Fundus Autofluorescence Patterns in Best Vitelliform Macular Dystrophy




Purpose


To provide a systematic classification of fundus autofluorescence (FAF) patterns in patients affected by Best vitelliform macular dystrophy.


Design


Cross-sectional prospective study.


Methods


Patients affected by Best vitelliform macular dystrophy at different stages of the disease were prospectively enrolled from January 2012 to July 2013. Eighty eyes of 40 patients were included in the study. All patients underwent a complete ophthalmologic examination, including genetic characterization, short-wavelength FAF, and near-infrared FAF. Main outcome measures were the recognition of the FAF patterns in the different stages and the identification of a relationship between FAF patterns and best-corrected visual acuity (BCVA).


Results


Six FAF patterns for both short-wavelength and near-infrared FAF were identified, including normal, hyper-autofluorescent, hypo-autofluorescent, patchy, multifocal, and spoke-like patterns. Applying Gass’s classification for defining consecutive stages of Best vitelliform macular dystrophy (namely vitelliform, pseudohypopyon, vitelliruptive, atrophic, and cicatricial) identified no pattern as stage-specific. Patchy patterns had the highest prevalence. A statistically significant difference (Kruskal-Wallis ANOVA) was found among hyper-autofluorescent, patchy, and hypo-autofluorescent patterns, both in short-wavelength ( P = .001) and near-infrared FAF ( P = .001). Hyper-autofluorescent and hypo-autofluorescent patterns were associated with better and worse BCVA, respectively.


Conclusions


Six main patterns on both short-wavelength and near-infrared FAF were identified in Best vitelliform macular dystrophy. No FAF pattern can be considered stage-specific. Although a difference in the BCVA among the FAF patterns was registered, only a longitudinal study designed to evaluate the clinical and FAF modifications over the follow-up will help clarify the prognostic implications of each FAF pattern.


Best vitelliform macular dystrophy is an autosomal dominant disease with variable penetrance and expressivity, caused by mutations in the BEST1 gene. In its classical description, Best vitelliform macular dystrophy is clinically characterized by a bilateral yellow lesion in the macula, which tends to alter over time. Gass’s classification identifies several stages of the lesion; namely, vitelliform, pseudohypopyon, vitelliruptive (scrambled egg), atrophic, and cicatricial. Histopathologic studies have demonstrated that patients affected by Best vitelliform macular dystrophy have an abnormal accumulation of lipofuscin within the retinal pigment epithelium (RPE) cells and in the sub-RPE space. Fundus autofluorescence (FAF) can significantly contribute to the clinical characterization of the disease. In particular, short-wavelength FAF, enabling the visualization of A2E and other bisretinoid pigments of lipofuscin in the RPE, provides a reliable, noninvasive tool for monitoring the progressive changes of Best vitelliform macular dystrophy. An autofluorescence signal from the retina can also be acquired using near-infrared light, similar to the wavelengths used for indocyanine green angiography. Near-infrared FAF appears to correspond to melanin (present in the RPE as well as the choroid) rather than lipofuscin. As such, it provides a different type of information, which may be complementary to short-wavelength FAF. Previous investigations have shown variable patterns of short-wavelength FAF in Best vitelliform macular dystrophy, varying from an increased signal, especially visible in the early stages, to a decreased response toward the later stages.


However, only limited information regarding a thorough description of the FAF patterns in the various stages of the disorder is available.


The aim of the present study is to provide a systematic classification of FAF patterns on both short-wavelength FAF and near-infrared FAF characteristic of the different stages of Best vitelliform macular dystrophy.


Methods


A consecutive series of patients affected by Best vitelliform macular dystrophy were prospectively recruited for the study. All the details of the purpose of the current study were discussed with each subject, who provided a written specific informed consent. The protocol was approved by the institutional review board of the University Vita-Salute, Scientific Institute San Raffaele, and the procedures adhered to the tenets of the Declaration of Helsinki. All patients provided blood samples for genetic testing and underwent a complete ophthalmic examination, including best-corrected visual acuity (BCVA), biomicroscopy, applanation tonometry, biomicroscopic examination, short-wavelength FAF, and near-infrared FAF.


Patients were excluded from the study if they had significant cataracts or other media opacities, and/or if they had other concomitant ocular diseases that could affect the results.


The diagnosis of Best vitelliform macular dystrophy was made based on the clinical appearance and was confirmed by identification of the mutation in the BEST1 gene. Patients were placed into 5 stages according to the characteristic of the lesion: stage 1 (subclinical, with no vitelliform alteration), stage 2 (vitelliform), stage 3 (pseudohypopyon), stage 4 (vitelliruptive/scrambled egg), and stage 5 (atrophic/cicatricial). FAF was obtained using a confocal scanning laser ophthalmoscope (Heidelberg Retinal Angiograph 2; Heidelberg Engineering, Heidelberg, Germany). Near-infrared FAF imaging was carried out using a diode laser at 787 nm wavelength for excitation and a barrier filter for detection of emitted light above 810 nm. Short-wavelength FAF images of ocular fundi were obtained at 488 nm excitation wavelength and a barrier filter with wavelength of 500 nm was used for the detection of emitted light. For both short-wavelength FAF and near-infrared FAF, 100 single images (30 × 30 degree view mode, 768*768 pixels) were averaged to obtain a high-quality image.


BCVA was recorded on ETDRS charts at 4 meters by a masked examiner and converted to logMAR. FAF images of each patient were independently analyzed by 2 masked examiners after identifying 6 well-defined FAF patterns for both short-wavelength FAF and near-infrared FAF (see below). In the absence of a unanimous consensus, a third examiner was recruited for the analysis.


The primary outcome of the study was the identification of the FAF patterns in the different stages of Best vitelliform macular dystrophy. The secondary outcome was the correlation of FAF patterns with BCVA.


Results were expressed as mean ± standard deviation for continuous variables and as frequency and percentages for categorical variables. Analysis of variance for nonparametric data distribution (ANOVA, Kruskal-Wallis test) was used to study the differences in the BCVA between groups of patients based on the FAF pattern. The χ 2 test was applied to evaluate the association between the different mutations in the BEST1 gene and the FAF pattern distribution. A P value of <.05 was considered statistically significant.




Results


Eighty eyes (40 patients) were included in the study. Mean age was 44 ± 12 years, with 21 male patients. Mean BCVA was 0.41 ± 0.38 logMAR (range: 1.30–0). All the patients showed clear media, allowing good-quality FAF images to be obtained. Ten eyes (12.5%) were in stage 1, 37 eyes (46%) in stage 2, 8 eyes (10%) in stage 3, 19 eyes (24%) in stage 4, and 6 eyes (7.5%) in stage 5.


Overall, 6 FAF patterns for both short-wavelength FAF and near-infrared FAF were identified: normal pattern (no difference in FAF appearance compared to a normal subject), hyper-autofluorescent pattern (increased FAF signal), hypo-autofluorescent pattern (decreased FAF signal), patchy pattern (combined reduced and increased FAF signal), multifocal pattern (multiple, isolated increased FAF signals), and spoke-like pattern (increased FAF signals with a spoke-like configuration) ( Figures 1 and 2 ).




Figure 1


Patterns of short-wavelength fundus autofluorescence in Best vitelliform macular dystrophy. Six main patterns were identified according to a qualitative classification: normal (Top left), hyper-autofluorescent (Top center), hypo-autofluorescent (Top right), patchy (Bottom left), spoke-like (Bottom center), and multifocal (Bottom right).



Figure 2


Patterns of near-infrared fundus autofluorescence in Best vitelliform macular dystrophy. Six main patterns were detected on near-infrared fundus autofluorescence: normal (Top left), hyper-autofluorescent (Top center), hypo-autofluorescent (Top right), patchy (Bottom left), spoke-like (Bottom center), and multifocal (Bottom right).


When considering the eyes in stage 1, 8 eyes had a normal pattern at short-wavelength FAF and a hypo-autofluorescent pattern at near-infrared FAF, whereas in 2 eyes both short-wavelength FAF and near-infrared FAF revealed a multifocal pattern ( Table 1 ). The 2 FAF techniques showed a pattern concordance in 2 eyes (20%). Mean BCVA was 0.0 ± 0.0 logMAR.



Table 1

Fundus Autofluorescence Pattern Distribution and Mean Best-Corrected Visual Acuity Values in the 10 Eyes With Stage 1 Best Vitelliform Macular Dystrophy





























Normal Fundus Autofluorescence Multifocal Fundus Autofluorescence Hypo-Fundus Autofluorescence
SW-FAF (no. eyes/%) 8 (80%) 2 (20%) 0
Mean BCVA (±SD) 0.0 ± 0.0 0.0 ± 0.0
NIR-FAF (no. eyes/%) 0 2 (20%) 8 (80%)
Mean BCVA (±SD) 0.0 ± 0.0 0.0 ± 0.0

BCVA = best-corrected visual acuity; NIR-FAF = near-infrared autofluorescence; SD = standard deviation; SW-FAF = short-wavelength fundus autofluorescence.


On short-wavelength FAF, eyes in stage 2 showed a hyper-autofluorescent pattern in 15 cases, a patchy pattern in 18 cases, and a hypo-autofluorescent pattern and a spoke-like pattern in 2 cases. On near-infrared FAF, the most frequent pattern was the patchy pattern, detectable in 27 eyes, whereas a hyper-autofluorescent pattern was visible in 7 eyes, a hypo-autofluorescent pattern in 1 eye, and a spoke-like pattern in 2 eyes ( Table 2 ). A pattern concordance between the 2 FAF techniques was registered in 27 eyes (73%). Mean BCVA was 0.29 ± 0.29 logMAR.



Table 2

Fundus Autofluorescence Pattern Distribution and Mean Best-Corrected Visual Acuity Values in 37 Eyes With Stage 2 Best Vitelliform Macular Dystrophy


































Hyper-Fundus Autofluorescence Patchy Spoke-like Hypo-Fundus Autofluorescence
SW-FAF (no. eyes/%) 15 (40%) 18 (49%) 2 (5%) 2 (5%)
Mean BCVA (±SD) 0.20 ± 0.19 0.35 ± 0.32 0.2 ± 0.0 0.5 ± 0.7
NIR-FAF (no. eyes/%) 7 (19%) 27 (73%) 2 (5%) 1 (3%)
Mean BCVA (±SD) 0.1 ± 0.1 0.32 ± 0.29 0.2 ± 0.0 1

BCVA = best-corrected visual acuity; NIR-FAF = near-infrared autofluorescence; SD = standard deviation; SW-FAF = short-wavelength fundus autofluorescence.


Short-wavelength FAF in stage 3 revealed a patchy and a hyper-autofluorescent pattern in 7 and 1 eyes, respectively, whereas near-infrared FAF showed a patchy pattern in all the eyes ( Table 3 ). Seven eyes (87.5%) revealed a pattern concordance on short-wavelength FAF and near-infrared FAF. Mean BCVA was 0.65 ± 0.32 logMAR.



Table 3

Fundus Autofluorescence Pattern Distribution and Mean Best-Corrected Visual Acuity Values in 8 Eyes With Stage 3 Best Vitelliform Macular Dystrophy
























Hyper-Fundus Autofluorescence Patchy
SW-FAF (no. eyes/%) 1 (12.5%) 7 (87.5%)
Mean BCVA (±SD) 0.4 0.70 ± 0.32
NIR-FAF (no. eyes/%) 0 8 (100%)
Mean BCVA (±SD) 0.66 ± 0.32

BCVA = best-corrected visual acuity; NIR-FAF = near-infrared autofluorescence; SD = standard deviation; SW-FAF = short-wavelength fundus autofluorescence.


The analysis of the 19 eyes in stage 4 disclosed that 16 and 3 eyes had a patchy and a hypo-autofluorescent pattern on short-wavelength FAF, respectively. On the other hand, near-infrared FAF identified a patchy pattern in 14 eyes, a hypo-autofluorescent pattern in 4 eyes, and a hyper-autofluorescent pattern in 1 eye ( Table 4 ). A pattern concordance for the 2 FAF techniques was found in 17 eyes (89%). Mean BCVA was 0.56 ± 0.31 logMAR.



Table 4

Fundus Autofluorescence Pattern Distribution and Mean Best-Corrected Visual Acuity Values in 19 Eyes With Stage 4 Best Vitelliform Macular Dystrophy





























Hyper-Fundus Autofluorescence Patchy Hypo-Fundus Autofluorescence
SW-FAF (no. eyes/%) 0 16 (84%) 3 (16%)
Mean BCVA (±SD) 0.56 ± 0.33 0.6 ± 0.17
NIR-FAF (no. eyes/%) 1 (5%) 14 (74%) 4 (21%)
Mean BCVA (±SD) 0.8 0.55 ± 0.34 0.57 ± 0.15

BCVA = best-corrected visual acuity; NIR-FAF = near-infrared autofluorescence; SD = standard deviation; SW-FAF = short-wavelength fundus autofluorescence.


The examination of the eyes in stage 5 revealed that 5 and 1 eyes revealed a hypo-autofluorescent and a patchy pattern, respectively, on short-wavelength FAF, whereas near-infrared FAF identified 3 patchy and 3 hypo-autofluorescent patterns ( Table 5 ). The 2 FAF techniques showed a pattern concordance in 4 eyes (66%). Mean BCVA was 1.05 ± 0.12 logMAR.



Table 5

Fundus Autofluorescence Pattern Distribution and Mean Best-Corrected Visual Acuity Values in 6 Eyes With Stage 5 Best Vitelliform Macular Dystrophy
























Hypo-Fundus Autofluorescence Patchy
SW-FAF (no. eyes/%) 5 (83%) 1 (17%)
Mean BCVA (±SD) 1.06 ± 0.13 1
NIR-FAF (no. eyes/%) 3 (50%) 3 (50%)
Mean BCVA (±SD) 1 ± 1.1 1 ± 0

BCVA = best-corrected visual acuity; NIR-FAF = near-infrared autofluorescence; SD = standard deviation; SW-FAF = short-wavelength fundus autofluorescence.

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Jan 8, 2017 | Posted by in OPHTHALMOLOGY | Comments Off on Fundus Autofluorescence Patterns in Best Vitelliform Macular Dystrophy

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