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Nauman, E. A.

Publications and source records attributed to Nauman, E. A..

2 recordsLinked to original sources

MRI-based quantification of cardiac-driven brain biomechanics for early detection of neurological disorders

We present a pipeline to quantify biomechanical environment of the brain using solely MRI-derived data in order to elucidate the role of biomechanical factors in neurodegenerative disorders. Neurological disorders, like Alzheimers and Parkinsons diseases, are associated with physical changes, including the accumulation of amyloid-{beta} and tau proteins, damage to the cerebral vasculature, hypertension, atrophy of the cortical gray matter, and lesions of the periventricular white matter. Alterations in the external mechanical environment of cells can trigger pathological processes, and it is known that AD causes reduced stiffness in the brain tissue during degeneration. However, there appears to be a significant lag time between microscale changes and macroscale obstruction of neurological function in the brain. Here, we present a pipeline to quantify the whole brain biomechanical environment to bridge the gap in understanding how underlying brain changes affect macroscale brain biomechanics. This pipeline enables image-based quantification of subject-specific displacement field of the whole brain to subject-specific strain, strain rate, and stress across 133 labeled functional brain regions. We have focused our development efforts on utilizing solely MRI-derived data to facilitate clinical applicability of our approach and have emphasized automation in all aspects of our methods to reduce operator dependance. Our pipeline has the potential to improve early detection of neurological disorders and facilitate the identification of disease before widespread, irreversible damage has occurred.

bioengineering↗

Intervertebral Disc Elastography to Relate Shear Modulus and Relaxometry in Compression and Bending

Intervertebral disc degeneration is the most recognized cause of low back pain, characterized by the decline of tissue structure and mechanics. Image-based mechanical parameters (e.g., strain, stiffness) may provide an ideal assessment of disc function that is lost with degeneration but unfortunately remains underdeveloped. Moreover, it is unknown whether strain or stiffness of the disc may be predicted by MRI relaxometry (e.g. T1 or T2), an increasingly accepted quantitative measure of disc structure. In this study, we quantified T1 and T2 relaxation times and in-plane strains using displacement-encoded MRI within the disc under physiological levels of compression and bending. We then estimated shear modulus in orthogonal image planes and compared these values to relaxation times and strains within regions of the disc. Intratissue strain depended on the loading mode, and shear modulus in the nucleus pulposus was typically an order of magnitude lower than the annulus fibrosis, except in bending, where the apparent stiffness depended on the loading. Relative shear moduli estimated from strain data derived under compression generally did not correspond with those from bending experiments, with no correlations in the sagittal plane and only 4 of 15 regions correlated in the coronal plane, suggesting that future inverse models should incorporate multiple loading conditions. Strain imaging and strain-based estimation of material properties may serve as imaging biomarkers to distinguish healthy and diseased discs. Additionally, image-based elastography and relaxometry may be viewed as complementary measures of disc structure and function to assess degeneration in longitudinal studies.

bioengineering↗