Comment on: Imaging Biomarkers for Early Differentiation of Candida and Aspergillus Endogenous Fungal Endophthalmitis: Multicenter Optical Coherence Tomography-Based Analysis

Sep 20, 2026 by in OPHTHALMOLOGY Comments Off on Comment on: Imaging Biomarkers for Early Differentiation of Candida and Aspergillus Endogenous Fungal Endophthalmitis: Multicenter Optical Coherence Tomography-Based Analysis
W e read with great interest the study by Agarwal et al., which presents a multicenter optical coherence tomography (OCT)-based analysis of culture-proven Candida and Aspergillus endogenous fungal endophthalmitis (EFE)….
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Comment on “Nonmydriatic Ocular Fundus Imaging in a General Emergency Department: Feasibility and Novel Considerations for Systematic Screening”

Sep 20, 2026 by in OPHTHALMOLOGY Comments Off on Comment on “Nonmydriatic Ocular Fundus Imaging in a General Emergency Department: Feasibility and Novel Considerations for Systematic Screening”
W e read with great interest the study by Shanmugam et al. examining the feasibility of systematic nonmydriatic ocular fundus photography combined with optical coherence tomography in a general emergency…
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Reply to Comment on “RNFL Thickness in a Population-Based Cohort: The Canadian Longitudinal Study on Aging M2M (Machine-to-Machine) Study”

Sep 20, 2026 by in OPHTHALMOLOGY Comments Off on Reply to Comment on “RNFL Thickness in a Population-Based Cohort: The Canadian Longitudinal Study on Aging M2M (Machine-to-Machine) Study”
We thank Aitha and colleagues for their thoughtful comments regarding our article. Several points warrant clarification. The first critique raises an important issue regarding the distinction between individual-level prediction error…
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Comment on “RNFL Thickness in a Population-Based Cohort: The Canadian Longitudinal Study on Aging M2M (Machine-to-Machine) Study”

Sep 20, 2026 by in OPHTHALMOLOGY Comments Off on Comment on “RNFL Thickness in a Population-Based Cohort: The Canadian Longitudinal Study on Aging M2M (Machine-to-Machine) Study”
We read with great interest the study by Azizi et al. , applying the machine-to-machine deep learning model to estimate retinal nerve fiber layer thickness from fundus photographs in the…
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Reply to Comment on: “Macular OCTA Biomarkers Predict Regional Retinal Nonperfusion Patterns on Ultra-Widefield Angiography in Diabetes”

Sep 20, 2026 by in OPHTHALMOLOGY Comments Off on Reply to Comment on: “Macular OCTA Biomarkers Predict Regional Retinal Nonperfusion Patterns on Ultra-Widefield Angiography in Diabetes”
W e thank Dr Wang for the thoughtful comments on our article and for raising the important issues of reproducibility, standardization, and clinical scalability in quantitative optical coherence tomography angiography…
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Comment on “Macular OCTA Biomarkers Predict Regional Retinal Nonperfusion Patterns on Ultra-Widefield Angiography in Diabetes”

Sep 20, 2026 by in OPHTHALMOLOGY Comments Off on Comment on “Macular OCTA Biomarkers Predict Regional Retinal Nonperfusion Patterns on Ultra-Widefield Angiography in Diabetes”
T he recent study by Kakihara et al. provides a compelling analysis of foveal avascular zone (FAZ) enlargement and geometric perfusion deficits (GPDd) as indicators of regional retinal nonperfusion. While…
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Reply to Comment on: “Optical Coherence Tomography Radiomics and Machine Learning Enable Accurate Detection of Forme Fruste Keratoconus”

Sep 20, 2026 by in OPHTHALMOLOGY Comments Off on Reply to Comment on: “Optical Coherence Tomography Radiomics and Machine Learning Enable Accurate Detection of Forme Fruste Keratoconus”
W e thank Shanthi and associates for their interest in our recently published article on optical coherence tomography (OCT) radiomics and machine learning for the detection of forme fruste keratoconus…
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Comment on: “Optical Coherence Tomography Radiomics and Machine Learning Enable Accurate Detection of Forme Fruste Keratoconus”

Sep 20, 2026 by in OPHTHALMOLOGY Comments Off on Comment on: “Optical Coherence Tomography Radiomics and Machine Learning Enable Accurate Detection of Forme Fruste Keratoconus”
W e read with great interest the study by Luo and associates who applied radiomics-based machine learning to optical coherence tomography (OCT) images for the detection of forme fruste keratoconus….
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