate, may be related to lower numbers of cardiovascular events. When looking at ocular diseases that have been associated with thromboembolic events, there has been some evidence that they may happen more frequently in males than in females. A large longitudinal study carried out in the United States found that sex female was protective against central retinal vein occlusion (CRVO).59,60 Retinal emboli, which are a risk factor for stroke, have been seen more frequently in males than in females.61 
There are several possible explanations for the differences in the ONH-MBR and pulse waveforms between sexes. First, it could be related to biological properties such as lower body height and size with higher heart rates and lower cardiac outputs in females.62 Shorter stature places the arterial pulse reflecting sites closer to the heart and brings the reflected wave back into the central aorta earlier in systole with a resultant decrease in pulse amplification. Second, the difference between sexes could be derived from the hormonal status, such as the presence of estrogen or testosterone. Rodriguez et al.63 found a significantly higher cerebral blood flow in premenopausal females compared with age-matched males. There are several reports that serum sex hormone levels were related to blood flow velocities and resistive indices.14,64 In the ophthalmologic field, a study investigating retrobulbar blood velocities found higher values for velocity in the ophthalmic artery and lower values in the short posterior ciliary artery in males compared with females in the younger age group (<40 years).65 Harris–Yitzhak et al.66 suggested that the extrabulbar branches of the ophthalmic artery may be responsible for this decrease in vascular resistance caused by estrogen. Our study showed that the intercept of the regression line of the MBR in the older age group was steeper than that in the younger age group (≤45 years) in the female group and that the intercepts of the regression lines of the MBR in the older male and female groups were very similar, suggesting that a change in hormone status, such as menopause, could affect the blood flow on the ONH. Third, it may be because of the hemoglobin concentration, which is significant lower in females in general. In the circumstance, faster movement of erythrocyte, causing steeper and higher peak, should be required to supply oxygen to tissue. Those complex factors would provide sex-related differences in the MBR of the ONH. 
In contrast to the ONH-MBR and pulse waveforms, no significant differences were observed in the choroidal MBR between sexes. There have been some reports which showed significantly higher choroidal blood flow in females aged <40 years than those aged >55 years with LDF.12 The cause of the discrepancy between those reports and our results regarding choroidal blood flow is unclear. However, the possibility cannot be denied that the choroid MBR derived from LSFG does not reflect correct blood flow, resulting in no significant difference, because blood flow on the ONH-MBR in this study and in other organs is different between sexes.5658 
Our multiple regression analysis revealed that age was an independent factor indicating the ONH, choroid MBR and six ONH pulse waveforms. The blood flow on the ONH38,6769 or choroid,70 measured in healthy subjects using LDF6770 and LSFG,38 reportedly had a negative correlation with age. In addition, retrobulbar vessels and retinal perfusion also showed a decrease with age.71 Aging leads to arteriosclerosis and reduction of elastic fibers, hardening the arterial wall. 
Figure 7 demonstrates that the falling rate, the skew, and the BOT were not correlated with sex; however, all three pulse waveforms were correlated with age. Based on the subjects' age, our results were consistent with the results from Tsuda et al.,38 which were that skew, BOT, and falling rate had a strong correlation with age. Vascular aging in the artery caused steepening and heightening of the peak of the blood flow waveform, and led to a faster drop-off in blood flow after the peak.72,73 Those three pulse waveforms were affected by the phenomenon of a faster drop-off in blood flow after the peak during a beat. Accordingly, the skew, BOT, and falling rate could detect a reflection in the MBR waveform of vascular changes from aging. Furthermore, only the falling rate was not correlated with sex or the circulation parameters; this differed from the skew and the BOT that were correlated with the circulation parameters (e.g., heart rate and blood pressure). This was because the falling rate can directly detect a faster drop-off in blood flow, and suggested that the falling rate should be the most sensitive parameter for the evaluation of vascular aging in the LSFG pulse waveform. 
Figure 7
 
A Venn diagram showing which pulse waveforms were shared by sex, age, and circulation factors (e.g., HR and BP).
Figure 7
 
A Venn diagram showing which pulse waveforms were shared by sex, age, and circulation factors (e.g., HR and BP).
Laser speckle flowgraphy can assess retinal blood flow for each retinal vessel as relative flow volume.74 However, the value depends on the distance from the ONH and it is meaningless to compare it between the individuals. In addition, the reproducibility for the retinal vessel is lower than the ONH and choroid using LSFG.39 Thus, we did not evaluate sex-related differences in ocular blood flow of the retinal vessel. 
Our study was limited by the small sample size, which resulted in an insufficient number of participants for comparing the ocular blood flow between pre- and postmenopausal volunteers. In addition, serum data (e.g., estrogen and testosterone, which can affect blood flow), were not measured and not compared with the various parameters derived from LSFG. Although eyes with axial length > 26.5 mm were excluded from this study, some eyes had myopia > 5 diopters (D). It is not denied that more specific data associated with sex-related differences could be obtained, if eyes with myopia > 5 D were excluded. Tropicamide/phenylephrine was used to dilate the pupil but phenylephrine may influence the ONH and choroid circulation.75 Further studies with laboratory data from a large number of healthy subjects using tropicamide for dilation will be necessary to determine the mechanism of sex-related differences on ocular blood flow. 
In conclusion, we revealed significant sex-related differences in the blood flow on the ONH in healthy subjects with LSFG. Multiple stepwise regression analyses revealed that sex was independent factor indicating the ONH-MBR and the five ONH pulse waveforms. The mean blur rate on the ONH was significantly higher in females than in males, but no significant differences were observed in the choroidal MBR between sexes. We believe that our results of sex-related differences need to be considered when interpreting blood flow data in eyes with diseases such as diabetes retinopathy, retinal vein occlusion, and glaucoma. 
Acknowledgments
Supported by a Grant-in-Aid for Scientific Research (C) (TI), Grant-in-Aid for Young Scientists (A) (HK) and a Grant-in-Aid for Scientific Research (B) (HT). 
Disclosure: K. Yanagida, None; T. Iwase, None; K. Yamamoto, None; E. Ra, None; H. Kaneko, None; K. Murotani, None; S. Matsui, None; H. Terasaki, None 
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Figure 1
 
Representative composite color maps using the MBR as measured by LSFG. The red color indicates a high MBR and the blue color indicates a low MBR. To measure the MBR on the ONH blood flow and choroidal blood flow, a circle was set around the ONH (A) and the center of a rectangle was set at the fovea (250 × 250 pixels, degree: 6.31 × 6.31°) (B). Change in the MBR on the ONH in a pulse. White arrow indicates one pulse (C). Pulse waves showing changes in the MBR, which is tuned to cardiac cycle for 4 seconds. The total number of frames is 118 in a scan (D).
Figure 1
 
Representative composite color maps using the MBR as measured by LSFG. The red color indicates a high MBR and the blue color indicates a low MBR. To measure the MBR on the ONH blood flow and choroidal blood flow, a circle was set around the ONH (A) and the center of a rectangle was set at the fovea (250 × 250 pixels, degree: 6.31 × 6.31°) (B). Change in the MBR on the ONH in a pulse. White arrow indicates one pulse (C). Pulse waves showing changes in the MBR, which is tuned to cardiac cycle for 4 seconds. The total number of frames is 118 in a scan (D).
Figure 2
 
The characteristics of the pulse-waveform analysis. The pulse waves showed changes in the MBR. Skew quantified the asymmetry of the waveform's distribution (A). The skew became zero if the shape of the wave was completely symmetrical, whereas the skew became positive or negative if the waveform was distributed leftward or rightward of the center point of the waveform, respectively. The blowout score functioned as an indicator of the strength of the blood flow that was maintained in the vessel between heartbeats (B). The blowout time represented the time that the wave maintained more than half of the mean of the maximum and minimum MBR during a beat (C). The rising rate was derived from the rising area of the waveform (D). It was the ratio between the rising area (S1) and the entire area (Sall) before the peak. The falling rate was derived from the falling area of the waveform (E). It was the ratio between the falling area (S2) and the entire area (Sall) after the peak. The acceleration time index was derived from the ratio of the length of time before reaching the peak to the length of time over the entire heartbeat (F).
Figure 2
 
The characteristics of the pulse-waveform analysis. The pulse waves showed changes in the MBR. Skew quantified the asymmetry of the waveform's distribution (A). The skew became zero if the shape of the wave was completely symmetrical, whereas the skew became positive or negative if the waveform was distributed leftward or rightward of the center point of the waveform, respectively. The blowout score functioned as an indicator of the strength of the blood flow that was maintained in the vessel between heartbeats (B). The blowout time represented the time that the wave maintained more than half of the mean of the maximum and minimum MBR during a beat (C). The rising rate was derived from the rising area of the waveform (D). It was the ratio between the rising area (S1) and the entire area (Sall) before the peak. The falling rate was derived from the falling area of the waveform (E). It was the ratio between the falling area (S2) and the entire area (Sall) after the peak. The acceleration time index was derived from the ratio of the length of time before reaching the peak to the length of time over the entire heartbeat (F).
Figure 3
 
Relationship between the age and ONH-MBR in male and female groups. The intercept of the regression line of the ONH-MBR in the older age group (>45 years) was steeper than that in the younger age group (≤45 years) in the female group (A), and the intercept of the regression line of the MBR was similar between the males and females in the older age groups (>45 years) (B).
Figure 3
 
Relationship between the age and ONH-MBR in male and female groups. The intercept of the regression line of the ONH-MBR in the older age group (>45 years) was steeper than that in the younger age group (≤45 years) in the female group (A), and the intercept of the regression line of the MBR was similar between the males and females in the older age groups (>45 years) (B).
Figure 4
 
Differences between sexes in the MBR determined by LSFG. The mean blur rate of the ONH in the female group was significantly higher than that in the male group (P < 0.001). No significant differences were observed in the choroidal MBR. NS, no significant difference.
Figure 4
 
Differences between sexes in the MBR determined by LSFG. The mean blur rate of the ONH in the female group was significantly higher than that in the male group (P < 0.001). No significant differences were observed in the choroidal MBR. NS, no significant difference.
Figure 5
 
Differences between sexes in pulse waveform parameters determined by LSFG. The blowout score was significantly higher in the male group than in the female group. The rising rate, the FAI, the ATI, and the resistivity index (P < 0.001) were significantly higher in the female group than in the males group.
Figure 5
 
Differences between sexes in pulse waveform parameters determined by LSFG. The blowout score was significantly higher in the male group than in the female group. The rising rate, the FAI, the ATI, and the resistivity index (P < 0.001) were significantly higher in the female group than in the males group.
Figure 6
 
Representative ONH-MBR waveforms from in male (A) and female (B) volunteers, and a comparison highlighting the changes to it over a beat (C). The maximum and minimum MBRs were higher in the female group, and a greater increment of the MBR to the peak was observed in the female group. In addition, the peak time of the MBR was almost same between the groups, although the number of frames was lower in the female group (B) because the heart rate was higher in the female group.
Figure 6
 
Representative ONH-MBR waveforms from in male (A) and female (B) volunteers, and a comparison highlighting the changes to it over a beat (C). The maximum and minimum MBRs were higher in the female group, and a greater increment of the MBR to the peak was observed in the female group. In addition, the peak time of the MBR was almost same between the groups, although the number of frames was lower in the female group (B) because the heart rate was higher in the female group.
Figure 7
 
A Venn diagram showing which pulse waveforms were shared by sex, age, and circulation factors (e.g., HR and BP).
Figure 7
 
A Venn diagram showing which pulse waveforms were shared by sex, age, and circulation factors (e.g., HR and BP).
Table 1
 
Clinical Characteristics of all Subjects
Table 1
 
Clinical Characteristics of all Subjects
Table 2
 
Result of Spearman's Rank Correlation Coefficient Between the MBRs and Clinical Parameters
Table 2
 
Result of Spearman's Rank Correlation Coefficient Between the MBRs and Clinical Parameters
Table 3
 
Results of Multiple Stepwise Regression Analysis for Independence of Factors Contributing to ONH-MBR
Table 3
 
Results of Multiple Stepwise Regression Analysis for Independence of Factors Contributing to ONH-MBR
Table 4
 
Results of Multiple Stepwise Regression Analysis for Independence of Factors Contributing to Choroid MBR
Table 4
 
Results of Multiple Stepwise Regression Analysis for Independence of Factors Contributing to Choroid MBR
Table 5
 
Results of Multiple Stepwise Regression Analysis for Independence of Factors Contributing to Pulse Waveform Para
Table 5
 
Results of Multiple Stepwise Regression Analysis for Independence of Factors Contributing to Pulse Waveform Para
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