Abstract #4790

Diffusion Tensor Imaging as a Methodology for Optic Nerve Evaluation

Kamri Clarke^1,2, Zakia Ben Youss^1,2,3, Patryk Filipiak^1,2, Antonio Verdone Sanchez^1,2, Mary Bruno^1,2, Vaidehi S. Dedania⁴, Kevin C. Chan^1,4,5, and Steven H. Baete^1,2,3

¹Center for Advanced Imaging Innovation and Research (CAI2R), Department of Radiology, NYU Langone Health, New York, NY, United States, ²Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, NYU Langone Health, New York, NY, United States, ³Vilcek Institute of Graduate Biomedical Sciences, NYU School of Medicine, New York, NY, United States, ⁴Department of Ophthalmology, NYU Langone Health, New York, NY, United States, ⁵Neuroscience Institute and Tech4Health Institute, NYU Langone Health, New York, NY, United States

Synopsis

Keywords: DWI/DTI/DKI, Diffusion Analysis and Visualization, Optic Nerve, Reproducibility, Test/Retest, DTI, Tractography

Motivation: Current diffusion MRI (dMRI) diagnostic techniques for optic nerve (ON) neuropathies can assess general degeneration and acute damage. We aim to provide more detailed representation of the ON microstructure for earlier and more targeted treatment.

Goal(s): Evaluate the reproducibility of ON Diffusion Tensor Imaging (DTI) metrics.

Approach: Test/retest values of Fractional Anisotropy (FA) and Apparent Diffusion Coefficient (ADC) were measured along the ONs of 8 healthy subjects. Reproducibility was evaluated with the intraclass correlation coefficient (ICC).

Results: We observed an average ICC score of 0.966 for FA and 0.970 for ADC at a 95% confidence interval, indicating good reliability.

Impact: Non-invasive optic nerve screening with DTI may provide additional insight into the optic nerve microstructure making it a potential avenue to identify optic neuropathies, such as glaucoma.

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