A Radiomic-Based Machine Learning System to Diagnose Age-Related Macular Degeneration from Ultra-Widefield Fundus Retinography.

The present study was conducted to investigate the potential of radiomics to develop an explainable AI-based system to be applied to ultra-widefield fundus retinographies (UWF-FRTs) with the objective of predicting the presence of the early signs of Age-related Macular Degeneration (AMD) and stratifying subjects with low- versus high-risk of AMD. The ultimate aim was to provide clinicians with an automatic classifier and a signature of objective quantitative image biomarkers of AMD. The use of Machine Learning (ML) and radiomics was based on intensity and texture analysis in the macular region, detected by a Deep Learning (DL)-based macular detector. Two-hundred and twenty six UWF-FRTs were retrospectively collected from two centres and manually annotated to train and test the algorithms. Notably, the combination of the ML-based radiomics model and the DL-based macular detector reported 93% sensitivity and 74% specificity when applied to the data of the centre used for external testing, capturing explainable features associated with drusen or pigmentary abnormalities. In comparison to the human operator's annotations, the system yielded a 0.79 Cohen κ, demonstrating substantial concordance. To our knowledge, these results are the first provided by a radiomic approach for AMD supporting the suitability of an explainable feature extraction method combined with ML for UWF-FRT.

How Reliable Is Pyramidal Wavefront-Based Sensor Aberrometry in Measuring the In Vivo Optical Behaviour of Multifocal IOLs?

Cataract or refractive lens surgery, along with the implantation of multifocal intraocular lenses (MF-IOL), enables a complete range of functional far, near and intermediate vision. Refractive, diffractive and extended depth of focus (EDoF) or combination of these principles represent the technology used to obtain this multifocality. Aberrometry makes it possible to study the aberrations induced by MF-IOLs. Among the different optical principles available to measure ocular aberrations, pyramidal wavefront-based sensor (PWS) aberrometry shows the highest resolution with MF-IOLs. Retinal image quality measured by a PWS aberrometer differed significantly according to the technology of the implanted lens. Monofocal and diffractive lenses showed the highest values of far-distance retinal image quality, followed by refractive and EDoF lenses; however, retinal image quality analysed in diffractive lenses appears to be more dependent on residual refractive error. Considering this limitation, PWS-aberrometry could be used to compare diffractive lenses. Nevertheless, further studies are needed to provide additional information about the clinical retinal image quality of MF-IOLs and to help surgeons in the important preoperative selection of IOLs.

Management of unresolved optic disc pit maculopathy with human amniotic membrane patch implant: A case report.

BACKGROUND/PURPOSE: Inverted Inner Limiting Membrane (ILM)-flap approach can fail in the treatment of Optic disc pit maculopathy (ODPM). We report a surgical technique involving human amniotic membrane (hAM) patch implant to treat unresolved ODPM after inverted (ILM)-flap technique. CASE REPORT: One patient with decreased visual acuity (1 LogMar) after unsuccessful inverted ILM-flap technique to treat ODPM, underwent hAM patch implant and was evaluated. A surgical approach including a 2 mm size graft patch of hAM implantation over the optic disc pit followed by fluid-air exchange was performed. A gas endotamponade was finally used. The patient was instructed to maintain face-down position for the first three days after surgery. The hAM patch remained detectable over the pit for the entire 6-months follow-up. The ODPM gradually resolved and visual acuity partially recovered to 0.17 LogMar during follow-up. No postoperative complications or recurrence were reported. CONCLUSION: hAM patch implant may be effective to manage ODPM after unsuccessful inverted ILM-flap.

Correlation between retinal vessel rarefaction and psychometric measures in an older Southern Italian population.

Objective: To explore the linear association between inner retinal layers thickness and macular capillary density compared to variations of global cognition evaluated by psychometric measures in a cohort of Mediterranean subjects aged 65+ years. Materials and methods: We performed a cross-sectional analysis of 574 participants aged 65 years+ drawn from a population-based Southern Italian study. All subjects underwent neurological evaluations, including global cognitive screening, the Mini-Mental State Examination (MMSE) and frontal assessment battery (FAB), together with an ophthalmic examination including optical coherence tomography (OCT) and OCT-Angiography. We assessed the average thickness of the ganglion cell complex (GCC) and the retinal nerve fiber layer (RNFL), the foveal avascular zone area, and vascular density (VD) of superficial (SVD) and deep (DVD) capillary plexi at the foveal and parafoveal area. Linear regression was applied to assess associations of ocular measurements with MMSE and FAB scores. Results: In the linear regression model, foveal DVD (beta = 0.01, 95% CI:0.004-0.052), whole DVD (beta = 0.04, 95% CI:0.02-0.08), and whole SVD (beta = 0.04, 95% CI:0.02-0.07) showed a positive association with MMSE. In addition, foveal SVD (beta = 0.01, 95% CI:0.003-0.05) and whole SVD (beta = 0.03, 95% CI:0.004-0.08) were positively associated with the FAB score. We found no further significant association between the MMSE score or the FAB score and the average thickness of the GCC and RNFL, and FAZ area. Conclusion: A direct linear association between the VD of the macular capillary plexi with global and frontal cognitive functions was observed in elderly subjects.