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In vivo optic nerve head biomechanics: performance testing of a three-dimensional tracking algorithm
Michaël J A Girard1, Nicholas G Strouthidis, Adrien Desjardins
1Department of Bioengineering, National University of Singapore, Singapore, Republic of Singapore. mgirard@invivobiomechanics.com
Journal of the Royal Society, Interface
|July 26, 2013
Summary
A new 3D algorithm tracks optic nerve head (ONH) deformations using optical coherence tomography (OCT) for glaucoma diagnosis. This robust method accurately quantifies in vivo ONH biomechanics, aiding in early disease detection and risk factor identification.
Area of Science:
- Ophthalmology
- Biomedical Engineering
- Medical Imaging
Background:
- Glaucoma management can benefit from measuring optic nerve head (ONH) deformations.
- In vivo assessment of ONH biomechanics is crucial for understanding glaucoma progression.
Purpose of the Study:
- To develop and validate a novel 3D tissue-tracking algorithm for in vivo ONH deformation measurement.
- To assess the accuracy and robustness of the proposed algorithm.
Main Methods:
- A 3D digital volume correlation algorithm was developed to analyze ONH displacements from OCT scans.
- Artificial deformations were applied to OCT data to test algorithm accuracy under varying noise and illumination conditions.
- Algorithm performance was evaluated by comparing computed deformations with known imposed values.
Main Results:
- The algorithm achieved high accuracy, with errors in displacement magnitude, orientation, and strain of 0.15 µm, 0.15°, and 0.0019, respectively, after optimization.
- The algorithm demonstrated robustness against OCT speckle noise and illumination variations.
- Signal averaging was found to improve the accuracy of the deformation measurements.
Conclusions:
- The developed 3D algorithm provides accurate and robust in vivo quantification of ONH biomechanics.
- This tool has significant potential for aiding in the clinical diagnosis and risk stratification of glaucoma patients.
- Further application of this algorithm can enhance the understanding and management of glaucoma.
