Purpose: To evaluate a prototype home optical coherence tomography device and automated analysis software for detection and quantification of retinal fluid relative to manual human grading in a cohort of patients with neovascular age-related macular degeneration. Methods: Patients undergoing anti-vascular endothelial growth factor therapy were enrolled in this prospective observational study. In 136 optical coherence tomography scans from 70 patients using the prototype home optical coherence tomography device, fluid segmentation was performed using automated analysis software and compared with manual gradings across all retinal fluid types using receiver-operating characteristic curves. The Dice similarity coefficient was used to assess the accuracy of segmentations, and correlation of fluid areas quantified end point agreement. Results: Fluid detection per B-scan had area under the receiver-operating characteristic curves of 0.95, 0.97, and 0.98 for intraretinal fluid, subretinal fluid, and subretinal pigment epithelium fluid, respectively. On a per volume basis, the values for intraretinal fluid, subretinal fluid, and subretinal pigment epithelium fluid were 0.997, 0.998, and 0.998, respectively. The average Dice similarity coefficient values across all B-scans were 0.64, 0.73, and 0.74, and the coefficients of determination were 0.81, 0.93, and 0.97 for intraretinal fluid, subretinal fluid, and subretinal pigment epithelium fluid, espectively. Conclusion: Home optical coherence tomography device images assessed using the automated analysis software showed excellent agreement to manual human grading.

Quantitative assessment of automated optical coherence tomography image analysis using a home-based device for self-monitoring neovascular age-related macular degeneration / J.D. Oakley, S. Verdooner, D.B. Russakoff, A.J. Brucker, J. Seaman, J. Sahni, C.D. Bianchi, M. Cozzi, J. Rogers, G. Staurenghi. - In: RETINA. - ISSN 0275-004X. - 43:3(2023 Mar), pp. 433-443. [10.1097/iae.0000000000003677]

Quantitative assessment of automated optical coherence tomography image analysis using a home-based device for self-monitoring neovascular age-related macular degeneration

M. Cozzi;G. Staurenghi
Ultimo
2023

Abstract

Purpose: To evaluate a prototype home optical coherence tomography device and automated analysis software for detection and quantification of retinal fluid relative to manual human grading in a cohort of patients with neovascular age-related macular degeneration. Methods: Patients undergoing anti-vascular endothelial growth factor therapy were enrolled in this prospective observational study. In 136 optical coherence tomography scans from 70 patients using the prototype home optical coherence tomography device, fluid segmentation was performed using automated analysis software and compared with manual gradings across all retinal fluid types using receiver-operating characteristic curves. The Dice similarity coefficient was used to assess the accuracy of segmentations, and correlation of fluid areas quantified end point agreement. Results: Fluid detection per B-scan had area under the receiver-operating characteristic curves of 0.95, 0.97, and 0.98 for intraretinal fluid, subretinal fluid, and subretinal pigment epithelium fluid, respectively. On a per volume basis, the values for intraretinal fluid, subretinal fluid, and subretinal pigment epithelium fluid were 0.997, 0.998, and 0.998, respectively. The average Dice similarity coefficient values across all B-scans were 0.64, 0.73, and 0.74, and the coefficients of determination were 0.81, 0.93, and 0.97 for intraretinal fluid, subretinal fluid, and subretinal pigment epithelium fluid, espectively. Conclusion: Home optical coherence tomography device images assessed using the automated analysis software showed excellent agreement to manual human grading.
automated analysis; home-monitoring; neovascular age-related macular degeneration; optical coherence tomography; quantitative assessment; retinal fluid
Settore MEDS-17/A - Malattie dell'apparato visivo
Settore MEDS-26/C - Scienze delle professioni sanitarie della riabilitazione
mar-2023
Article (author)
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/1115958
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