Purpose: Simultaneous multislice (SMS) acquisitions play an important role in the challenge of increasing single-shot imaging speed. We show that sensitivity encoding in two spatial dimensions (two-dimensional sensitivity encoding [2D-SENSE]) can be used to reconstruct SMS acquisitions with periodic but otherwise arbitrary undersampling patterns.
Theory And Methods: By adopting a 3D k-space representation of the SMS sampling process, the accelerated in-plane and slice-encoding directions form a 2D-reconstruction problem that is equivalent to volumetric controlled aliasing in parallel imaging results in higher acceleration (CAIPIRINHA). 2D-SENSE does not otherwise distinguish between standard volumetric and SMS imaging with arbitrary CAIPIRINHA sampling.
Results: Use of the SENSE algorithm is demonstrated for in vivo brain data obtained with blipped-CAIPRINHA sampling in 2D SMS-echo planar imaging (EPI) and rapid acquisition with relaxation enhancement (RARE) acquisitions as well as 3D-EPI with various in-plane and through-plane acceleration factors and CAIPIRINHA shifts. The proposed SENSE reconstruction works for any combination of SMS-factor and CAIPIRINHA shift by the addition of "dummy slices" that allow for noninteger undersampling in the slice direction. Images with commonly used slice-generalized autocalibrating partially parallel acquisitions reconstruction are shown for reference.
Conclusion: SENSE is conceptually simple and provides a one-step reconstruction along both undersampled dimensions. It also provides a contrast-independent parallel imaging reconstruction for SMS.
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http://dx.doi.org/10.1002/mrm.25519 | DOI Listing |
Dentomaxillofac Radiol
January 2025
Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100730, China.
Objectives: To compare integrated slice-specific dynamic shimming (iShim) and simultaneous multi-slice (SMS) readout-segmented echo-planar imaging (RESOLVE) for diffusion-weighted imaging (DWI) of malignant head and neck tumours.
Methods: In this prospective study, 45 patients with malignant head and neck lesions underwent iShim- and SMS-RESOLVE imaging with two b-values (0, 800 s/mm2) at 3 T. Subjective image quality scores (lesion distortion, signal loss, fat saturation, and artefacts), quantitative lesion distortion, quantitative image quality [signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and SNR efficiency], ADC values, and total acquisition times of iShim- and SMS-RESOLVE imaging were evaluated and compared.
J Magn Reson Imaging
December 2024
Utah Center for Advanced Imaging Research (UCAIR), Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, Utah, USA.
Background: Modified Look-Locker imaging (MOLLI) T1 mapping sequences are acquired during breath-holding and require ECG gating with consistent R-R intervals, which is problematic for patients with atrial fibrillation (AF). Consequently, there is a need for a free-breathing and ungated framework for cardiac T1 mapping.
Purpose: To develop and evaluate a free-breathing ungated radial simultaneous multi-slice (SMS) cardiac T1 mapping (FURST) framework.
Br J Radiol
December 2024
Department of Radiology, West China Hospital, Sichuan University, Chengdu 610041, China.
Objectives: To investigate the diagnostic performance of simultaneous multislice diffusion-weighted imaging (SMS-DWI) in differentiating malignant and benign breast lesions, and compare it with conventional single shot and readout segmented echo planar imaging without the SMS technique.
Methods: The literature search was performed in PubMed, Embase, and Web of Science to identify comparative studies reporting the diagnostic performance of SMS-DWI and conventional DWI in patients with breast lesions. Histopathological analysis was used as a reference standard for malignant breast lesions.
Cureus
November 2024
Department of Joint Research in Advanced Medicine for Electromagnetic Engineering, Shimane University, Izumo, JPN.
NMR Biomed
January 2025
Department of Radiology, Case Western Reserve University, Cleveland, Ohio, USA.
Magnetic Resonance Fingerprinting (MRF) can be accelerated with simultaneous multislice (SMS) imaging for joint T and T quantification. However, the high inter-slice and in-plane acceleration in SMS-MRF causes severe aliasing artifacts, limiting the multiband (MB) factors to typically 2 or 3. Deep learning has demonstrated superior performance compared to the conventional dictionary matching approach for single-slice MRF, but its effectiveness in SMS-MRF remains unexplored.
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