@article{TerekhovElabyadSchreiber2021, author = {Terekhov, Maxim and Elabyad, Ibrahim A. and Schreiber, Laura M.}, title = {Global optimization of default phases for parallel transmit coils for ultra-high-field cardiac MRI}, series = {PLoS One}, volume = {16}, journal = {PLoS One}, number = {8}, doi = {10.1371/journal.pone.0255341}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-265737}, year = {2021}, abstract = {The development of novel multiple-element transmit-receive arrays is an essential factor for improving B\(_1\)\(^+\) field homogeneity in cardiac MRI at ultra-high magnetic field strength (B\(_0\) > = 7.0T). One of the key steps in the design and fine-tuning of such arrays during the development process is finding the default driving phases for individual coil elements providing the best possible homogeneity of the combined B\(_1\)\(^+\)-field that is achievable without (or before) subject-specific B\(_1\)\(^+\)-adjustment in the scanner. This task is often solved by time-consuming (brute-force) or by limited efficiency optimization methods. In this work, we propose a robust technique to find phase vectors providing optimization of the B-1-homogeneity in the default setup of multiple-element transceiver arrays. The key point of the described method is the pre-selection of starting vectors for the iterative solver-based search to maximize the probability of finding a global extremum for a cost function optimizing the homogeneity of a shaped B\(_1\)\(^+\)-field. This strategy allows for (i) drastic reduction of the computation time in comparison to a brute-force method and (ii) finding phase vectors providing a combined B\(_1\)\(^+\)-field with homogeneity characteristics superior to the one provided by the random-multi-start optimization approach. The method was efficiently used for optimizing the default phase settings in the in-house-built 8Tx/16Rx arrays designed for cMRI in pigs at 7T.}, language = {en} } @article{SchreiberLohrBaltesetal.2023, author = {Schreiber, Laura M. and Lohr, David and Baltes, Steffen and Vogel, Ulrich and Elabyad, Ibrahim A. and Bille, Maya and Reiter, Theresa and Kosmala, Aleksander and Gassenmaier, Tobias and Stefanescu, Maria R. and Kollmann, Alena and Aures, Julia and Schnitter, Florian and Pali, Mihaela and Ueda, Yuichiro and Williams, Tatiana and Christa, Martin and Hofmann, Ulrich and Bauer, Wolfgang and Gerull, Brenda and Zernecke, Alma and Erg{\"u}n, S{\"u}leyman and Terekhov, Maxim}, title = {Ultra-high field cardiac MRI in large animals and humans for translational cardiovascular research}, series = {Frontiers in Cardiovascular Medicine}, volume = {10}, journal = {Frontiers in Cardiovascular Medicine}, issn = {2297-055X}, doi = {10.3389/fcvm.2023.1068390}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-317398}, year = {2023}, abstract = {A key step in translational cardiovascular research is the use of large animal models to better understand normal and abnormal physiology, to test drugs or interventions, or to perform studies which would be considered unethical in human subjects. Ultrahigh field magnetic resonance imaging (UHF-MRI) at 7 T field strength is becoming increasingly available for imaging of the heart and, when compared to clinically established field strengths, promises better image quality and image information content, more precise functional analysis, potentially new image contrasts, and as all in-vivo imaging techniques, a reduction of the number of animals per study because of the possibility to scan every animal repeatedly. We present here a solution to the dual use problem of whole-body UHF-MRI systems, which are typically installed in clinical environments, to both UHF-MRI in large animals and humans. Moreover, we provide evidence that in such a research infrastructure UHF-MRI, and ideally combined with a standard small-bore UHF-MRI system, can contribute to a variety of spatial scales in translational cardiovascular research: from cardiac organoids, Zebra fish and rodent hearts to large animal models such as pigs and humans. We present pilot data from serial CINE, late gadolinium enhancement, and susceptibility weighted UHF-MRI in a myocardial infarction model over eight weeks. In 14 pigs which were delivered from a breeding facility in a national SARS-CoV-2 hotspot, we found no infection in the incoming pigs. Human scanning using CINE and phase contrast flow measurements provided good image quality of the left and right ventricle. Agreement of functional analysis between CINE and phase contrast MRI was excellent. MRI in arrested hearts or excised vascular tissue for MRI-based histologic imaging, structural imaging of myofiber and vascular smooth muscle cell architecture using high-resolution diffusion tensor imaging, and UHF-MRI for monitoring free radicals as a surrogate for MRI of reactive oxygen species in studies of oxidative stress are demonstrated. We conclude that UHF-MRI has the potential to become an important precision imaging modality in translational cardiovascular research.}, language = {en} } @article{MartensPanzervandenWijngaardetal.2020, author = {Martens, Johannes and Panzer, Sabine and van den Wijngaard, Jeroen and Siebes, Maria and Schreiber, Laura M.}, title = {Influence of contrast agent dispersion on bolus-based MRI myocardial perfusion measurements: A computational fluid dynamics study}, series = {Magnetic Resonance in Medicine}, volume = {84}, journal = {Magnetic Resonance in Medicine}, number = {1}, doi = {10.1002/mrm.28125}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-208698}, pages = {467-483}, year = {2020}, abstract = {Purpose: Bolus-based dynamic contrast agent (CA) perfusion measurements of the heart are subject to systematic errors due to CA bolus dispersion in the coronary arteries. To better understand these effects on quantification of myocardial blood flow and myocardial perfusion reserve (MPR), an in-silico model of the coronary arteries down to the pre-arteriolar vessels has been developed. Methods: In this work, a computational fluid dynamics analysis is performed to investigate these errors on the basis of realistic 3D models of the left and right porcine coronary artery trees, including vessels at the pre-arteriolar level. Using advanced boundary conditions, simulations of blood flow and CA transport are conducted at rest and under stress. These are evaluated with regard to dispersion (assessed by the width of CA concentration time curves and associated vascular transport functions) and errors of myocardial blood flow and myocardial perfusion reserve quantification. Results: Contrast agent dispersion increases with traveled distance as well as vessel diameter, and decreases with higher flow velocities. Overall, the average myocardial blood flow errors are -28\% ± 16\% and -8.5\% ± 3.3\% at rest and stress, respectively, and the average myocardial perfusion reserve error is 26\% ± 22\%. The calculated values are different in the left and right coronary tree. Conclusion: Contrast agent dispersion is dependent on a complex interplay of several different factors characterizing the cardiovascular bed, including vessel size and integrated vascular length. Quantification errors evoked by the observed CA dispersion show nonnegligible distortion in dynamic CA bolus-based perfusion measurements. We expect future improvements of quantitative perfusion measurements to make the systematic errors described here more apparent.}, language = {en} } @article{HerzStefanescuLohretal.2022, author = {Herz, Stefan and Stefanescu, Maria R. and Lohr, David and Vogel, Patrick and Kosmala, Aleksander and Terekhov, Maxim and Weng, Andreas M. and Grunz, Jan-Peter and Bley, Thorsten A. and Schreiber, Laura M.}, title = {Effects of image homogeneity on stenosis visualization at 7 T in a coronary artery phantom study: With and without B1-shimming and parallel transmission}, series = {PloS One}, volume = {17}, journal = {PloS One}, number = {6}, doi = {10.1371/journal.pone.0270689}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-300129}, year = {2022}, abstract = {Background To investigate the effects of B\(_1\)-shimming and radiofrequency (RF) parallel transmission (pTX) on the visualization and quantification of the degree of stenosis in a coronary artery phantom using 7 Tesla (7 T) magnetic resonance imaging (MRI). Methods Stenosis phantoms with different grades of stenosis (0\%, 20\%, 40\%, 60\%, 80\%, and 100\%; 5 mm inner vessel diameter) were produced using 3D printing (clear resin). Phantoms were imaged with four different concentrations of diluted Gd-DOTA representing established arterial concentrations after intravenous injection in humans. Samples were centrally positioned in a thorax phantom of 30 cm diameter filled with a custom-made liquid featuring dielectric properties of muscle tissue. MRI was performed on a 7 T whole-body system. 2D-gradient-echo sequences were acquired with an 8-channel transmit 16-channel receive (8 Tx / 16 Rx) cardiac array prototype coil with and without pTX mode. Measurements were compared to those obtained with identical scan parameters using a commercially available 1 Tx / 16 Rx single transmit coil (sTX). To assess reproducibility, measurements (n = 15) were repeated at different horizontal angles with respect to the B0-field. Results B\(_1\)-shimming and pTX markedly improved flip angle homogeneity across the thorax phantom yielding a distinctly increased signal-to-noise ratio (SNR) averaged over a whole slice relative to non-manipulated RF fields. Images without B\(_1\)-shimming showed shading artifacts due to local B\(_1\)\(^+\)-field inhomogeneities, which hampered stenosis quantification in severe cases. In contrast, B\(_1\)-shimming and pTX provided superior image homogeneity. Compared with a conventional sTX coil higher grade stenoses (60\% and 80\%) were graded significantly (p<0.01) more precise. Mild to moderate grade stenoses did not show significant differences. Overall, SNR was distinctly higher with B\(_1\)-shimming and pTX than with the conventional sTX coil (inside the stenosis phantoms 14\%, outside the phantoms 32\%). Both full and half concentration (10.2 mM and 5.1 mM) of a conventional Gd-DOTA dose for humans were equally suitable for stenosis evaluation in this phantom study. Conclusions B\(_1\)-shimming and pTX at 7 T can distinctly improve image homogeneity and therefore provide considerably more accurate MR image analysis, which is beneficial for imaging of small vessel structures.}, language = {en} } @article{ElabyadTerekhovLohretal.2020, author = {Elabyad, Ibrahim A. and Terekhov, Maxim and Lohr, David and Stefanescu, Maria R. and Baltes, Steffen and Schreiber, Laura M.}, title = {A Novel Mono-surface Antisymmetric 8Tx/16Rx Coil Array for Parallel Transmit Cardiac MRI in Pigs at 7T}, series = {Scientific Reports}, volume = {10}, journal = {Scientific Reports}, number = {1}, doi = {10.1038/s41598-020-59949-6}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-229436}, year = {2020}, abstract = {A novel mono-surface antisymmetric 16-element transmit/receive (Tx/Rx) coil array was designed, simulated, constructed, and tested for cardiac magnetic resonance imaging (cMRI) in pigs at 7T. The cardiac array comprised of a mono-surface 16-loops with two central elements arranged antisymmetrically and flanked by seven elements on either side. The array was configured for parallel transmit (pTx) mode to have an eight channel transmit and 16-channel receive (8Tx/16Rx) coil array. Electromagnetic (EM) simulations, bench-top measurements, phantom, and MRI experiments with two pig cadavers (68 and 46 kg) were performed. Finally, the coil was used in pilot in-vivo measurements with a 60 kg pig. Flip angle (FA), geometry factor (g-factor), signal-to-noise ratio (SNR) maps, and high-resolution cardiac images were acquired with an in-plane resolution of 0.6 mm x 0.6 mm (in-vivo) and 0.3 mm x 0.3 mm (ex-vivo). The mean g-factor over the heart was 1.26 (R = 6). Static phase B-1(+) shimming in a pig body phantom with the optimal phase vectors makes possible to improve the B-1(+) homogeneity by factor > 2 and transmit efficiency by factor > 3 compared to zero phases (before RF shimming). Parallel imaging performed in the in-vivo measurements demonstrated well preserved diagnostic quality of the resulting images at acceleration factors up to R = 6. The described hardware design can be adapted for arrays optimized for animals and humans with a larger number of elements (32-64) while maintaining good decoupling for various MRI applications at UHF (e.g., cardiac, head, and spine).}, language = {en} } @article{BeyhoffLohrThieleetal.2020, author = {Beyhoff, Niklas and Lohr, David and Thiele, Arne and Foryst-Ludwig, Anna and Klopfleisch, Robert and Schreiber, Laura M. and Kintscher, Ulrich}, title = {Myocardial Infarction After High-Dose Catecholamine Application—A Case Report From an Experimental Imaging Study}, series = {Frontiers in Cardiovascular Medicine}, volume = {7}, journal = {Frontiers in Cardiovascular Medicine}, doi = {10.3389/fcvm.2020.580296}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-217959}, year = {2020}, abstract = {Although heart failure following myocardial infarction (MI) represents a major health burden, underlying microstructural and functional changes remain incompletely understood. Here, we report on a case of unexpected MI after treatment with the catecholamine isoproterenol in an experimental imaging study in mice using different state-of-the-art imaging modalities. The decline in cardiac function was documented by ultrahigh-frequency echocardiography and speckle-tracking analyses. Myocardial microstructure was studied ex vivo at a spatial resolution of 100 × 100 × 100 μm\(^{3}\) using diffusion tensor magnetic resonance imaging (DT-MRI) and histopathologic analyses. Two weeks after ISO treatment, the animal showed an apical aneurysm accompanied by reduced radial strain in corresponding segments and impaired global systolic function. DT-MRI revealed a loss of contractile fiber tracts together with a disarray of remaining fibers as corresponding microstructural correlates. This preclinical case report provides valuable insights into pathophysiology and morphologic-functional relations of heart failure following MI using emerging imaging technologies.}, language = {en} } @article{AnkenbrandShainbergHocketal.2021, author = {Ankenbrand, Markus J. and Shainberg, Liliia and Hock, Michael and Lohr, David and Schreiber, Laura M.}, title = {Sensitivity analysis for interpretation of machine learning based segmentation models in cardiac MRI}, series = {BMC Medical Imaging}, volume = {21}, journal = {BMC Medical Imaging}, number = {1}, doi = {10.1186/s12880-021-00551-1}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-259169}, pages = {27}, year = {2021}, abstract = {Background Image segmentation is a common task in medical imaging e.g., for volumetry analysis in cardiac MRI. Artificial neural networks are used to automate this task with performance similar to manual operators. However, this performance is only achieved in the narrow tasks networks are trained on. Performance drops dramatically when data characteristics differ from the training set properties. Moreover, neural networks are commonly considered black boxes, because it is hard to understand how they make decisions and why they fail. Therefore, it is also hard to predict whether they will generalize and work well with new data. Here we present a generic method for segmentation model interpretation. Sensitivity analysis is an approach where model input is modified in a controlled manner and the effect of these modifications on the model output is evaluated. This method yields insights into the sensitivity of the model to these alterations and therefore to the importance of certain features on segmentation performance. Results We present an open-source Python library (misas), that facilitates the use of sensitivity analysis with arbitrary data and models. We show that this method is a suitable approach to answer practical questions regarding use and functionality of segmentation models. We demonstrate this in two case studies on cardiac magnetic resonance imaging. The first case study explores the suitability of a published network for use on a public dataset the network has not been trained on. The second case study demonstrates how sensitivity analysis can be used to evaluate the robustness of a newly trained model. Conclusions Sensitivity analysis is a useful tool for deep learning developers as well as users such as clinicians. It extends their toolbox, enabling and improving interpretability of segmentation models. Enhancing our understanding of neural networks through sensitivity analysis also assists in decision making. Although demonstrated only on cardiac magnetic resonance images this approach and software are much more broadly applicable.}, language = {en} }