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Meyer NK, In MH, Black DF, Campeau NG, Welker KM, Huston J, Halverson MA, Bernstein MA, Trzasko JD. Model-based iterative reconstruction for direct imaging with point spread function encoded echo planar MRI. Magn Reson Imaging 2024; 109:189-202. [PMID: 38490504 DOI: 10.1016/j.mri.2024.03.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2023] [Revised: 03/08/2024] [Accepted: 03/08/2024] [Indexed: 03/17/2024]
Abstract
BACKGROUND Echo planar imaging (EPI) is a fast measurement technique commonly used in magnetic resonance imaging (MRI), but is highly sensitive to measurement non-idealities in reconstruction. Point spread function (PSF)-encoded EPI is a multi-shot strategy which alleviates distortion, but acquisition of encodings suitable for direct distortion-free imaging prolongs scan time. In this work, a model-based iterative reconstruction (MBIR) framework is introduced for direct imaging with PSF-EPI to improve image quality and acceleration potential. METHODS An MBIR platform was developed for accelerated PSF-EPI. The reconstruction utilizes a subspace representation, is regularized to promote local low-rankedness (LLR), and uses variable splitting for efficient iteration. Comparisons were made against standard reconstructions from prospectively accelerated PSF-EPI data and with retrospective subsampling. Exploring aggressive partial Fourier acceleration of the PSF-encoding dimension, additional comparisons were made against an extension of Homodyne to direct PSF-EPI in numerical experiments. A neuroradiologists' assessment was completed comparing images reconstructed with MBIR from retrospectively truncated data directly against images obtained with standard reconstructions from non-truncated datasets. RESULTS Image quality results were consistently superior for MBIR relative to standard and Homodyne reconstructions. As the MBIR signal model and reconstruction allow for arbitrary sampling of the PSF space, random sampling of the PSF-encoding dimension was also demonstrated, with quantitative assessments indicating best performance achieved through nonuniform PSF sampling combined with partial Fourier. With retrospective subsampling, MBIR reconstructs high-quality images from sub-minute scan datasets. MBIR was shown to be superior in a neuroradiologists' assessment with respect to three of five performance criteria, with equivalence for the remaining two. CONCLUSIONS A novel image reconstruction framework is introduced for direct imaging with PSF-EPI, enabling arbitrary PSF space sampling and reconstruction of diagnostic-quality images from highly accelerated PSF-encoded EPI data.
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Affiliation(s)
- Nolan K Meyer
- Department of Radiology, Mayo Clinic, 200 First Street SW, Rochester, MN 55905, USA
| | - Myung-Ho In
- Department of Radiology, Mayo Clinic, 200 First Street SW, Rochester, MN 55905, USA
| | - David F Black
- Department of Radiology, Mayo Clinic, 200 First Street SW, Rochester, MN 55905, USA
| | - Norbert G Campeau
- Department of Radiology, Mayo Clinic, 200 First Street SW, Rochester, MN 55905, USA
| | - Kirk M Welker
- Department of Radiology, Mayo Clinic, 200 First Street SW, Rochester, MN 55905, USA
| | - John Huston
- Department of Radiology, Mayo Clinic, 200 First Street SW, Rochester, MN 55905, USA
| | - Maria A Halverson
- Department of Radiology, Mayo Clinic, 200 First Street SW, Rochester, MN 55905, USA
| | - Matt A Bernstein
- Department of Radiology, Mayo Clinic, 200 First Street SW, Rochester, MN 55905, USA
| | - Joshua D Trzasko
- Department of Radiology, Mayo Clinic, 200 First Street SW, Rochester, MN 55905, USA.
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Kim DK, Lee SY, Lee J, Huh YJ, Lee S, Lee S, Jung JY, Lee HS, Benkert T, Park SH. Deep learning-based k-space-to-image reconstruction and super resolution for diffusion-weighted imaging in whole-spine MRI. Magn Reson Imaging 2024; 105:82-91. [PMID: 37939970 DOI: 10.1016/j.mri.2023.11.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2023] [Revised: 10/30/2023] [Accepted: 11/04/2023] [Indexed: 11/10/2023]
Abstract
PURPOSE To assess the feasibility of deep learning (DL)-based k-space-to-image reconstruction and super resolution for whole-spine diffusion-weighted imaging (DWI). METHOD This retrospective study included 97 consecutive patients with hematologic and/or oncologic diseases who underwent DL-processed whole-spine MRI from July 2022 to March 2023. For each patient, conventional (CONV) axial single-shot echo-planar DWI (b = 50, 800 s/mm2) was performed, followed by DL reconstruction and super resolution processing. The presence of malignant lesions and qualitative (overall image quality and diagnostic confidence) and quantitative (nonuniformity [NU], lesion contrast, signal-to-noise ratio [SNR], contrast-to-noise ratio [CNR], and ADC values) parameters were assessed for DL and CONV DWI. RESULTS Ultimately, 67 patients (mean age, 63.0 years; 35 females) were analyzed. The proportions of vertebrae with malignant lesions for both protocols were not significantly different (P: [0.55-0.99]). The overall image quality and diagnostic confidence scores were higher for DL DWI (all P ≤ 0.002) than CONV DWI. The NU, lesion contrast, SNR, and CNR of each vertebral segment (P ≤ 0.04) but not the NU of the sacral segment (P = 0.51) showed significant differences between protocols. For DL DWI, the NU was lower, and lesion contrast, SNR, and CNR were higher than those of CONV DWI (median values of all segments; 19.8 vs. 22.2, 5.4 vs. 4.3, 7.3 vs. 5.5, and 0.8 vs. 0.7). Mean ADC values of the lesions did not significantly differ between the protocols (P: [0.16-0.89]). CONCLUSIONS DL reconstruction can improve the image quality of whole-spine diffusion imaging.
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Affiliation(s)
- Dong Kyun Kim
- Department of Radiology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - So-Yeon Lee
- Department of Radiology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea.
| | - Jinyoung Lee
- Department of Radiology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Yeon Jong Huh
- Department of Radiology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Seungeun Lee
- Department of Radiology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Sungwon Lee
- Department of Radiology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Joon-Yong Jung
- Department of Radiology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Hyun-Soo Lee
- MR research Collaboration, Siemens Healthineers Ltd, Seoul, Republic of Korea
| | - Thomas Benkert
- MR Application Predevelopment, Siemens Healthcare GmbH, Erlangen, Germany
| | - Sung-Hong Park
- Department of Bio and Brain Engineering, KAIST, Daejeon, Republic of Korea
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Yu T, Cai LY, Torrisi S, Vu AT, Morgan VL, Goodale SE, Ramadass K, Meisler SL, Lv J, Warren AEL, Englot DJ, Cutting L, Chang C, Gore JC, Landman BA, Schilling KG. Distortion correction of functional MRI without reverse phase encoding scans or field maps. Magn Reson Imaging 2023; 103:18-27. [PMID: 37400042 PMCID: PMC10528451 DOI: 10.1016/j.mri.2023.06.016] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2023] [Revised: 06/27/2023] [Accepted: 06/28/2023] [Indexed: 07/05/2023]
Abstract
Functional magnetic resonance images (fMRI) acquired using echo planar sequences typically suffer from spatial distortions due to susceptibility induced off-resonance fields, which may cause geometric mismatch with structural images and affect subsequent quantification and localization of brain function. State-of-the art distortion correction methods (for example, using FSL's topup or AFNI's 3dQwarp algorithms) require the collection of additional scans - either field maps or images with reverse phase encoding directions (i.e., blip-up/blip-down acquisitions) - to estimate and correct distortions. However, not all imaging protocols acquire these additional data and thus cannot take advantage of these post-acquisition corrections. In this study, we aim to enable state-of-the art processing of historical or limited datasets that do not include specific sequences for distortion correction by using only the acquired functional data and a single commonly acquired structural image. To achieve this, we synthesize an undistorted image with contrast similar to the fMRI data and use the non-distorted synthetic image as an anatomical target for distortion correction. We evaluate the efficacy of this approach, named SynBOLD-DisCo (Synthetic BOLD contrast for Distortion Correction), and show that this distortion correction process yields fMRI data that are geometrically similar to non-distorted structural images, with distortion correction virtually equivalent to acquisitions that do contain both blip-up/blip-down images. Our method is available as a Singularity container, source code, and an executable trained model to facilitate evaluation and integration into existing fMRI preprocessing pipelines.
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Affiliation(s)
- Tian Yu
- Department of Computer Science, Vanderbilt University, Nashville, TN, USA
| | - Leon Y Cai
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA
| | - Salvatore Torrisi
- San Francisco VA Health Care System, San Francisco, CA, USA; Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA, USA
| | - An Thanh Vu
- San Francisco VA Health Care System, San Francisco, CA, USA; Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA, USA
| | - Victoria L Morgan
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA; Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, USA; Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Sarah E Goodale
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA
| | - Karthik Ramadass
- Department of Electrical and Computer Engineering, Vanderbilt University, Nashville, TN, USA
| | - Steven L Meisler
- Program in Speech and Hearing Bioscience and Technology, Harvard University, Cambridge, MA, USA
| | - Jinglei Lv
- School of Biomedical Engineering, Faculty of Engineering, The University of Sydney, Sydney, NSW, Australia; Brain and Mind Centre, The University of Sydney, Sydney, NSW, Australia
| | - Aaron E L Warren
- Department of Neurosurgery, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Dario J Englot
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA; Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, USA; Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, USA; Department of Electrical and Computer Engineering, Vanderbilt University, Nashville, TN, USA; Department of Neurosurgery, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Laurie Cutting
- Department of Computer Science, Vanderbilt University, Nashville, TN, USA; Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, USA; Vanderbilt Kennedy Center, Vanderbilt University Medical Center, Nashville, TN, USA; Department of Special Education, Vanderbilt University, Nashville, TN, USA; Department of Psychology, Vanderbilt University, Nashville, TN, USA
| | - Catie Chang
- Department of Computer Science, Vanderbilt University, Nashville, TN, USA; Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA; Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, USA; Department of Electrical and Computer Engineering, Vanderbilt University, Nashville, TN, USA
| | - John C Gore
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, USA; Department of Electrical and Computer Engineering, Vanderbilt University, Nashville, TN, USA
| | - Bennett A Landman
- Department of Computer Science, Vanderbilt University, Nashville, TN, USA; Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA; Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, USA; Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, USA; Department of Electrical and Computer Engineering, Vanderbilt University, Nashville, TN, USA
| | - Kurt G Schilling
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, USA; Department of Electrical and Computer Engineering, Vanderbilt University, Nashville, TN, USA.
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Yang JYM, Chen J, Alexander B, Schilling K, Kean M, Wray A, Seal M, Maixner W, Beare R. Assessment of intraoperative diffusion EPI distortion and its impact on estimation of supratentorial white matter tract positions in pediatric epilepsy surgery. Neuroimage Clin 2022; 35:103097. [PMID: 35759887 PMCID: PMC9250069 DOI: 10.1016/j.nicl.2022.103097] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2022] [Revised: 05/18/2022] [Accepted: 06/20/2022] [Indexed: 10/26/2022]
Abstract
The effectiveness of correcting diffusion Echo Planar Imaging (EPI) distortion and its impact on tractography reconstruction have not been adequately investigated in the intraoperative MRI setting, particularly for High Angular Resolution Diffusion Imaging (HARDI) acquisition. In this study, we evaluated the effectiveness of EPI distortion correction using 27 legacy intraoperative HARDI datasets over two consecutive surgical time points, acquired without reverse phase-encoded data, from 17 children who underwent epilepsy surgery at our institution. The data was processed with EPI distortion correction using the Synb0-Disco technique (Schilling et al., 2019) and without distortion correction. The corrected and uncorrected b0 diffusion-weighted images (DWI) were first compared visually. The mutual information indices between the original T1-weighted images and the fractional anisotropy images derived from corrected and uncorrected DWI were used to quantify the effect of distortion correction. Sixty-four white matter tracts were segmented from each dataset, using a deep-learning based automated tractography algorithm for the purpose of a standardized and unbiased evaluation. Displacement was calculated between tracts generated before and after distortion correction. The tracts were grouped based on their principal morphological orientations to investigate whether the effects of EPI distortion vary with tract orientation. Group differences in tract distortion were investigated both globally, and regionally with respect to proximity to the resecting lesion in the operative hemisphere. Qualitatively, we observed notable improvement in the corrected diffusion images, over the typically affected brain regions near skull-base air sinuses, and correction of additional distortion unique to intraoperative open cranium images, particularly over the resection site. This improvement was supported quantitatively, as mutual information indices between the FA and T1-weighted images were significantly greater after the correction, compared to before the correction. Maximum tract displacement between the corrected and uncorrected data, was in the range of 7.5 to 10.0 mm, a magnitude that would challenge the safety resection margin typically tolerated for tractography-informed surgical guidance. This was particularly relevant for tracts oriented partially or fully in-line with the acquired diffusion phase-encoded direction. Portions of these tracts passing close to the resection site demonstrated significantly greater magnitude of displacement, compared to portions of tracts remote from the resection site in the operative hemisphere. Our findings have direct clinical implication on the accuracy of intraoperative tractography-informed image guidance and emphasize the need to develop a distortion correction technique with feasible intraoperative processing time.
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Affiliation(s)
- Joseph Yuan-Mou Yang
- Department of Neurosurgery, Neuroscience Advanced Clinical Imaging Service (NACIS), The Royal Children's Hospital, Melbourne, Australia; Developmental Imaging, Murdoch Children's Research Institute, Melbourne, Australia; Neuroscience Research, Murdoch Children's Research Institute, Melbourne, Australia; Department of Paediatrics, The University of Melbourne, Melbourne, Australia.
| | - Jian Chen
- Developmental Imaging, Murdoch Children's Research Institute, Melbourne, Australia
| | - Bonnie Alexander
- Department of Neurosurgery, Neuroscience Advanced Clinical Imaging Service (NACIS), The Royal Children's Hospital, Melbourne, Australia; Developmental Imaging, Murdoch Children's Research Institute, Melbourne, Australia
| | - Kurt Schilling
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Centre, Nashville, USA
| | - Michael Kean
- Developmental Imaging, Murdoch Children's Research Institute, Melbourne, Australia; Department of Paediatrics, The University of Melbourne, Melbourne, Australia; Medical Imaging, The Royal Children's Hospital, Melbourne, Australia
| | - Alison Wray
- Department of Neurosurgery, Neuroscience Advanced Clinical Imaging Service (NACIS), The Royal Children's Hospital, Melbourne, Australia; Neuroscience Research, Murdoch Children's Research Institute, Melbourne, Australia
| | - Marc Seal
- Developmental Imaging, Murdoch Children's Research Institute, Melbourne, Australia; Department of Paediatrics, The University of Melbourne, Melbourne, Australia
| | - Wirginia Maixner
- Department of Neurosurgery, Neuroscience Advanced Clinical Imaging Service (NACIS), The Royal Children's Hospital, Melbourne, Australia; Neuroscience Research, Murdoch Children's Research Institute, Melbourne, Australia
| | - Richard Beare
- Developmental Imaging, Murdoch Children's Research Institute, Melbourne, Australia; Peninsula Clinical School, Faculty of Medicine, Monash University, Melbourne, Australia
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Lee SH, Broadwater MA, Ban W, Wang TWW, Kim HJ, Dumas JS, Vetreno RP, Herman MA, Morrow AL, Besheer J, Kash TL, Boettiger CA, Robinson DL, Crews FT, Shih YYI. An isotropic EPI database and analytical pipelines for rat brain resting-state fMRI. Neuroimage 2021; 243:118541. [PMID: 34478824 PMCID: PMC8561231 DOI: 10.1016/j.neuroimage.2021.118541] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2021] [Revised: 08/08/2021] [Accepted: 08/30/2021] [Indexed: 12/24/2022] Open
Abstract
Resting-state functional magnetic resonance imaging (fMRI) has drastically expanded the scope of brain research by advancing our knowledge about the topologies, dynamics, and interspecies translatability of functional brain networks. Several databases have been developed and shared in accordance with recent key initiatives in the rodent fMRI community to enhance the transparency, reproducibility, and interpretability of data acquired at various sites. Despite these pioneering efforts, one notable challenge preventing efficient standardization in the field is the customary choice of anisotropic echo planar imaging (EPI) schemes with limited spatial coverage. Imaging with anisotropic resolution and/or reduced brain coverage has significant shortcomings including reduced registration accuracy and increased deviation in brain feature detection. Here we proposed a high-spatial-resolution (0.4 mm), isotropic, whole-brain EPI protocol for the rat brain using a horizontal slicing scheme that can maintain a functionally relevant repetition time (TR), avoid high gradient duty cycles, and offer unequivocal whole-brain coverage. Using this protocol, we acquired resting-state EPI fMRI data from 87 healthy rats under the widely used dexmedetomidine sedation supplemented with low-dose isoflurane on a 9.4 T MRI system. We developed an EPI template that closely approximates the Paxinos and Watson's rat brain coordinate system and demonstrated its ability to improve the accuracy of group-level approaches and streamline fMRI data pre-processing. Using this database, we employed a multi-scale dictionary-learning approach to identify reliable spatiotemporal features representing rat brain intrinsic activity. Subsequently, we performed k-means clustering on those features to obtain spatially discrete, functional regions of interest (ROIs). Using Euclidean-based hierarchical clustering and modularity-based partitioning, we identified the topological organizations of the rat brain. Additionally, the identified group-level FC network appeared robust across strains and sexes. The "triple-network" commonly adapted in human fMRI were resembled in the rat brain. Through this work, we disseminate raw and pre-processed isotropic EPI data, a rat brain EPI template, as well as identified functional ROIs and networks in standardized rat brain coordinates. We also make our analytical pipelines and scripts publicly available, with the hope of facilitating rat brain resting-state fMRI study standardization.
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Affiliation(s)
- Sung-Ho Lee
- Center for Animal MRI, University of North Carolina, Chapel Hill, NC, USA,Biomedical Research Imaging Center, University of North Carolina, Chapel Hill, NC, USA,Department of Neurology, University of North Carolina, Chapel Hill, NC, USA,Bowles Center for Alcohol Studies University of North Carolina, Chapel Hill, NC, USA,Corresponding authors at: Center for Animal MRI, 125 Mason Farm Road, CB# 7513, University of North Carolina, Chapel Hill, NC 27599, USA. (S.-H. Lee), (Y.-Y.I. Shih)
| | - Margaret A. Broadwater
- Center for Animal MRI, University of North Carolina, Chapel Hill, NC, USA,Biomedical Research Imaging Center, University of North Carolina, Chapel Hill, NC, USA,Department of Neurology, University of North Carolina, Chapel Hill, NC, USA,Bowles Center for Alcohol Studies University of North Carolina, Chapel Hill, NC, USA
| | - Woomi Ban
- Center for Animal MRI, University of North Carolina, Chapel Hill, NC, USA,Biomedical Research Imaging Center, University of North Carolina, Chapel Hill, NC, USA
| | - Tzu-Wen Winnie Wang
- Center for Animal MRI, University of North Carolina, Chapel Hill, NC, USA,Biomedical Research Imaging Center, University of North Carolina, Chapel Hill, NC, USA
| | - Hyeon-Joong Kim
- Center for Animal MRI, University of North Carolina, Chapel Hill, NC, USA,Biomedical Research Imaging Center, University of North Carolina, Chapel Hill, NC, USA,Department of Neurology, University of North Carolina, Chapel Hill, NC, USA
| | - Jaiden Seongmi Dumas
- Center for Animal MRI, University of North Carolina, Chapel Hill, NC, USA,Department of Neurology, University of North Carolina, Chapel Hill, NC, USA,Department of Quantitative Biology, University of North Carolina, Chapel Hill, NC, USA
| | - Ryan P. Vetreno
- Bowles Center for Alcohol Studies University of North Carolina, Chapel Hill, NC, USA,Department of Pharmacology, University of North Carolina, Chapel Hill, NC, USA
| | - Melissa A. Herman
- Bowles Center for Alcohol Studies University of North Carolina, Chapel Hill, NC, USA,Department of Pharmacology, University of North Carolina, Chapel Hill, NC, USA
| | - A. Leslie Morrow
- Bowles Center for Alcohol Studies University of North Carolina, Chapel Hill, NC, USA,Department of Psychiatry, University of North Carolina, Chapel Hill, NC, USA,Department of Pharmacology, University of North Carolina, Chapel Hill, NC, USA
| | - Joyce Besheer
- Bowles Center for Alcohol Studies University of North Carolina, Chapel Hill, NC, USA,Department of Psychiatry, University of North Carolina, Chapel Hill, NC, USA
| | - Thomas L. Kash
- Bowles Center for Alcohol Studies University of North Carolina, Chapel Hill, NC, USA,Department of Pharmacology, University of North Carolina, Chapel Hill, NC, USA
| | - Charlotte A. Boettiger
- Bowles Center for Alcohol Studies University of North Carolina, Chapel Hill, NC, USA,Department of Psychiatry, University of North Carolina, Chapel Hill, NC, USA,Department of Psychology and Neuroscience, University of North Carolina, Chapel Hill, NC, USA
| | - Donita L. Robinson
- Bowles Center for Alcohol Studies University of North Carolina, Chapel Hill, NC, USA,Department of Psychiatry, University of North Carolina, Chapel Hill, NC, USA
| | - Fulton T. Crews
- Bowles Center for Alcohol Studies University of North Carolina, Chapel Hill, NC, USA,Department of Psychiatry, University of North Carolina, Chapel Hill, NC, USA,Department of Pharmacology, University of North Carolina, Chapel Hill, NC, USA
| | - Yen-Yu Ian Shih
- Center for Animal MRI, University of North Carolina, Chapel Hill, NC, USA,Biomedical Research Imaging Center, University of North Carolina, Chapel Hill, NC, USA,Department of Neurology, University of North Carolina, Chapel Hill, NC, USA,Bowles Center for Alcohol Studies University of North Carolina, Chapel Hill, NC, USA,Corresponding authors at: Center for Animal MRI, 125 Mason Farm Road, CB# 7513, University of North Carolina, Chapel Hill, NC 27599, USA. (S.-H. Lee), (Y.-Y.I. Shih)
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Raimondo L, Oliveira ĹAF, Heij J, Priovoulos N, Kundu P, Leoni RF, van der Zwaag W. Advances in resting state fMRI acquisitions for functional connectomics. Neuroimage 2021; 243:118503. [PMID: 34479041 DOI: 10.1016/j.neuroimage.2021.118503] [Citation(s) in RCA: 41] [Impact Index Per Article: 13.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2021] [Revised: 08/16/2021] [Accepted: 08/22/2021] [Indexed: 01/21/2023] Open
Abstract
Resting state functional magnetic resonance imaging (rs-fMRI) is based on spontaneous fluctuations in the blood oxygen level dependent (BOLD) signal, which occur simultaneously in different brain regions, without the subject performing an explicit task. The low-frequency oscillations of the rs-fMRI signal demonstrate an intrinsic spatiotemporal organization in the brain (brain networks) that may relate to the underlying neural activity. In this review article, we briefly describe the current acquisition techniques for rs-fMRI data, from the most common approaches for resting state acquisition strategies, to more recent investigations with dedicated hardware and ultra-high fields. Specific sequences that allow very fast acquisitions, or multiple echoes, are discussed next. We then consider how acquisition methods weighted towards specific parts of the BOLD signal, like the Cerebral Blood Flow (CBF) or Volume (CBV), can provide more spatially specific network information. These approaches are being developed alongside the commonly used BOLD-weighted acquisitions. Finally, specific applications of rs-fMRI to challenging regions such as the laminae in the neocortex, and the networks within the large areas of subcortical white matter regions are discussed. We finish the review with recommendations for acquisition strategies for a range of typical applications of resting state fMRI.
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Affiliation(s)
- Luisa Raimondo
- Spinoza Centre for Neuroimaging, Amsterdam, the Netherlands; Experimental and Applied Psychology, VU University, Amsterdam, the Netherlands
| | - Ĺcaro A F Oliveira
- Spinoza Centre for Neuroimaging, Amsterdam, the Netherlands; Experimental and Applied Psychology, VU University, Amsterdam, the Netherlands
| | - Jurjen Heij
- Spinoza Centre for Neuroimaging, Amsterdam, the Netherlands; Experimental and Applied Psychology, VU University, Amsterdam, the Netherlands
| | | | - Prantik Kundu
- Hyperfine Research Inc, Guilford, CT, United States; Icahn School of Medicine at Mt. Sinai, New York, United States
| | - Renata Ferranti Leoni
- InBrain, Department of Physics, FFCLRP, University of São Paulo, Ribeirão Preto, Brazil
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Morita K, Nakaura T, Yoneyama M, Nagayama Y, Kidoh M, Uetani H, Ikeda O, Yamashita Y, Hirai T. Non-contrast renal MRA using multi-shot gradient echo EPI at 3-T MRI. Eur Radiol 2021; 31:5959-66. [PMID: 33475775 DOI: 10.1007/s00330-020-07653-4] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2020] [Revised: 11/26/2020] [Accepted: 12/18/2020] [Indexed: 10/22/2022]
Abstract
OBJECTIVES The purpose of this study was to investigate the feasibility of non-contrast renal MRA using multi-shot gradient echo planar imaging (MSG-EPI) with a 3-T MRI system. METHODS Seventeen healthy volunteers underwent non-contrast renal MRA using MSG-EPI and balanced steady-state free precession (b-SSFP) sequences on a 3-T MRI system. Two radiologists independently recorded the images' contrast, noise, sharpness, artifacts, and overall quality on 4-point scales. The signal-to-noise ratio (SNR) for the renal artery, the contrast ratio (CR) between the renal artery and erector spinae, and acquisition time were compared between the two sequences. RESULTS The SNR and CR were significantly higher with MSG-EPI than with the b-SSFP sequence (17.80 ± 3.67 vs. 10.84 ± 2.86 and 0.77 ± 0.05 and 0.66 ± 0.09, respectively; p < 0.05), and the acquisition time was significantly lower (164.5 ± 34.0 vs. 261.5 ± 39.3 s, respectively; p < 0.05). There were significant differences in image contrast, noise, sharpness, artifacts, and overall image quality between the two sequences (p < 0.01). CONCLUSIONS The MSG-EPI sequence is a promising technique that can shorten the scan time and improve the image quality of non-contrast renal MRA with a 3-T MRI system. KEY POINTS • The multi-shot gradient echo planar imaging with an inversion pulse is a brand-new fast scan technique for an unenhanced renal MRA. • The image quality of multi-shot gradient echo planar imaging is better than that of b-SSFP for an unenhanced renal MRA.
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Hu Y, Zhan C, Yang Z, Zhang X, Zhang H, Liu W, Xia L, Ai T. Accelerating acquisition of readout-segmented echo planar imaging with a simultaneous multi-slice (SMS) technique for diagnosing breast lesions. Eur Radiol 2020; 31:2667-2676. [PMID: 33146797 DOI: 10.1007/s00330-020-07393-5] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2020] [Revised: 09/09/2020] [Accepted: 10/08/2020] [Indexed: 10/23/2022]
Abstract
OBJECTIVES To investigate the feasibility and effectiveness of SMS rs-EPI for evaluating breast lesions. METHODS This prospective study was approved by IRB. Ninety-six patients had 102 histopathologically verified lesions (80 malignant and 22 benign) that were evaluated. Conventional rs-EPI and SMS rs-EPI data were acquired on a 3T scanner. Mean kurtosis (MK), mean diffusion (MD), and apparent diffusion coefficient (ADC) values were quantitatively calculated for each lesion on both sequences. Images were qualitatively and quantitatively analyzed with respect to image sharpness, geometric distortion, lesion conspicuity, anatomic structure, overall image quality, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR). Student's t test, Pearson correlation, receiver operating characteristic curve, Wilcoxon rank sum test, and paired-sample t tests were used for statistical analysis. RESULTS Compared to conventional rs-EPI, the acquisition time of SMS rs-EPI was markedly reduced (2:17 min vs 4:27 min). Pearson's correlations showed excellent linear relationships for each parameter between conventional rs-EPI and SMS rs-EPI (MK, r = 0.908; MD, r = 0.938; and ADC, r = 0.975; p < 0.01 for all). Furthermore, SMS rs-EPI had similar diagnostic performance compared with conventional rs-EPI. SMS rs-EPI had comparable visual image quality as conventional rs-EPI, with excellent inter-reader reliability (ICC = 0.851-0.940). No differences existed between conventional rs-EPI and SMS rs-EPI for either SNR or CNR (p > 0.05). CONCLUSIONS Applying the SMS technique can significantly reduce the acquisition time and produce similar diagnostic accuracy while generating comparable image quality as the conventional rs-EPI. KEY POINTS • SMS rs-EPI reduces scan time from 4:27 min to 2:17 min compared with conventional rs-EPI. • SMS rs-EPI has a comparable diagnostic performance to conventional rs-EPI in the differentiation between malignant and benign breast lesions. • SMS rs-EPI demonstrates comparable image quality to conventional rs-EPI with shorter scan time.
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Affiliation(s)
- Yiqi Hu
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, Hubei, China
| | - Chenao Zhan
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, Hubei, China
| | - Zhenlu Yang
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, Hubei, China
| | - Xiaoyong Zhang
- MR Collaborations, Siemens Healthcare, Shenzhen, 518000, China
| | - Huiting Zhang
- MR Scientific Marketing, Siemens Healthcare, Wuhan, 430030, Hubei, China
| | - Wei Liu
- Siemens Shenzhen Magnetic Resonance, Shenzhen, 518000, China
| | - Liming Xia
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, Hubei, China
| | - Tao Ai
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, Hubei, China.
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9
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Koh YH, Shih YC, Lim SL, Kiew YS, Lim EW, Ng SM, Ooi LQR, Tan WQ, Chung YC, Rumpel H, Tan EK, Chan LL. Evaluation of trigeminal nerve tractography using two-fold-accelerated simultaneous multi-slice readout-segmented echo planar diffusion tensor imaging. Eur Radiol 2020; 31:640-649. [PMID: 32870393 DOI: 10.1007/s00330-020-07193-x] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2020] [Revised: 06/18/2020] [Accepted: 08/13/2020] [Indexed: 11/25/2022]
Abstract
OBJECTIVES Simultaneous multi-slice (SMS) imaging with short repetition time (TR) accelerates diffusion tensor imaging (DTI) acquisitions. However, its impact when combined with readout-segmented echo planar imaging (RESOLVE) on the cranial nerves given the challenging skull base/posterior fossa terrain is unexplored. We evaluated the reliability of trigeminal nerve DTI metrics using SMS with RESOLVE-DTI. METHODS Eight healthy controls and six patients with unilateral trigeminal neuralgia (TN) underwent brain MRI scan. Three different RESOLVE-DTI protocols were performed on a 3-T MRI system: non-SMS (TR = 4330 ms), SMS with identical TR (4330 ms), and SMS with short TR (2400 ms). Pontine signal-to-noise ratio (SNR) and DTI metrics of the trigeminal nerve streamlines tracked by two independent raters using deterministic tractography and standardized tracking protocol were obtained. These were statistically analyzed and compared across the three protocols using intra-rater and inter-rater intraclass correlation coefficients (ICCs), one-way analysis of variance (ANOVA), post hoc analysis, and linear regression. RESULTS On visual screening, there were no artifacts across the trigeminal nerves. All data also cleared objective image quality assurance analysis. Pontine SNR was similar for the two SMS protocols and higher for the non-SMS RESOLVE-DTI (F(2,36) = 4.40, p = 0.02). Intra-rater and inter-rater ICCs were very good (> 0.85). Trigeminal nerve DTI metrics were consistently measured by the three protocols, revealing significant linear relationships between non-SMS- and SMS-derived DTI metrics. CONCLUSION SMS RESOLVE-DTI enables fast and reliable evaluation of microstructural integrity of the trigeminal nerve, with potential application in the clinical management of TN. KEY POINTS • Readout-segmented diffusion-weighted echo planar imaging (RESOLVE-DTI) reduces image distortion artifacts in the posterior fossa but its long acquisition time limits clinical utility. • Simultaneous multi-slice (SMS) imaging combined with RESOLVE-DTI provides reliable trigeminal nerve tractography with potential applications in trigeminal neuralgia. • Two-fold-accelerated RESOLVE-DTI yields comparable trigeminal nerve streamlines and DTI metrics while near-halving acquisition time.
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Affiliation(s)
- Yeow Hoay Koh
- Department of Neurology, National Neuroscience Institute - Outram Campus, 20 College Road, Singapore, 169856, Singapore
| | - Yao-Chia Shih
- Department of Diagnostic Radiology, Singapore General Hospital, Outram Rd, Singapore, 169608, Singapore.,Duke-NUS Medical School, 8 College Rd, Singapore, 169857, Singapore
| | - Soo Lee Lim
- Department of Diagnostic Radiology, Singapore General Hospital, Outram Rd, Singapore, 169608, Singapore
| | - Yen San Kiew
- Department of Diagnostic Radiology, Singapore General Hospital, Outram Rd, Singapore, 169608, Singapore
| | - Ee Wei Lim
- Department of Neurology, National Neuroscience Institute - Outram Campus, 20 College Road, Singapore, 169856, Singapore
| | - See Mui Ng
- Department of Diagnostic Radiology, Singapore General Hospital, Outram Rd, Singapore, 169608, Singapore
| | - Leon Qi Rong Ooi
- Department of Neurology, National Neuroscience Institute - Outram Campus, 20 College Road, Singapore, 169856, Singapore
| | - Wen Qi Tan
- Department of Diagnostic Radiology, Singapore General Hospital, Outram Rd, Singapore, 169608, Singapore.,Duke-NUS Medical School, 8 College Rd, Singapore, 169857, Singapore
| | - Yiu-Cho Chung
- Siemens Healthcare, 60 MacPherson Rd, Singapore, 348615, Singapore
| | - Helmut Rumpel
- Department of Diagnostic Radiology, Singapore General Hospital, Outram Rd, Singapore, 169608, Singapore
| | - Eng King Tan
- Department of Neurology, National Neuroscience Institute - Outram Campus, 20 College Road, Singapore, 169856, Singapore.,Duke-NUS Medical School, 8 College Rd, Singapore, 169857, Singapore
| | - Ling Ling Chan
- Department of Diagnostic Radiology, Singapore General Hospital, Outram Rd, Singapore, 169608, Singapore. .,Duke-NUS Medical School, 8 College Rd, Singapore, 169857, Singapore.
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10
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Duong STM, Phung SL, Bouzerdoum A, Schira MM. An unsupervised deep learning technique for susceptibility artifact correction in reversed phase-encoding EPI images. Magn Reson Imaging 2020; 71:1-10. [PMID: 32407764 DOI: 10.1016/j.mri.2020.04.004] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2020] [Revised: 03/17/2020] [Accepted: 04/11/2020] [Indexed: 10/24/2022]
Abstract
Echo planar imaging (EPI) is a fast and non-invasive magnetic resonance imaging technique that supports data acquisition at high spatial and temporal resolutions. However, susceptibility artifacts, which cause the misalignment to the underlying structural image, are unavoidable distortions in EPI. Traditional susceptibility artifact correction (SAC) methods estimate the displacement field by optimizing an objective function that involves one or more pairs of reversed phase-encoding (PE) images. The estimated displacement field is then used to unwarp the distorted images and produce the corrected images. Since this conventional approach is time-consuming, we propose an end-to-end deep learning technique, named S-Net, to correct the susceptibility artifacts the reversed-PE image pair. The proposed S-Net consists of two components: (i) a convolutional neural network to map a reversed-PE image pair to the displacement field; and (ii) a spatial transform unit to unwarp the input images and produce the corrected images. The S-Net is trained using a set of reversed-PE image pairs and an unsupervised loss function, without ground-truth data. For a new image pair of reversed-PE images, the displacement field and corrected images are obtained simultaneously by evaluating the trained S-Net directly. Evaluations on three different datasets demonstrate that S-Net can correct the susceptibility artifacts in the reversed-PE images. Compared with two state-of-the-art SAC methods (TOPUP and TISAC), the proposed S-Net runs significantly faster: 20 times faster than TISAC and 369 times faster than TOPUP, while achieving a similar correction accuracy. Consequently, S-Net accelerates the medical image processing pipelines and makes the real-time correction for MRI scanners feasible. Our proposed technique also opens up a new direction in learning-based SAC.
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Affiliation(s)
- Soan T M Duong
- School of Electrical, Computer and Telecommunications Engineering, University of Wollongong, Australia.
| | - Son L Phung
- School of Electrical, Computer and Telecommunications Engineering, University of Wollongong, Australia
| | - Abdesselam Bouzerdoum
- School of Electrical, Computer and Telecommunications Engineering, University of Wollongong, Australia; ICT Division, College of Science and Engineering, Hamad Bin Khalifa University, Qatar
| | - Mark M Schira
- School of Psychology, University of Wollongong, Australia
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11
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Ke Z, Yan X, Min X, Cai W, Zhang P, You H, Fan C, Wang L. Validation of SE-EPI-based T2 mapping for characterization of prostate cancer: a new method compared with the traditional CPMG method. Abdom Radiol (NY) 2019; 44:3432-3440. [PMID: 31218387 DOI: 10.1007/s00261-019-02105-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Abstract
PURPOSE We aim to compare the results of spin echo-echo planar imaging (SE-EPI)-based T2 mapping with those of the conventional Carr-Purcell-Meiboom-Gill (CPMG) method and to investigate the potential validity of SE-EPI-T2 mapping for the characterization of prostate cancer (PCa). METHODS Our retrospective study included 42 PCa patients and 42 noncancer patients who underwent 3.0T MRI with b values ranging from 0 to 2000 s/mm2 and echo times (TEs) ranging from 32 to 100 ms before biopsies. Bland-Altman analysis was used to compare the agreement between the two methods. The correlations between CPMG-T2 values and SE-EPI-T2 values at different b values were determined by Spearman's rho analysis or Pearson analysis. The Mann-Whitney U test and two-sample t tests were used to analyze the differences between the cancerous and noncancerous groups. RESULTS Substantial agreement regarding the measurements was observed between the two methods. The average correlation between the CPMG-T2 values and SE-EPI-T2 values was moderate and positive, and the best correlations were found at b = 200 s/mm2 in the noncancer group (r = 0.557, P = 0.000) and at b = 100 s/mm2 in the cancer group (r = 0.537, P = 0.000). In addition, statistically significant differences were found between the noncancer and cancer groups in T2 values and ADC values (diff TEs) (P = 0.000). CONCLUSIONS Substantial agreement in the measurements was found between the SE-EPI method and CPMG method. SE-EPI-based T2 mapping has potential clinical value for the prostate and can be considered an alternative to the traditional CPMG-T2 mapping method.
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Affiliation(s)
- Zan Ke
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, No. 1095 Jiefang Road, Wuhan, 430030, Hubei, China
| | - Xu Yan
- MR Collaboration NE Asia, Siemens Healthcare, Shanghai, 201321, China
| | - Xiangde Min
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, No. 1095 Jiefang Road, Wuhan, 430030, Hubei, China
| | - Wei Cai
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, No. 1095 Jiefang Road, Wuhan, 430030, Hubei, China
| | - Peipei Zhang
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, No. 1095 Jiefang Road, Wuhan, 430030, Hubei, China
| | - Huijuan You
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, No. 1095 Jiefang Road, Wuhan, 430030, Hubei, China
| | - Chanyuan Fan
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, No. 1095 Jiefang Road, Wuhan, 430030, Hubei, China
| | - Liang Wang
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, No. 1095 Jiefang Road, Wuhan, 430030, Hubei, China.
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12
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Oh H, Kim JH, Yau JM. EPI distortion correction for concurrent human brain stimulation and imaging at 3T. J Neurosci Methods 2019; 327:108400. [PMID: 31434000 DOI: 10.1016/j.jneumeth.2019.108400] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2019] [Revised: 08/15/2019] [Accepted: 08/17/2019] [Indexed: 01/21/2023]
Abstract
BACKGROUND Transcranial magnetic stimulation (TMS) can be paired with functional magnetic resonance imaging (fMRI) in concurrent TMS-fMRI experiments. These multimodal experiments enable causal probing of network architecture in the human brain which can complement alternative network mapping approaches. Critically, merely introducing the TMS coil into the scanner environment can sometimes produce substantial magnetic field inhomogeneities and spatial distortions which limit the utility of concurrent TMS-fMRI. METHOD AND RESULTS We assessed the efficacy of point spread function corrected echo planar imaging (PSF-EPI) in correcting for the field inhomogeneities associated with a TMS coil at 3 T. In phantom and brain scans, we quantitatively compared the coil-induced distortion artifacts measured in EPI scans with and without PSF correction. We found that the application of PSF corrections to the EPI data significantly improved signal-to-noise and reduced distortions. In phantom scans with the PSF-EPI sequence, we also characterized the temporal profile of dynamic artifacts associated with TMS delivery and found that image quality remained high as long as the TMS pulse preceded the RF excitation pulses by at least 50 ms. Lastly, we validated the PSF-EPI sequence in human brain scans involving TMS and motor behavior as well as resting state fMRI scans. CONCLUSIONS Our collective results demonstrate the potential benefits of PSF-EPI for concurrent TMS-fMRI when coil-related artifacts are a concern. The ability to collect high quality resting state fMRI data in the same session as the concurrent TMS-fMRI experiment offers a unique opportunity to interrogate network architecture in the human brain.
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13
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Schilling KG, Blaber J, Huo Y, Newton A, Hansen C, Nath V, Shafer AT, Williams O, Resnick SM, Rogers B, Anderson AW, Landman BA. Synthesized b0 for diffusion distortion correction (Synb0-DisCo). Magn Reson Imaging 2019; 64:62-70. [PMID: 31075422 DOI: 10.1016/j.mri.2019.05.008] [Citation(s) in RCA: 60] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2018] [Revised: 04/02/2019] [Accepted: 05/04/2019] [Indexed: 02/07/2023]
Abstract
Diffusion magnetic resonance images typically suffer from spatial distortions due to susceptibility induced off-resonance fields, which may affect the geometric fidelity of the reconstructed volume and cause mismatches with anatomical images. State-of-the art susceptibility correction (for example, FSL's TOPUP algorithm) typically requires data acquired twice with reverse phase encoding directions, referred to as blip-up blip-down acquisitions, in order to estimate an undistorted volume. Unfortunately, not all imaging protocols include a blip-up blip-down acquisition, and cannot take advantage of the state-of-the art susceptibility and motion correction capabilities. In this study, we aim to enable TOPUP-like processing with historical and/or limited diffusion imaging data that include only a structural image and single blip diffusion image. We utilize deep learning to synthesize an undistorted non-diffusion weighted image from the structural image, and use the non-distorted synthetic image as an anatomical target for distortion correction. We evaluate the efficacy of this approach (named Synb0-DisCo) and show that our distortion correction process results in better matching of the geometry of undistorted anatomical images, reduces variation in diffusion modeling, and is practically equivalent to having both blip-up and blip-down non-diffusion weighted images.
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Affiliation(s)
- Kurt G Schilling
- Vanderbilt University Institute of Imaging Science, Vanderbilt University, Nashville, TN, United States of America.
| | - Justin Blaber
- Electrical Engineering & Computer Science, Vanderbilt University, Nashville, TN, United States of America
| | - Yuankai Huo
- Department of Electrical Engineering, Vanderbilt University, Nashville, TN, United States of America
| | - Allen Newton
- Vanderbilt University Institute of Imaging Science, Vanderbilt University, Nashville, TN, United States of America; Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, United States of America
| | - Colin Hansen
- Department of Electrical Engineering, Vanderbilt University, Nashville, TN, United States of America
| | - Vishwesh Nath
- Electrical Engineering & Computer Science, Vanderbilt University, Nashville, TN, United States of America
| | - Andrea T Shafer
- Laboratory of Behavioral Neuroscience, National Institute on Aging, National Institutes of Health, Baltimore, MD, United States of America
| | - Owen Williams
- Laboratory of Behavioral Neuroscience, National Institute on Aging, National Institutes of Health, Baltimore, MD, United States of America
| | - Susan M Resnick
- Laboratory of Behavioral Neuroscience, National Institute on Aging, National Institutes of Health, Baltimore, MD, United States of America
| | - Baxter Rogers
- Vanderbilt University Institute of Imaging Science, Vanderbilt University, Nashville, TN, United States of America
| | - Adam W Anderson
- Vanderbilt University Institute of Imaging Science, Vanderbilt University, Nashville, TN, United States of America
| | - Bennett A Landman
- Vanderbilt University Institute of Imaging Science, Vanderbilt University, Nashville, TN, United States of America; Department of Electrical Engineering, Vanderbilt University, Nashville, TN, United States of America; Electrical Engineering & Computer Science, Vanderbilt University, Nashville, TN, United States of America
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14
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Cristobal-Huerta A, Poot DHJ, Vogel MW, Krestin GP, Hernandez-Tamames JA. Compressed Sensing 3D-GRASE for faster High-Resolution MRI. Magn Reson Med 2019; 82:984-999. [PMID: 31045280 PMCID: PMC6619236 DOI: 10.1002/mrm.27789] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2018] [Revised: 03/04/2019] [Accepted: 04/08/2019] [Indexed: 12/25/2022]
Abstract
Purpose High‐resolution three‐dimensional (3D) structural MRI is useful for delineating complex or small structures of the body. However, it requires long acquisition times and high SAR, limiting its clinical use. The purpose of this work is to accelerate the acquisition of high‐resolution images by combining compressed sensing and parallel imaging (CSPI) on a 3D‐GRASE sequence and to compare it with a (CS)PI 3D‐FSE sequence. Several sampling patterns were investigated to assess their influence on image quality. Methods The proposed k‐space sampling patterns are based on two undersampled k‐space grids, variable density (VD) Poisson‐disc, and VD pseudo‐random Gaussian, and five different trajectories described in the literature. Bloch simulations are performed to obtain the transform point spread function and evaluate the coherence of each sampling pattern. Image resolution was assessed by the full‐width at half‐maximum (FWHM). Prospective CSPI 3D‐GRASE phantom and in vivo experiments in knee and brain are carried out to assess image quality, SNR, SAR, and acquisition time compared to PI 3D‐GRASE, PI 3D‐FSE, and CSPI 3D‐FSE acquisitions. Results Sampling patterns with VD Poisson‐disc obtain the lowest coherence for both PD‐weighted and T2‐weighted acquisitions. VD pseudo‐random Gaussian obtains lower FWHM, but higher sidelobes than VD Poisson‐disc. CSPI 3D‐GRASE reduces acquisition time (43% for PD‐weighted and 40% for T2‐weighted) and SAR (∼45% for PD‐weighted and T2‐weighted) compared to CSPI 3D‐FSE. Conclusions CSPI 3D‐GRASE reduces acquisition time compared to a CSPI 3DFSE acquisition, preserving image quality. The design of the sampling pattern is crucial for image quality in CSPI 3D‐GRASE image acquisitions.
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Affiliation(s)
- A Cristobal-Huerta
- Department of Radiology and Nuclear Medicine, Erasmus MC, Rotterdam, The Netherlands
| | - D H J Poot
- Department of Radiology and Nuclear Medicine, Erasmus MC, Rotterdam, The Netherlands.,Department of Medical Informatics, Erasmus MC, Rotterdam, The Netherlands
| | - M W Vogel
- GE Healthcare, Hoevelaken, The Netherlands
| | - G P Krestin
- Department of Radiology and Nuclear Medicine, Erasmus MC, Rotterdam, The Netherlands
| | - J A Hernandez-Tamames
- Department of Radiology and Nuclear Medicine, Erasmus MC, Rotterdam, The Netherlands
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15
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Abstract
Functional MRI (fMRI) at 7T and above provides improved Signal-to-Noise Ratio and Contrast-to-Noise Ratio compared to 3T acquisitions. In addition to the beneficial effects on spin polarization and magnetization of deoxyhemoglobin, the increased applied field also further magnetizes air and tissue. While the magnets themselves typically provide a static B0 field with sufficient spatial homogeneity, the diamagnetism of tissue and the paramagnetism of air causes local field deviations inside the human head. These spatially-varying field offsets (ΔB0) cause image artifacts, especially in single shot EPI, including geometric distortion, signal dropout, and blurring. These effects are particularly strong near air-tissue interfaces such as the frontal sinus, and ear canals. Furthermore, if the field offsets are dynamically modulated through physiological processes such as respiration or motion, then the effect on the image time-series can be even more problematic. While post-processing methods have been developed to mitigate these effects, the ideal solution would be to reduce the ΔB0 variations at their source. Typically 7T scanners contain 2nd and some 3rd order spherical harmonic shim coil terms to cancel static ΔB0 variations of low spatial order. In this article, we will motivate the need for improved, higher-order compensation for B0 inhomogeneity and potentially add dynamic control of these fields. We discuss and compare several promising hardware approaches for static and dynamic B0 shimming using either higher-order spherical harmonic shim coils or multi-coil shim arrays as well as passive shimming approaches, and active variants such and adaptive current networks.
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Affiliation(s)
- Jason P Stockmann
- A. A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA 02129, United States.
| | - Lawrence L Wald
- A. A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA 02129, United States; Harvard Medical School, Boston, MA, United States
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16
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Santos-Díaz A, Obruchkov SI, Schulte RF, Noseworthy MD. Phosphorus magnetic resonance spectroscopic imaging using flyback echo planar readout trajectories. MAGMA 2018; 31:553-564. [PMID: 29383517 DOI: 10.1007/s10334-018-0675-y] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/03/2017] [Revised: 01/09/2018] [Accepted: 01/09/2018] [Indexed: 01/07/2023]
Abstract
OBJECT To present and evaluate a fast phosphorus magnetic resonance spectroscopic imaging (MRSI) sequence using echo planar spectroscopic imaging with flyback readout gradient trajectories. MATERIALS AND METHODS Waveforms were designed and implemented using a 3 Tesla MRI system. 31P spectra were acquired with 2 × 2 cm2 and 3 × 3 cm2 resolution over a 20- and 21-cm field of view and spectral bandwidths up to 1923 Hz. The sequence was first tested using a 20-cm-diameter phosphate phantom, and subsequent in vivo tests were performed on healthy human calf muscles and brains from five volunteers. RESULTS Flyback EPSI achieved 10× and 7× reductions in acquisition time, with 68.0 ± 1.2 and 69.8 ± 2.2% signal-to-noise ratio (SNR) per unit of time efficiency (theoretical SNR efficiency was 74.5 and 76.4%) for the in vivo experiments, compared to conventional phase-encoded MRSI for the 2 × 2 cm2 and 3 × 3 cm2 resolution waveforms, respectively. Statistical analysis showed no difference in the quantification of most metabolites. Time savings and SNR comparisons were consistent across phantom, leg and brain experiments. CONCLUSION EPSI using flyback readout trajectories was found to be a reliable alternative for acquiring 31P-MRSI data in a shorter acquisition time.
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Affiliation(s)
- Alejandro Santos-Díaz
- School of Biomedical Engineering, McMaster University, Hamilton, ON, Canada.,Imaging Research Center, St. Joseph's Healthcare, Hamilton, ON, Canada
| | - Sergei I Obruchkov
- Robinson Research Institute, Victoria University of Wellington, Wellington, New Zealand
| | | | - Michael D Noseworthy
- School of Biomedical Engineering, McMaster University, Hamilton, ON, Canada. .,Imaging Research Center, St. Joseph's Healthcare, Hamilton, ON, Canada. .,Department of Electrical and Computer Engineering, McMaster University, Engineering Technology Building, ETB-406, 1280 Main St. West, Hamilton, ON, L8S 4K1, Canada.
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17
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Iyama Y, Nakaura T, Nagayama Y, Oda S, Utsunomiya D, Kidoh M, Yuki H, Hirata K, Namimoto T, Kitajima M, Morita K, Funama Y, Takemura A, Tokuyasu S, Okuaki T, Yamashita Y. Comparison between multi-shot gradient echo EPI and balanced SSFP in unenhanced 3T MRA of thoracic aorta in healthy volunteers. Eur J Radiol 2017; 96:85-90. [PMID: 29103481 DOI: 10.1016/j.ejrad.2017.09.012] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2017] [Revised: 06/11/2017] [Accepted: 09/18/2017] [Indexed: 11/17/2022]
Abstract
PURPOSE The purpose of this study was to compare scan time and image quality between magnetic resonance angiography (MRA) of the thoracic aorta using a multi-shot gradient echo planar imaging (MSG-EPI) and MRA using balanced steady-state free precession (b-SSFP). MATERIALS AND METHODS Healthy volunteers (n=17) underwent unenhanced thoracic aorta MRA using balanced steady-state free precession (b-SSFP) and MSG-EPI sequences on a 3T MRI. The acquisition time, total scan time, signal-to-noise ratio (SNR) of the thoracic aorta, and the coefficient of variation (CV) of thoracic aorta were compared with paired t-tests. Two radiologists independently recorded the images' contrast, noise, sharpness, artifacts, and overall quality on a 4-point scale. RESULTS The acquisition time was 36.2% shorter for MSG-EPI than b-SSFP (115.5±14.4 vs 181.0±14.9s, p<0.01). The total scan time was 40.4% shorter for MSG-EPI than b-SSFP (272±78 vs 456±144s, p<0.01). There was no significant difference in mean SNR between MSG-EPI and b-SSFP scans (17.3±3.6 vs 15.2±4.3, p=0.08). The CV was significantly lower for MSG-EPI than b-SSFP (0.2±0.1 vs. 0.5±0.2, p<0.01). All qualitative scores except for image noise were significantly higher in MSG-EPI than b-SSFP scans (p<0.05). CONCLUSION The MSG-EPI sequence is a promising technique for shortening scan time and yielding more homogenous image quality in MRA of thoracic aorta on 3T scanners compared with the b-SSFP.
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Affiliation(s)
- Yuji Iyama
- Department of Diagnostic Radiology, Graduate School of Medical Sciences, Kumamoto University, Honjo 1-1-1, Kumamoto, Kumamoto 860-8556, Japan.
| | - Takeshi Nakaura
- Department of Diagnostic Radiology, Graduate School of Medical Sciences, Kumamoto University, Honjo 1-1-1, Kumamoto, Kumamoto 860-8556, Japan.
| | - Yasunori Nagayama
- Department of Diagnostic Radiology, Graduate School of Medical Sciences, Kumamoto University, Honjo 1-1-1, Kumamoto, Kumamoto 860-8556, Japan.
| | - Seitaro Oda
- Department of Diagnostic Radiology, Graduate School of Medical Sciences, Kumamoto University, Honjo 1-1-1, Kumamoto, Kumamoto 860-8556, Japan.
| | - Daisuke Utsunomiya
- Department of Diagnostic Radiology, Graduate School of Medical Sciences, Kumamoto University, Honjo 1-1-1, Kumamoto, Kumamoto 860-8556, Japan.
| | - Masafumi Kidoh
- Department of Diagnostic Radiology, Graduate School of Medical Sciences, Kumamoto University, Honjo 1-1-1, Kumamoto, Kumamoto 860-8556, Japan.
| | - Hideaki Yuki
- Department of Diagnostic Radiology, Graduate School of Medical Sciences, Kumamoto University, Honjo 1-1-1, Kumamoto, Kumamoto 860-8556, Japan.
| | - Kenichiro Hirata
- Department of Diagnostic Radiology, Graduate School of Medical Sciences, Kumamoto University, Honjo 1-1-1, Kumamoto, Kumamoto 860-8556, Japan.
| | - Tomohiro Namimoto
- Department of Diagnostic Radiology, Graduate School of Medical Sciences, Kumamoto University, Honjo 1-1-1, Kumamoto, Kumamoto 860-8556, Japan.
| | - Mika Kitajima
- Department of Diagnostic Radiology, Graduate School of Medical Sciences, Kumamoto University, Honjo 1-1-1, Kumamoto, Kumamoto 860-8556, Japan.
| | - Kosuke Morita
- Department of Diagnostic Radiology, Graduate School of Medical Sciences, Kumamoto University, Honjo 1-1-1, Kumamoto, Kumamoto 860-8556, Japan.
| | - Yoshinori Funama
- Department of Medical Physics, Faculty of Life Sciences, Kumamoto University, Kuhonji 4-24-1, Kumamoto, Kumamoto 860-8556, Japan.
| | - Atsushi Takemura
- Philips Healthcare Japan, 13-37 Kohnan 2-chome, Minato-ku, Tokyo 108-8507, Japan.
| | - Shinichi Tokuyasu
- Philips Healthcare Japan, 13-37 Kohnan 2-chome, Minato-ku, Tokyo 108-8507, Japan.
| | - Tomoyuki Okuaki
- Philips Healthcare Japan, 13-37 Kohnan 2-chome, Minato-ku, Tokyo 108-8507, Japan.
| | - Yasuyuki Yamashita
- Department of Diagnostic Radiology, Graduate School of Medical Sciences, Kumamoto University, Honjo 1-1-1, Kumamoto, Kumamoto 860-8556, Japan.
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Marhabaie S, Bodenhausen G, Pelupessy P. The effects of molecular diffusion in spatially encoded magnetic resonance imaging. J Magn Reson 2016; 273:98-104. [PMID: 27821292 DOI: 10.1016/j.jmr.2016.10.010] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/29/2016] [Revised: 10/10/2016] [Accepted: 10/14/2016] [Indexed: 06/06/2023]
Abstract
In spatially encoded MRI, the signal is acquired sequentially for different coordinates. In particular for single-scan acquisitions in inhomogeneous fields, spatially encoded methods improve the image quality compared to traditional k-space encoding. Previously, much attention has been paid in order to homogenize T2 losses across the sample. In this work, we investigate the effects of diffusion on the image quality in spatially encoded MRI. We show that losses due to diffusion are often not uniform along the spatially encoded dimension, and how to adapt spatially encoded sequences in order to obtain uniformly diffusion-weighted images.
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Affiliation(s)
- Sina Marhabaie
- Département de Chimie, École Normale Supérieure, PSL Research University, UPMC Univ Paris 06, CNRS, Laboratoire des Biomolecules (LBM), 24 rue Lhomond, 75005 Paris, France; Sorbonne Universités, UPMC Univ. Paris 06, École Normale Supérieure, CNRS, Laboratoire des Biomolecules (LBM), Paris, France
| | - Geoffrey Bodenhausen
- Département de Chimie, École Normale Supérieure, PSL Research University, UPMC Univ Paris 06, CNRS, Laboratoire des Biomolecules (LBM), 24 rue Lhomond, 75005 Paris, France; Sorbonne Universités, UPMC Univ. Paris 06, École Normale Supérieure, CNRS, Laboratoire des Biomolecules (LBM), Paris, France; Institut des Sciences et Ingéniérie Chimiques, Ecole Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland
| | - Philippe Pelupessy
- Département de Chimie, École Normale Supérieure, PSL Research University, UPMC Univ Paris 06, CNRS, Laboratoire des Biomolecules (LBM), 24 rue Lhomond, 75005 Paris, France; Sorbonne Universités, UPMC Univ. Paris 06, École Normale Supérieure, CNRS, Laboratoire des Biomolecules (LBM), Paris, France.
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19
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Glodeck D, Hesser J, Zheng L. Distortion correction of EPI data using multimodal nonrigid registration with an anisotropic regularization. Magn Reson Imaging 2015; 34:127-36. [PMID: 26545733 DOI: 10.1016/j.mri.2015.10.032] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2015] [Accepted: 10/25/2015] [Indexed: 10/22/2022]
Abstract
In this paper, a novel strategy for correcting both geometric and image intensity distortions of echo-planar imaging (EPI) MRI data is presented. To deal with small local distortions caused by rapid changes of the magnetic field, an improved multimodal registration framework using normalized mutual information (NMI) in combination with a multi-scale technique is presented to estimate a dense displacement field. To ensure the robustness of this high dimensional ill-posed inverse problem, a novel anisotropic regularization functional is used. In order to quantify geometric distortions, a new quality measure, called standardized contour distance (SCD), is introduced. It uses the outer structure shape (OSS) information as basis for the evaluation. The new registration method was evaluated with one monomodal phantom data set and two multimodal human brain data sets (BrainSuite trainings data, SPM Subject data). By comparing with recent and efficient techniques of the state of the art, in the monomodal case, the new approach achieves results comparable to the sum of squared differences as data term. In the multimodal cases, our new registration strategy improves the mean of the SCD from 0.96±0.11 to 0.60±0.13 in case of the SPM Subject data and from 0.92±0.07 to 0.78±0.11 in case of the BrainSuite trainings data.
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Affiliation(s)
- Daniel Glodeck
- Experimental Radiation Oncology, Department of Radiation Oncology, University Medical Center Mannheim, Heidelberg University, Germany.
| | - Jürgen Hesser
- Experimental Radiation Oncology, Department of Radiation Oncology, University Medical Center Mannheim, Heidelberg University, Germany.
| | - Lei Zheng
- Experimental Radiation Oncology, Department of Radiation Oncology, University Medical Center Mannheim, Heidelberg University, Germany.
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20
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Irfanoglu MO, Modi P, Nayak A, Hutchinson EB, Sarlls J, Pierpaoli C. DR-BUDDI (Diffeomorphic Registration for Blip-Up blip-Down Diffusion Imaging) method for correcting echo planar imaging distortions. Neuroimage 2015; 106:284-99. [PMID: 25433212 PMCID: PMC4286283 DOI: 10.1016/j.neuroimage.2014.11.042] [Citation(s) in RCA: 118] [Impact Index Per Article: 13.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2014] [Revised: 11/04/2014] [Accepted: 11/19/2014] [Indexed: 11/17/2022] Open
Abstract
We propose an echo planar imaging (EPI) distortion correction method (DR-BUDDI), specialized for diffusion MRI, which uses data acquired twice with reversed phase encoding directions, often referred to as blip-up blip-down acquisitions. DR-BUDDI can incorporate information from an undistorted structural MRI and also use diffusion-weighted images (DWI) to guide the registration, improving the quality of the registration in the presence of large deformations and in white matter regions. DR-BUDDI does not require the transformations for correcting blip-up and blip-down images to be the exact inverse of each other. Imposing the theoretical "blip-up blip-down distortion symmetry" may not be appropriate in the presence of common clinical scanning artifacts such as motion, ghosting, Gibbs ringing, vibrations, and low signal-to-noise. The performance of DR-BUDDI is evaluated with several data sets and compared to other existing blip-up blip-down correction approaches. The proposed method is robust and generally outperforms existing approaches. The inclusion of the DWIs in the correction process proves to be important to obtain a reliable correction of distortions in the brain stem. Methods that do not use DWIs may produce a visually appealing correction of the non-diffusion weighted images, but the directionally encoded color maps computed from the tensor reveal an abnormal anatomy of the white matter pathways.
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Affiliation(s)
- M Okan Irfanoglu
- Section on Tissue Biophysics and Biomimetics, National Institute of Child Health and Human Development, National Institutes of Health, Bethesda 20892, USA; Center for Neuroscience and Regenerative Medicine, Uniformed Services University of the Health Sciences, Bethesda, MD 20814, USA.
| | - Pooja Modi
- Section on Tissue Biophysics and Biomimetics, National Institute of Child Health and Human Development, National Institutes of Health, Bethesda 20892, USA
| | - Amritha Nayak
- Section on Tissue Biophysics and Biomimetics, National Institute of Child Health and Human Development, National Institutes of Health, Bethesda 20892, USA; Center for Neuroscience and Regenerative Medicine, Uniformed Services University of the Health Sciences, Bethesda, MD 20814, USA
| | - Elizabeth B Hutchinson
- Section on Tissue Biophysics and Biomimetics, National Institute of Child Health and Human Development, National Institutes of Health, Bethesda 20892, USA; Center for Neuroscience and Regenerative Medicine, Uniformed Services University of the Health Sciences, Bethesda, MD 20814, USA
| | - Joelle Sarlls
- NIH MRI Research Facility, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20892, USA
| | - Carlo Pierpaoli
- Section on Tissue Biophysics and Biomimetics, National Institute of Child Health and Human Development, National Institutes of Health, Bethesda 20892, USA
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21
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Abstract
Diffusion-weighted imaging (DWI) is a technique that assesses the cellularity, tortuosity of the extracellular/extravascular space, and cell membrane density based on differences in water proton mobility in tissues. The strength of the diffusion weighting is reflected by the b value. DWI using several b values enables the quantification of the apparent diffusion coefficient. DWI is increasingly used in liver imaging for multiple reasons: it can add useful qualitative and quantitative information to conventional imaging sequences; it is acquired relatively quickly; it is easily incorporated into existing clinical protocols; and it is a noncontrast technique.
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Affiliation(s)
- Sara Lewis
- Department of Radiology, Icahn School of Medicine at Mount Sinai, One Gustave Levy Place, Box 1234, New York, NY 10029, USA
| | - Hadrien Dyvorne
- Translational and Molecular Imaging Institute, Icahn School of Medicine at Mount Sinai, One Gustave Levy Place, Box 1234, New York, NY 10029, USA
| | - Yong Cui
- Translational and Molecular Imaging Institute, Icahn School of Medicine at Mount Sinai, One Gustave Levy Place, Box 1234, New York, NY 10029, USA
| | - Bachir Taouli
- Department of Radiology, Icahn School of Medicine at Mount Sinai, One Gustave Levy Place, Box 1234, New York, NY 10029, USA; Translational and Molecular Imaging Institute, Icahn School of Medicine at Mount Sinai, One Gustave Levy Place, Box 1234, New York, NY 10029, USA.
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Abstract
OBJECTIVE Geniculate neuralgia is an uncommon pain syndrome that can be severe and disabling and is difficult to diagnose. METHODS The literature was reviewed for geniculate neuralgia, including anatomy, presentation, and treatment. A case illustration was presented that demonstrates the novel brainstem functional imaging findings for geniculate neuralgia. A 39-year-old man presented with a history of left "deep" ear pain within his ear canal. He noted occasional pain on the left side of his face around the ear. He had been treated with neuropathic pain medications without relief. His wife described suicidal ideations discussed by her husband because of the intense pain. RESULTS The patient's neurologic examination was normal, and otolaryngologic consultation revealed no underlying structural disorder. Anatomic imaging revealed a tortuous vertebral artery-posterior inferior cerebellar artery complex with the posterior inferior cerebellar artery loop impinging on the root entry zone of the nervus intermedius-vestibulocochlear nerve complex and just inferior to the root entry zone of the facial nerve and a small anterior inferior cerebellar artery loop interposed between the cranial nerve VII-VIII complex and the hypoglossal and glossopharyngeal nerves. A left-sided retromastoid craniotomy was performed, and the nervus intermedius was transected. An arterial loop in contact with the lower cranial nerves at the level of the brainstem was mobilized with a polytetrafluoroethylene implant. CONCLUSIONS The patient indicated complete relief of his preoperative pain after surgery. He has remained pain-free with intact hearing and balance.
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Affiliation(s)
- R Shane Tubbs
- Pediatric Neurosurgery, Children's Hospital, Birmingham, Alabama, USA
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