Frequency Doubling Technology Perimetry for Detection of Visual Field Progression in Glaucoma: A Pointwise Linear Regression Analysis

Abstract

Purpose.: We compared the detection of visual field progression and its rate of change between standard automated perimetry (SAP) and Matrix frequency doubling technology perimetry (FDTP) in glaucoma.

Methods.: We followed prospectively 217 eyes (179 glaucoma and 38 normal eyes) for SAP and FDTP testing at 4-month intervals for ≥36 months. Pointwise linear regression analysis was performed. A test location was considered progressing when the rate of change of visual sensitivity was ≤−1 dB/y for nonedge and ≤−2 dB/y for edge locations. Three criteria were used to define progression in an eye: ≥3 adjacent nonedge test locations (conservative), any three locations (moderate), and any two locations (liberal) progressed. The rate of change of visual sensitivity was calculated with linear mixed models.

Results.: Of the 217 eyes, 6.1% and 3.9% progressed with the conservative criteria, 14.5% and 5.6% of eyes progressed with the moderate criteria, and 20.1% and 11.7% of eyes progressed with the liberal criteria by FDTP and SAP, respectively. Taking all test locations into consideration (total, 54 × 179 locations), FDTP detected more progressing locations (176) than SAP (103, P < 0.001). The rate of change of visual field mean deviation (MD) was significantly faster for FDTP (all with P < 0.001). No eyes showed progression in the normal group using the conservative and the moderate criteria.

Conclusions.: With a faster rate of change of visual sensitivity, FDTP detected more progressing eyes than SAP at a comparable level of specificity. Frequency doubling technology perimetry can provide a useful alternative to monitor glaucoma progression.

Introduction

Frequency doubling in visual responses was described first by Kelly ¹ 50 years ago. When achromatic sinusoidal gratings of low spatial frequency flicker at a high temporal frequency, the spatial frequency of the grating appears to be doubled. This phenomenon was suggested to be related to the appearance of a second-harmonic distortion that may involve rectification and response compression. ^2,3 Despite the findings that subjects may, in fact, report a higher or lower spatial frequency than its true frequency, and that the frequency-doubling effect may not be generated by the retinal ganglion cells (RGCs) of the magnocellular pathway, but by many types of RGCs, ^4–7 the first and second generations of the frequency doubling technology perimetry (FDTP) have been shown to be useful to detect early visual field damage in glaucoma. ⁸ However, less is known about the performance of FDTP in following visual field progression. The rate of change of visual sensitivity has not been established in the Matrix FDTP and the role of FDTP in monitoring glaucoma progression remains unclear. 

The Matrix perimeter (Carl Zeiss Meditec, Inc., Dublin, CA, USA) is the second generation of FDTP with a spatial resolution similar to the 24-2 testing pattern in standard automated perimetry (SAP). As the Matrix FDTP and SAP test the same 54 locations in the visual field, it is feasible to have pointwise comparison for progression analysis between the perimetric tests. In this prospective, longitudinal study, we adopted the pointwise linear regression to investigate the performance of progression detection, and compare the rates of change of visual field loss between Matrix FDTP and SAP in 179 eyes from 148 glaucoma patients, who had been followed every 4 months for at least 36 months. A normal group comprising 38 eyes of 28 subjects also was included to evaluate the specificity of perimetric tests. 

Methods

Subjects

Totals of 179 eyes of 148 glaucoma patients and 38 eyes of 28 normal subjects were enrolled consecutively and followed during the period from January 2005 through April 2012 at the Hong Kong Eye Hospital, the Chinese University of Hong Kong. All patients underwent a full ophthalmic examination, including measurement of visual acuity, refraction, and IOP; gonioscopy; and fundus examination. Optic discs were examined with slit-lamp biomicroscopy and color optic disc stereophotographs. Subjects were included if they had a visual acuity of at least 20/40, and excluded if they had clinical evidence of macular disease, refractive or retinal surgery, neurologic disease, or diabetes. All glaucomatous eyes had optic disc changes, including narrowing of neuroretinal rim and/or retinal nerve fiber layer thinning with corresponding visual field loss (described in Visual Field Testing). Normal individuals had no structural optic disc abnormalities, no history of IOP measured at >21 mm Hg, and no visual field defect. Each patient underwent SAP (Humphrey Field Analyzer II; Carl Zeiss Meditec, Inc.) and FDTP (Matrix Frequency Doubling Perimeter; Carl Zeiss Meditec, Inc.) testing in a random order with at least a 10-minute break in-between in the same visit (described in Visual Field Testing) by a team of four experienced technicians in the baseline visit, and then in 4-month intervals for at least 36 months. During the follow-up, patients were observed or treated at the discretion of the attending physicians with reference to the target IOP and the risk of progression. The study was conducted in accordance with the ethical standards stated in the 1964 Declaration of Helsinki and approved by local research ethics committee with informed consent obtained. 

Visual Field Testing: SAP and Matrix FDTP

Standard automated white-on-white threshold perimetry (SAP) was performed with the 24-2 SITA standard program (version 4.1) of the Humphrey Field Analyzer II (Carl Zeiss Meditec, Inc.). Each of the achromatic Goldman size III targets was presented for 200 ms on a background illumination of 10 cd/m². The FDTP was performed with the Matrix FDT perimeter (Carl Zeiss Meditec, Inc.), and 0.5-cycle/degree sinusoidal gratings undergoing counter phase flickering at 18 Hz were displayed sequentially over 54 5° × 5° squares using the 24-2 zippy estimation by sequential testing (ZEST) thresholding algorithm. For SAP, the patients' appropriate near refraction was corrected with a trial lens inserted in the lens holder. For Matrix FDTP, the patients wore their own prescription glasses as recommended by the manufacturer. Only reliable visual fields (fixation losses, and false-negative and false-positive errors ≤20% for SAP and FDTP) were analyzed (Table 1 shows the reliability indices of Matrix FDTP and SAP). A visual field defect was defined as a cluster of three nonedge points, all of which were indicated at a probability level <5% with at least one <1% in the pattern deviation plot, and confirmed with at least two consecutive examinations by the same types of perimetry. The same definition of visual field defect was applied for SAP and FDTP. In the glaucoma group (179 eyes of 148 patients), only eyes with visual field defects detected in both perimetric tests at the time of enrollment were included. In the normal group (38 eyes of 28 subjects, Matrix FDTP was performed in both eyes in 10 subjects and in one randomly selected eye in each of the remaining 18 subjects), eyes had no visual field defects in SAP and FDTP throughout the follow-up period. 

Table 1

 

Comparison of Reliability Indices Between Matrix FDTP and SAP

	Mean, %	SD, %	Median, %	Minimum, %	Maximum, %	P Value*
Glaucoma group
Matrix FDTP
Fixation loss	4.0	6.3	0.0	0.0	20.0	0.001
False-negative	2.8	5.5	0.0	0.0	20.0	0.757
False-positive	2.6	6.1	0.0	0.0	16.7	0.193
SAP
Fixation loss	4.8	5.6	5.3	0.0	20.0
False-negative	2.7	4.2	0.0	0.0	20.0
False-positive	2.2	2.8	1.0	0.0	17.0
Normal group
Matrix FDTP
Fixation loss	4.3	6.5	0.0	0.0	20.0	0.337
False-negative	1.9	4.6	0.0	0.0	20.0	<0.001
False-positive	0.3	2.2	0.0	0.0	16.7	<0.001
SAP
Fixation loss	4.9	5.5	6.3	0.0	18.8
False-negative	0.7	1.7	0.0	0.0	12.0
False-positive	2.4	3.0	1.0	0.0	15.0

*  Comparisons between Matrix FDTP and SAP were performed using linear mixed modeling.

Export and Processing of Visual Field Data

Threshold sensitivity data of each of the 54 test locations from a total of 2788 Matrix FDTP and 2913 SAP examinations were exported from the Matrix and Humphrey perimeters (the central location of Matrix FDTP was excluded from the analysis as this was not available in SAP). Since the number of visual field examinations available for analysis in each eye would influence the power and estimation of coefficients in the trend analysis, we only included concurrent visual fields that were reliable for Matrix FDTP and SAP in the same visit to minimize potential selection bias in the comparison between the perimetric tests. After excluding visual fields with fixation losses, false-negative errors or false-positive errors of >20%, totals of 2329 Matrix FDTP and 2329 SAP examinations were available for analysis. Threshold sensitivity in Matrix FDTP was estimated by the mean of probability density function, which was adjusted according to patients' responses to 4 presentations of stimuli. ^9–12 Because two of the 16 possible combinations of the four yes/no responses gave a similar mean, the threshold estimates assumed 15 discrete levels of threshold measurement. Figures 1A and 1B show the distribution of the threshold values of individual test locations obtained from Matrix FDTP and SAP in the glaucoma group. While the range of visual sensitivity was comparable (0–41 dB for SAP, 0–38 dB for Matrix FDPT), the step sizes were different between the two perimetric tests. For Matrix FDTP, the thresholds were found at 15 discrete levels at 0, 2, 3, 6, 7, 11, 12, 13, 18, 20, 23, 27, 32, 34, and 38 dB, whereas for SAP, the step size was fixed at 1 dB. To facilitate a more direct comparison between SAP and Matrix FDTP, all the SAP threshold values were transformed to the nearest threshold values fitting into the 15 thresholds as in Matrix FDTP (i.e., the SAP thresholds were rebinned into the 15 threshold values, Fig. 1C). Progression analyses were performed with and without such transformation (designated as SAP [transformed] and SAP, respectively). 

Figure 1

 

Frequency distribution of the threshold values of the 54 individual test locations obtained from the Matrix FDTP (A) and SAP (B) results in the glaucoma group. For SAP (transformed) (C), all the SAP thresholds were transformed into values fitting into the 15 thresholds as in Matrix FDTP using the nearest-point interpolation.

Definitions of Visual Field Progression

The pointwise linear regression (PLR) analysis was used to evaluate progression. ^13–15 In this study, progression at a test location was identified when the rate of change of visual sensitivity was ≤−1 dB/y for nonedge locations, and ≤−2 dB/y for edge locations, with P < 0.05. Three levels of criteria were used to define progression: (1) at least three adjacent nonedge (except for the two nasal edge points) test locations detected with progression, (2) any three locations detected with progression, and (3) any two locations detected with progression. The same criteria were applied for SAP and Matrix FDTP. An improvement at a particular test location was defined when the rate of change of visual sensitivity was ≥+1 dB/y for nonedge locations, and ≥+2 dB/y for edge locations, with P < 0.05. 

Statistics

Statistical analyses were performed using Stata version 10.0 (StataCorp, College Station, TX, USA). Visual field mean deviation (MD) and pattern standard deviation (PSD) measurements between the baseline and the final follow-up visits were compared to linear mixed models after adjustment of correlation between fellow eyes. The χ² test was used to compare the proportion of progression and improvement events between the perimetric tests. The agreement of progression detection between SAP and FDTP was calculated with κ statistics. A value between 0.0 and 0.2 indicates slight agreement, 0.21 and 0.40 is fair, 0.41 and 0.60 is moderate, 0.61 and 0.80 is substantial, and 0.81 and 1 is almost perfect agreement. ¹⁶ Longitudinal MD, superior and inferior hemifield visual sensitivity measurements were fitted with linear mixed models with follow-up duration as the fixed effect. Random intercepts and coefficients were included at the subject and eye levels (each eye nested within subject) for the effect of follow-up duration (random effects). Comparisons of the rates of change of MD and visual sensitivities between FDTP and SAP were evaluated with likelihood ratio test between the goodness of fit of the linear mixed models. The sample size required for the linear mixed models was calculated based on the estimates of random intercept variance, random slope variance, residual variance, the covariance between random slope and random intercept, and the working correlation matrix derived from the linear mixed models, and assuming that all longitudinal measurements were collected at regular time intervals (every 4 months for 36 months). ¹⁷ Sample size calculation revealed that at least 78 eyes would be required to detect a rate of change of MD ≤ −0.5 dB/y with a statistical power of 80%. A post hoc power calculation comparing the differences in proportions of progressing locations between SAP/SAP (transformed) and Matrix FDT perimetry indicated that the current sample size attained a power of ≥84.3% at an alpha of 0.05. To compute the Kaplan-Meier survival curves for Matrix FDTP and SAP, progression analysis was performed at each follow-up visit from the third follow-up visit onwards. The survival probabilities of Matrix FDTP and SAP/SAP (transformed) were compared using log-rank tests. P < 0.05 was considered statistically significant in all analyses. 

Results

This study included a total of 179 eyes of 148 glaucoma patients and 38 eyes of 28 normal subjects with serial SAP and Matrix FDTP performed for at least 36 months. The demographics are shown in Table 2. After excluding visual fields with fixation losses, false-negative or false-positive errors of >20%, the median number of visual field tests available for progression analysis in each eye was 11 (range, 6–15) in the glaucoma group and 12 (range, 4–15) in the normal group. The baseline MD and PSD in the glaucoma group were −9.20 ± 8.03 and 7.07 ± 4.45 dB, respectively, for SAP, and −10.53 ± 6.57 and 6.49 ± 2.14 dB, respectively, for Matrix FDTP. 

Table 2

 

Demographics and Visual Field Measurements

	Demographics
	Glaucoma	Normal
Total n of eyes	179	38
Age, y ± SD	50.9 ± 14.2	60.2 ± 8.0
Duration of follow-up, mo ± SD	46.9 ± 8.9	49.1 ± 4.0
Baseline Matrix FDTP MD, dB ± SD	−10.53 ± 6.57	−1.34 ± 2.55
Baseline Matrix FDTP PSD, dB ± SD	6.49 ± 2.14	2.84 ± 0.51
Baseline SAP MD, dB ± SD	−9.20 ± 8.03	−0.69 ± 1.49
Baseline SAP PSD, dB ± SD	7.07 ± 4.45	1.67 ± 0.88

Detection of Visual Field Progression

Pointwise linear regression analysis was performed to estimate the rate of change of visual sensitivity in the 54 test locations. Using the conservative criteria to define progression (at least three adjacent nonedge (except for the two nasal edge points) locations with a rate of change of visual sensitivity of ≤−1 dB/y), there were 11 (6.1%), 7 (3.9%), and 6 (3.4%) eyes detected with progression by Matrix FDTP, SAP, and SAP (transformed), respectively (Fig. 2A). With the moderate criteria (any three locations with ≤−1 dB/y for nonedge and ≤−2 dB/y for edge locations), there were 26 (14.5%), 10 (5.6%), and 13 (7.3%) eyes that progressed, respectively (Fig. 2B). With the liberal criteria (any two locations with ≤−1 dB/y for nonedge and ≤−2 dB/y for edge locations), 36 (20.1%), 21 (11.7%), and 24 (13.4%) eyes progressed, respectively (Fig. 2C). Matrix FDTP detected significantly more progressing eyes than SAP using the liberal and moderate criteria (P ≤ 0.042). Likewise, the survival probability of Matrix FDTP for detection of progression was significantly worse compared to SAP (P ≤ 0.042) and SAP (transformed) (P ≤ 0.005) using the liberal and the moderate criteria (Fig. 3). The agreement of progression detection between Matrix FDTP and SAP, and between Matrix FDTP and SAP (transformed) was poor to fair (κ ranged between 0.066 and 0.403) independent of the criteria of progression. In the normal group, Matrix FDTP detected two progressing eyes using the liberal criteria. No eyes showed progression in Matrix FDTP/SAP using the conservative and the moderate criteria. 

Figure 2

 

Venn diagrams showing the number of progressing eyes detected by Matrix FDTP, SAP, and SAP (transformed) using the conservative criteria (at least three adjacent nonedge [except for the two nasal edge points] locations with a rate of change of visual sensitivity ≤ −1 dB/y, [A]), moderate criteria (at least three locations at any locations with ≤−1 dB/y for nonedge locations and ≤−2 dB/y for edge locations, [B]), and liberal criteria (at least two locations at any locations with ≤−1 dB/y for nonedge, and ≤−2 dB/y for edge locations, [C]) to define progression.

Figure 3

 

Kaplan Meier survival curves showing the survival probability of Matrix FDTP, SAP, and SAP (transformed) for detection of visual field progression using the moderate criteria. The hash marks represent censored observations.

Taking all the 54 test locations into consideration (a total of 54 × 179 = 9666 locations) and defining a location as progressing when its rate of change was ≤−1 dB/y for nonedge and ≤−2 dB/y for edge locations (P < 0.05), Matrix FDTP detected a total of 176 progressing locations in the glaucoma group, which was significantly greater than SAP (103, P < 0.001), and SAP (transformed) (124, P = 0.003, Fig. 4). There were no significant differences in the number of significant improvement (≥1 dB/y for nonedge locations and ≥2 dB/y for edge locations) between Matrix FDTP (n = 5) and SAP (n = 10, P = 0.804), and between Matrix FDTP and SAP (transformed) (n = 14, P = 0.848, Fig. 5). This frequency distribution of the rates of change of visual sensitivity of individual locations of Matrix FDTP, SAP, and SAP (transformed) are shown in Figure 6. Figure 7 shows the spatial distribution of the progressing locations detected by Matrix FDTP and SAP for individual eyes. The spatial agreement of progression detection between the two perimetric tests was poor. 

Figure 4

 

Number of progression events detected in individual test locations using the criteria of ≤−1 dB/y for nonedge and ≤−2 dB/y for edge locations in Matrix FDTP (A), SAP (B), and SAP (transformed) (C). Color coding was added with color intensity correlating to the number of progression events. Test locations for left eye were converted to right eye format. S, superior; I, inferior; T, temporal; N, nasal.

Figure 5

 

Number of events with significant improvement (≥1 dB/y for nonedge locations and ≥2 dB/y for edge locations) in Matrix FDTP (A), SAP (B), and SAP (transformed) (C). Color coding was added with color intensity correlating to the number of improvement events. Test locations for left eye were converted to right eye format.

Figure 6

 

Frequency distribution of the rates of change of visual sensitivity of individual test locations (linear regression analysis with P < 0.05) obtained from the Matrix FDTP (A), SAP (B), and SAP (transformed) (C).

Figure 7

 

Spatial distribution of the number of progressing events detected by Matrix FDTP and SAP (A), and by Matrix FDT perimetry and SAP (transformed) (B) for individual eyes.

Rate of Change of Visual Sensitivity

With estimation from linear mixed modeling, the rate of change of MD was −0.26 dB/y (95% confidence interval [CI], −0.36 to −0.16 dB/y) for Matrix FDTP and −0.20 dB/y (95% CI, −0.28 to −0.12 dB/y) for SAP (Table 3). The former was significantly faster than the latter (P < 0.001). With respect to the superior hemifield, the mean rate of change of visual sensitivity was faster for Matrix FDTP (−0.31 dB/y; 95% CI, −0.45 to −0.18 dB/y) than SAP (−0.17 dB/y; 95% CI, −0.25 to −0.09 dB/y; P < 0.001; Table 4). Likewise, in the inferior hemifield, Matrix FDTP also detected visual sensitivity reduction at a significantly faster rate (−0.30 dB/y; 95% CI, −0.43 to −0.17 dB/y) than SAP (−0.24 dB/y; 95% CI, −0.31 to −0.16 dB/y; P < 0.001; Table 5). While the rate of change of MD for Matrix FDTP was insignificant (P = 0.846) in the normal group (Table 6), a positive trend was observed for SAP (0.104 dB/y, P = 0.005). 

Table 3

 

Rate of Change of MD of Matrix FDTP and SAP in the Glaucoma Group (179 Eyes)

	Fixed Effect				P Value	Random Effect
	Parameter	Coefficient	95% CI			Level	SD
Matrix FDTP MD	Duration, y	−0.260	−0.364	−0.156	<0.001	Subject	0.458
	Intercept	−10.278	−11.327	−9.229	<0.001		4.080
	Duration, y					Eye	0.114
	Intercept						4.883
						Residual	1.525
SAP MD	Duration, y	−0.202	−0.282	−0.122	<0.001	Subject	0.331
	Intercept	−9.340	−10.491	−8.189	<0.001		0.000
	Duration, y					Eye	0.212
	Intercept						7.828
						Residual	1.137

Table 4

 

Rate of Change of Visual Sensitivities in the Superior Hemifield in Matrix FDTP and SAP in the Glaucoma Group (179 Eyes)

	Fixed Effect				P Value	Random Effect
	Parameter	Coefficient	95% CI			Level	SD
Matrix FDTP	Duration, y	−0.313	−0.450	−0.177	<0.001	Subject	0.503
	Intercept	25.163	24.397	25.929	<0.001		2.109
	Duration, y					Eye	0.077
	Intercept						4.215
						Residual	2.630
SAP	Duration, y	−0.167	−0.245	−0.089	<0.001	Subject	0.197
	Intercept	28.256	27.499	29.013	<0.001		3.598
	Duration, y					Eye	0.112
	Intercept						2.342
						Residual	1.804

Table 5

 

Rate of Change of Visual Sensitivities in the Inferior Hemifield in Matrix FDTP and SAP in the Glaucoma Group (179 Eyes)

	Fixed Effect				P Value	Random Effect
	Parameter	Coefficient	95% CI			Level	SD
Matrix FDTP	Duration, y	−0.295	−0.425	−0.165	<0.001	Subject	0.399
	Intercept	25.916	25.226	26.605	<0.001		2.526
	Duration, y					Eye	0.367
	Intercept						3.138
						Residual	2.433
SAP	Duration, y	−0.236	−0.311	−0.161	<0.001	Subject	0.127
	Intercept	29.886	29.475	30.297	<0.001		1.510
	Duration, y					Eye	0.343
	Intercept						1.899
						Residual	1.316

Table 6

 

Rate of Change of Visual Sensitivities of the Matrix FDTP and SAP in the Normal Group (38 Eyes)

	Fixed Effect				P Value	Random Effect
	Parameter	Coefficient	95% CI			Level	SD
Matrix FDTP	Duration, y	−0.016	−0.174	0.143	0.846	Subject	0.179
	Intercept	−1.057	−1.890	−0.223	0.013		1.897
	Duration, y					Eye	0.139
	Intercept						0.936
						Residual	1.855
SAP MD	Duration, y	0.104	0.031	0.177	0.005	Subject	0.124
	Intercept	−0.788	−1.065	−0.512	0.000		0.540
	Duration, y					Eye	0.035
	Intercept						0.425
						Residual	0.747

Discussion

Following 179 eyes of 148 glaucoma patients over a mean of 46.9 ± 8.9 months and taking all visual field test locations into consideration (54 × 179 = 9666 locations), we found that Matrix FDTP detected a significantly greater number of progressing locations (176) compared to SAP (103, P < 0.001) and SAP (transformed) (124, P = 0.003), with a similar number of locations showing improvement (Matrix FDTP, 5; SAP, 10; SAP (transformed), 14; P ≥ 0.804). With a faster rate of reduction in visual sensitivity (Tables 3 1552–5), Matrix FDTP may detect visual field changes earlier than SAP and provide an effective alternative to follow visual field progression in glaucoma management. 

Although an abnormal FDTP result is predictive of visual field progression by SAP, ^18,19 the role of FDTP in following glaucoma progression remains elusive. Prospective studies evaluating the performance of the FDTP for progression detection are sparse. To our knowledge, only two longitudinal studies have investigated glaucoma progression using Matrix FDTP. Xin et al. ²⁰ followed 33 glaucoma patients for 21.1 ± 1.8 months (range, 18–26 months) and analyzed progression by event analysis (defined as a change in MD greater than the test–retest variability). They showed that SAP and Matrix FDTP detected 8 (14.5%) and 13 (23.6%) progressing eyes, respectively (the number of eyes with improvement was not reported). ²⁰ In our previous study following 76 glaucoma suspects with normal visual fields at the baseline examination for at least 30 months, we demonstrated that the rate of change of PSD was faster for Matrix FDTP compared to SAP and that Matrix FDTP could detect development of visual field defects (defined as appearance of a cluster of 3 nonedge points, all of which were indicated at a probability level ≤5% with at least one ≤1% in the pattern deviation plot, and confirmed by at least two consecutive examinations) earlier than SAP. ²¹ These studies, however, did not examine visual field progression with trend analysis. The criteria of detecting the development of new visual field defects in glaucoma suspects as used in our previous study would be inadequate to detect change in patients with moderate and advanced visual field loss. To our knowledge, this is the first study comparing Matrix FDTP and SAP with trend analysis in glaucoma patients. 

Having a median of 11 to 12 visual fields available for each eye for analysis, it is feasible to obtain relatively reliable estimates of the rate of change of visual sensitivity. Although PLR originally was designed and applied in SAP, we believe that PLR also is applicable in Matrix FDTP as the dynamic range between it (0–38 dB) and SAP (0–41 dB) is comparable. One caveat in applying linear regression analysis in Matrix FDTP is that the step size of Matrix FDTP is not uniform. Therefore, we transformed all the SAP thresholds into the 15 discrete levels as in Matrix FDTP to facilitate the comparison with SAP (Fig. 1). We showed that Matrix FDTP detected more progressing eyes than SAP with or without transformation, independent of the criteria of progression (Fig. 2). Likewise, the number of progressing locations detected by Matrix FDTP also was greater than SAP with or without transformation (Fig. 4). That the number of test locations demonstrating improvement was comparable between the perimetric tests in the glaucoma group (Fig. 5) and that no eyes showed progression using the conservative and the moderate criteria in the normal group (only two eyes were detected with progression by Matrix FDTP using the liberal criteria) suggest that the specificity of Matrix FDTP and SAP was similarly high. Taken together, the observation that the rates of change of MD, and visual sensitivity in the superior and inferior hemifields were all faster in Matrix FDTP (P < 0.001, Tables 3 1552–5), it is reasonable to infer that Matrix FDTP may detect visual field progression earlier than SAP. However, lacking a reference standard, it is not feasible to compare directly the sensitivity between the perimetric tests. We did not take reference from structural measures as it has been shown that detectable change in the optic disc often precedes visual field progression, and that progression in structure and function may not occur concomitantly within the study period. ^22,23  

It is interesting to note that SAP MD showed a significant positive trend in the normal eyes (Table 6). While a learning effect cannot be excluded, such learning effect was not observed in Matrix FDTP. The significant positive trend of SAP MD corroborates the observation of a greater number of locations showing improvement (5 in Matrix FDTP, 10 in SAP, and 14 in SAP [transformed], Fig. 5) and a more negative rate of change of visual sensitivity for Matrix FDTP compared to SAP (Tables 3 1552–5) in the glaucoma group. This finding underscores a higher specificity for Matrix FDTP. 

While a number of algorithms have been validated and compared for detection of visual field progression in SAP (e.g., Guided Progression Analysis, PROGRESSOR), ²⁴ the strategies for progression detection have not been optimized for Matrix FDTP. Unlike SAP, no commercially available packages are available for progression analysis in FDTP. The test–retest repeatabilities of SAP and Matrix FDTP are different ²⁵ and a different set of criteria (including the rate of change of visual sensitivity threshold and the P value) may be necessary to define progression in Matrix FDTP. However, without a validated algorithm for detection of progression in Matrix FDTP, standardizing the criteria for progression analysis would deem appropriate to obtain a meaningful comparison between the perimetric tests. Adopting a P value of 0.05 to define a significant rate of change of visual sensitivity for an individual location, we observed 5, 10, and 14 locations showing a significant positive trend for Matrix FDTP, SAP, and SAP (transformed), respectively, in the glaucoma group. With a total of 9666 (54 × 179) test locations examined, the respective proportions were 0.05%, 0.10%, and 0.14%. In the normal group, no eyes showed progression using the conservative and moderate criteria. These findings suggested that adopting a P value of 0.05 already provided a high specificity for change analysis. Using a smaller P value to define progression would increase the specificity at the expense of a reduced sensitivity, which may render the comparison between SAP and Matrix FDT perimetry less practical. 

The comparison of progression analysis between SAP and Matrix FDTP is not straightforward because the measurement scales between the perimetric tests may not be comparable in spite of their similar dynamic ranges. Of note, SAP and FDTP measure different domains of visual function. The SAP measures the responses to the change in light intensities, whereas Matrix FDTP measures the minimum contrast necessary to detect the stimulus. Progression detected by one modality may not be translatable to another. As shown in this study, SAP and Matrix FDTP had a poor agreement in the number of progressing eyes (Fig. 2) and in the number of progressing locations (Fig. 7). Understanding the relationship between visual function and the measurement units is critical in the evaluation and comparison of rates of change of visual sensitivity. 

In summary, Matrix FDTP is useful to monitor disease progression in glaucoma patients. Matrix FDTP detected more progressing events than SAP at similar specificities. With a faster rate of change of visual sensitivity, Matrix FDTP may detect visual field progression earlier than SAP. This study established the feasibility of pointwise linear regression to detect change in glaucoma patients and demonstrated a high specificity of such analysis, laying the foundation for follow-up studies to examine the impact of test–retest variability and frequency of testing on detection of glaucoma progression in clinical practice. 

Acknowledgments

Disclosure: S. Liu, None; M. Yu, None; R.N. Weinreb, Carl Zeiss Meditec (F, C), Heidelberg Engineering (F), Optovue (F), Nidek (F), Topcon (F, C); G. Lai, None; D.S.-C. Lam, None; C.K.-S. Leung, Carl Zeiss Meditec (F, R), Optovue (F)