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Rachel L. Eddy^1,2, Marrissa J McIntosh³, Alexander M Matheson³, David G McCormack⁴, Christopher Licskai⁴, and Grace Parraga^5
1Centre for Heart Lung Innovation, St. Paul’s Hospital, University of British Columbia, Vancouver, BC, Canada, ²Division of Respiratory Medicine, Department of Medicine, University of British Columbia, Vancouver, BC, Canada, ³Robarts Research Institute, Department of Medical Biophysics, Western University, London, ON, Canada, ⁴Division of Respirology, Department of Medicine, Western University, London, ON, Canada, ⁵Robarts Research Institute, Department of Medical Biophysics; Division of Respirology, Department of Medicine, Western University, London, ON, Canada

Keywords: YIA, Lung

Pulmonary functional MRI measurements have never been evaluated for the generation of imaging-based asthma patient clusters, although computed tomography (CT)-based clusters have been determined. Here we investigated hyperpolarized ¹²⁹XeMRI ventilation in combination with CT airway measurements in 45 patients with asthma and identified 4 phenotypic clusters with distinct structure-function and clinical characteristics. Our results revealed a novel cluster of patients only distinguished by MRI ventilation measurements, underscoring the utility of MRI to discriminate airway pathologies in asthma. Imaging-based clusters of asthma provide novel structure-function insights that may be exploited in future studies and challenge current clinical paradigms for asthma phenotyping.

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Taylor Froelich¹, Lance DelaBarre¹, Paul Wang², Jerahmie Radder¹, Efrain Torres², and Michael Garwood^2
1Center for Magnetic Resonance Research & Department of Radiology, University of Minnesota, Minneapolis, MN, United States, ²Center for Magnetic Resonance Research & Department of Radiology; Department of Biomedical Engineering, University of Minnesota, Minneapolis, MN, United States

Keywords: YIA, Gradients

Recent efforts to expand access to MRI have focused on low-cost, portable MRI systems that eliminate pulsed B₀ gradients in favor of radio-frequency imaging techniques. In this work we present a new multi-echo version of FREE (Frequency-modulated Rabi Encoded Echoes) that utilizes nonlinear B₁⁺ gradients to perform spatial encoding. This new technique leverages the acceleration of conventional FSE approaches and nonlinear gradients to eliminate the need for conventional B₀ gradients while also achieving very high spatial resolution.

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Ruiqi Geng¹, Collin J. Buelo¹, Mahalakshmi Sundaresan², Jitka Starekova³, Nikolaos Panagiotopoulos^3,4, Thekla Helene Oechtering^3,4, Edward M. Lawrence³, Marcin Ignaciuk³, Scott B Reeder⁵, and Diego Hernando^6
1Departments of Medical Physics, Radiology, University of Wisconsin, Madison, Madison, WI, United States, ²Department of Electrical and Computer Engineering, University of Wisconsin, Madison, Madison, WI, United States, ³Department of Radiology, University of Wisconsin, Madison, Madison, WI, United States, ⁴Department of Radiology and Nuclear Medicine, Universität zu Lübeck, Lübeck, Germany, ⁵Departments of Medical Physics, Radiology, Medicine, Emergency Medicine, Biomedical Engineering, University of Wisconsin, Madison, Madison, WI, United States, ⁶Departments of Medical Physics, Radiology, Electrical and Computer Engineering, Biomedical Engineering, University of Wisconsin, Madison, Madison, WI, United States

Keywords: YIA, Liver

This work developed a novel automated AI-based method for liver image prescription from a localizer and evaluated it in a large retrospective patient cohort (1,039 patients for training/testing), across pathologies, field strengths, and against radiologists’ inter-reader reproducibility performance. AI-based 3D axial prescription achieved a S/I shift of <2.3 cm compared to manual prescription for 99.5% of test dataset. The AI method performed well across all sub-cohorts and better in 3D axial prescription than radiologists’ inter-reader reproducibility performance. We successfully implemented the AI method on a clinical MR system, which demonstrated robust performance across localizer sequences.

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Valerie Klein^1,2,3, Jaume Coll-Font^2,3,4, Livia Vendramini², Donald Staney², Mathias Davids^2,3, Natalie G. Ferris^2,5, Lothar R. Schad^1,6, David E. Sosnovik^2,3,4,5, Christopher Nguyen^7,8,9, Lawrence L Wald^2,3,5, and Bastien Guérin^2,3
1Computer Assisted Clinical Medicine, Medical Faculty Mannheim, Heidelberg University, Heidelberg, Germany, ²A. A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, United States, ³Harvard Medical School, Boston, MA, United States, ⁴Cardiovascular Research Center, Cardiology Division, Massachusetts General Hospital, Charlestown, MA, United States, ⁵Harvard-MIT Division of Health Sciences and Technology, Cambridge, MA, United States, ⁶Mannheim Institute for Intelligent Systems in Medicine, Medical Faculty Mannheim, Heidelberg University, Heidelberg, Germany, ⁷Cardiovascular Innovation Research Center, Heart Vascular & Thoracic Institute, Cleveland Clinic, Cleveland, OH, United States, ⁸Department of Radiology, Imaging Institute, Cleveland Clinic, Cleveland, OH, United States, ⁹Department of Biomedical Engineering, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, United States

Keywords: YIA, Heart

High-amplitude gradient systems can surpass the IEC regulatory limit for cardiac stimulation (CS), which is based on animal electrostimulation data and simplified electromagnetic modeling. We assess CS in MRI by performing the first cardiac magnetostimulation threshold measurements in pigs, the primary animal model of the human cardiovascular system. We use the measurements to validate a detailed CS modeling pipeline applicable to both pigs and humans. Experimental thresholds and predictions in porcine-specific models agree within 19% NRMSE. CS modeling in a detailed human body model indicates that CS thresholds of the Connectome gradient are ~25-fold greater than the IEC CS limit.

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Philip Meng-en Lee¹, Hsin-Yu Chen², Jeremy W. Gordon², Zhen J Wang², Robert Bok², Ralph Hashoian³, Yaewon Kim², Xiaoxi Liu², Tanner Nickles¹, Kiersten Cheung², Francesca De Las Alas², Heather Daniel², Peder EZ Larson¹, Cornelius von Morze⁴, Daniel B Vigneron¹, and Michael A Ohliger^2,5
1UC Berkeley-UCSF Graduate Program in Bioengineering; Dept. of Radiology & Biomedical Imaging, University of California, San Francisco, San Francisco, CA, United States, ²Department of Radiology & Biomedical Imaging, University of California, San Francisco, San Francisco, CA, United States, ³Clinical MR Solutions, Brookfield, WI, United States, ⁴Mallinckrodt Institute of Radiology, Washington University in St. Louis, St. Louis, MO, United States, ⁵Department of Radiology and Biomedical Imaging, Zuckerberg San Francisco General Hospital and Trauma Center, San Francisco, CA, United States

Keywords: YIA, Hyperpolarized MR (Non-Gas), Body - Liver

Whole-abdomen imaging with hyperpolarized ¹³C is challenging due to B₀ and B₁ inhomogeneities, respiratory motion, and broad spatial coverage. There is also little baseline data about healthy metabolism in abdominal organs. We developed and describe here a reliable imaging method to overcome these challenges, enabling metabolic imaging of the entire abdomen in a series of healthy volunteers. We present observed conversation rates of HP [1-¹³C]pyruvate to lactate and alanine in key organs such as the liver, kidneys, pancreas, and spleen. Methods established here set a firm foundation for investigating a broad spectrum of metabolic and neoplastic abnormalities in the liver.

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Zengping Lin¹, Ziyu Meng¹, Tianyao Wang², Rong Guo^3,4, Yibo Zhao^3,5, Yudu Li^3,5, Bin Bo¹, Yue Guan¹, Jun Liu², Hong Zhou⁶, Xin Yu⁷, David J Lin⁸, Zhi-Pei Liang^3,5, Parashkev Nachev⁹, and Yao Li^1
1School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China, ²Radiology Department, Shanghai Fifth People's Hospital, Fudan University, Shanghai, China, ³Beckman Institute for Advanced Science & Technology, University of Illinois at Urbana-Champaign, Urbana, IL, United States, ⁴Siemens Medical Solutions USA, Inc, Urbana, IL, United States, ⁵Department of Electrical & Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, IL, United States, ⁶Department of Radiology, The First Affiliated Hospital of South China of University, South China of University, Hengyang, China, ⁷Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, United States, ⁸Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States, ⁹Institute of Neurology, University College London, London, United Kingdom

Keywords: YIA, Ischemia

Neurometabolite concentrations provide a direct index of infarct progression in stroke, but their relationship with stroke onset time remains unclear. Using a fast high-resolution 3D MRSI technique, this study assessed the temporal dynamics of N-acetylaspartate (NAA), creatine, choline, and lactate and estimated their value in predicting early (<6 hours) vs late (6–24 hours) hyperacute ischemic stroke groups. We found that lesional NAA and creatine was reduced from acute to subacute stroke patients and NAA level was inversely related to onset time in hyperacute patients. The changes in neurometabolite levels provided good discrimination between patients for early & late hyperacute time windows.

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Gian Franco Piredda^1,2,3, Samuele Caneschi¹, Tom Hilbert^1,4,5, Gabriele Bonanno^1,6,7, Arun Joseph^1,6,7, Karl Egger⁸, Jessica Peter⁹, Stefan Klöppel⁹, Elisabeth Jehli^10,11, Matthias Grieder¹⁰, Johannes Slotboom¹², David Seiffge¹³, Martina Goeldlin¹³, Robert Hoepner¹³, Tom Willems¹⁴, Serge Vulliemoz¹⁵, Margitta Seeck¹⁵, Punith B. Venkategowda¹⁶, Ricardo A. Corredor Jerez^1,4,5, Bénédicte Maréchal^1,4,5, Jean-Philippe Thiran^4,5, Roland Weist^6,12, Tobias Kober^1,4,5, and Piotr Radojewski^6,12
1Advanced Clinical Imaging Technology, Siemens Healthineers International AG, Lausanne, Switzerland, ²Human Neuroscience Platform, Fondation Campus Biotech Geneva, Geneva, Switzerland, ³CIBM-AIT, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland, ⁴Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland, ⁵LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland, ⁶Translational Imaging Center (TIC), Swiss Institute for Translational and Entrepreneurial Medicine, Bern, Switzerland, ⁷Magnetic Resonance Methodology, Institute of Diagnostic and Interventional Neuroradiology, University of Bern, Bern, Switzerland, ⁸Department of Neuroradiology, Faculty of Medicine, University of Freiburg, Freiburg, Germany, ⁹University Hospital of Old Age Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland, ¹⁰Translational Research Center, University Hospital of Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland, ¹¹Department of Neurosurgery, University Hospital of Zurich, Zurich, Switzerland, ¹²Support Center for Advanced Neuroimaging, Institute for Diagnostic and Interventional Neuroradiology, Inselspital, University of Bern, Bern, Switzerland, ¹³Department of Neurology, University Hospital of Bern, University of Bern, Bern, Switzerland, ¹⁴Institute of Psychology, University of Bern, Geneva, Switzerland, ¹⁵EEG & Epilepsy Unit, Department of Clinical Neurosciences, Geneva University Hospitals & Faculty of Medicine, Geneva, Switzerland, ¹⁶Siemens Healthcare Pvt. Ltd., Bangalore, India

Keywords: YIA, Tissue Characterization, Acquisition & Analysis, Quantitative Imaging, Ultra-high field MRI

Databases of normative values from healthy tissues are needed to leverage the improved comparability and hardware independence of quantitative MRI, and thus enable patient-specific detection of abnormalities in visual interpretation. Here, we present normative atlases of T₁ relaxation times in the brain at 3T (1 mm isotropic) and 7T (0.6 mm isotropic) from two large cohorts of healthy subjects. The atlases were tested in single‐subject comparisons for detection of abnormal relaxation times in patients scanned at both field strengths. The presented detection of subtle alterations not visible in conventional MRI showed the clinical potential of the method.

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Xingfeng Shao¹, Chenyang Zhao¹, Qinyang Shou¹, Keith S St Lawrence^2,3, and Danny JJ Wang^1
1Laboratory of FMRI Technology (LOFT), Mark & Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States, ²Lawson Health Research Institute, London, ON, Canada, ³Department of Medical Biophysics, Western University, London, ON, Canada

Keywords: YIA, Diffusion/other diffusion imaging techniques, Blood-brain barrier, water exchange, diffusion weighted perfusion imaging

We developed an innovate pulse sequence and acquired diffusion weighted pCASL signals from a wide range of PLDs with improved SNR and spatial resolution. A 3-compartment single-pass approximation (SPA) model, which includes an additional venous compartment, was proposed to capture the full dynamics of the labeled blood bolus passing through capillaries while exchanging into tissue space before flowing into venules, and a LRL method was proposed for individual kw quantification.