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Huo Z, Wen K, Luo Y, Neji R, Kunze KP, Ferreira PF, Pennell DJ, Scott AD, Nielles-Vallespin S. Referenceless Nyquist ghost correction outperforms standard navigator-based method and improves efficiency of in vivo diffusion tensor cardiovascular magnetic resonance. Magn Reson Med 2024; 91:2403-2416. [PMID: 38263908 DOI: 10.1002/mrm.30012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2023] [Revised: 11/20/2023] [Accepted: 12/28/2023] [Indexed: 01/25/2024]
Abstract
PURPOSE The study aims to assess the potential of referenceless methods of EPI ghost correction to accelerate the acquisition of in vivo diffusion tensor cardiovascular magnetic resonance (DT-CMR) data using both computational simulations and data from in vivo experiments. METHODS Three referenceless EPI ghost correction methods were evaluated on mid-ventricular short axis DT-CMR spin echo and STEAM datasets from 20 healthy subjects at 3T. The reduced field of view excitation technique was used to automatically quantify the Nyquist ghosts, and DT-CMR images were fit to a linear ghost model for correction. RESULTS Numerical simulation showed the singular value decomposition (SVD) method is the least sensitive to noise, followed by Ghost/Object method and entropy-based method. In vivo experiments showed significant ghost reduction for all correction methods, with referenceless methods outperforming navigator methods for both spin echo and STEAM sequences at b = 32, 150, 450, and 600 smm - 2 $$ {\mathrm{smm}}^{-2} $$ . It is worth noting that as the strength of the diffusion encoding increases, the performance gap between the referenceless method and the navigator-based method diminishes. CONCLUSION Referenceless ghost correction effectively reduces Nyquist ghost in DT-CMR data, showing promise for enhancing the accuracy and efficiency of measurements in clinical practice without the need for any additional reference scans.
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Affiliation(s)
- Zimu Huo
- CMR Unit, Royal Brompton Hosptial, Guy's and St Thomas' NHS Foundation Trust, London, UK
- Department of Bioengineering, Imperial College London, London, UK
| | - Ke Wen
- CMR Unit, Royal Brompton Hosptial, Guy's and St Thomas' NHS Foundation Trust, London, UK
- NHLI, Imperial College London, London, UK
| | - Yaqing Luo
- CMR Unit, Royal Brompton Hosptial, Guy's and St Thomas' NHS Foundation Trust, London, UK
- NHLI, Imperial College London, London, UK
| | - Radhouene Neji
- MR Research Collaborations, Siemens Healthcare Limited, Camberley, UK
| | - Karl P Kunze
- MR Research Collaborations, Siemens Healthcare Limited, Camberley, UK
| | - Pedro F Ferreira
- CMR Unit, Royal Brompton Hosptial, Guy's and St Thomas' NHS Foundation Trust, London, UK
- NHLI, Imperial College London, London, UK
| | - Dudley J Pennell
- CMR Unit, Royal Brompton Hosptial, Guy's and St Thomas' NHS Foundation Trust, London, UK
- NHLI, Imperial College London, London, UK
| | - Andrew D Scott
- CMR Unit, Royal Brompton Hosptial, Guy's and St Thomas' NHS Foundation Trust, London, UK
- NHLI, Imperial College London, London, UK
| | - Sonia Nielles-Vallespin
- CMR Unit, Royal Brompton Hosptial, Guy's and St Thomas' NHS Foundation Trust, London, UK
- NHLI, Imperial College London, London, UK
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Pan Z, Ma X, Dai E, Auerbach EJ, Guo H, Uğurbil K, Wu X. Reconstruction for 7T high-resolution whole-brain diffusion MRI using two-stage N/2 ghost correction and L1-SPIRiT without single-band reference. Magn Reson Med 2023; 89:1915-1930. [PMID: 36594439 PMCID: PMC9992311 DOI: 10.1002/mrm.29573] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2022] [Revised: 11/28/2022] [Accepted: 12/19/2022] [Indexed: 01/04/2023]
Abstract
PURPOSE To combine a new two-stage N/2 ghost correction and an adapted L1-SPIRiT method for reconstruction of 7T highly accelerated whole-brain diffusion MRI (dMRI) using only autocalibration scans (ACS) without the need of additional single-band reference (SBref) scans. METHODS The proposed ghost correction consisted of a 3-line reference approach in stage 1 and the reference-free entropy method in stage 2. The adapted L1-SPIRiT method was formulated within the 3D k-space framework. Its efficacy was examined by acquiring two dMRI data sets at 1.05-mm isotropic resolutions with a total acceleration of 6 or 9 (i.e., 2-fold or 3-fold slice and 3-fold in-plane acceleration). Diffusion analysis was performed to derive DTI metrics and estimate fiber orientation distribution functions (fODFs). The results were compared with those of 3D k-space GRAPPA using only ACS, all in reference to 3D k-space GRAPPA using both ACS and SBref (serving as a reference). RESULTS The proposed ghost correction eliminated artifacts more robustly than conventional approaches. Our adapted L1-SPIRiT method outperformed 3D k-space GRAPPA when using only ACS, improving image quality to what was achievable with 3D k-space GRAPPA using both ACS and SBref scans. The improvement in image quality further resulted in an improvement in estimation performances for DTI and fODFs. CONCLUSION The combination of our new ghost correction and adapted L1-SPIRiT method can reliably reconstruct 7T highly accelerated whole-brain dMRI without the need of SBref scans, increasing acquisition efficiency and reducing motion sensitivity.
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Affiliation(s)
- Ziyi Pan
- Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China
| | - Xiaodong Ma
- Center for Magnetic Resonance Research, Radiology, Medical School, University of Minnesota, Minneapolis, MN, United States
| | - Erpeng Dai
- Department of Radiology, Stanford University, Stanford, CA, United States
| | - Edward J. Auerbach
- Center for Magnetic Resonance Research, Radiology, Medical School, University of Minnesota, Minneapolis, MN, United States
| | - Hua Guo
- Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China
| | - Kâmil Uğurbil
- Center for Magnetic Resonance Research, Radiology, Medical School, University of Minnesota, Minneapolis, MN, United States
| | - Xiaoping Wu
- Center for Magnetic Resonance Research, Radiology, Medical School, University of Minnesota, Minneapolis, MN, United States
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Li S, Wu J, Ma L, Cai S, Cai C. A simultaneous multi-slice T 2 mapping framework based on overlapping-echo detachment planar imaging and deep learning reconstruction. Magn Reson Med 2022; 87:2239-2253. [PMID: 35014727 DOI: 10.1002/mrm.29128] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2021] [Revised: 11/29/2021] [Accepted: 11/29/2021] [Indexed: 12/16/2022]
Abstract
PURPOSE Quantitative MRI (qMRI) is of great importance to clinical medicine and scientific research. However, most qMRI techniques are time-consuming and sensitive to motion, especially when a large 3D volume is imaged. To accelerate the acquisition, a framework is proposed to realize reliable simultaneous multi-slice T2 mapping. METHODS The simultaneous multi-slice T2 mapping framework is based on overlapping-echo detachment (OLED) planar imaging (dubbed SMS-OLED). Multi-slice overlapping-echo signals were generated by multiple excitation pulses together with echo-shifting gradients. The signals were excited and acquired with a single-channel coil. U-Net was used to reconstruct T2 maps from the acquired overlapping-echo image. RESULTS Single-shot double-slice and two-shot triple-slice SMS-OLED scan schemes were designed according to the framework for evaluation. Simulations, water phantom, and in vivo rat brain experiments were carried out. Overlapping-echo signals were acquired, and T2 maps were reconstructed and compared with references. The results demonstrate the superior performance of our method. CONCLUSION Two slices of T2 maps can be obtained in a single shot within hundreds of milliseconds. Higher quality multi-slice T2 maps can be obtained via multiple shots. SMS-OLED provides a lower specific absorption rate scheme compared with conventional SMS methods with a coil with only a single receiver channel. The new method is of potential in dynamic qMRI and functional qMRI where temporal resolution is vital.
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Affiliation(s)
- Simin Li
- Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, Xiamen, China
| | - Jian Wu
- Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, Xiamen, China
| | - Lingceng Ma
- Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, Xiamen, China
| | - Shuhui Cai
- Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, Xiamen, China
| | - Congbo Cai
- Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, Xiamen, China
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What's New and What's Next in Diffusion MRI Preprocessing. Neuroimage 2021; 249:118830. [PMID: 34965454 PMCID: PMC9379864 DOI: 10.1016/j.neuroimage.2021.118830] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2021] [Revised: 10/26/2021] [Accepted: 12/15/2021] [Indexed: 02/07/2023] Open
Abstract
Diffusion MRI (dMRI) provides invaluable information for the study of tissue microstructure and brain connectivity, but suffers from a range of imaging artifacts that greatly challenge the analysis of results and their interpretability if not appropriately accounted for. This review will cover dMRI artifacts and preprocessing steps, some of which have not typically been considered in existing pipelines or reviews, or have only gained attention in recent years: brain/skull extraction, B-matrix incompatibilities w.r.t the imaging data, signal drift, Gibbs ringing, noise distribution bias, denoising, between- and within-volumes motion, eddy currents, outliers, susceptibility distortions, EPI Nyquist ghosts, gradient deviations, B1 bias fields, and spatial normalization. The focus will be on “what’s new” since the notable advances prior to and brought by the Human Connectome Project (HCP), as presented in the predecessing issue on “Mapping the Connectome” in 2013. In addition to the development of novel strategies for dMRI preprocessing, exciting progress has been made in the availability of open source tools and reproducible pipelines, databases and simulation tools for the evaluation of preprocessing steps, and automated quality control frameworks, amongst others. Finally, this review will consider practical considerations and our view on “what’s next” in dMRI preprocessing.
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Sanderink WBG, Teuwen J, Appelman L, Moy L, Heacock L, Weiland E, Karssemeijer N, Baltzer PAT, Sechopoulos I, Mann RM. Comparison of simultaneous multi-slice single-shot DWI to readout-segmented DWI for evaluation of breast lesions at 3T MRI. Eur J Radiol 2021; 138:109626. [PMID: 33711569 DOI: 10.1016/j.ejrad.2021.109626] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/24/2020] [Revised: 02/15/2021] [Accepted: 03/01/2021] [Indexed: 01/09/2023]
Abstract
PURPOSE To compare diffusion-weighted imaging of the breast performed with a conventional readout-segmented echo-planar imaging (rs-EPI) sequence to when using a prototype simultaneous multi-slice single-shot EPI (SMS-ss-EPI) acquisition. METHOD From September 2017 to December 2018, 26 women with histologically proven breast cancer were scanned with the conventional rs-EPI and the SMS-ss-EPI at 3 T during the same imaging examination. Four breast radiologists (4-13 years of experience) independently scored both acquired series of 25 women (one case was used for training) for overall image quality (1: extremely poor to 9: excellent) and artifacts (1: very disturbing to 5: not present). All lesions (n = 52; 40 malignant, 12 benign) were also evaluated for visibility (1: not visible, 2: visible if location is given, 3: visible). In addition, lesion characteristics were rated, and a BI-RADS score was given. Results were analyzed using visual grading characteristics and the resulting area under the curve (AUCVGC), weighted kappa, McNemar test, and dependent-samples t-test when appropriate. RESULTS Overall, radiologists significantly preferred the image quality in rs-EPI over that of SMS-ss-EPI (AUCVGC: 0.698, P = 0.002). Infolding and ghosting, and distortion artifacts were significantly less apparent in the rs-EPI (AUCVGC: 0.660, P = 0.022 and AUCVGC: 0.700 P = 0.002, respectively). Lesions were, however, significantly better visible on the SMS-ss-EPI images (AUCVGC: 0.427, P = 0.016). Malignant lesions had significantly higher visibility with SMS-ss-EPI (P = 0.035). Sensitivity and specificity were comparable between both sequences (P = 0.760 and P = 0.549, respectively). CONCLUSIONS Despite the perceived lower image quality and the increased presence of artifacts in the SMS-ss-EPI sequence, malignant lesions are better visualized using this sequence.
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Affiliation(s)
- Wendelien B G Sanderink
- Medical Imaging, Radboud University Medical Centre, Geert Grooteplein Zuid 10, Nijmegen, 6525GA, the Netherlands.
| | - Jonas Teuwen
- Medical Imaging, Radboud University Medical Centre, Geert Grooteplein Zuid 10, Nijmegen, 6525GA, the Netherlands
| | - Linda Appelman
- Medical Imaging, Radboud University Medical Centre, Geert Grooteplein Zuid 10, Nijmegen, 6525GA, the Netherlands
| | - Linda Moy
- Department of Radiology, New York University Langone Medical Center, 660 First Avenue, 4(th) Floor, New York, NY, 10016, United States
| | - Laura Heacock
- Department of Radiology, New York University Langone Medical Center, 660 First Avenue, 4(th) Floor, New York, NY, 10016, United States
| | - Elisabeth Weiland
- MR Application Predevelopment, Siemens Healthcare, Allee am Roethelheimpark 2, Erlangen, 91052, Germany
| | - Nico Karssemeijer
- Medical Imaging, Radboud University Medical Centre, Geert Grooteplein Zuid 10, Nijmegen, 6525GA, the Netherlands
| | - Pascal A T Baltzer
- Department of Biomedical Imaging and Image-guided Therapy, Vienna General Hospital, Währinger Gürtel 18-20, Vienna, 1090, Austria
| | - Ioannis Sechopoulos
- Medical Imaging, Radboud University Medical Centre, Geert Grooteplein Zuid 10, Nijmegen, 6525GA, the Netherlands
| | - Ritse M Mann
- Medical Imaging, Radboud University Medical Centre, Geert Grooteplein Zuid 10, Nijmegen, 6525GA, the Netherlands
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Moran CJ, Cheng JY, Sandino CM, Carl M, Alley MT, Rosenberg J, Daniel BL, Pittman SM, Rosen EL, Hargreaves BA. Diffusion-weighted double-echo steady-state with a three-dimensional cones trajectory for non-contrast-enhanced breast MRI. J Magn Reson Imaging 2020; 53:1594-1605. [PMID: 33382171 DOI: 10.1002/jmri.27492] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2020] [Revised: 12/08/2020] [Accepted: 12/10/2020] [Indexed: 12/30/2022] Open
Abstract
The image quality limitations of echo-planar diffusion-weighted imaging (DWI) are an obstacle to its widespread adoption in the breast. Steady-state DWI is an alternative DWI method with more robust image quality but its contrast for imaging breast cancer is not well-understood. The aim of this study was to develop and evaluate diffusion-weighted double-echo steady-state imaging with a three-dimensional cones trajectory (DW-DESS-Cones) as an alternative to conventional DWI for non-contrast-enhanced MRI in the breast. This prospective study included 28 women undergoing clinically indicated breast MRI and six asymptomatic volunteers. In vivo studies were performed at 3 T and included DW-DESS-Cones, DW-DESS-Cartesian, DWI, and CE-MRI acquisitions. Phantom experiments (diffusion phantom, High Precision Devices) and simulations were performed to establish framework for contrast of DW-DESS-Cones in comparison to DWI in the breast. Motion artifacts of DW-DESS-Cones were measured with artifact-to-noise ratio in volunteers and patients. Lesion-to-fibroglandular tissue signal ratios were measured, lesions were categorized as hyperintense or hypointense, and an image quality observer study was performed in DW-DESS-Cones and DWI in patients. Effect of DW-DESS-Cones method on motion artifacts was tested by mixed-effects generalized linear model. Effect of DW-DESS-Cones on signal in phantom was tested by quadratic regression. Correlation was calculated between DW-DESS-Cones and DWI lesion-to-fibroglandular tissue signal ratios. Inter-observer agreement was assessed with Gwet's AC. Simulations predicted hyperintensity of lesions with DW-DESS-Cones but at a 3% to 67% lower degree than with DWI. Motion artifacts were reduced with DW-DESS-Cones versus DW-DESS-Cartesian (p < 0.05). Lesion-to-fibroglandular tissue signal ratios were not correlated between DW-DESS-Cones and DWI (r = 0.25, p = 0.38). Concordant hyperintensity/hypointensity was observed between DW-DESS-Cones and DWI in 11/14 lesions. DW-DESS-Cones improved sharpness, distortion, and overall image quality versus DWI. DW-DESS-Cones may be able to eliminate motion artifacts in the breast allowing for investigation of higher degrees of steady-state diffusion weighting. Malignant breast lesions in DW-DESS-Cones demonstrated hyperintensity with respect to surrounding tissue without an injection of contrast. LEVEL OF EVIDENCE: 2. TECHNICAL EFFICACY STAGE: 1.
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Affiliation(s)
- Catherine J Moran
- Department of Radiology, Stanford University, Stanford, California, USA
| | - Joseph Y Cheng
- Department of Electrical Engineering, Stanford University, Stanford, California, USA
| | - Christopher M Sandino
- Department of Electrical Engineering, Stanford University, Stanford, California, USA
| | - Michael Carl
- Global MR Application and Workflow, GE Healthcare, San Diego, California, USA
| | - Marcus T Alley
- Department of Radiology, Stanford University, Stanford, California, USA
| | - Jarrett Rosenberg
- Department of Radiology, Stanford University, Stanford, California, USA
| | - Bruce L Daniel
- Department of Radiology, Stanford University, Stanford, California, USA
| | - Sarah M Pittman
- Department of Radiology, Stanford University, Stanford, California, USA
| | - Eric L Rosen
- Department of Radiology, Stanford University, Stanford, California, USA
| | - Brian A Hargreaves
- Department of Radiology, Stanford University, Stanford, California, USA.,Department of Electrical Engineering, Stanford University, Stanford, California, USA
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