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Matthew R Ford, Andrew M Rollins, William J Dupps; Quantitative In Vivo Corneal Elastography by Doppler Shear Wave Imaging. Invest. Ophthalmol. Vis. Sci. 2014;55(13):3724.
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© ARVO (1962-2015); The Authors (2016-present)
To quantitatively measure the in vivo biomechanical properties of the cornea to provide assistance with disease diagnosis and aid in intervention planning.
Utilizing a custom built 1310nm Fourier Domain Optical Coherence Tomography (FDOCT) Anterior Segment Imaging system, a volunteer's healthy cornea was imaged while a shear wave was applied to the eyelid. The shear wave magnitude was maintained at less than the 4um limit specified by the FDA for acoustic retinal imaging. A standard Doppler algorithm (sometimes referred to as Phase Sensitive OCT) was then applied to the acquired data to visualize the shear wave in the tissue. A series of fast Fourier transform windows were applied perpendicular to the direction of the wave’s travel to measure the frequency of the wave in the tissue. The shear wave speed was then calculated by means of the Doppler shift between the applied wave and the measured wave passing through the tissue given by C=Vf0/(f-f0) where C is the speed of the shear wave in the tissue, V is the scan velocity, f0 is the applied wave form frequency, and f is the measured waveform frequency . The Shear Modulus and Young’s Modulus of the tissue were then calculated by G=(C/ρ)1/2, and E=3G where G is the Shear Modulus, C is the velocity of the wave in tissue, ρ is the density of the tissue, and E is Young’s Modulus.
Figure 1 shows the three steps in the image processing sequence. Image A is the acquired FDOCT image of the cornea. Image B is the Doppler (phase sensitive) data from the FDOCT image data, and image C is the Young’s modulus map calculated from the Doppler data. The cornea shown here has a Shear Modulus of 177kPa with a standard deviation of 93kPa, and a Young’s Modulus of 530kPa and a standard deviation of 270kPa.
We successfully demonstrated the ability to quantitatively measure Young’s modulus in an in vivo setting without significant hardware modifications to an existing FDOCT system. The low cost, speed, comfort, and simplicity of this technique make it ideal for use in a clinical setting. Further work is planned to assess the performance of the technique in characterizing disease states and the effect of clinical interventions.
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