Datenbestand vom 15. November 2024

Warenkorb Datenschutzhinweis Dissertationsdruck Dissertationsverlag Institutsreihen     Preisrechner

aktualisiert am 15. November 2024

ISBN 9783843952521

72,00 € inkl. MwSt, zzgl. Versand


978-3-8439-5252-1, Reihe Medizintechnik

Martin Schwartz
Recording and Processing of Magnetic Resonance Imaging and Electromyographic Data for Assessment of Spontaneous Neuromuscular Activities

241 Seiten, Dissertation Universität Stuttgart (2023), Softcover, A5

Zusammenfassung / Abstract

Spontaneous activities in resting skeletal musculature in humans occur under different physiological conditions, but changes in their spatio-temporal patterns can also indicate neuromuscular disease or abnormality. These are currently detected by diagnostic techniques, such as invasive needle electromyography or non-invasive muscle sonography, and clinically classified on the basis of their temporal pattern and rate of occurrence. However, the available clinically established diagnostic techniques are not only in part invasive but are also spatially limited and therefore can only provide very localized information about the spontaneous activities of resting musculature. Moreover, a whole-body examination or the inspection of several different muscle groups requires multiple consecutive invasive procedures to assess the current state of the resting musculature. Magnetic Resonance Imaging (MRI), as a non-invasive, three-dimensional imaging measurement technique, has the potential to address these limitations of established diagnostic techniques and to complement them. In particular, Diffusion-Weighted (DW)-MRI could make an important contribution due to its inherent sensitivity with respect to all kind of incoherent motion.

This work focuses on the technical aspects and characteristics of visualizing unique spontaneous activities of resting human musculature by DW-MRI in combination with simultaneously recorded non-invasive Surface ElectroMyoGraphy (sEMG) measurements. Within the scope of this thesis, the physiological relationships between signal voids visible in diffusion-weighted images and single myoelectric spontaneous activities are identified. On this basis, image acquisition is optimized to this specific and challenging task using state-of-the-art imaging techniques and newly introduced concepts.