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intra-test variability compared to SAP and FDT (Hutchings et al., 2001), which is the result of a number of factors: difficulty in detecting the stimulus, intra-test fatigue effect, higher range of sensitivities within the tested areas (the hill of vision has a steeper shape than SAP and FDT, as described above) (Landers et al., 2006). Overall, these features enlarge the confidence intervals for normality, thus reducing the diagnostic power of this perimetry.

A novel software, SITA SWAP, has been included in the latest version of the Humphrey Field Analyzer (HFA II-i); although clinical data are still missing, it may hopefully overcome the problems of the full-threshold strategy and improve the clinical use of this perimetry for glaucoma detection. A preliminary work confirmed that this procedure could reduce 50% of test duration with encouraging diagnostic results; the confidence intervals for the point-to-point sensitivity are reduced compared to full-threshold SWAP, and this program may identify the same number of visual field losses as the previous version (Bengtsson and Heijl, 2006).

FDT: clinical data

Maddess and Henry were the first to suggest that the frequency-doubling illusion could be useful in detecting glaucomatous field loss. In their study, a group of ocular hypertensive (OH) patients with initial SAP defects were tested with FDT. Compared to a control group, these patients detected stimuli only when an abnormally high luminance was applied, thus suggesting that the measurement of the contrast sensitivity of a frequency-doubled grating may represent a good indicator of neural damage from elevated intraocular pressure (Maddess and Henry, 1992).

Thereafter, several clinical studies have been conducted to determine the accuracy of glaucoma detection by FDT. Johnson and Samuels reported a sensitivity of 93% and a specificity of 100% when testing 15 normal subjects and 15 agematched patients with early or moderate glaucoma damage with full-threshold FDT (Johnson and

Samuels, 1997). Trible found a specificity of 91% and a sensitivity of 35, 88, and 100% for early, moderate, and severe glaucoma, respectively (Trible et al., 2000). These ancillary findings on the comparison between performances at SAP and FDT were confirmed by a number of studies; overall, when conventional perimetry was used as a ‘‘gold standard,’’ FDT obtained good specificity, with sensitivities ranging from moderate to excellent depending on the stage of the disease. A review by the American Academy of Ophthalmology stated that FDT ‘‘showed sensitivity and specificity greater than 97% for detecting moderate and advanced glaucoma, and sensitivity of 85% and specificity of 90% for early glaucoma’’ (Delgado et al., 2002). Very similar sensitivities and specificities were obtained by the secondgeneration FDT using the 24-2 program (Brusini et al., 2006a, b; Spry et al., 2007).

One of the most interesting applications of FDT is to detect early glaucomatous defects. Abnormal FDT results were obtained in 20–54% of patients with retinal nerve fiber layer (RNFL) defects but normal SAP (the so-called ‘‘pre-perimetric’’ glaucomas) (Brusini et al., 2006a, b; Ferreras et al., 2007; Kim et al., 2007; Lee et al. 2007). These findings are in contrast with two studies which, using a morphological ‘‘gold standard,’’ obtained similar performances for SAP and FDT (Spry et al., 2005; Burgansky-Eliash et al., 2007). The major limitation of these studies is the crosssectional design, which does not allow any inspection on the true potentiality of FDT in diagnosing early-stage patients who will develop SAP abnormalities only after years of follow-up.

Longitudinal, comparative data on FDT and SAP have recently been provided (Haymes et al., 2005). In their study of 65 glaucoma patients, Haymes and coworkers performed FDT and SAP every 6 months for a mean follow-up of 3.5 years. They showed that FDT and SAP detected progression in the same number of patients (49%), although the proportion of patients who showed progression with both FDT and SAP was small (25%), possibly indicating that the two techniques identified patients with different patterns of the disease.

Several diagnostic parameters (presence of at least 1 or 2 location(s) with Po5% or o1% in the total or pattern deviation map) and scoring systems have been proposed for first-generation FDT; being Matrix FDT similar to SAP 24-2, it is reasonable to adopt the criteria for abnormality used for conventional perimetry (Hodapp et al., 1993). Until now, none of these FDT criteria has been clearly validated over the others. As a general rule, a higher specificity is obtained using a cut-off for abnormality of Po1%; on the other hand, sensitivity may increase when using the fullthreshold N-30 test at a strategy of Po5% and selecting looser diagnostic criteria. In any case, the diagnostic power of FDT seems to be only marginally affected by the generation of the perimeter, the criteria adopted to define abnormality, the program (C-20 vs. N-30 vs. 24-2), or the strategy (full-threshold vs. screening) (Delgado et al., 2002; Fogagnolo et al., 2005).

Regardless of the criteria used to define abnormality, in the case of apparently abnormal results retest is recommended, since this would improve specificity with a negligible loss in sensitivity (Gardiner et al., 2006). This is particularly convenient for screening procedures (which are low time-consuming) and it is strongly suggested when a test with low MD is obtained from subjects unexperienced to perimetry, as they may be prone to learning effect (Brush and Chen, 2004; Contestabile et al., 2007).

Criteria for progression are also lacking (Sample et al., 2000a, b), although the staging systems proposed by Brusini et al. may represent a useful tool to stage the severity of the functional damage and to correctly distinguish among generalized, localized, and mixed defects (Brusini and Tosoni, 2003; Brusini, 2006).

Compared to the other perimetric techniques, FDT has a number of advantages. Intraand intertest variability for FDT is comparable to SAP in healthy subjects. In glaucomatous patients, SAP variability seems to increase as defect severity increases while it remains stable and low for FDT (Artes et al., 2005). Moreover, the shape of the ‘‘hill of vision’’ for FDT is significantly flatter than for SAP and SWAP (Landers et al., 2006). This

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topography is probably the result of the retinotopic distribution of M-RGCs (increasing cell density with increasing eccentricity) and it allows lower point-to-point confidence intervals and, hence, a more precise discrimination between normal and abnormal responses. The learning effect (which is a well-known phenomenon occurring in many psychophysical examinations, defined as the improvement of performances over test repetitions) is absent in a large number of tested subjects; for the small percentage of subjects showing improvement of performance upon retest, only the first examination seems to be affected (Brush and Chen, 2004; Contestabile et al., 2007). As for other perimetries, MD was the parameter most sensitive to learning. FDT has been successfully used in clinical practice also to test children (Blumenthal et al., 2004). Finally, FDT is supposed to be unaffected by defocus (Anderson and Johnson, 2003), although a previous study was in contrast with this finding (Artes et al., 2003).

SWAP: clinical data

The first two studies showing the clinical efficacy of SWAP in glaucoma were published by Johnson and coworkers in 1993. In the first study, they tested 76 OH and 124 normal eyes with SAP and SWAP at baseline every 12 months for 5 years (Johnson et al., 1993a). At baseline, SAP was normal in all cases, whereas nine OH patients had abnormal SWAP tests. At the end of the study, five out of nine of these patients developed SAP glaucomatous defects, thus showing that SWAP can predict the development of glaucomatous defects from 3 to 5 years before SAP. The second study aimed at validating SWAP as a tool to identify early glaucoma progression (Johnson et al., 1993b). Thirty-two eyes of 16 glaucoma patients underwent SWAP and SAP tests once a year for 5 years and were deemed stable or progressing on the basis of the eventual changes at SAP during the study period. The authors showed that, at baseline, SWAP defects were larger than SAP in 80% of cases. Whereas SWAP

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defects were twice as large as SAP in the group of stable patients, they were three to four times larger in the group with progressive field loss. Therefore, the presence of large SWAP defects may predict glaucoma progression at SAP.

The results of these ancillary studies were confirmed by a series of cross-sectional data (Girkin et al., 2000; Polo et al., 2002; Ferreras et al., 2007; Leeprechanon et al., 2007). In particular, a good association between RNFL defects and SWAP abnormalities has been shown (Polo et al., 1998; Mok et al., 2003; Sa´nchezGaleana et al., 2004).

A prospective study was conducted on 47 glaucoma patients tested every 6 months with both SAP and SWAP over a mean follow-up of 4 years. Stability or progression of the disease was defined independently from SAP (it was in fact defined on the basis of ONH stereophotography). At the end of the study, progression was found in 22/47 patients and SWAP obtained a better area under the curve compared to SAP, thus confirming that SWAP may improve the detection of progressive glaucoma compared to SAP (Girkin et al., 2000).

Other studies reporting data on sensitivity and specificity for SWAP in comparison to FDT are discussed in the next session. In their review of published literature, Delgado and coworkers confirmed the clinical usefulness of SWAP, reporting a mean sensitivity and specificity of 88 and 92%, respectively (Delgado et al., 2002).

Also for SWAP, a consensus on criteria for abnormality is still missing. One study reported that the optimum criterion to define glaucomatous abnormalities is the presence of a cluster of four points lower than Po5% or a cluster of three points lower than Po1% (Polo et al., 2001). Another study suggested that GHT is the most sensitive parameter to identify the disease and its progression (Johnson et al., 2002). Contrary to FDT, a high variability in results is generally obtained if different criteria are used to define abnormality (Reus et al., 2005).

Unfortunately, SWAP applicability in clinical settings is still limited by a number of factors. SWAP is a demanding test, since stimuli are more difficult to detect than those of SAP and

FDT; the full-threshold strategy has a high duration (about 15–18 min); hence, patients are prone to a ‘‘fatigue effect’’ during examination.

SWAP must be conducted only on patients with clear media, since the presence of opacities, in particular cataract, affects the results (abnormally lower sensitivities were also found in the case of modest opacities, Sample et al., 1996).

A correction for light absorption can be performed, but this procedure is time-consuming (about 35 min). Patients suffering from migraine (McKendrick et al., 2002), epilepsy (Hosking and Hilton, 2002), ocular conditions such as diabetic maculopathy (Remky et al., 2000), and optic neuropathies (Keltner and Johnson, 1995) and those using drugs interfering with neurotransmitters (Paczka et al., 2001) may frequently obtain false-positive results at SWAP.

One of the main limitations of this perimetry is the presence of learning effect (Rossetti et al., 2006; Wild et al., 2006). We conducted a study on 30 patients at risk for glaucoma and already experienced with SAP (which represented a group of subjects who could highly benefit from early detection of the disease by SWAP); they performed a battery of 5 SWAP within 1 month. Eighty five percent of patients showed a significant learning effect: MD improved 0.6 dB per repetition and it was supposed to reach a plateau only at the sixth repetition; mean duration decreased 17 s per examination without reaching a plateau at the end of the study. The analysis of demographic, clinical, and perimetric data excluded the possibility of identifying a subgroup of patients more prone to learning effect at SWAP before carrying out the battery of tests. We concluded that at least three repetitions are required to rule out the presence of a learning effect, although a subgroup of patients could need up to five repetitions before providing clinically useful results. In Fig. 3, the first and the last SWAP of a patient in this study are shown, and substantial learning effect is evident for perimetric indices, duration, and number of abnormal points.

Finally, SWAP is also limited by statistical biases. In normal subjects, the inter-individual threshold variability is higher for SWAP than

SAP (Wild et al., 1998; Blumenthal et al., 2003); therefore, confidence intervals are wider, thus negatively affecting the ability to discriminate between normal and glaucoma cases. SWAP intertest variability in suspect and manifest glaucoma is also augmented at about 0.5–0.7 dB

compared to SAP (Wild et al., 1998; Hutchings et al., 2001; Blumenthal et al., 2003), which makes it difficult to assess progression accurately. Several factors could respond to this high variability: the difficulty of stimulus detection, the long test duration, the high sensitivity of SWAP to pupil