Investigative Ophthalmology & Visual Science Cover Image for Volume 65, Issue 7
June 2024
Volume 65, Issue 7
Open Access
ARVO Annual Meeting Abstract  |   June 2024
Introducing the Biomechanics-Function Relationship in Glaucoma: Improved Visual Field Loss Predictions from IOP-induced Neural Tissue Strains
Author Affiliations & Notes
  • Thanadet Chuangsuwanich
    ophthalmology, National University of Singapore, Singapore, Singapore
    Singapore Eye Research Institute, Singapore, Singapore
  • Monisha Esther Nongpiur
    Singapore Eye Research Institute, Singapore, Singapore
  • Tin A Tun
    Singapore Eye Research Institute, Singapore, Singapore
  • Fabian Albert Braeu
    Singapore Eye Research Institute, Singapore, Singapore
  • Xiaofei Wang
    Beihang University, Beijing, Beijing, China
  • George Barbastathis
    Massachusetts Institute of Technology, Cambridge, Massachusetts, United States
  • Tin Aung
    Singapore Eye Research Institute, Singapore, Singapore
    Duke-NUS Medical School, Singapore, Singapore
  • Michael J A Girard
    Singapore Eye Research Institute, Singapore, Singapore
    Duke-NUS Medical School, Singapore, Singapore
  • Footnotes
    Commercial Relationships   Thanadet Chuangsuwanich None; Monisha Nongpiur None; Tin Tun None; Fabian Braeu None; Xiaofei Wang None; George Barbastathis None; Tin Aung None; Michael Girard Abyss Processing Pte Ltd, Code S (non-remunerative)
  • Footnotes
    Support  (1) the Singapore Ministry of Education, Academic Research Funds, Tier 2 (R-397-000-280-112; R-397-000-308-112), (2) Singapore Ministry of Education, Academic Research Funds, Tier 1 (R-397000-294-114), (3) the National Medical Research Council (Grant NMRC/ STAR/0023/2014), (4) National Natural Science Foundation of China (12002025), (5) Tracking and Reducing Glaucoma Blindness with Emerging Technologies (TARGET, MOH-OFLCG21jun-0003) and (6) the ’Retinal Analytics through Machine learning aiding Physics (RAMP)’ project supported by the National Research Foundation, Prime Minister’s Office, Singapore under its Intra-Create Thematic Grant ’Intersection Of Engineering And Health’ - NRF2019-THE002-0006 awarded to the Singapore MIT Alliance for Research and Technology (SMART) Centre.
Investigative Ophthalmology & Visual Science June 2024, Vol.65, 2491. doi:
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    • Get Citation

      Thanadet Chuangsuwanich, Monisha Esther Nongpiur, Tin A Tun, Fabian Albert Braeu, Xiaofei Wang, George Barbastathis, Tin Aung, Michael J A Girard; Introducing the Biomechanics-Function Relationship in Glaucoma: Improved Visual Field Loss Predictions from IOP-induced Neural Tissue Strains. Invest. Ophthalmol. Vis. Sci. 2024;65(7):2491.

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      © ARVO (1962-2015); The Authors (2016-present)

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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.

Methods : We recruited 238 glaucoma subjects from the Singapore National Eye Centre. 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 33 mmHg) achieved through ophthalmo-dynamometry. Automatic segmentation of neural tissues (retinal nerve fiber layer [RNFL] and pre-lamina) was performed for each OCT volume. Digital volume correlation (DVC) analysis was employed to compute IOP-induced neural tissue strains as detailed in Chuangsuwanich et al. (Ophthalmology, 2023). To predict visual field loss from neural tissue structure and biomechanics, we used a robust geometric deep learning approach known as Point-Net. This method takes 3D point-clouds of neural tissues as inputs (see Figure 1a), together with local tissue strain and thickness, in order to predict the full 24-2 pattern standard deviation (PSD) maps. 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 assessed using 5-fold cross-validation and the Dice coefficient, which measures point-wise agreement between the true and predicted PSD maps. The model's performance was compared with and without the inclusion of IOP-induced strains.

Results : Integrating biomechanical (IOP-induced neural tissue strains) and structural (neural tissues thickness) information yielded a robust predictive model (Dice score: 0.79 ± 0.03) across test subjects (Figure 1b), accurately identifying defective hemispheres. In contrast, relying only on structural information resulted in a significantly lower Dice score of 0.72 ± 0.02 (p < 0.05, Figure 1c).

Conclusions : Our study has shown that the integration of biomechanical data can significantly improve the accuracy of visual field loss predictions. This highlights the importance of the biomechanics-function relationship in glaucoma, and suggests that biomechanics may serve as a crucial indicator for the development and progression of glaucoma.

This abstract was presented at the 2024 ARVO Annual Meeting, held in Seattle, WA, May 5-9, 2024.

 

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