ISMRM25 - Bioeffect, Magnetic Field & System Imperfections

ISMRM & ISMRT Annual Meeting & Exhibition • 10-15 May 2025 • Honolulu, Hawai'i

ISMRM & ISMRT 2025 Annual Meeting & Exhibition

Digital Poster

Bioeffect, Magnetic Field & System Imperfections

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Bioeffect, Magnetic Field & System Imperfections

Digital Poster

Physics & Engineering

Wednesday, 14 May 2025

Exhibition Hall

14:30 - 15:30

Session Number: D-202

No CME/CE Credit

		Computer Number: 145 3800. Radial Approach for Dipole Inversion (RADI): A deep learning-based 2D approach to quantitative susceptibility mapping View Presentation Video T. Wataya, S. Fuchibe, H. Takahashi, H. Kato, M. Hori, S. Kido, N. Tomiyama, Y. Watanabe Shiga University of Medical Science, Otsu, Japan Impact: We propose a 2D deep learning-based approach to the dipole inversion in QSM called “Radial Approach for Dipole Inversion (RADI)”. RADI can accelerate the calculation process of QSM and reduce artifacts that appear in conventional methods.
		Computer Number: 146 3801. Electromagnetic Halbach Cylinder to Investigate Magnetic Field Effects on Cellular Metabolism View Presentation Video D. Bowen, O. Benavides, A. Walsh, M. McDougall Texas A&M University, College Station, United States Impact: The electromagnetic Halbach array produces a controllable and homogeneous field orthogonal to a fluorescent light source, allowing for further investigation of magnetic field effects on cellular metabolism.
		Computer Number: 147 3802. Investigation of optimal NMR-on-a-chip sensor positions for monitoring physiological magnetic field changes View Presentation Video F. Bschorr, T. Hüfken, T. Lobmeyer, F. Dreyer, J. Schüle, J. Zhao, J. Anders, V. Rasche Ulm University Medical Center, Ulm, Germany Impact: In this work, different locations for contactless sensing of physiological motion with a NMR-on-a-chip sensor around the torso were investigated. It is shown that both contributions might be separated with either bandpass filtering or principal component analysis.
		Computer Number: 148 3803. Evaluating and Predicting Non-linear Acoustics Using Multi-Axis Gradient Variations and Convolutional Neural Networks View Presentation Video B. Jolicoeur, A. Alexander, S. Kecskemeti, K. Johnson Univeristy of Wisconsin-Madison, Madison, United States Impact: This study challenges existing linear acoustic models in MRI, offering a more complex and accurate understanding of SPL dynamics. With improved acoustic noise estimation, more informed choices can be made when developing pulse sequences with reduced SPL.
		Computer Number: 149 3804. Validity of Transfer Function (TF) Model for Partial in Partial out (PIPO) Device under Different MR Radio Frequencies View Presentation Video Z. Zuo, M. Z. Islam, J. Zheng, H. Jeong, A. Kumar, J. Chen University of Houston, Houston, United States Impact: The reliability of TF method characterization of PIPO devices is confirmed for frequencies below 128 MHz (3T) and TF method becomes error-proned at very high field MRI frequencies.
		Computer Number: 150 3805. B1 Correction for MRSI using Unified Subspace Model for Multi-Center Study View Presentation Video Z. Meng, Y. Zhao, C. Xu, Y. Li, W. Jin, B. Bo, Y. Tang, W. Tang, T. Wang, Z-P Liang, Y. Li Shanghai Jiao Tong University, Shanghai, China Impact: The proposed $$$B_{1}$$$ correction method will enhance the quantitative accuracy of metabolite measurements and thus enhance the robustness and practical usefulness of MRSI in clinical applications.
		Computer Number: 151 3806. METHOD for CENTER FREQUENCY CALIBRATION USING STIR ON/OFF SPECTRA View Presentation Video A. Wheaton Canon Medical Research USA, Mayfield Heights, United States Impact: Accurate and consistent center frequency calibration is critical for reliable image quality. The proposed method is robust to a wide range of clinical conditions and anatomies, including tissues with high off-resonance (e.g. cervical spine) or high fat content (e.g. breast).
		Computer Number: 152 3807. Energy Consumption of MRI Systems: An Evaluation of the Relative Contribution of Chillers View Presentation Video A. Martin, S. Dai, P. Su, A. Becker, V. Deshpande, S. Gruebel, C. Hess, S. Woolen UCSF, San Francisco, United States Impact: Energy consumption by MRI systems is an important contributor to the carbon footprint of health care. A clear understanding of the relative contribution that system cooling plays will help develop impactful ways to improve MRI energy efficiency.
		Computer Number: 153 3808. Towards Establishing Comparability in Scanner Stability Measurements for Quality Assurance View Presentation Video Q. Chen, N. Wehkamp, C. Wan, P. Hucker, M. Büchert, S. Littin, J-F Nielsen, M. Zaitsev Division of Medical Physics, Department of Radiology, University Medical Center Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany Impact: This work underscores the importance of controlling various factors in scanner stability measurements to ensure comparability for quality assurance, particularly in longitudinal, cross-vendor, multi-center fMRI studies. Furthermore, we provide practical recommendations for establishing standardized quality assurance protocols.
		Computer Number: 154 3809. Gradient Waveform Pre-emphasis using Deep Neural Network View Presentation Video G. Dan, Z. Zhong, Q. Liu, J. Xu United Imaging Healthcare North America, Houston, United States Impact: This method enhances MRI image quality by reducing artifacts and improving spatial accuracy through gradient waveform pre-emphasis using deep learning.
		Computer Number: 155 3810. Improved bias field correction by combining Deep Learning and pre-scan information View Presentation Video T. Krieg, W. Liu, P. Liebig, D. Grodzki, L. Pfaff, A. Maier, T. Hülnhagen Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany Impact: This research addresses MRI intensity inhomogeneity issues by combining deep learning models and additional context information. The approach improves image quality and holds the promise to enhance bias field correction and potentially reduce diagnostic errors with minimal processing overhead.
		Computer Number: 156 3811. Geometric Fidelity of a Head-Specific 0.5T MR System: An Inter-Scanner Reproducibility Study View Presentation Video C. Wiens, C. Harris, J. Marduhaev, I. Connell Synaptive Medical, Toronto, Canada Impact: This study’s impact consists of characterizing the geometric fidelity of a head-specific, small-footprint MRI system and assessing its variance across multiple sites.
		Computer Number: 157 3812. Real-world Performance of Clinical MRI Faraday Cages View Presentation Video J. Small, D. Price, J. Martin, A. Wright, A. Price, J. Ansell, E. Stamou, A. Kruezi, S. Shah, C. O'Brien, H. Rogers, F. Padormo, G. Charles-Edwards Guy's & St. Thomas' NHS Foundation Trust, London, United Kingdom Impact: This work shows that having an independent check of RF cage performance after scanner installation can be helpful if Faraday cage attenuation has been reduced during the installation process.
		Computer Number: 158 3813. EPI gradient trajectory noise measurement and simulation of related artifacts View Presentation Video N. Wehkamp, Q. Chen, P. Hucker, J. Fischer, S. Littin, J-F Nielsen, M. Zaitsev University Medical Center Freiburg, Freiburg, Germany Impact: Enhance understanding of gradient related artifact sources in fMRI neuroimaging studies. Our open-source simulation routine allows to partially reproduce artifacts from dynamic zero and first-order trajectory deviations. The improved understanding lays the groundwork for development of more reliable future MRI-systems.

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