Medizinische Klinik und Poliklinik I
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Das Ziel der vorliegenden Arbeit war die Entwicklung neuer, robuster Methoden der Spin-Lock-basierten MRT. Im Fokus stand hierbei vorerst die T1ρ-Quantifizierung des Myokards im Kleintiermodell. Neben der T1ρ-Bildgebung bietet Spin-Locking jedoch zusätzlich die Möglichkeit der Detektion ultra-schwacher, magnetischer Feldoszillationen. Die Projekte und Ergebnisse, die im Rahmen dieses Promotionsvorhabens umgesetzt und erzielt wurden, decken daher ein breites Spektrum der Spin-lock basierten Bildgebung ab und können grob in drei Bereiche unterteilt werden. Im ersten Schritt wurde die grundlegende Pulssequenz des Spin-Lock-Experimentes durch die Einführung des balancierten Spin-Locks optimiert. Der zweite Schritt war die Entwicklung einer kardialen MRT-Sequenz für die robuste Quantifizierung der myokardialen T1ρ-Relaxationszeit an einem präklinischen Hochfeld-MRT. Im letzten Schritt wurden Konzepte der robusten T1ρ-Bildgebung auf die Methodik der Felddetektion mittels Spin-Locking übertragen. Hierbei wurden erste, erfolgreiche Messungen magnetischer Oszillationen im nT-Bereich, welche lokal im untersuchten Gewebe auftreten, an einem klinischen MRT-System im menschlichen Gehirn realisiert.
To evaluate an iterative learning approach for enhanced performance of robust artificial‐neural‐networks for k‐space interpolation (RAKI), when only a limited amount of training data (auto‐calibration signals [ACS]) are available for accelerated standard 2D imaging.
Methods
In a first step, the RAKI model was tailored for the case of limited training data amount. In the iterative learning approach (termed iterative RAKI [iRAKI]), the tailored RAKI model is initially trained using original and augmented ACS obtained from a linear parallel imaging reconstruction. Subsequently, the RAKI convolution filters are refined iteratively using original and augmented ACS extracted from the previous RAKI reconstruction. Evaluation was carried out on 200 retrospectively undersampled in vivo datasets from the fastMRI neuro database with different contrast settings.
Results
For limited training data (18 and 22 ACS lines for R = 4 and R = 5, respectively), iRAKI outperforms standard RAKI by reducing residual artifacts and yields better noise suppression when compared to standard parallel imaging, underlined by quantitative reconstruction quality metrics. Additionally, iRAKI shows better performance than both GRAPPA and standard RAKI in case of pre‐scan calibration with varying contrast between training‐ and undersampled data.
Conclusion
RAKI benefits from the iterative learning approach, which preserves the noise suppression feature, but requires less original training data for the accurate reconstruction of standard 2D images thereby improving net acceleration.
Background
Fast and accurate T1ρ mapping in myocardium is still a major challenge, particularly in small animal models. The complex sequence design owing to electrocardiogram and respiratory gating leads to quantification errors in in vivo experiments, due to variations of the T\(_{1p}\) relaxation pathway. In this study, we present an improved quantification method for T\(_{1p}\) using a newly derived formalism of a T\(_{1p}\)\(^{*}\) relaxation pathway.
Methods
The new signal equation was derived by solving a recursion problem for spin-lock prepared fast gradient echo readouts. Based on Bloch simulations, we compared quantification errors using the common monoexponential model and our corrected model. The method was validated in phantom experiments and tested in vivo for myocardial T\(_{1p}\) mapping in mice. Here, the impact of the breath dependent spin recovery time T\(_{rec}\) on the quantification results was examined in detail.
Results
Simulations indicate that a correction is necessary, since systematically underestimated values are measured under in vivo conditions. In the phantom study, the mean quantification error could be reduced from − 7.4% to − 0.97%. In vivo, a correlation of uncorrected T\(_{1p}\) with the respiratory cycle was observed. Using the newly derived correction method, this correlation was significantly reduced from r = 0.708 (p < 0.001) to r = 0.204 and the standard deviation of left ventricular T\(_{1p}\) values in different animals was reduced by at least 39%.
Conclusion
The suggested quantification formalism enables fast and precise myocardial T\(_{1p}\) quantification for small animals during free breathing and can improve the comparability of study results. Our new technique offers a reasonable tool for assessing myocardial diseases, since pathologies that cause a change in heart or breathing rates do not lead to systematic misinterpretations. Besides, the derived signal equation can be used for sequence optimization or for subsequent correction of prior study results.
Spin-lock based functional magnetic resonance imaging (fMRI) has the potential for direct spatially-resolved detection of neuronal activity and thus may represent an important step for basic research in neuroscience. In this work, the corresponding fundamental effect of Rotary EXcitation (REX) is investigated both in simulations as well as in phantom and in vivo experiments. An empirical law for predicting optimal spin-lock pulse durations for maximum magnetic field sensitivity was found. Experimental conditions were established that allow robust detection of ultra-weak magnetic field oscillations with simultaneous compensation of static field inhomogeneities. Furthermore, this work presents a novel concept for the emulation of brain activity utilizing the built-in MRI gradient system, which allows REX sequences to be validated in vivo under controlled and reproducible conditions. Via transmission of Rotary EXcitation (tREX), we successfully detected magnetic field oscillations in the lower nano-Tesla range in brain tissue. Moreover, tREX paves the way for the quantification of biomagnetic fields.
Purpose
T\(_{1P}\) dispersion quantification can potentially be used as a cardiac magnetic resonance index for sensitive detection of myocardial fibrosis without the need of contrast agents. However, dispersion quantification is still a major challenge, because T\(_{1P}\) mapping for different spin lock amplitudes is a very time consuming process. This study aims to develop a fast and accurate T\(_{1P}\) mapping sequence, which paves the way to cardiac T1ρ dispersion quantification within the limited measurement time of an in vivo study in small animals.
Methods
A radial spin lock sequence was developed using a Bloch simulation-optimized sampling pattern and a view-sharing method for image reconstruction. For validation, phantom measurements with a conventional sampling pattern and a gold standard sequence were compared to examine T\(_{1P}\) quantification accuracy. The in vivo validation of T\(_{1P}\) mapping was performed in N = 10 mice and in a reproduction study in a single animal, in which ten maps were acquired in direct succession. Finally, the feasibility of myocardial dispersion quantification was tested in one animal.
Results
The Bloch simulation-based sampling shows considerably higher image quality as well as improved T\(_{1P}\) quantification accuracy (+ 56%) and precision (+ 49%) compared to conventional sampling. Compared to the gold standard sequence, a mean deviation of - 0.46 ± 1.84% was observed. The in vivo measurements proved high reproducibility of myocardial T\(_{1P}\) mapping. The mean T\(_{1P}\) in the left ventricle was 39.5 ± 1.2 ms for different animals and the maximum deviation was 2.1% in the successive measurements. The myocardial T\(_{1P}\) dispersion slope, which was measured for the first time in one animal, could be determined to be 4.76 ± 0.23 ms/kHz.
Conclusion
This new and fast T\(_{1P}\) quantification technique enables high-resolution myocardial T\(_{1P}\) mapping and even dispersion quantification within the limited time of an in vivo study and could, therefore, be a reliable tool for improved tissue characterization.
Simultaneous measurements of 3D wall shear stress and pulse wave velocity in the murine aortic arch
(2021)
Purpose
Wall shear stress (WSS) and pulse wave velocity (PWV) are important parameters to characterize blood flow in the vessel wall. Their quantification with flow-sensitive phase-contrast (PC) cardiovascular magnetic resonance (CMR), however, is time-consuming. Furthermore, the measurement of WSS requires high spatial resolution, whereas high temporal resolution is necessary for PWV measurements. For these reasons, PWV and WSS are challenging to measure in one CMR session, making it difficult to directly compare these parameters. By using a retrospective approach with a flexible reconstruction framework, we here aimed to simultaneously assess both PWV and WSS in the murine aortic arch from the same 4D flow measurement.
Methods
Flow was measured in the aortic arch of 18-week-old wildtype (n = 5) and ApoE\(^{−/−}\) mice (n = 5) with a self-navigated radial 4D-PC-CMR sequence. Retrospective data analysis was used to reconstruct the same dataset either at low spatial and high temporal resolution (PWV analysis) or high spatial and low temporal resolution (WSS analysis). To assess WSS, the aortic lumen was labeled by semi-automatically segmenting the reconstruction with high spatial resolution. WSS was determined from the spatial velocity gradients at the lumen surface. For calculation of the PWV, segmentation data was interpolated along the temporal dimension. Subsequently, PWV was quantified from the through-plane flow data using the multiple-points transit-time method. Reconstructions with varying frame rates and spatial resolutions were performed to investigate the influence of spatiotemporal resolution on the PWV and WSS quantification.
Results
4D flow measurements were conducted in an acquisition time of only 35 min. Increased peak flow and peak WSS values and lower errors in PWV estimation were observed in the reconstructions with high temporal resolution. Aortic PWV was significantly increased in ApoE\(^{−/−}\) mice compared to the control group (1.7 ± 0.2 versus 2.6 ± 0.2 m/s, p < 0.001). Mean WSS magnitude values averaged over the aortic arch were (1.17 ± 0.07) N/m\(^2\) in wildtype mice and (1.27 ± 0.10) N/m\(^2\) in ApoE\(^{−/−}\) mice.
Conclusion
The post processing algorithm using the flexible reconstruction framework developed in this study permitted quantification of global PWV and 3D-WSS in a single acquisition. The possibility to assess both parameters in only 35 min will markedly improve the analyses and information content of in vivo measurements.
Growth, ageing and atherosclerotic plaque development alter the biomechanical forces acting on the vessel wall. However, monitoring the detailed local changes in wall shear stress (WSS) at distinct sites of the murine aortic arch over time has been challenging. Here, we studied the temporal and spatial changes in flow, WSS, oscillatory shear index (OSI) and elastic properties of healthy wildtype (WT, n = 5) and atherosclerotic apolipoprotein E-deficient (Apoe\(^{−/−}\), n = 6) mice during ageing and atherosclerosis using high-resolution 4D flow magnetic resonance imaging (MRI). Spatially resolved 2D projection maps of WSS and OSI of the complete aortic arch were generated, allowing the pixel-wise statistical analysis of inter- and intragroup hemodynamic changes over time and local correlations between WSS, pulse wave velocity (PWV), plaque and vessel wall characteristics. The study revealed converse differences of local hemodynamic profiles in healthy WT and atherosclerotic Apoe\(^{−/−}\) mice, and we identified the circumferential WSS as potential marker of plaque size and composition in advanced atherosclerosis and the radial strain as a potential marker for vascular elasticity. Two-dimensional (2D) projection maps of WSS and OSI, including statistical analysis provide a powerful tool to monitor local aortic hemodynamics during ageing and atherosclerosis. The correlation of spatially resolved hemodynamics and plaque characteristics could significantly improve our understanding of the impact of hemodynamics on atherosclerosis, which may be key to understand plaque progression towards vulnerability.
Atherosclerosis is an inflammatory disease of large and medium-sized arteries, characterized by the growth of atherosclerotic lesions (plaques). These plaques often develop at inner curvatures of arteries, branchpoints, and bifurcations, where the endothelial wall shear stress is low and oscillatory. In conjunction with other processes such as lipid deposition, biomechanical factors lead to local vascular inflammation and plaque growth. There is also evidence that low and oscillatory shear stress contribute to arterial remodeling, entailing a loss in arterial elasticity and, therefore, an increased pulse-wave velocity. Although altered shear stress profiles, elasticity and inflammation are closely intertwined and critical for plaque growth, preclinical and clinical investigations for atherosclerosis mostly focus on the investigation of one of these parameters only due to the experimental limitations. However, cardiovascular magnetic resonance imaging (MRI) has been demonstrated to be a potent tool which can be used to provide insights into a large range of biological parameters in one experimental session. It enables the evaluation of the dynamic process of atherosclerotic lesion formation without the need for harmful radiation. Flow-sensitive MRI provides the assessment of hemodynamic parameters such as wall shear stress and pulse wave velocity which may replace invasive and radiation-based techniques for imaging of the vascular
function and the characterization of early plaque development. In combination with inflammation imaging, the analyses and correlations of these parameters could not only significantly advance basic preclinical investigations of atherosclerotic lesion formation and progression, but also the diagnostic clinical evaluation for early identification of high-risk plaques, which are prone to rupture. In this review, we summarize the key applications of magnetic resonance imaging for the evaluation of plaque characteristics through flow sensitive and morphological measurements. The simultaneous measurements of functional and structural parameters will further preclinical research on atherosclerosis and has the potential to fundamentally improve the detection of inflammation and vulnerable plaques in patients.
This longitudinal study was performed to evaluate the feasibility of detecting the interaction between wall shear stress (WSS) and plaque development. 20 ApoE\(^{-/-}\)mice were separated in 12 mice with Western Diet and 8 mice with Chow Diet. Magnetic resonance (MR) scans at 17.6 Tesla and histological analysis were performed after one week, eight and twelve weeks. Allin vivoMR measurements were acquired using a flow sensitive phase contrast method for determining vectorial flow. Histological sections were stained with Hematoxylin and Eosin, Elastica van Gieson and CD68 staining. Data analysis was performed using Ensight and a Matlab-based "Flow Tool". The body weight of ApoE\(^{-/-}\)mice increased significantly over 12 weeks. WSS values increased in the Western Diet group over the time period; in contrast, in the Chow Diet group the values decreased from the first to the second measurement point. Western Diet mice showed small plaque formations with elastin fragmentations after 8 weeks and big plaque formations after 12 weeks; Chow Diet mice showed a few elastin fragmentations after 8 weeks and small plaque formations after 12 weeks. Favored by high-fat diet, plaque formation results in higher values of WSS. With wall shear stress being a known predictor for atherosclerotic plaque development, ultra highfield MRI can serve as a tool for studying the causes and beginnings of atherosclerosis.
Increased aortic stiffness is known to be associated with atherosclerosis and has a predictive value for cardiovascular events. This study aims to investigate the local distribution of early arterial stiffening due to initial atherosclerotic lesions. Therefore, global and local pulse wave velocity (PWV) were measured in ApoE\(^{-/-}\) and wild type (WT) mice using ultrahigh field MRI. For quantification of global aortic stiffness, a new multi-point transit-time (TT) method was implemented and validated to determine the global PWV in the murine aorta. Local aortic stiffness was measured by assessing the local PWV in the upper abdominal aorta, using the flow/area (QA) method. Significant differences between age matched ApoE\(^{-/-}\) and WT mice were determined for global and local PWV measurements (global PWV: ApoE\(^{-/-}\): 2.7 ±0.2m/s vs WT: 2.1±0.2m/s, P<0.03; local PWV: ApoE\(^{-/-}\): 2.9±0.2m/s vs WT: 2.2±0.2m/s, P<0.03). Within the WT mouse group, the global PWV correlated well with the local PWV in the upper abdominal aorta (R\(^2\) = 0.75, P<0.01), implying a widely uniform arterial elasticity.
In ApoE\(^{-/-}\) animals, however, no significant correlation between individual local and global PWV was present (R\(^2\) = 0.07, P = 0.53), implying a heterogeneous distribution of vascular stiffening in early atherosclerosis. The assessment of global PWV using the new multi-point TT measurement technique was validated against a pressure wire measurement in a vessel
phantom and showed excellent agreement. The experimental results demonstrate that vascular stiffening caused by early atherosclerosis is unequally distributed over the length of large vessels. This finding implies that assessing heterogeneity of arterial stiffness by multiple local measurements of PWV might be more sensitive than global PWV to identify early atherosclerotic lesions.