Quantifying deformations and strains in human intervertebral discs using Digital Volume Correlation combined with MRI (DVC-MRI).

Quantifying deformations and strains in human intervertebral discs using Digital Volume Correlation combined with MRI (DVC-MRI).

Tavana, S;Clark, J N;Prior, J;Baxan, N;Masouros, S D;Newell, N;Hansen, U;
journal of biomechanics 2020 pp. 109604
205
tavana2020quantifyingjournal

Abstract

Physical disruptions to intervertebral discs (IVDs) can cause mechanical changes that lead to degeneration and to low back pain which affects 75% of us in our lifetimes. Quantifying the effects of these changes on internal IVD strains may lead to better preventative strategies and treatments. Digital Volume Correlation (DVC) is a non-invasive technique that divides volumetric images into subsets, and measures strains by tracking the internal patterns within them under load. Applying DVC to MRIs may allow non-invasive strain measurements. However, DVC-MRI for strain measurements in IVDs has not been used previously. The purpose of this study was to quantify the strain and deformation errors associated with DVC-MRI for measurements in human IVDs. Eight human lumbar IVDs were MRI scanned (9.4 T) for a 'zero-strain study' (multiple unloaded scans to quantify noise within the system), and a loaded study (2 mm axial compression). Three DVC methodologies: Fast-Fourier transform (FFT), direct correlation (DC), and a combination of both FFT and DC approaches were compared with subset sizes ranging from 8 to 88 voxels to establish the optimal DVC methodology and settings which were then used in the loaded study. FFT + DC was the optimal method and a subset size of 56 voxels (2520 µm) was found to be a good compromise between errors and spatial resolution. Displacement and strain errors did not exceed 28 µm and 3000 microstrain, respectively. These findings demonstrate that DVC-MRI can quantify internal strains within IVDs non-invasively and accurately. The method has unique potential for assessing IVD strains within patients.

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