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Alexander James Wilson^1,2,3, Xiaojian Kang², Tyler Cork¹, Luigi Perotti⁴, and Daniel Ennis^1,2,3
1Radiological Sciences Laboratory, Stanford University, Stanford, CA, United States, ²Division of Radiology, Veterans Administration Health Care System, Palo Alto, CA, United States, ³Cardiovascular Institute, Stanford University, Stanford, CA, United States, ⁴Department of Mechanical and Aerospace Engineering, University of Central Florida, Orlando, FL, United States

Keywords: Myocardium, Diffusion Tensor Imaging

Ex vivo DTI was performed in hearts suffering from myocardial infarction. Data was reconstructed using both tensor-based and voxel-based analysis. The fixel number (FN) consistently showed that there was a single fiber population (FN=1) in both infarcted and healthy myocardium. The complexity (CX) indicates the spread and magnitude of diffusion along different directions, but was not significantly different between infarct and healthy regions. The apparent fiber density (AFD) reveals the density of each fiber population within a voxel, and curiously increased in the infarct region, which may indicate the compaction of fiber populations running through the infarct.

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Xavier Sieber¹, Ludovica Romanin^1,2, Chris W. Roy¹, Jessica AM Bastiaansen^3,4, Jérôme Yerly¹, Jonas Richiardi¹, Matthias Stuber^1,5, and Ruud B. van Heeswijk^1
1Department of Diagnostic and Interventional Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland, ²Advanced Clinical Imaging Technology, Siemens Healthineers International AG, Lausanne, Switzerland, ³Department of Diagnostic, Interventional and Pediatric Radiology (DIPR), Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland, ⁴Translation Imaging Center (TIC), Swiss Institute for Translational and Entrepreneurial Medicine, Bern, Switzerland, ⁵Division of Cardiology, CIBM Center for Biomedical Imaging, Lausanne, Switzerland

Keywords: Vessels, RF Pulse Design & Fields

The incomplete or time-inefficient suppression of fat signals is an unsolved issue in 3D cardiovascular MR imaging (CMR). We present a flexible framework named OptiPulse to design spectrally-selective radiofrequency (RF) pulses using numerical optimization of Bloch equation simulations. The RF pulse performance was assessed using a composite loss function for both fat suppression and power requirement. OptiPulse was used to design a B-splines-interpolated pulse for use in a free-running 3D whole-heart pulse sequence.  Its fat suppression performance was ascertained both in vitro and in vivo, where it resulted in more homogeneous fat suppression when compared to other WE pulses (P<0.01).

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Tabita Catalán¹, Matías Courdurier^1,2, Axel Osses^1,3, René Botnar^1,4,5, Francisco Sahli Costabal^1,4, and Claudia Prieto^1,4
1Millennium Nucleus For Applied Control And Inverse Problems, Santiago, Chile, ²Department of Mathematics, Pontificia Universidad Católica de Chile, Santiago, Chile, ³Department of Mathematical Engineering, Universidad de Chile, Santiago, Chile, ⁴School of Engineering, Pontificia Universidad Católica de Chile, Santiago, Chile, ⁵Institute for Biological and Medical Engineering, Pontificia Universidad Católica de Chile, Santiago, Chile

Keywords: Image Reconstruction, Heart

Neural fields cardiac MRI (NF-cMRI), a method for highly accelerated CINE reconstruction using deep learning, is proposed. NF-cMRI relies on an intensity network, based on neural fields with Fourier features to encode a continuous reconstruction. The network is trained with one undersampled radial k-space data set without the need of a fully-sampled reference image. Good image quality of the heart is achieved with 8 radial spokes/cardiac frame. Results are compared against GRASP. Future work will focus on reducing reconstruction time and evaluating the proposed approach in prospectively undersampled k-space data.

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Hazar Benan Unal¹, Shahriar Zeynali¹, Subha Raman², Balaji Tamarappoo², Rohan Dharmakumar², and Behzad Sharif^1,2
1Laboratory for Translational Imaging of Microcirculation, Indiana University School of Medicine, Indianapolis, IN, United States, ²Krannert Cardiovascular Research Center, Indiana University School of Medicine, Indianapolis, IN, United States

Keywords: Myocardium, Ischemia, dobutamine

Myocardial T1 reactivity, defined as the relative T1 change from rest to stress, has been proposed as a marker for detection of ischemic heart disease. Commonly used MOLLI T1 mapping is sensitive to B0 field inhomogeneities and can have susceptibility/banding artifacts because of bSSFP readouts, especially at 3T. In this study, we investigated the feasibility of free-breathing SR-FLASH T1 mapping for ferumoxytol-enhanced (FE) dobutamine-stress T1 reactivity studies at 3T in preclinical settings. We showed the feasibility of using a widely available perfusion sequence for T1 reactivity studies under Ferumoxytol-enhancement.

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Eric S. Michael¹, Claire A. Dick¹, Franciszek Hennel¹, Christian T. Stoeck^1,2, and Klaas P. Pruessmann^1
1Institute for Biomedical Engineering, ETH Zurich and University of Zurich, Zurich, Switzerland, ²Center for Surgical Research, University Hospital Zurich, University of Zurich, Zurich, Switzerland

Keywords: Heart, Ischemia

Diffusion dispersion mapping is a recently proposed method for probing tissue microstructure and quantifying microstructural disorder based on differences in the impact of diffusion restrictions over different length scales. In this work, this method was employed in the ex vivo heart to investigate the utility of diffusion dispersion in identifying and characterizing ischemic tissue. Our results show that ischemic cardiac lesions exhibit reduced diffusion dispersion rates, in agreement with known microstructural changes, and can be differentiated with respect to surrounding tissue. These findings demonstrate that microstructure-sensitive contrast offers a novel avenue for probing and characterizing cardiac pathologies.

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Pierre CABANIS^1,2, Julie MAGAT^1,2, Jairo RODRIGUEZ-PADILLA³, Girish RAMLUGUN², Maxime YON², Yann BIHANPOUDEC⁴, Nestor PALLARES-LUPON², Fanny VAILLANT², Philippe PASDOIS², Pierre JAIS^2,5, Pierre DOS-SANTOS^2,5, Marion CONSTANTIN², David BENOIST², Line POURTAU², Virginie DUBES², Julien ROGIER^2,5, Louis LABROUSSE^2,5, Michel HAISSAGUERRE^2,5, Olivier BERNUS², Bruno QUESSON^1,2, Richard WALTON², Josselin DUCHATEAU^2,5, Edward VIGMOND², and Valéry OZENNE^1,2
1Univ. Bordeaux, CNRS, CRMSB, UMR 5536, Bordeaux, France, ²Liryc, Electrophysiology and Heart Modeling Institute, Fondation Bordeaux Université, Pessac-Bordeaux, France, ³Inria Epione Team, Université Côte d'Azur, Biot, France, ⁴Centre de Neuroscience Cognitive, CNRS, Université Claude Bernard Lyon I, Villeurbanne, France, ⁵Cardiology Departement, Bordeaux University Hospital (CHU), Pessac, France

Keywords: Myocardium, Microstructure, Fiber

The knowledge of the cardiac microstructure and the 3D myofiber architecture grow years after years with the multiplication and the upgrade of imaging technologies. However,  the course of events of pathophysiological processes like cardiac remodeling, and the link with clinical phenotypes are not yet clearly understood. Some concerns have been raised regarding the interpretation of the late gadolinium enhancement (LGE) at the right ventricle attachment or insertion point (RVIP) however 3D microstructure organization of the RVIP has not been extensively described in the literature.

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Anastasia Fotaki¹, Camila Munoz¹, Alina Hua¹, Karl P Kunze^1,2, Radhouene Neji^1,2, Tevfik F Ismail¹, Rene M Botnar^1,3,4,5, and Claudia Prieto^1,3,4,5
1Biomedical Engineering, King's College London, London, United Kingdom, ²MR Research Collaborations, Siemens Healthcare Limited, Camberley, United Kingdom, ³Institute for Biological and Medical Engineering, Pontificia Universidad Católica de Chile, Santiago, Chile, ⁴Millennium Institute for Intelligent Healthcare Engineering, Santiago, Chile, ⁵School of Engineering, Pontificia Universidad Católica de Chile, Santiago, Chile

Keywords: Vessels, New Signal Preparation Schemes, Pulse Sequence Design

Dark-blood imaging is an important tool for vascular imaging in cardiovascular disease. A novel free-breathing water/fat DANTE-prepared sequence is introduced for 3D dark-blood imaging of the thoracic and abdominal aorta. The framework integrates image navigation to enable translational and non-rigid motion correction resulting in a predictable scan time along with dual-echo Dixon gradient-echo readout for robust fat suppression. Results from healthy subjects and patients demonstrate the feasibility of the sequence for high-resolution, aortic imaging in ~7-minute acquisition time.

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Jonathan Weine¹, Stefano Buoso¹, Charles McGrath¹, and Sebastian Kozerke^1
1University and ETH Zurich, Zurich, Switzerland

Keywords: Heart, Diffusion Tensor Imaging

Myocardial strains and microstructure are considered important indicators of muscle contractility and function, which can be investigated with cardiac diffusion tensor imaging (cDTI) and tissue-velocity mapping. In this work we perform simulations incorporating contractile motion and model based diffusion contrast to investigate jointly encoding the information by modifying existing cDTI protocols. Key characteristics of the results agree with practical findings and suggest sufficient estimation accuracy for velocities and diffusion tensors.

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Zimu Huo^1,2, Ke Wen¹, Yaqing Luo¹, Pedro F Ferreira¹, Radhouene Neji^3,4, Dudley Pennell¹, Andrew D Scott¹, and Sonia Nielles-Vallespin^1
1CMR Unit, Royal Brompton Hospital and NHLI, Imperial college London, London, United Kingdom, ²Department of Bioengineering, Imperial College London, London, United Kingdom, ³School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom, ⁴MR Research Collaborations, Siemens Healthcare Limited, Frimley, United Kingdom

Keywords: Myocardium, Diffusion Tensor Imaging

Nyquist ghosting is a common artefact in echo planar imaging (EPI), typically corrected using separately acquired reference data. Here we demonstrate that reference free Nyquist ghost correction algorithms based on entropy and Ghost/Object ratio minimization can outperform navigator based methods and improve imaging efficiency for in vivo diffusion tensor cardiovascular magnetic resonance.

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Xiao Li¹, Jianjian Zhang¹, Huilin Zhao¹, and Chengcheng Zhu^2
1Ren ji Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai, China, ²University of Washington, Seattle, WA, United States

Keywords: Vessels, Vessels

Both aneurysm wall enhancement (AWE) and irregular pulsation have been suggested as potential candidates for intracranial aneurysms (IAs) instability. However, no studies have compared irregular pulsation and AWE for evaluation symptoms in unruptured IAs. By using vessel wall MRI and four-dimensional computed tomography angiography, we found combination of aneurysm wall enhancement and irregular pulsation improve the diagnostic efficiency of symptomatic intracranial aneurysm compared with irregular pulsation or AWE alone. Further longitudinal studies are needed to validate the role of the two imaging markers in predicting aneurysm growth and rupture.

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Manuel Morales¹, Manuel A Morales¹, Siyeop Yoon¹, Jennifer Rodriguez¹, Warren J Manning¹, and Reza Nezafat^1
1BIDMC, Boston, MA, United States

Keywords: Heart, Machine Learning/Artificial Intelligence

Combined cardiac MRI with exercise (Ex-CMR) is a stress test with promising applications. However, standard ECG-segmented cine imaging during exercise is challenging. Free-breathing ECG-free real time cine can be achieved with compressed sensing. Yet tradeoff remains between temporal and spatial temporal resolution. Thus, we sought to develop a highly accelerated high-frame-rate cine for Ex-CMR by accelerating spatial resolution using Resolution Enhancement Generative Adversarial Inline Network (REGAIN), followed by synthesizing new frames using Deformation ENcoding Transformer (DENT). REGAIN enabled 14-fold scan acceleration, DENT enabled 2-fold improvement in temporal resolution. We achieved  spatiotemporal resolution of 1.9 × 1.9 mm² and 16 ms.

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Qing Zou¹, Sarv Priya², Prashant Nagpal³, and Mathews Jacob^2
1University of Texas Southwestern Medical Center, Dallas, TX, United States, ²University of Iowa, Iowa City, IA, United States, ³University of Wisconsin–Madison, Madison, WI, United States

Keywords: Heart, Machine Learning/Artificial Intelligence, Reconstruction

The main focus of this work is to introduce a deep generative model for simultaneous free-breathing cardiac $$$T_1$$$ mapping and CINE MRI. The data is acquired by a gradient echo inversion recovery sequence with intermittent delays for magnetization recovery. The joint reconstruction of the image time-series is performed using a patient-specific deep manifold reconstruction algorithm which learns a CNN generative model and its latent vectors from the measured k-t space data in an unsupervised fashion. Following learning, the model can be used to generate synthetic images at specific motion and contrast states.

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Jérôme Yerly ^1,2, Christopher W Roy¹, Milan Prsa³, Bastien Milani¹, and Matthias Stuber^1,2
1Department of Diagnostic and Interventional Radiology, Lausanne University Hospital, Lausanne, Switzerland, ²Center for Biomedical Imaging (CIBM), Lausanne, Switzerland, ³Woman-Mother-Child Department, Lausanne University Hospital, Lausanne, Switzerland

Keywords: Heart, Image Reconstruction

The reconstruction of 5D cardiac and respiratory motion-resolved images with the free-running framework (FRF) requires careful optimization of the regularization weights to avoid compression of physiological motion, which in turn may lead to underestimated left ventricular ejection fraction (LVEF). This study presents a novel cardiac and respiratory motion-resolved reconstruction with inter-bin compensation of cardiac motion. We demonstrate that the proposed framework significantly improves image quality while preserving accurate LVEF when compared to the original 5D framework. This work highlights important considerations when reconstructing cardiac resolved images without compensation and provides a robust approach for the assessment of LVEF.

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Wen Li¹, Xianchang Zhang², Jing An³, Jens Wetzl⁴, Qing Gu⁵, and Jianguo He^6
1State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China, ²MR Collaboration, Siemens Healthineers Ltd, Beijing, China, ³Siemens Shenzhen Magnetic Resonance Ltd, Shenzhen, China, ⁴Magnetic Resonance, Siemens Healthcare, Erlangen, Germany, ⁵Emergency Center, State Key Laboratory of Cardiovascular Disease, Key Laboratory of Pulmonary Vascular Medicine, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China, ⁶Center of Pulmonary Vascular Disease, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China

Keywords: Myocardium, Rare disease, Strain, right ventricle

This is the first study to describe the distribution pattern of right ventricular layer-specific strain/strain rate in pulmonary arterial hypertension patients by processing cine cardiovascular MR images using a deformation registration algorithm based strain analysis software.

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Hui Zhou¹, Jing Luo¹, Huiting Zhang², and Xiaoming Bi^3
1Department of Radiology, Xiangya Hospital Central South University, Changsha, China, ²Scientific Marketing, Siemens Healthineers Ltd., Wuhan, China, ³MR Collabration, Siemens Healthineers, Los Angeles, CA, United States

Keywords: Cardiomyopathy, Myocardium, Late gadolinium enhancement

This study investigated the advantages and potential disadvantages of the MOCO-LGE sequence. The results showed that MOCO-LGE can effectively improve the image quality compared to BH-LGE. Meanwhile, the MOCO-LGE images could overestimate epicardial hyperenhancement and pericardial effusion, which might lead to overdiagnosis of myocarditis in clinical work. The study indicates that further refinement of this useful sequence may be needed.

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Irvin Teh¹, Sam Coveney¹, Richard J. Foster¹, Filip Szczepankiewicz², Samo Lasič^3,4, Henrik Lundell³, David Shelley⁵, Lars Mueller¹, Maryam Afzali^1,6, Noor Sharrack¹, Nadira Y. Yuldasheva¹, Sven Plein¹, Erica Dall'Armellina¹, and Jürgen E. Schneider^1
1Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, United Kingdom, ²Medical Radiation Physics, Clinical Sciences Lund, Lund University, Lund, Sweden, ³Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Amager and Hvidovre, Copenhagen, Denmark, ⁴Random Walk Imaging, Lund, Sweden, ⁵Leeds Teaching Hospitals Trust, Leeds, United Kingdom, ⁶Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, United Kingdom

Keywords: Myocardium, Diffusion Tensor Imaging, Time dependence, microstructure, motion compensation

Conventional spin-echo based cardiac diffusion tensor imaging (DTI) has a relatively limited range of encoding frequencies, and hence limited sensitivity to diffusion at different length scales. Here, we explored the feasibility of applying a broader range of frequencies to evaluate the effects of time-dependent diffusion. We employed diffusion encoding waveforms with up to 4^th order motion-compensation in a cohort of healthy volunteers, and report trends of decreasing MD and FA with increasing encoding frequencies. The availability of higher frequencies enhances the sensitivity of DTI to shorter length scales, and may be more greatly weighted towards diffusion properties of sub-cellular structures.

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Dongyue Si¹, Lan Cheng^2,3, Xiangchuang Kong^2,3, Rui Guo⁴, Daniel A. Herzka⁵, and Haiyan Ding^1
1Center for Biomedical Imaging Research, Department of Biomedical Engineering, Tsinghua University, Beijing, China, ²Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China, ³Hubei Province Key Laboratory of Molecular Imaging, Wuhan, China, ⁴School of Medical Technology, Beijing Institute of Technology, Beijing, China, ⁵Department of Radiology, Case Western Reserve University, Cleveland, OH, United States

Keywords: Cardiomyopathy, Tissue Characterization

Multi-parametric SAturation recovery and Variable flip Angle (mSAVA) acquires four 3D volumes with different T₁ and T₂ weightings during free-breathing to simultaneously generate whole heart T₁ and T₂ parametric maps. We proposed a fast and simple CMR protocol using pre- and post-contrast mSAVA acquisitions to additionally generate ECV maps, and bright-blood and dark-blood LGE images. mSAVA could comprehensively assess the myocardium over the whole heart within ~6+6 min in a cohort of twenty patients.

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Rui Guo¹, Dongyue Si², Yingwei Fan¹, Haina Zhang³, Haiying Ding², and Xiaoying Tang^4
1School of Medical Technology, Beijing Institute of Technology, Beijing, China, ²Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China, ³Center for Community Health Service, Peking University Health Science Center, Beijing, China, ⁴School of Life Science, Beijing Institute of Technology, Beijing, China

Keywords: Myocardium, Machine Learning/Artificial Intelligence, Cardiac T1 and T2 mapping, myocardium tissue characterization

The most used curve-fitting method for map reconstruction of the cardiovascular magnetic resonance mapping is sensitive to the initial conditions, time-consuming, and prone to fitting error. In this study, we sought to develop a deep-learning approach (DeepFittingNet) to perform T₁ and T₂ calculations for the most clinically used cardiac parametric mappings, to simplify the clinical workflow of cardiac T₁/T₂ measurements and improve the robustness. In testing, DeepFittingNet could perform T₁/T₂ estimation tasks for MOLLI, SASHA, and T₂-prep bSSFP. Compared to the curve-fitting algorithm, DeepFittingNet could improve the robustness for inversion-recovery T₁ estimation and have comparable accuracy and precision.