March 2012
Volume 53, Issue 14
Free
ARVO Annual Meeting Abstract  |   March 2012
The Effect of Optical Coherence Tomography Speckle Noise Upon An Optic Nerve Head Displacement Tracking Algorithm
Author Affiliations & Notes
  • Nicholas G. Strouthidis
    NIHR Biomedical Sciences Centre, Moorfields Eye Hospital and UCL Institute of Ophthalmology, London, United Kingdom
  • Adrien Desjardins
    Department of Medical Physics and Bioengineering, University College London, London, United Kingdom
  • C. Ross Ethier
    Department of Bioengineering, Imperial College, London, United Kingdom
  • Michael J. Girard
    Department of Bioengineering, Imperial College, London, United Kingdom
  • Footnotes
    Commercial Relationships  Nicholas G. Strouthidis, None; Adrien Desjardins, None; C. Ross Ethier, None; Michael J. Girard, None
  • Footnotes
    Support  Royal Society Wolfson Research Merit Award (CRE), Imperial College Junior Research Fellowship (MJAG)
Investigative Ophthalmology & Visual Science March 2012, Vol.53, 678. doi:
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      Nicholas G. Strouthidis, Adrien Desjardins, C. Ross Ethier, Michael J. Girard; The Effect of Optical Coherence Tomography Speckle Noise Upon An Optic Nerve Head Displacement Tracking Algorithm. Invest. Ophthalmol. Vis. Sci. 2012;53(14):678.

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

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Abstract

Purpose: : OCT imaging has the potential to quantify tissue deformation in vivo and thus establish biomechanical risk factors for glaucomatous optic neuropathy. The accuracy of the quantification of deformation, and its sensitivity to noise, have not yet been determined. Here we test the robustness of an optical coherence tomography (OCT)-based 3D tissue tracking algorithm against varying degrees of speckle noise.

Methods: : We developed a 3D tracking algorithm, based on the principle of digital volume correlation, that can extract optic nerve head (ONH) displacements in vivo from a set of two ONH volumes (undeformed and deformed) captured with spectral domain OCT (Spectralis, Heidelberg Engineering). The undeformed volume was obtained from a baseline OCT scan of a patient’s ONH (97 B-Scans with 768 A-Scans of 496 pixels each). The matching deformed volume was obtained by applying a predetermined artificial deformation to the baseline scan (3D radial expansion of the ocular globe with radial tissue thinning, thus mimicking the effects of increased intraocular pressure). In addition to the artificial deformation, speckle noise (approximated by an exponential distribution) was added to the OCT image of the deformed volume. Differing levels of speckle noise were obtained by averaging OCT B-scans (1X, 10X, 20X, 30X), with speckle noise reducing with increasing scan averaging. Displacements were tracked at 1210 points in two areas that covered all tissues within and surrounding the prelaminar and laminar ONH (retina, choroid, sclera, prelaminar tissues and lamina cribrosa).

Results: : Total errors in displacement magnitude decreased with increasing signal averaging and were 2.09 μm, 0.54 μm, 0.30 μm and 0.23 μm, for the 1X, 10X, 20X, and 30X B-scan averages, respectively. This translated into errors in effective strain, the relevant measure of local tissue deformation, of 2.29%, 0.57%, 0.37% and 0.33%, respectively. By way of comparison, we currently observe strain levels of up to 10% following IOP-lowering by trabeculectomy in glaucoma subjects, suggesting that the strain errors achieved in this study are acceptable.

Conclusions: : Our algorithm is robust to OCT speckle noise, and increasing signal averaging can produce excellent results; displacement errors can be less than 1 μm whilst OCT axial resolution is 3.8 μm and lateral resolution is 11.5 μm. This algorithm can be used to assist in the quantification of ONH biomechanics in vivo for the first time, which may lead to the identification of risk indicators for glaucoma in human subjects.

Keywords: optic nerve • imaging methods (CT, FA, ICG, MRI, OCT, RTA, SLO, ultrasound) • image processing 
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