Ophthalmology science · 2025
Longitudinal Validation of the Artificial Intelligence Algorithm in Home OCT for Age-Related Macular Degeneration-Report 3.
СтатьяНазвание и аннотация: Перевод пока не подготовлен
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Leng Theodore, Leung Ella H, Mukkamala S Krishna, Taban Mehran R, Havilio Moshe, Nahen Kester, Mohan Nishant, Benyamini Gidi, Keenan Tiarnan D L
Аннотация
PURPOSE: Longitudinal validation of the artificial intelligence-based Notal OCT Analyzer (NOA) for identification of clinically significant changes in the trajectories of retinal total hypo-reflective volume (TRO) from daily home OCT (HOCT) self-imaging in eyes with age-related macular degeneration.
DESIGN: Post hoc analysis of the HOCT Fluid Visualization Agreement Study.
PARTICIPANTS: Three hundred seventeen eyes of 180 participants who self-imaged daily using the HOCT for 5 weeks.
METHODS: For each eye study, the ground truth of TRO stability or change was defined by human experts grading the 5-week time series of HOCT volume scans. The TRO trajectory of the 5 weeks was plotted separately for each study eye by NOA. Three approaches to identifying the optimal threshold (OT) for a clinically significant change in TRO were pursued: (1) personalized approach based on the reference change value methodology used in laboratory medicine; (2) optimized uniform approach; (3) uniform approach commonly used of 10 volume units (VU). The personalized approach comprised TRO curve-fitting to evaluate the change in amplitude (signal) and within-subject variations (noise), followed by receiver operating characteristic analysis of the signal-to-noise ratio (SNR) to identify the OT for determination of a clinically significant change in TRO.
MAIN OUTCOME MEASURES: Area under the receiver operating characteristic curve (AUROC); sensitivity, specificity, and accuracy at the OT.
RESULTS: Of the 296 trajectories analyzed, 107 (36.1%) were classified as changing and the remaining 189 (63.9%) as stable. The personalized approach had an AUROC of 0.9811 (with 99.1% sensitivity, 89.4% specificity, and 94.2% accuracy), at OT of SNR = 2.42. The optimized uniform approach had an AUROC of 0.9687 (with 94.4% sensitivity, 89.4% specificity, and 91.9% accuracy), at OT of 3.88 VU. The 10 VU uniform approach had 76.6% sensitivity, 94.7% specificity, and 85.7% accuracy.
CONCLUSIONS: The NOA-generated trajectories permitted highly accurate determination of TRO change vs. stability, with favorable SNR. The personalized approach had higher sensitivity in detecting TRO change at 99.1% than the uniform approaches. Notal OCT analyzer and its trajectories were a reliable tool for identifying clinically relevant changes in retinal fluid status by the quality standards of laboratory medicine.
FINANCIAL DISCLOSURES: Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.
DESIGN: Post hoc analysis of the HOCT Fluid Visualization Agreement Study.
PARTICIPANTS: Three hundred seventeen eyes of 180 participants who self-imaged daily using the HOCT for 5 weeks.
METHODS: For each eye study, the ground truth of TRO stability or change was defined by human experts grading the 5-week time series of HOCT volume scans. The TRO trajectory of the 5 weeks was plotted separately for each study eye by NOA. Three approaches to identifying the optimal threshold (OT) for a clinically significant change in TRO were pursued: (1) personalized approach based on the reference change value methodology used in laboratory medicine; (2) optimized uniform approach; (3) uniform approach commonly used of 10 volume units (VU). The personalized approach comprised TRO curve-fitting to evaluate the change in amplitude (signal) and within-subject variations (noise), followed by receiver operating characteristic analysis of the signal-to-noise ratio (SNR) to identify the OT for determination of a clinically significant change in TRO.
MAIN OUTCOME MEASURES: Area under the receiver operating characteristic curve (AUROC); sensitivity, specificity, and accuracy at the OT.
RESULTS: Of the 296 trajectories analyzed, 107 (36.1%) were classified as changing and the remaining 189 (63.9%) as stable. The personalized approach had an AUROC of 0.9811 (with 99.1% sensitivity, 89.4% specificity, and 94.2% accuracy), at OT of SNR = 2.42. The optimized uniform approach had an AUROC of 0.9687 (with 94.4% sensitivity, 89.4% specificity, and 91.9% accuracy), at OT of 3.88 VU. The 10 VU uniform approach had 76.6% sensitivity, 94.7% specificity, and 85.7% accuracy.
CONCLUSIONS: The NOA-generated trajectories permitted highly accurate determination of TRO change vs. stability, with favorable SNR. The personalized approach had higher sensitivity in detecting TRO change at 99.1% than the uniform approaches. Notal OCT analyzer and its trajectories were a reliable tool for identifying clinically relevant changes in retinal fluid status by the quality standards of laboratory medicine.
FINANCIAL DISCLOSURES: Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.