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Research Papers

Sequential-Digital Image Correlation for Mapping Human Posterior Sclera and Optic Nerve Head Deformation

[+] Author and Article Information
Jeffrey D. Pyne

Department of Aerospace and
Mechanical Engineering,
BIO5 Institute,
University of Arizona,
Tucson, AZ 85721

Katia Genovese

School of Engineering,
University of Basilicata,
Potenza 85100, Italy

Luciana Casaletto

School of Engineering,
University of Basilicata,
Potenza 85100, Italy

Jonathan P. Vande Geest

Associate Professor
Department of Aerospace and
Mechanical Engineering,
Biomedical Engineering Graduate
Interdisciplinary Program,
Department of Biomedical Engineering,
BIO5 Institute,
University of Arizona,
Tucson, AZ 85721
e-mail: jpv1@email.arizona.edu

1J. D. Pyne and K. Genovese contributed equally to this work.

2Corresponding author.

Contributed by the Bioengineering Division of ASME for publication in the Journal of Biomechanical Engineering. Manuscript received September 2, 2013; final manuscript received December 6, 2013; accepted manuscript posted December 12, 2013; published online February 5, 2014. Editor: Victor H. Barocas.

J Biomech Eng 136(2), 021002 (Feb 05, 2014) (12 pages) Paper No: BIO-13-1406; doi: 10.1115/1.4026224 History: Received September 02, 2013; Revised December 06, 2013; Accepted December 12, 2013

Optic nerve head (ONH) deformations may be involved in the onset or further development of glaucoma, including in patients with relatively normal intraocular pressures (IOPs). Characterizing posterior scleral deformations over physiological pressures may provide a better understanding of how changes in IOP lead to changes in the mechanical environment of the ONH and possibly retinal ganglion cell death. Pressure inflation measurement test protocols are commonly used to measure deformation of the peripapillary sclera with full-field noncontact optical methods. The purpose of this work was to develop and validate a new sequential 3D digital image correlation (S-DIC) approach for quantification of posterior scleral pressure induced deformation that improves z (in-depth) resolution of the DIC measurement without losing in-plane sensitivity, while also being able to contour and map deformations of the complex-shaped ONH. Our approach combines two orthogonal axes of parallax with standard 3D DIC methods using a single high-resolution camera. The enhanced capabilities of S-DIC with respect to standard 3D DIC has been demonstrated by carrying out a complete benchmark for shape, deformation, and strain measurement on an object of known complex geometry. Our S-DIC method provided a reconstruction accuracy of 0.17% and an uncertainty in z-position measurement of 8 μm. The developed methodology has also been applied to a human posterior scleral shell, including the full peripapillary sclera and optic nerve. The relatively inexpensive S-DIC approach may provide new information on the biomechanical deformations of the optic nerve head and, thus, the death of retinal ganglion cells in primary open angle glaucoma.

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Figures

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Fig. 1

The sequential DIC-approach emulates a user-defined number of virtual cameras looking at the target from different angles along two orthogonal directions of parallax (axis x and y). The red cameras show a typical 3D stereo DIC setup. Only a few views have been sketched for clarity of representation.

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Fig. 2

(a) Picture of the entire experimental setup for S-DIC measurement; (b) close up view of the sample/conical target assembly; (c) target used for evaluating the metrological performance of the S-DIC system

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Fig. 3

The D set of images for S-DIC measurement on the target in Fig. 2(c)

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Fig. 4

The reconstructed calibration target: (a) radius and (b) z coordinate, (c) point cloud

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Fig. 5

Maps of the correlation coefficient C for the DIC-SA (a) and DIC-LA (b) systems. Values closer to 1 indicate an accurate correlation. For DIC-SA, one virtual camera was at 45 deg (3_1) and other at 43 deg (3_2). For DIC-LA, one virtual camera was at 45 deg (3_1) and other at 31 deg (3_6).

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Fig. 6

Central x-z sections of the target as reconstructed by the S-DIC (a) and the DIC-SA (b) systems superimposed to the theoretical target section. For DIC-SA, one virtual camera was at 45 deg (3_1) and other at 43 deg (3_2).

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Fig. 7

Plot of a horizontal line of control points on the left y-z vertical face of the target as reconstructed by standard-DIC and S-DIC (shifted upward for clarity of representation)

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Fig. 8

Magnitude of the norm of the total displacement dtot after a rigid body rotation of the calibration target plotted on the measured shape with the S-DIC (a) and the DIC-SA (b) systems

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Fig. 9

Distribution of the first invariant of the Green–Lagrange strain tensor as resulting from a rigid body rotation of the calibration target

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Fig. 10

The human posterior scleral sample tested in this work: S stands for superior, T for temporal, N for nasal, and I for inferior. Circled with red is the area at higher spatial resolution considered for the ONH measurement (a). Two views of the reconstructed scleral shell point cloud at 5 mmHg (b) with superimposed the more dense data points of the ONH area.

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Fig. 11

Top view of the scleral displacement fields between 5 and 15 mmHg. Displacements in x, y, z directions are labeled as u (a), v (b), w (c), respectively, and error in radius with the best-fitting sphere is shown in (d).

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Fig. 12

Circumferential strain Eθθ (a) and meridional stain Eφφ (b) for the posterior scleral shell

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Fig. 13

Circumferential strain Eθθ (a) and meridional strain Eφφ (b) for the ONH (region circled in red in Fig. 10(a))

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