Nouri-Mahdavi Kouros

Mohammadzadeh Vahid, Su Erica, Besharati Sajad, Liu Abraham, Law Simon K, Coleman Anne L et al.

A Bayesian model found central visual field points with 5-20 dB sensitivity show high variability. Excluding these points could improve glaucoma progression detection.

Su Erica, Lee Kwanghyun, Liu Abraham, Mohammadzadeh Vahid, Besharati Sajad, Caprioli Joseph et al.

This study found a Bayesian model more accurately links macular structure and function changes in glaucoma than standard methods. This improves monitoring and understanding of disease progression.

Demer Joseph L, Clark Robert A, Suh Soh Youn, Giaconi JoAnn A, Nouri-Mahdavi Kouros, Law Simon K et al.

Eye movements normally pump CSF around the optic nerve, but this pumping was subnormal in glaucoma and NA-AION, suggesting impaired CSF dynamics may contribute to these optic neuropathies.

Zhuang Iris, Ashrafkhorasani Maryam, Mohammadzadeh Vahid, Nouri-Mahdavi Kouros

This study found that RNFL and BMO-MRW measurements in glaucoma eyes can mismatch in ~8% of sectors, mainly due to large blood vessels or other anatomical variations, highlighting their impact on structural assessment.

Mohammadi Massood, Su Erica, Mohammadzadeh Vahid, Besharati Sajad, Martinyan Arthur, Coleman Anne L et al.

This study found that while both GCC and RNFL detect glaucoma progression, RNFL's utility diminishes in advanced disease. Clinically, GCC may be more valuable for monitoring severe glaucoma.

Besharati Sajad, Su Erica, Mohammadzadeh Vahid, Mohammadi Massood, Caprioli Joseph, Weiss Robert E et al.

This study found a Bayesian model (HSL) more efficiently detects rapid macular ganglion cell loss in glaucoma than linear regression, improving early identification of fast progressors.

Su Erica, Mohammadzadeh Vahid, Mohammadi Massood, Shi Lynn, Law Simon K, Coleman Anne L et al.

A new statistical model (Bayesian HSL) more accurately tracks macular nerve fiber layer thinning in glaucoma than standard methods, enabling earlier and more efficient detection of disease progression.

Mohammadzadeh Vahid, Li Leyan, Fei Zhe, Davis Tyler, Morales Esteban, Wu Kara et al.

Smoothing visual field data with NN and VAE algorithms improves signal-to-noise, enabling earlier and more effective detection of glaucoma progression in patients.

Yousefi Siamak, Huang Xiaoqin, Poursoroush Asma, Majoor Julek, Lemij Hans, Vermeer Koen et al.

An AI system objectively staged glaucoma severity using RNFL thickness, finding optimal thresholds for normal, early, moderate, and advanced loss, offering a consistent clinical tool.

Shi Lynn, Mohammadi Massood, Mohammadzadeh Vahid, Su Erica, Weiss Robert E, Caprioli Joseph et al.

This study found retinal nerve fiber layer (RNFL) OCT measurements better detect structural change and progression than Bruch membrane opening-minimum rim width (BMO-MRW) in moderate-to-advanced glaucoma.

Mohammadzadeh Vahid, Su Erica, Mohammadi Massood, Law Simon K, Coleman Anne L, Caprioli Joseph et al.

This study found lower diastolic blood pressure combined with higher intraocular pressure accelerates macular ganglion cell thinning in glaucoma, suggesting blood pressure management may be a therapeutic consideration.

Mohammadi Massood, Su Erica, Chew Leila, Mohammadzadeh Vahid, Caprioli Joseph, Weiss Robert E et al.

This study found GCL thins more than IPL in glaucoma suspects, while IPL thins more in established glaucoma, suggesting GCL changes are earlier indicators of glaucoma progression.

Rasheed Haroon Adam, Davis Tyler, Morales Esteban, Fei Zhe, Grassi Lourdes, De Gainza Agustina et al.

DDLSNet, a deep learning system, moderately agreed with clinicians in grading glaucoma severity from fundus photos, demonstrating the feasibility of automated optic disc assessment for clinical use.

Rasheed Haroon Adam, Davis Tyler, Morales Esteban, Fei Zhe, Grassi Lourdes, De Gainza Agustina et al.

RimNet, a deep learning system, accurately identified and measured optic disc rim parameters in glaucoma, offering a valuable tool for automated glaucoma severity grading.

De Gainza Agustina, Morales Esteban, Rabiolo Alessandro, Yu Fei, Afifi Abdelmonem A, Nouri-Mahdavi Kouros et al.

Researchers developed a "metascore" combining different glaucoma imaging measurements (HRT, OCT) into a single scale. This unifies long-term structural data from various devices, improving patient follow-up despite instrument changes.

Mohammadzadeh Vahid, Cheng Melodyanne, Zadeh Sepideh Heydar, Edalati Kiumars, Yalzadeh Dariush, Caprioli Joseph et al.

New OCT macular shape measures effectively detect early glaucoma, showing high accuracy and potential as segmentation-independent biomarkers for clinical diagnosis.

Zarei Reza, Azimi Ali, Fakhraei Ghasem, Eslami Yadollah, Naderan Morteza, Nouri-Mahdavi Kouros et al.

This study found phacoviscocanalostomy provided better long-term medication reduction and success rates than phacoemulsification alone for mild-to-moderate glaucoma and cataract, suggesting it's a good option for skilled surgeons.

Mohammadzadeh Vahid, Su Erica, Shi Lynn, Coleman Anne L, Law Simon K, Caprioli Joseph et al.

This study modeled longitudinal macular GCC changes in glaucoma, finding strong spatiotemporal correlations and distinct regional patterns. This improves understanding of glaucoma progression and refines predictive modeling for better patient care.

de Gainza Agustina, Morales Esteban, Salazar Diana, Yu Fei, Afifi Abdelmonem, Nouri-Mahdavi Kouros et al.

Researchers developed a method to visualize glaucoma progression by integrating structural (OCT) and functional (visual field) data into a 2D space, offering clinicians a rapid, intuitive summary of disease trajectory.

Mohammadzadeh Vahid, Su Erica, Rabiolo Alessandro, Shi Lynn, Zadeh Sepideh Heydar, Law Simon K et al.

This study found that macular Ganglion Cell Complex (GCC) thickness is the optimal OCT measure for detecting structural progression in moderate-to-severe glaucoma, despite full macular thickness showing more change.

Mahmoudinezhad Golnoush, Salazar Diana, Morales Esteban, Tran Peter, Lee Janet, Hubschman Jean-Pierre et al.

This study found more severe glaucoma and younger age are associated with microcystic macular edema (MME), but MME doesn't predict faster visual field loss, potentially confounding glaucoma monitoring.

Francone Anibal, Govetto Andrea, Yun Lisa, Essilfie Juliet, Nouri-Mahdavi Kouros, Sarraf David et al.

This study found RVO patients with co-occurring glaucoma had more microcystoid macular abnormalities, worse vision, and needed more anti-VEGF injections, highlighting glaucoma's negative impact on RVO outcomes.

Mohammadzadeh Vahid, Su Erica, Heydar Zadeh Sepideh, Law Simon K, Coleman Anne L, Caprioli Joseph et al.

This study developed a Bayesian model to track local macular GCC thinning via OCT. It efficiently estimates individual glaucoma progression rates, aiding early detection and management.

Nouri-Mahdavi Kouros, Mohammadzadeh Vahid, Rabiolo Alessandro, Edalati Kiumars, Caprioli Joseph, Yousefi Siamak

This study found OCT structural changes, especially macular GCIPL, can predict visual field progression in moderate-advanced glaucoma with good accuracy, aiding earlier clinical intervention.

Nouri-Mahdavi Kouros, Weiss Robert E

This review identified challenges in using macular OCT to detect glaucoma progression, like variability and aging. Solutions, including AI and better analysis, could improve its utility for monitoring central vision.