Thanadet Chuangsuwanich, Monisha E Nongpiur, Fabian A Braeu, Tin A Tun, Alexandre Thiery, Shamira Perera, Ching Lin Ho, Martin Buist, George Barbastathis, Tin Aung, Michaël J A Girard
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引用次数: 0
Abstract
Purpose: (1) To assess whether neural tissue structure and biomechanics could predict functional loss in glaucoma; (2) To evaluate the importance of biomechanics in making such predictions.
Design: Clinic-based cross-sectional study.
Methods: We recruited 238 glaucoma subjects (Chinese ethnicity, more than 50 years old). For one eye of each subject, we imaged the optic nerve head (ONH) using spectral-domain OCT under the following conditions: (1) primary gaze and (2) primary gaze with acute IOP elevation (to approximately 35 mmHg) achieved through ophthalmo-dynamometry. We utilized automatic segmentation of optic nerve head (ONH) tissues and digital volume correlation (DVC) analysis to compute intraocular pressure (IOP)-induced neural tissue strains. A robust geometric deep learning approach, known as Point-Net, was employed to predict the full Humphrey 24-2 pattern standard deviation (PSD) maps from ONH structural and biomechanical information. For each point in each PSD map, we predicted whether it exhibited no defect or a PSD value of less than 5%. Predictive performance was evaluated using 5-fold cross-validation and the F1-score. We compared the model's performance with and without the inclusion of IOP-induced strains to assess the impact of biomechanics on prediction accuracy.
Results: Integrating biomechanical (IOP-induced neural tissue strains) and structural (tissue morphology and neural tissues thickness) information yielded a significantly better predictive model (F1-score: 0.76 ± 0.02) across validation subjects, as opposed to relying only on structural information, which resulted in a significantly lower F1-score of 0.71 ± 0.02 (p < 0.05). Our subjects had a mean age of 69±5 years. Among them, 88 were female. The cohort included a wide range of glaucoma severity, with Mean Deviation (MD) values ranging from -1.8 (mild) to -25.2 (severe), and an average MD value of -7.25±5.05.
Conclusion: Our study has shown that the integration of biomechanical data can significantly improve the accuracy of visual field loss predictions and highlights the importance of the biomechanics-function relationship in glaucoma.
期刊介绍:
The American Journal of Ophthalmology is a peer-reviewed, scientific publication that welcomes the submission of original, previously unpublished manuscripts directed to ophthalmologists and visual science specialists describing clinical investigations, clinical observations, and clinically relevant laboratory investigations. Published monthly since 1884, the full text of the American Journal of Ophthalmology and supplementary material are also presented online at www.AJO.com and on ScienceDirect.
The American Journal of Ophthalmology publishes Full-Length Articles, Perspectives, Editorials, Correspondences, Books Reports and Announcements. Brief Reports and Case Reports are no longer published. We recommend submitting Brief Reports and Case Reports to our companion publication, the American Journal of Ophthalmology Case Reports.
Manuscripts are accepted with the understanding that they have not been and will not be published elsewhere substantially in any format, and that there are no ethical problems with the content or data collection. Authors may be requested to produce the data upon which the manuscript is based and to answer expeditiously any questions about the manuscript or its authors.