Kazunori Hirasawa

Identifying "preperimetric" glaucoma in standard automated perimetry visual fields.

PURPOSE To compare the visual fields (VFs) of preperimetric open angle glaucoma (OAG) patients (preperimetric glaucoma VFs, PPGVFs) with the VFs of healthy eyes, and to discriminate these two groups by using the Random Forests machine-learning method. METHODS All VFs before a first diagnosis of manifest glaucoma (Anderson-Patellas criteria) were classified as PPGVFs. Series of VFs were obtained with the Humphrey Field Analyzer 30-2 program from 171 PPGVFs from 53 eyes in 51 OAG or OAG suspect patients and 108 healthy eyes of 87 normal subjects. The area under the receiver operating characteristic curve (AROC) in discriminating between PPGVFs and healthy VFs was calculated by using the Random Forests method, with 52 total deviation (TD) values, mean deviation (MD), and pattern standard deviation (PSD) as predictors. RESULTS There was a significant difference in MD between healthy VFs and PPGVFs (-0.03 ± 1.11 and -0.91 ± 1.56 dB [mean ± standard deviation], respectively; P < 0.001, linear mixed model) and in PSD (1.56 ± 0.33 and 1.97 ± 0.43 dB, respectively; P < 0.001). A significant difference was observed in the TD values between healthy VFs and PPGVFs at 25 (P < 0.001) of 52 test points (linear mixed model). The AROC obtained by using the Random Forests method was 79.0% (95% confidence interval, 73.5%-84.5%). CONCLUSIONS Differences exist between healthy VFs and VFs of preperimetric glaucoma eyes, which go on to develop manifest glaucoma; these two groups of VFs could be well distinguished by using the Random Forests classifier.

Learning Effect and Repeatability of Automated Kinetic Perimetry in Healthy Participants

Abstract Purpose: To evaluate the learning effect and repeatability of automated kinetic perimetry in inexperienced and experienced healthy young participants. Methods: Forty-six eyes of 46 healthy participants (23 eyes of 23 participants in the inexperienced group and 23 eyes of 23 participants in the experienced group; mean age, 25.9 years) were enrolled in this prospective study. Automated kinetic perimetry was performed using the Octopus 900 perimeter with Goldmann stimuli III4e, I4e, I3e, I2e and I1e. The participants underwent testing at 14 predetermined meridians for each stimulus with a stimulus velocity of 3°/s. The learning effect was evaluated for kinetic sensitivity and test duration using three measurements. Repeatability was evaluated by calculating the mean square (MS) and coefficient of variance (CoV) of the kinetic sensitivity between the second and third measurements. Results: A learning effect was seen only in the inexperienced group between the first and second measurements. The kinetic sensitivity for III4e and I4e increased by 1.5° (p < 0.01) and 1.1° (p = 0.02), respectively, and the test duration decreased to 20.1 seconds (p = 0.02). There was no demonstrated learning effect in the inexperienced and experienced groups between the second and third measurements. Regarding the repeatability in the inexperienced and experienced groups, the MS and CoV values of the kinetic sensitivity for I3e, I2e and I1e increased by a median of 1.2–2.7° (p < 0.01) and 1.6–13.6% (p < 0.01), respectively, compared with those of III4e and I4e. Conclusion: The results of the first measurement in the inexperienced participants require careful evaluation, especially for III4e and I4e measured in the peripheral areas. However, because III4e and I4e both showed good repeatability in inexperienced and experienced participants, automated kinetic perimetry may be suitable for measuring the peripheral area using higher stimulus intensities such as III4e and I4e.

Assessing Visual Fields in Patients with Retinitis Pigmentosa Using a Novel Microperimeter with Eye Tracking: The MP-3

Purpose The purpose of the current study is to investigate the test-retest reproducibility of visual fields (VFs) measured with the MP-3 microperimeter, in patients with retinitis pigmentosa (RP). Method VFs were twice measured with the MP-3 and also the Humphrey Field Analyzer, using the 10–2 test grid pattern in both perimeters, in 30 eyes (15 right and 15 left eyes) of 18 RP patients (11 males and 7 females). Test-retest reproducibility was assessed using the mean absolute deviation (MAD) measure at all 68 points in the test grid. Reproducibility was also evaluated using the intraclass correlation coefficient (ICC) of VF sensitivities. Result The mean sensitivity measured in the HFA 10–2 was significantly higher than that measured in the MP-3 in both the first and second VF tests (p <0.0001, linear mixed model). The MAD was 2.4±0.6 [1.1 to 3.6] dB for MP-3 and 2.4±0.9 [1.1 to 5.1] dB for HFA 10–2, which was not significantly different (p = 0.76, linear mixed model). The ICC value associated with the MP-3 VFs was 0.81±0.13 [0.49 to 0.98], which was significantly larger than that observed for the HFA 10–2 VFs: 0.77±0.19 [0.20 to 0.94] (p = 0.043, linear mixed model). Conclusion The MP-3 microperimeter appears to be useful to evaluate central visual function in RP eyes, exhibiting test-retest reproducibility that is equal to, or better than, that observed in HFA 10–2 VFs.

The Relationship Between Visual Acuity and the Reproducibility of Visual Field Measurements in Glaucoma Patients.

PURPOSE The purpose of this study was to investigate the association between visual acuity (VA) and reproducibility of test-retest visual field (VF) measurements in glaucoma patients. METHODS Subjects were comprised of 627 eyes of 627 open-angle glaucoma patients. The reproducibility of two Humphrey VFs (24-2 or 30-2 Swedish Interactive Threshold Algorithm tests) examined twice within the period of 3 months was calculated using the root mean squared error (RMSE) of each VF test points sensitivity. Visual acuity was measured once at the time of either of the VF measurements. Linear modeling was used to investigate the relationship between reproducibility of VF tests (RMSE) and the following variables: mean total deviation value (mTD), fixation losses (FLs), false positives (FPs), false negatives (FNs), refractive error, age, and VA. RESULTS The optimal model to predict test-retest variability (RMSE) of VFs included age, VA, mTD, and FNs as dependent variables. Root mean squared error was significantly larger in eyes with logMAR VA > 0.5 than in eyes with logMAR VA ≤ 0. CONCLUSIONS Reproducibility of VF tests becomes poor with the deterioration of VA. Careful consideration is needed when a patients logMAR VA exceeds 0.5.

The usefulness of CorvisST Tonometry and the Ocular Response Analyzer to assess the progression of glaucoma

Corneal Visualization Scheimpflug Technology (CST) and Ocular Response Analyzer (ORA) measurements were carried out in 105 eyes of 69 patients with primary open-angle glaucoma. All patients had axial length (AL), central corneal thickness (CCT), intraocular pressure (IOP) with Goldmann applanation tonometry (GAT) and eight visual fields (VF)s with the Humphrey Field Analyzer. VF progression was summarized using a time trend analysis of mean total deviation (mTD) and the association between mTD progression rate and a number of ocular parameters (including CST and ORA measurements) was assessed using mixed linear regression analysis. The optimal model of VF progression selected based on the corrected Akaike Information Criteria (AICc) included ORA’s corneal hysteresis (CH) parameter as well as a number of CST measurements: mTD progression rate = 1.2–0.070 * mean GAT + 0.090 * CH–1.5 * highest concavity deformation amplitude with CST + 9.4 * A1 deformation amplitude with CST–0.05 * A2 length with CST (AICc = 125.8). Eyes with corneas that experience deep indentation at the maximum deformation, shallow indentation at the first applanation and wide indentation at the second applanation in the CST measurement are more likely to experience faster rates of VF progression.

Evaluation of stimulus velocity in automated kinetic perimetry in young healthy participants.

This prospective study aimed to evaluate the stimulus velocity for automated kinetic perimetry based on the test duration, the kinetic sensitivity, and the variability of the kinetic sensitivity in 31 eyes of 31 young healthy participants. Automated kinetic perimetry was performed using an Octopus 900 perimeter with Goldmann stimuli III4e, I4e, I3e, I2e, and I1e. The participants underwent testing at 14 predetermined meridians for each stimulus, with velocities of 2°, 3°, 4°, 5°, and 10°/s; each velocity was tested twice. The test duration, kinetic sensitivity, and variability of kinetic sensitivity were compared among the stimulus velocities. Twenty-nine eyes from 29 participants were analyzed, and two participants were excluded. The test durations at the velocities of 2°, 3°, 4°, 5°, and 10°/s were negatively correlated with the stimulus velocity (p<0.01). The variability of the kinetic sensitivities did not significantly differ among the stimulus velocities. The kinetic sensitivities at 2° and 3°/s did not differ significantly for all stimuli. However, those at 4°/s decreased for III4e, I4e, and I1e (p<0.05), and those at 5° and 10°/s decreased for all stimuli (p<0.05) compared with those at 2° or 3°/s. Although the test durations for each stimulus velocity were negatively correlated with the stimulus velocities, a stimulus velocity of 3° or 4°/s might be recommended for automated kinetic perimetry based on the changes in the kinetic sensitivity. As this study included only young participants, further studies in elderly participants may also be necessary.

Determination of Axial Length Requiring Adjustment of Measured Circumpapillary Retinal Nerve Fiber Layer Thickness for Ocular Magnification

Purpose To determine the axial length requiring adjustment of measured circumpapillary retinal nerve fiber layer (cpRNFL) thickness to account for ocular magnification during spectral-domain optical coherence tomography (SD-OCT). Methods In this prospective study, 148 eyes of 148 healthy student volunteers were imaged by two examiners using three-dimensional SD-OCT. In 54 randomly selected eyes, total cpRNFL thickness was measured with and without adjustment for ocular magnification to establish intra-examiner and inter-examiner measurement error. The 148 eyes were then divided into three groups according to the error values: control group (difference in the corrected and uncorrected total cpRNFL thickness was within the measurement error range), thinner group (the corrected total cpRNFL thickness was less than the uncorrected one), and thicker group (the corrected total cpRNFL thickness was more than the uncorrected one). The cutoff values of axial length between the control and the other groups were calculated by receiver operating characteristic analysis. Results Measurement error ranged from 4.2 to 5.3 µm; the threshold value was defined as 5.3 µm. The cutoff values of axial length between the thinner and the control groups and between the control and the thicker groups were 23.60 (area under the curve [AUC] = 0.959) and 25.55 (AUC = 0.944) mm, respectively. Conclusions Axial lengths shorter than 23.60 mm and longer than 25.55 mm require adjustment of measured cpRNFL thickness to account for ocular magnification during SD-OCT. Clinical Trial Registration UMIN Clinical Trials Registry (http://www.umin.ac.jp/) under unique trial number UMIN000013248 (date of registration: 02/24/2014)

The Relationship between Corvis ST Tonometry and Ocular Response Analyzer Measurements in Eyes with Glaucoma

It is important to compare the results of Corneal Visualization Scheimpflug Technology instrument (CST) measurements and Reichert Ocular Response Analyzer (ORA) parameters. The purpose of the study was to investigate the association between CST measurements and ORA parameters in ninety-five patients with primary open-angle glaucoma. Measurements of CST, ORA, axial length (AL), average corneal curvature (CC), central corneal thickness (CCT) and intraocular pressure (IOP) with Goldmann applanation tonometry (GAT) were carried out. The association between CST and ORA parameters was assessed using linear regression analysis, with model selection based on the second order bias corrected Akaike Information Criterion index. Measurements from ORA (corneal hysteresis [CH] and corneal response factor [CRF]) had high intraclass correlation coefficients (ICC) and low coefficients of variation, but some CST parameters showed much lower reproducibility, namely: A1 length, A2 length, highest concavity time and peak distance. Of 12 CST parameters tested, 8 were significantly correlated with CH and 10 were significantly correlated with CRF, however, the magnitude of the correlation coefficients were weak to moderate at best. The optimal model to explain CH using CST measurements was given by: CH = -76.3 + 4.6*A1 time + 1.9*A2 time + 3.1 * highest concavity deformation amplitude + 0.016*CCT (R2 = 0.67, p <0.001). Similarly, the optimal model for CRF was given by: CRF = -53.5 + 4.2*A1 time + 1.9*A1 length + 20.8*A1 deformation amplitude + 0.8*A2 time + 0.017*CCT (R2 = 0.73, p <0.001). ORA parameters show higher reproducibility than CST measurements. Although many CST parameters are significantly related to ORA parameters, the strengths of these relationships are weak to moderate.

Using CorvisST tonometry to assess glaucoma progression.

Purpose To investigate the utility of the Corneal Visualization Scheimpflug Technology instrument (CST) to assess the progression of visual field (VF) damage in primary open angle glaucoma patients. Method A total of 75 eyes from 111 patients with primary open-angle glaucoma were investigated. All patients underwent at least nine VF measurements with the Humphrey Field Analyzer, CST measurements, axial length (AL), central corneal thickness (CCT) and intraocular pressure (IOP) with Goldmann applanation tonometry (GAT). Mean total deviation (mTD) progression rates of the eight VFs, excluding the first VF, were calculated and the association between progression rate and the other listed measurements was analyzed using linear regression, and the optimal to describe mTD progression rate was selected based on the second order bias corrected Akaike Information Criterion (AICc) index. Results VF progression was described best in a model that included CST parameters as well as other ocular measurements. The optimal linear model to describe mTD progression rate was given by the equation: -8.9–0.068 x mean GAT + 0.68 x A1 time + 0.31 x A2 time -0.39 x A2 length– 1.26 x highest deformation amplitude. Conclusion CST measurements are useful when assessing VF progression in glaucoma patients. In particular, careful consideration should be given to patients where: (i) an eye is observed to be applanated fast in the first and second applanations, (ii) the applanated area is wide in the second applanation and (iii) the indentation is deep at the maximum deformation, since these eyes appear to be at greater risk of VF progression.

Comparison of size modulation and conventional standard automated perimetry with the 24-2 test protocol in glaucoma patients

This prospective randomized study compared test results of size modulation standard automated perimetry (SM-SAP) performed with the Octopus 600 and conventional SAP (C-SAP) performed with the Humphrey Field Analyzer (HFA) in glaucoma patients. Eighty-eight eyes of 88 glaucoma patients underwent SM-SAP and C-SAP tests with the Octopus 600 24-2 Dynamic and HFA 24-2 SITA-Standard, respectively. Fovea threshold, mean defect, and square loss variance of SM-SAP were significantly correlated with the corresponding C-SAP indices (P < 0.001). The false-positive rate was slightly lower, and false-negative rate slightly higher, with SM-SAP than C-SAP (P = 0.002). Point-wise threshold values obtained with SM-SAP were moderately to strongly correlated with those obtained with C-SAP (P < 0.001). The correlation coefficients of the central zone were significantly lower than those of the middle to peripheral zone (P = 0.031). The size and depth of the visual field (VF) defect were smaller (P = 0.039) and greater (P = 0.043), respectively, on SM-SAP than on C-SAP. Although small differences were observed in VF sensitivity in the central zone, the defect size and depth and the reliability indices between SM-SAP and C-SAP, global indices of the two testing modalities were well correlated.