ISMRM25 - Optimized Sampling Patterns & Tailored Forward Models

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

Optimized Sampling Patterns & Tailored Forward Models

Oral

Acquisition & Reconstruction

Thursday, 15 May 2025

313B

15:30 - 17:30

Moderators: Hongyu An & Catherine Moran

Session Number: O-04

No CME/CE Credit

15:30		1363. Field-Correcting GRAPPA (FCG): a generalizable technique to correct spatiotemporal varying odd-even phase errors in EPI, SMS-EPI and 3D-EPI PDF Poster View Presentation Video N. Wang, D. Abraham, H. Wu, C. Liao, X. Cao, J. Polimeni, R. Huber, Q. Liu, L. Ning, Y. Rathi, N. Abad, B. Yang, A. Kerr, C-F Westin, K. Setsompop Stanford University, Stanford, United States Impact: A field-correcting GRAPPA (FCG) technique for high-quality correction of odd-even phase errors in EPI and a flexible pipeline for separate data correction and reconstruction was developed and validated, unleashing EPI applications for higher undersampling, stronger gradient systems, and higher fields.
15:42		1364. Multi-shot Dual-Polarity GRAPPA for Nyquist Ghost and Fuzzy Ripple Artifact Correction of Echo-Planar Imaging View Presentation Video J. Zhang, T. Qian, B. Zhang, Q. Li, W. Liu Qiyuan Lab, Beijing, China Impact: The proposed method can correct or reduce two common artifacts in sub-millimeter fMRI without reducing the temporal resolution. It may help to improve the image quality and stability of high-resolution fMRI, especially in ultra-high-field systems.
15:54		1365. Robust Nyquist ghost correction for high-resolution EPI using multishot dual-polarity GRAPPA reconstruction View Presentation Video Y. Jiang, Y. Jun, Q. Liu, W. Zhong, Y. Rathi, H. Guo, B. Bilgic Tsinghua University, Beijing, China Impact: The proposed msDPG method provides robust Nyquist ghost correction for multishot EPI, effectively suppressing ghosts on modern scanners and facilitating seamless integration with other advanced reconstruction techniques.
16:06		1366. A Novel k-Space Model for Non-Cartesian Reconstruction View Presentation Video C-C Chan, J. Haldar University of Southern California, Los Angeles, United States Impact: We identify previously-unknown issues with the most popular (decades-old) approach to model-based non-Cartesian MRI reconstruction, and propose a new modeling approach that resolves these issues and offers better modeling accuracy, reduced susceptibility to artifacts, and greater computational efficiency.
16:18		1367. QuickSamp: Towards simple, real-time-optimized Sampling Patterns for 3D Accelerated MRI View Presentation Video J. Bae, C. Alkan, S. Vasanawala, J. Pauly, K. Setsompop Stanford University, Stanford, United States Impact: Our method simplifies the complexity and drastically improve the speed of sampling pattern generation using only a few parameters. This eliminates extensive retraining, offering a practical alternative for optimizing MRI acquisition across different configurations and use cases.
16:30		1368. Joint Optimization of Sampling Pattern and Image Reconstruction for 3D Dual-Echo Spoiled Gradient Echo MRI View Presentation Video A. Sun, C. Alkan, M. Alley, Y. Wu, C. Zhang, A. Syed, J. Pauly, D. Ennis, S. Vasanawala Stanford University, Stanford, United States Impact: This work offers a novel approach to accelerating dual-echo MRI by enhancing image quality through joint sampling and reconstruction optimization. Our method provides valuable insights into sampling pattern design and reconstruction strategies, potentially broadening clinical applications of fast multi-echo MRI.
16:42		1369. Controlling sharpness, SNR and SAR for 3D fast spin echo measurements at 7T by end-to-end learning View Presentation Video P. Dawood, M. Blaimer, J. Herrler, P. Liebig, S. Weinmüller, S. Malik, P. M. Jakob, M. Zaiss University Hospital Erlangen, Erlangen, Germany Impact: This work paves the way to the flexible tuning of the PSF- or SNR-like flavour of dedicated variable flip angles at 7T to enhance visibility of small stuctures or SNR in 3D fast spin-echo sequences with very long echo trains.
16:54		1370. MR fingerprinting with implicit neural representation (FINR) for free-breathing 3D whole-liver water T1, water T2, fat fraction, and R2* mapping View Presentation Video C. Li, J. Li, J. Zhang, E. Solomon, A. Dimov, P. Spincemaille, T. Nguyen, M. Prince, Y. Wang Weill Cornell Medicine, New York, United States Impact: Our work enables 3D whole-liver quantification of water T1, water T2, PDFF, and R2* in a single free-breathing MR acquisition. It also provides a novel solution to reconstruct 5D MRI images (3D spatial + contrast + motion dimension) using INR.
17:06		1371. Laterally Oscillating Trajectory for Undersampling Slices (LOTUS) View Presentation Video M. Sothynathan, P. Dubovan, C. Baron Western University, London, Canada Impact: We introduce a k-space trajectory that enables higher slice accelerations compared to traditional approaches, especially compared to Blipped-CAIPI EPI. This may be useful to reduce scan times for advanced diffusion MRI acquisitions or improve temporal resolution of functional MRI.
17:18		1372. Instead of just undersampling, sample more and faster: 0.6mm isotropic MPRAGE at 7T in under 2 minutes View Presentation Video T. Yu, J. Philippe, N. Montemayor, E. Sleight, A. Klauser, L. Bacha, T. Di Noto, B. Maréchal, D. Nickel, P. Liebig, T. Kober, T. Hilbert, G. F. Piredda Siemens Healthineers International AG, Lausanne, Switzerland Impact: This study demonstrates the effectiveness of using deep learning image reconstruction in combination with optimized sequence parameters for scan speed to further accelerate a clinical MPRAGE acquisition, in contrast to simply increasing undersampling factors.

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