RT info:eu-repo/semantics/doctoralThesis
T1 Optimized acquisition and estimation techniques in diffusion MRI for quantitative imaging
A1 Peña Nogales, Óscar
A2 Universidad de Valladolid. Escuela Técnica Superior de Ingenieros de Telecomunicación
K1 Resonancia magnética
K1 Optimización
K1 Imágenes cuantitativas
K1 33 Ciencias Tecnológicas
K1 3325 Tecnología de las Telecomunicaciones
AB Diffusion-Weighted Magnetic Resonance Imaging (DW-MRI) is able to measure intrinsicproperties of tissue structure non-invasively. By applying diffusion-weighting,DW-MRI is sensitive to microscopic water displacements, with multiple applicationsfor tissue characterization, diagnosis and treatment monitoring. Nevertheless,the application of these long and powerful diffusion-weighting gradients results incompelling imaging challenges. Consequently, this Thesis focuses on the optimizationof the Spin Echo (SE) Diffusion-Weighted Imaging (DWI) sequence to improveimage quality and estimation of the diffusion-related parametric maps.As far as image quality is concerned, traditional SE DWI acquisition experiencesartefacts from signal dephasing due to bulk motion, Concomitant Gradients (CGs),and Eddy Currents (ECs) which decrease image quality and complicate image interpretation.Additionally, it also suffers from severe signal attenuation due to the longEcho Time (TE) needed to achieve strong diffusion-weightings. Multiple approacheshave been proposed to diminish these DWI artefacts, from synchronization, gatingand complex DWI sequences such as the Twice Refocused Spin Echo (TRSE)to the application of diffusion-weighting gradients with nth-order motion-nullingand/or EC-nulling. Nevertheless, these techniques generally result in suboptimalacquisitions with long TEs. In this Thesis, we propose a versatile formulation forthe design of optimized diffusion-weighting gradient waveforms that alleviates theprevious drawbacks while minimizing the TE of the acquisition.The estimation of the diffusion-related parametric maps is usually affected by severalconfounding factors such as low accuracy and precision and lack of repeatabilityand reproducibility, partially caused by the previous artefacts. These confoundingfactors appear in both the monoexponential and the Intravoxel Incoherent Motion(IVIM) Diffusion-Weighted (DW) signal models, and hinder the establishmentof their diffusion-related parametric maps as quantitative imaging biomarkers.Accuracy of the estimates, particularly of the Apparent Diffusion Coefficient (ADC)of the monoexponential DWsignal model, can be increased by using the appropriateestimator. However, the set of diffusion-weightings (i.e., set of b-values) thatincreases the precision of the estimated parametric maps remains unclear. Inthis Thesis, we derive the Cramér-Rao Lower Bound (CRLB) of both DW signalmodels under the assumption of DW to be affected by Rician distributed noise, andpropose a formulation for the optimization of the set of b-values that maximizesthe noise performance (i.e., minimizes the variance and maximizes the precision) ofthe estimated diffusion-related parametric maps.
YR 2021
FD 2021
LK https://uvadoc.uva.es/handle/10324/47602
UL https://uvadoc.uva.es/handle/10324/47602
LA eng
NO Departamento de Teoría de la Señal y Comunicaciones e Ingeniería Telemática
DS UVaDOC
RD 18-nov-2024