Hood Donald C

Leshno Ari, Tsamis Emmanouil, Hood Donald C, Vyas Charu, Kim Mijeung, De Moraes Carlos Gustavo et al.

Retinal vessel position variability impacts sectoral RNFL thickness. Larger MVP angles correlate with thicker nasal and thinner temporal RNFL. Adjusting for MVP could improve RNFL normative data accuracy, reducing false glaucoma diagnoses.

Hood Donald C, Durbin Mary, Lee Chris, Guzman Anya, Gebhardt Tayna, Wang Yujia et al.

Larger real-world OCT reference databases improve glaucoma flagging accuracy by reducing random error, leading to different classifications for glaucoma eyes. This enhances precision in glaucoma diagnosis and monitoring.

Hood Donald C, Lau Wai Tak, Stowman Arin L, Gebhardt Tayna, Mao Grace, La Bruna Sol et al.

A deep learning model detected glaucoma from OCT reports, but its "heat maps" often didn't precisely highlight clinically relevant damage locations, suggesting current AI guidance isn't optimal for clinicians.

Lau Wai Tak, Tsamis Emmanouil, Hood Donald C, Thakoor Kaveri

A deep learning model for glaucoma detection from OCT reports showed superior sensitivity and specificity compared to conventional metrics, offering a promising tool for screening and clinical diagnosis.

Kim Mi Jeung, Tsamis Emmanouil, Leshno Ari, Gomide Gabriel, De Moraes Carlos G, Cioffi George A et al.

This study found a model of macular GCL damage, starting temporally and progressing nasally, helps distinguish glaucoma from other issues in myopic eyes, even with coexisting macular pathology.

Hood Donald C, La Bruna Sol, Durbin Mary, Lee Chris, Guzman Anya, Gebhardt Tayna et al.

A new OCT metric, based on glaucoma damage patterns, significantly outperformed existing methods in detecting glaucoma, potentially improving early diagnosis and referrals from primary care.

Hood Donald C, Durbin Mary, La Bruna Sol, Lee Chris, Hsiao Yi Sing, El-Nimri Nevin W et al.

This study compared a large optometry-derived healthy eye OCT database to a commercial one, finding similar characteristics but the larger database offers more precise healthy ranges, improving glaucoma diagnosis accuracy.

Sun Anna J, Gomide Gabriel, Tsamis Emmanouil, Mao Grace, Leshno Ari, La Bruna Sol et al.

OCT revealed diverse macular GCL damage patterns in advanced glaucoma, consistently following a temporal-to-nasal progression model. This aids clinical monitoring and trial design for preserving central vision.

Hood Donald C, La Bruna Sol, Durbin Mary, Lee Chris, Hsiao Yi S, De Moraes Carlos G et al.

This study found four anatomical features, beyond age/disc area, significantly influence healthy OCT cpRNFL thickness. Considering these improves diagnostic accuracy for glaucoma.

Leshno Ari, Tsamis Emmanouil, Hirji Sitara, Gomide Gabriel A, Harizman Noga, De Moraes Carlos Gustavo et al.

An OCT reading center accurately identified established glaucoma with high sensitivity and specificity using OCT alone, validating its real-world clinical utility for detection.

Hood Donald C, La Bruna Sol, Leshno Ari, Gomide Gabriel A, Kim Mi Jeung, Cioffi George A et al.

This model predicts macular GCL damage patterns in glaucoma, helping clinicians identify typical glaucomatous loss versus other causes, and suggesting new clinical trial endpoints.

Leshno Ari, De Moraes Carlos Gustavo, Tsamis Emmanouil, La Bruna Sol, Cioffi George A, Liebmann Jeffrey M et al.

This review highlights that comparing individual OCT scans to normative databases for glaucoma detection can be misleading due to artifacts, impacting accurate diagnosis and management.

Tsamis Emmanouil, La Bruna Sol, Rai Anvit, Leshno Ari, Grossman Jennifer, Cioffi George et al.

This study found combining OCT metrics, especially circumpapillary retinal nerve fiber layer and ganglion cell layer, significantly improves specificity for detecting glaucoma progression, though sole reliance on metrics is not recommended.

Leshno Ari, Tsamis Emmanouil, Harizman Noga, Cioffi George A, Wang Qing, La Bruna Sol et al.

ICD-10 glaucoma severity, based on visual fields, often underestimates actual damage compared to OCT. This means many patients' glaucoma severity is misclassified, highlighting the need to integrate OCT for accurate staging and care.

Chang Angela Y, Tsamis Emmanouil, Blumberg Dana M, Al-Aswad Lama A, Cioffi George A, Hood Donald C et al.

Macular OCT and visual field parameters better reflect IOP-related glaucoma progression than conventional measures. Systemic hypertension was not linked to progression in this study, highlighting macular metrics as sensitive endpoints.

Zemborain Zane Z, Tsamis Emmanouil, La Bruna Sol, Leshno Ari, De Moraes C Gustavo, Ritch Robert et al.

This study found a novel OCT metric (RMS cpRNFL) best distinguished healthy from glaucomatous eyes with low nerve fiber layer thickness, achieving 90% accuracy, improving diagnosis in challenging cases.

La Bruna Sol, Rai Anvit, Mao Grace, Kerr Jennifer, Amin Heer, Zemborain Zane Z et al.

OCT RNFL maps frequently show glaucoma-like artifacts in healthy eyes. A "vertical midline" rule helps distinguish true glaucoma, but other OCT data are crucial for high sensitivity, especially in early disease.

Liebmann Jeffrey M, Hood Donald C, de Moraes Carlos Gustavo, Blumberg Dana M, Harizman Noga, Kresch Yocheved S et al.

Researchers developed an OCT-based method to detect glaucoma without perimetry, offering a potential new diagnostic tool for clinical practice and research, pending further validation.

Hood Donald C, La Bruna Sol, Tsamis Emmanouil, Thakoor Kaveri A, Rai Anvit, Leshno Ari et al.

This study developed a model to differentiate glaucoma from common OCT p-map artifacts caused by normal anatomical variations, improving OCT-based glaucoma detection for clinical decisions, research, screening, and AI development.

Yu Sarah N, Hood Donald C, Blumberg Dana M, Chang Stanley, Greenstein Vivienne C

This study found that careful pre-operative comparison of visual fields and OCT scans helps guide macular surgery and evaluate outcomes in glaucoma patients.

Hood Donald C, Melchior Bruna, Tsamis Emmanouil, Liebmann Jeffrey M, De Moraes Carlos G

This paper argues that OCT Guided Progression Analysis and summary statistics are insufficient for detecting glaucoma progression between two visits, advocating for topographical comparison of OCT maps and images for better clinical decisions.

Khan Sabine S, Hirji Sitara H, Hood Donald C, Liebmann Jeffrey M, Blumberg Dana M

This study investigated if macular nerve damage in glaucoma affects facial recognition, finding a potential link between structural damage and this visual function.

Thakoor Kaveri A, Li Xinhui, Tsamis Emmanouil, Zemborain Zane Z, De Moraes Carlos Gustavo, Sajda Paul et al.

This study found data augmentation and confident image training improve CNN glaucoma detection from OCT. Consistent reference standards are crucial for optimal performance and clinical deployment.

Sun Ashley, Tsamis Emmanouil, Eguia Melvi D, Liebmann Jeffrey M, Blumberg Dana M, Al-Aswad Lama A et al.

This study found global OCT metrics for glaucoma progression have high false positive/negative rates due to scanning errors and missing local damage, questioning their clinical utility.

Hirji Sitara H, Hood Donald C, Liebmann Jeffrey M, Blumberg Dana M

This study found diffuse, not focal, glaucomatous macular damage significantly impairs contrast sensitivity and facial recognition. Identifying diffuse damage via OCT/VF can help minimize visual disability.