Chiara Olivieri

Dr. Chiara Olivieri

orcid

Research Focus & Metrics

Academic Career Length

3Years (2024-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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30 August 2024 in Ophthalmology Retina
Verified
Journal Article
Open access
Enrico BorrelliEnrico Borrelli
Enrico Borrelli
COChiara Olivieri
Chiara Olivieri
SSSonia Serafino
Sonia Serafino
Andrea ColettoAndrea Coletto
Andrea Coletto
FRFederico Ricardi
Federico Ricardi
MRMichele Reibaldi
Michele Reibaldi
Macular atrophy is a common complication in neovascular age-related macular degeneration (AMD) and is associated with poorer visual outcomes. This study evaluated inter-reader and inter-modality variability in measuring macular atrophy in previously-treated neovascular AMD eyes without exudation, using six imaging modalities. Prospective, cohort study. Thirty participants with previously-treated neovascular AMD, showing no signs of exudation at the time of enrollment, and exhibiting macular atrophy. During the same clinic visit, patients were imaged using six different imaging modalities: color fundus photography (CFP; Clarus, Carl Zeiss Meditec), near-infrared imaging (NIR; Spectralis; Heidelberg Engineering, Heidelberg, Germany), structural optical coherence tomography (OCT; Spectralis; Heidelberg Engineering, Heidelberg, Germany), green fundus autofluorescence (GAF; Clarus, Carl Zeiss Meditec), blue fundus autofluorescence (BAF; Spectralis; Heidelberg Engineering, Heidelberg, Germany), and pseudocolor imaging (MultiColor; Spectralis; Heidelberg Engineering, Heidelberg, Germany). Two readers independently measured the macular atrophy area. Inter-reader and inter-modality agreement. The 95% coefficient of repeatability (CR) was 5.98 mm2 for CFP, 4.46 mm2 for MultiColor, 3.90 mm2 for BAF, 3.92 mm2 for GAF, 4.86 mm2 for NIR, and 3.55 mm2 for OCT. Similarly, the coefficient of variation (CV) was lowest for the OCT-based grading at 0.08 and highest for the NIR-based grading at 0.28. Accordingly, the intraclass correlation coefficient (ICC) was 0.742 for CFP, 0.805 for MultiColor, 0.857 for BAF, 0.850 for GAF, 0.755 for NIR, and 0.917 for OCT. The 6 different imaging modalities presented measurements with different mean values, with only a limited number of comparisons not significantly different between the instruments, although measurements were correlated. The largest size of macular atrophy was with the structural OCT-based grading (median=4.65 mm2; interquartile range [IQR]=4.78 mm2) and the smallest was with the CFP-based grading (median=3.86 mm2; IQR=5.06 mm2). Inconsistencies arose from various factors. In patients with neovascular AMD, macular atrophy measurements vary significantly depending on the imaging technique used. CFP-based assessments yielded the smallest macular atrophy sizes, while structural OCT-based assessments produced the largest. These discrepancies stem from both the inherent limitations of each modality in assessing RPE atrophy and factors related to neovascularization, such as the coexistence of fibrosis.

17 June 2024 in Medicina
Verified
Journal Article
Open access
PDF file
Enrico BorrelliEnrico Borrelli
Enrico Borrelli
SSSonia Serafino
Sonia Serafino
FRFederico Ricardi
Federico Ricardi
Andrea ColettoAndrea Coletto
Andrea Coletto
GNGiovanni Neri
Giovanni Neri
MRMichele Reibaldi
Michele Reibaldi
Background and objectives: Age-related macular degeneration (AMD) is a complex and multifactorial condition that can lead to permanent vision loss once it progresses to the neovascular exudative stage. This review aims to summarize the use of deep learning in neovascular AMD. Materials and Methods: Pubmed search. Results: Deep learning has demonstrated effectiveness in analyzing structural OCT images in patients with neovascular AMD. This review outlines the role of deep learning in identifying and measuring biomarkers linked to an elevated risk of transitioning to the neovascular form of AMD. Additionally, deep learning techniques can quantify critical OCT features associated with neovascular AMD, which have prognostic implications for these patients. Incorporating deep learning into the assessment of neovascular AMD eyes holds promise for enhancing clinical management strategies for affected individuals. Conclusion: Several studies have demonstrated effectiveness of deep learning in assessing neovascular AMD patients and this has a promising role in the assessment of these patients.

29 August 2024 in Turkish Journal of Ophthalmology
Verified
Journal Article
Open access
GNGiovanni Neri
Giovanni Neri
COChiara Olivieri
Chiara Olivieri
SSSonia Serafino
Sonia Serafino
PVPasquale Viggiano
Pasquale Viggiano
PMPaola Marolo
Paola Marolo
Enrico BorrelliEnrico Borrelli
Enrico Borrelli
Choriocapillaris in Age-Related Macular Degeneration - Turkish Journal of Ophthalmology

21 June 2025 in Canadian Journal of Ophthalmology
Verified
Journal Article
Open access
Andrea ColettoAndrea Coletto
Andrea Coletto
SSSonia Serafino
Sonia Serafino
COChiara Olivieri
Chiara Olivieri
VMValentina Marica
Valentina Marica
PVPasquale Viggiano
Pasquale Viggiano
MRMichele Reibaldi
Michele Reibaldi
To assess inter-reader and intermodality variability in quantifying macular fibrosis in patients with neovascular age-related macular degeneration (AMD) using 4 imaging modalities: color fundus photography (CFP), near-infrared reflectance (NIR), structural optical coherence tomography (OCT), and MultiColor imaging. Prospective, cross-sectional case series. Thirty eyes of 30 patients with neovascular AMD and macular fibrosis, previously treated with anti-vascular endothelial growth factor therapy. Imaging was performed using CFP, NIR, structural OCT, and MultiColor modalities. Two masked graders evaluated the size of macular fibrosis using each modality. The study assessed inter-reader agreement using the intraclass correlation coefficient (ICC), coefficient of variation (CV), and 95% coefficient of repeatability. Intermodality variability was analyzed using repeated measures ANOVA and pairwise comparisons. Structural OCT demonstrated the highest inter-reader agreement (ICC = 0.983; CV = 0.04), while NIR exhibited the lowest (ICC = 0.461; CV = 0.26). The median macular fibrosis size was largest on structural OCT (4.87 mm²) and smallest on MultiColor imaging (2.03 mm²). Significant differences were observed between imaging modalities, with fibrosis measurements from different modalities not consistently comparable. Structural OCT is the most reliable modality for quantifying macular fibrosis in neovascular AMD. The observed intermodality variability highlights the need for standardized criteria in fibrosis assessment across imaging techniques, as differences can impact clinical interpretation and management.

8 November 2025 in Biomolecules
Verified
Journal Article
Open access
PDF file
SISimona Intonti
Simona Intonti
COChiara Olivieri
Chiara Olivieri
MRMichele Reibaldi
Michele Reibaldi
Enrico BorrelliEnrico Borrelli
Enrico Borrelli
CCClaudia Curcio
Claudia Curcio
FCFederica Maria Conedera
Federica Maria Conedera
Age-related macular degeneration (AMD) is a leading cause of irreversible central vision loss. Its pathogenesis is complex and multifactorial, involving genetic predisposition, inflammation, oxidative stress, and environmental influences, which underscores the need to better understand biomarkers associated with the disease. This review provides a comprehensive translational overview of biomarkers linked to both dry and wet forms of AMD by integrating findings from human studies and preclinical mouse models, including chemical, genetic, and laser-induced paradigms. It outlines key tissue, fluid, and systemic biomarkers related to oxidative stress, inflammation, complement activation, extracellular matrix remodeling, angiogenesis, and gut microbiota alterations. The main findings highlight similarities and differences between human AMD and animal models, identify challenges in biomarker validation, and emphasize the potential of combining biomarker profiles from ocular tissues, blood, tear fluid, aqueous and vitreous humor, and gut microbiome samples to improve early diagnosis, therapeutic monitoring, and personalized treatment strategies. These insights suggest that integrating experimental and clinical biomarker data could advance precision medicine in AMD, facilitating better early detection and individualized therapies. Future research should aim to bridge these datasets to optimize biomarker-driven approaches for AMD management.

1 June 2026 in Ophthalmology Science
Verified
Journal Article
Open access
COChiara Olivieri
Chiara Olivieri
GPGiacomo Perin
Giacomo Perin
XZXuenan Zhuang
Xuenan Zhuang
GNGiovanni Neri
Giovanni Neri
GPGuglielmo Parisi
Guglielmo Parisi
Enrico BorrelliEnrico Borrelli
Enrico Borrelli
To evaluate baseline structural OCT biomarkers associated with the development of macular atrophy or fibrosis in treatment-naïve eyes with exudative neovascular age-related macular degeneration (AMD) managed with a treat-and-extend (T&E) anti-VEGF regimen. A retrospective, cohort study. Eighty-nine eyes of 89 patients with newly diagnosed exudative neovascular AMD, treated with a T&E regimen and followed for 24 months. Eyes with evidence of macular atrophy or fibrosis at baseline were excluded. Structural OCT scans were assessed at baseline for morphological features including, macular neovascularization (MNV) subtype and presence of subretinal fluid, intraretinal fluid (IRF), subretinal hyperreflective material, hyperreflective foci, and subretinal drusenoid deposits. Two masked graders independently evaluated each scan, with adjudication for discrepancies. Cox regression models were used to determine baseline predictors of macular atrophy and fibrosis over 24 months. Development of macular atrophy or fibrosis during 24 months, expressed as hazard ratios (HRs) with 95% confidence intervals (CIs). During follow-up, 28 eyes (31.5%) developed macular atrophy and 12 eyes (13.5%) developed macular fibrosis, with 10 eyes showing both complications. Multivariate Cox regression identified baseline IRF (HR, 6.07; 95% CI, 2.23–16.48) and type 3 MNV (HR, 4.38; 95% CI, 1.63–11.73) as independent predictors of macular atrophy, whereas type 1 MNV was protective (HR, 0.23; 95% CI, 0.09–0.61). Type 2 MNV emerged as the strongest predictor of macular fibrosis (HR, 7.28; 95% CI, 1.51–35.10). Baseline OCT biomarkers, particularly IRF and type 3 MNV, strongly predict macular atrophy, while type 2 MNV predicts fibrosis in eyes with exudative neovascular AMD treated with a T&E regimen. Type 1 MNV may confer protection against atrophy. These exploratory findings underscore the value of comprehensive baseline OCT assessment for anticipating long-term structural outcomes and guiding clinical management. Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.