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1.
Am J Ophthalmol ; 263: 35-49, 2024 Feb 03.
Article in English | MEDLINE | ID: mdl-38311152

ABSTRACT

PURPOSE: The NIGHT study aimed to assess the natural history of choroideremia (CHM), an X-linked inherited chorioretinal degenerative disease leading to blindness, and determine which outcomes would be the most sensitive for monitoring disease progression. DESIGN: A prospective, observational, multicenter cohort study. METHODS: Males aged ≥18 years with genetically confirmed CHM, visible active disease within the macular region, and best-corrected visual acuity (BCVA) ≥34 Early Treatment Diabetic Retinopathy Study (ETDRS) letters at baseline were assessed for 20 months. The primary outcome was the change in BCVA over time at Months 4, 8, 12, 16, and 20. A range of functional and anatomical secondary outcome measures were assessed up to Month 12, including retinal sensitivity, central ellipsoid zone (EZ) area, and total area of fundus autofluorescence (FAF). Additional ocular assessments for safety were performed. RESULTS: A total of 220 participants completed the study. The mean BCVA was stable over 20 months. Most participants (81.4% in the worse eye and 77.8% in the better eye) had change from baseline > -5 ETDRS letters at Month 20. Interocular symmetry was low overall. Reductions from baseline to Month 12 were observed (worse eye, better eye) for retinal sensitivity (functional outcome; -0.68 dB, -0.48 dB), central EZ area (anatomical outcome; -0.276 mm2, -0.290 mm2), and total area of FAF (anatomical outcome; -0.605 mm2, -0.533 mm2). No assessment-related serious adverse events occurred. CONCLUSIONS: Retinal sensitivity, central EZ area, and total area of FAF are more sensitive than BCVA in measuring the natural progression of CHM.

2.
Sci Rep ; 13(1): 20354, 2023 11 21.
Article in English | MEDLINE | ID: mdl-37990107

ABSTRACT

To create a deep learning (DL) classifier pre-trained on fundus autofluorescence (FAF) images that can assist the clinician in distinguishing age-related geographic atrophy from extensive macular atrophy and pseudodrusen-like appearance (EMAP). Patients with complete outer retinal and retinal pigment epithelium atrophy secondary to either EMAP (EMAP Group) or to dry age related macular degeneration (AMD group) were retrospectively selected. Fovea-centered posterior pole (30° × 30°) and 55° × 55° degree-field-of-view FAF images of sufficiently high quality were collected and used to train two different deep learning (DL) classifiers based on ResNet-101 design. Testing was performed on a set of images coming from a different center. A total of 300 patients were recruited, 135 belonging to EMAP group and 165 belonging to AMD group. The 30° × 30° FAF based DL classifier showed a sensitivity of 84.6% and a specificity of 85.3% for the diagnosis of EMAP. The 55° × 55° FAF based DL classifier showed a sensitivity of 90% and a specificity of 84.6%, a performance that was significantly higher than that of the 30° × 30° classifer (p = 0.037). Artificial intelligence can accurately distinguish between atrophy caused by AMD or by EMAP on FAF images. Its performance are improved using wide field acquisitions.


Subject(s)
Deep Learning , Geographic Atrophy , Macular Degeneration , Humans , Retrospective Studies , Artificial Intelligence , Geographic Atrophy/diagnosis , Fluorescein Angiography , Macular Degeneration/diagnostic imaging , Fundus Oculi , Atrophy
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