Incidence of macular displacement after rhegmatogenous retinal detachment surgery using ultra-widefield fundus autofluorescence.

PURPOSE: The incidence of retinal displacement after rhegmatogenous retinal detachment (RRD) surgery is variable and its clinical consequences are unclear. The aim of this study was to assess the incidence and clinical features of retinal displacement after RRD surgery by using ultra-widefield (UWF) imaging. METHODS: Retrospective observational study including all consecutive patients who underwent RRD surgery at the Rothschild Foundation Hospital. Postoperative data included the visual acuity and symptoms of visual impairment. Macular retinal displacement occurrence and its features were assessed and measured by using the autofluorescence images. RESULTS: A total of 123 eyes were included. UWF fundus autofluorescence revealed the presence of macular retinal displacement in 14 (11%) eyes. All displacements were inferior, with a mean angle of 3.8°. Patients with and without macular displacement did not differ in postoperative visual acuity. The retinal detachment extent and preoperative macular involvement were not significantly associated with the occurrence of retinal displacement. CONCLUSION: In this representative cohort of eyes that underwent RRD surgery with systematic screening for postoperative retinal displacement by UWF fundus autofluorescence, 11% of eyes experienced an inferior retinal shift. As in other cohorts, the presence of metamorphopsia was not associated with the occurrence of retinal shift.

A novel RLBP1 gene mutation associated to a flecked retina syndrome.

PURPOSE: To present an unusual fleck retina condition associated to a novel RLBP1 gene mutation.Methods/Results: A 25-year old male presented flecks on fundoscopic examination. Clinical presentation, multimodal imaging and ERG were compatible with the diagnosis of benign familial fleck retina. Genetic analysis detected an RLBP1 gene, a gene commonly associated with more severe retinal disease. CONCLUSION: Flecked retina syndromes and other genetic retinal diseases have a complex genotype-phenotype relation and need further research for their pathophysiology to be fully understood.

Deep Learning for prediction of late recurrence of retinal detachment using preoperative and postoperative ultra-wide field imaging.

PURPOSE: To elaborate a deep learning (DL) model for automatic prediction of late recurrence (LR) of rhegmatogenous retinal detachment (RRD) using pseudocolor and fundus autofluorescence (AF) ultra-wide field (UWF) images obtained preoperatively and postoperatively. MATERIALS AND METHODS: We retrospectively included patients >18 years who underwent either scleral buckling (SB) or pars plana vitrectomy (PPV) for primary or recurrent RRD with a post-operative follow-up >2 years. Records of RRD recurrence between 6 weeks and 2 years after surgery served as a ground truth for the training of the deep learning (DL) models. Four separate DL models were trained to predict LR within the 2 postoperative years (binary outputs) using, respectively, UWF preoperative and postoperative pseudocolor images and UWF preoperative and postoperative AF images. RESULTS: A total of 412 eyes were included in the study (332 eyes treated with PPV and 80 eyes with SB). The mean follow-up was 4.0 ± 2.1 years. The DL models based on preoperative and postoperative pseudocolor UWF imaging predicted recurrence with 85.6% (sensitivity 86.7%, specificity 85.4%) and 90.2% accuracy (sensitivity 87.0%, specificity 90.8%) in PPV-treated eyes, and 87.0% (sensitivity 86.7%, specificity 87.0%) and 91.1% (sensitivity 88.2%, specificity 91.9%) in SB-treated eyes, respectively. The DL models using preoperative and postoperative AF-UWF imaging predicted recurrence with 87.6% (sensitivity 84.0% and specificity 88.3%) and 91.0% (sensitivity 88.9%, specificity 91.5%) accuracy in PPV eyes, and 86.5% (sensitivity 87.5%; specificity 86.2%) and 90.6% (sensitivity 90.0%, specificity 90.7%) in SB eyes, respectively. Among the risk factors detected with visualisation methods, potential novel ones were extensive laser retinopexy and asymmetric staphyloma. CONCLUSIONS: DL can accurately predict the LR of RRD based on UWF images (especially postoperative ones), which can help refine follow-up strategies. Saliency maps might provide further insight into the dynamics of RRD recurrence.