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Weigel M, Celicanin Z, Haas T, Bieri O. Feasibility of interleaved multislice averaged magnetization inversion-recovery acquisitions of the spinal cord. Magn Reson Med 2024; 92:2588-2595. [PMID: 39051628 DOI: 10.1002/mrm.30223] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2023] [Revised: 06/24/2024] [Accepted: 06/26/2024] [Indexed: 07/27/2024]
Abstract
PURPOSE To establish an interleaved multislice variant of the averaged magnetization inversion-recovery acquisitions (AMIRA) approach for 2D spinal cord imaging with increased acquisition efficiency compared with the conventional 2D single-slice approach(es), and to determine essential prerequisites for a working interleaved multislice AMIRA approach in practice. METHODS The general AMIRA concept is based on an inversion recovery-prepared, segmented, and time-limited cine balanced SSFP sequence, generating images of different contrast. For AMIRA imaging of multiple, independent slices in a 2D interleaved fashion, a slice loop within the acquisition loops was programmed. The former non-selective inversions were replaced with slice-selective inversions with user-definable slice thickness. RESULTS The thickness of the slice-selective inversion in 2D interleaved multislice AMIRA should be doubled compared with the manufacturer's standard setting to avoid an increased sensitivity to flow and pulsation effects particularly in the CSF. However, this solution also limits its practical applicability, as slices located at directly adjacent vertebrae cannot be imaged together. Successful interleaved two-slice AMIRA imaging for a "reference" in vivo protocol with 0.50 × 0.50 mm2 in-plane resolution and 8-mm slice thickness is demonstrated, therefore halving its acquisition time per slice from 3 min down to 1.5 min. CONCLUSION The investigated 2D interleaved two-slice AMIRA variant facilitates spinal cord imaging that maintains similar contrast and the same resolution as the conventional 2D single-slice AMIRA approach, but does so with a halved acquisition time.
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Affiliation(s)
- Matthias Weigel
- Division of Radiological Physics, Department of Radiology, University Hospital Basel, Basel, Switzerland
- Department of Biomedical Engineering, University of Basel, Allschwil, Switzerland
- Translational Imaging in Neurology (ThINk) Basel, Department of Biomedical Engineering, Faculty of Medicine, University Hospital Basel and University of Basel, Basel, Switzerland
- Department of Neurology, University Hospital Basel, Basel, Switzerland
- Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel and University of Basel, Basel, Switzerland
| | - Zarko Celicanin
- Division of Radiological Physics, Department of Radiology, University Hospital Basel, Basel, Switzerland
- Center for Proton Therapy, Paul Scherrer Institute, Villigen PSI, Switzerland
| | - Tanja Haas
- Division of Radiological Physics, Department of Radiology, University Hospital Basel, Basel, Switzerland
| | - Oliver Bieri
- Division of Radiological Physics, Department of Radiology, University Hospital Basel, Basel, Switzerland
- Department of Biomedical Engineering, University of Basel, Allschwil, Switzerland
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Kan CK, Stirnberg R, Montequin M, Gulban OF, Morgan AT, Bandettini P, Huber LR. T1234: A distortion-matched structural scan solution to misregistration of high resolution fMRI data. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.09.19.613939. [PMID: 39372770 PMCID: PMC11451623 DOI: 10.1101/2024.09.19.613939] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/08/2024]
Abstract
Purpose High-resolution fMRI at 7T is challenged by suboptimal alignment quality between functional data and structural scans. This study aims to develop a rapid acquisition method that provides distortion-matched, artifact-mitigated structural reference data. Methods We introduce an efficient sequence protocol termed T1234, which offers adjustable distortions. This approach involves a T1-weighted 2-inversion 3D-EPI sequence with four spatial encoding directions optimized for high-resolution fMRI. A forward Bloch model was used for T1 quantification and protocol optimization. Twenty participants were scanned at 7T using both structural and functional protocols to evaluate the utility of T1234. Results Results from two protocols are presented. A fast distortion-free protocol reliably produced whole-brain segmentations at 0.8mm isotropic resolution within 3:00-3:40 minutes. It demonstrates robustness across sessions, participants, and three different 7T SIEMENS scanners. For a protocol with geometric distortions that matched functional data, T1234 facilitates layer-specific fMRI signal analysis with enhanced laminar precision. Conclusion This structural mapping approach enables precise registration with fMRI data. T1234 has been successfully implemented, validated, and tested, and is now available to users at our center and at over 50 centers worldwide.
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Manhard MK, Kilpattu Ramaniharan A, Tkach JA, Trout AT, Dillman JR, Pednekar AS. Simultaneous Multiparameter Mapping of the Liver in a Single Breath-Hold or Respiratory-Triggered Acquisition Using Multi-Inversion Spin and Gradient Echo MRI. J Magn Reson Imaging 2024. [PMID: 39192381 DOI: 10.1002/jmri.29584] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2024] [Revised: 08/06/2024] [Accepted: 08/07/2024] [Indexed: 08/29/2024] Open
Abstract
BACKGROUND Quantitative parametric mapping is an increasingly important tool for noninvasive assessment of chronic liver disease. Conventional parametric mapping techniques require multiple breath-held acquisitions and provide limited anatomic coverage. PURPOSE To investigate a multi-inversion spin and gradient echo (MI-SAGE) technique for simultaneous estimation of T1, T2, and T2* of the liver. STUDY TYPE Prospective. SUBJECTS Sixteen research participants, both adult and pediatric (age 17.5 ± 4.6 years, eight male), with and without known liver disease (seven asymptomatic healthy controls, two fibrotic liver disease, five steatotic liver disease, and two fibrotic and steatotic liver disease). FIELD STRENGTH/SEQUENCE 1.5 T, single breath-hold and respiratory triggered MI-SAGE, breath-hold modified Look-Locker inversion recovery (MOLLI, T1 mapping), breath-hold gradient and spin echo (GRASE, T2 mapping), and multiple gradient echo (mGRE, T2* mapping) sequences. ASSESSMENT Agreement between hepatic T1, T2, and T2* estimated using MI-SAGE and conventional parametric mapping sequences was evaluated. Repeatability and reproducibility of MI-SAGE were evaluated using a same-session acquisition and second-session acquisition. STATISTICAL TESTS Bland-Altman analysis with bias assessment and limits of agreement (LOA) and intraclass correlation coefficients (ICC). RESULTS Hepatic T1, T2, and T2* estimates obtained using the MI-SAGE technique had mean biases of 72 (LOA: -22 to 166) msec, -3 (LOA: -10 to 5) msec, and 2 (LOA: -5 to 8) msec (single breath-hold) and 36 (LOA: -43 to 120) msec, -3 (LOA: -17 to 11) msec, and 4 (LOA: -3 to 11) msec (respiratory triggered), respectively, in comparison to conventional acquisitions using MOLLI, GRASE, and mGRE. All MI-SAGE estimates had strong repeatability and reproducibility (ICC > 0.72). DATA CONCLUSION Hepatic T1, T2, and T2* estimates obtained using an MI-SAGE technique were comparable to conventional methods, although there was a 12%/6% for breath-hold/respiratory triggered underestimation of T1 values compared to MOLLI. Both respiratory triggered and breath-hold MI-SAGE parameter maps demonstrated strong repeatability and reproducibility. LEVEL OF EVIDENCE 1 TECHNICAL EFFICACY: Stage 2.
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Affiliation(s)
- Mary Kate Manhard
- Department of Radiology, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, USA
- Department of Radiology, University of Cincinnati College of Medicine, Cincinnati, Ohio, USA
| | | | - Jean A Tkach
- Department of Radiology, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, USA
- Department of Radiology, University of Cincinnati College of Medicine, Cincinnati, Ohio, USA
| | - Andrew T Trout
- Department of Radiology, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, USA
- Department of Radiology, University of Cincinnati College of Medicine, Cincinnati, Ohio, USA
| | - Jonathan R Dillman
- Department of Radiology, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, USA
- Department of Radiology, University of Cincinnati College of Medicine, Cincinnati, Ohio, USA
| | - Amol S Pednekar
- Department of Radiology, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, USA
- Department of Radiology, University of Cincinnati College of Medicine, Cincinnati, Ohio, USA
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Fischbach AK, Satpute AB, Quigley K, Kragel PA, Chen D, Bianciardi M, Wald L, Wager TD, Choi JK, Zhang J, Barrett LF, Theriault JE. Seven Tesla Evidence for Columnar and Rostral-Caudal Organization of the Human Periaqueductal Gray Response in the Absence of Threat: A Working Memory Study. J Neurosci 2024; 44:e1757232024. [PMID: 38664013 PMCID: PMC11211719 DOI: 10.1523/jneurosci.1757-23.2024] [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: 09/12/2023] [Revised: 03/01/2024] [Accepted: 04/08/2024] [Indexed: 06/28/2024] Open
Abstract
The periaqueductal gray (PAG) is a small midbrain structure that surrounds the cerebral aqueduct, regulates brain-body communication, and is often studied for its role in "fight-or-flight" and "freezing" responses to threat. We used ultra-high-field 7 T fMRI to resolve the PAG in humans and distinguish it from the cerebral aqueduct, examining its in vivo function during a working memory task (N = 87). Both mild and moderate cognitive demands elicited spatially similar patterns of whole-brain blood oxygenation level-dependent (BOLD) response, and moderate cognitive demand elicited widespread BOLD increases above baseline in the brainstem. Notably, these brainstem increases were not significantly greater than those in the mild demand condition, suggesting that a subthreshold brainstem BOLD increase occurred for mild cognitive demand as well. Subject-specific masks were group aligned to examine PAG response. In PAG, both mild and moderate demands elicited a well-defined response in ventrolateral PAG, a region thought to be functionally related to anticipated painful threat in humans and nonhuman animals-yet, the present task posed only the most minimal (if any) "threat," with the cognitive tasks used being approximately as challenging as remembering a phone number. These findings suggest that the PAG may play a more general role in visceromotor regulation, even in the absence of threat.
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Affiliation(s)
| | - Ajay B Satpute
- Department of Psychology, Northeastern University, Boston, Massachusetts 02115
| | - Karen Quigley
- Department of Psychology, Northeastern University, Boston, Massachusetts 02115
| | - Philip A Kragel
- Department of Psychology, Emory University, Atlanta, Georgia 30322
| | - Danlei Chen
- Department of Psychology, Northeastern University, Boston, Massachusetts 02115
| | - Marta Bianciardi
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, Massachusetts 02129
| | - Larry Wald
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, Massachusetts 02129
| | - Tor D Wager
- Department of Psychological and Brain Sciences, Dartmouth College, Hanover, New Hampshire 03755
| | - Ji-Kyung Choi
- Department of Surgery, University of California, San Francisco, California 94143
| | - Jiahe Zhang
- Department of Psychology, Northeastern University, Boston, Massachusetts 02115
| | | | - Jordan E Theriault
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, Massachusetts 02129
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Choi KH, Heo YJ, Baek HJ, Kim JH, Jang JY. Comparison of Inter-Method Agreement and Reliability for Automatic Brain Volumetry Using Three Different Clinically Available Software Packages. MEDICINA (KAUNAS, LITHUANIA) 2024; 60:727. [PMID: 38792912 PMCID: PMC11122718 DOI: 10.3390/medicina60050727] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/28/2024] [Revised: 04/21/2024] [Accepted: 04/25/2024] [Indexed: 05/26/2024]
Abstract
Background and Objectives: No comparative study has evaluated the inter-method agreement and reliability between Heuron AD and other clinically available brain volumetric software packages. Hence, we aimed to investigate the inter-method agreement and reliability of three clinically available brain volumetric software packages: FreeSurfer (FS), NeuroQuant® (NQ), and Heuron AD (HAD). Materials and Methods: In this study, we retrospectively included 78 patients who underwent conventional three-dimensional (3D) T1-weighed imaging (T1WI) to evaluate their memory impairment, including 21 with normal objective cognitive function, 24 with mild cognitive impairment, and 33 with Alzheimer's disease (AD). All 3D T1WI scans were analyzed using three different volumetric software packages. Repeated-measures analysis of variance, intraclass correlation coefficient, effect size measurements, and Bland-Altman analysis were used to evaluate the inter-method agreement and reliability. Results: The measured volumes demonstrated substantial to almost perfect agreement for most brain regions bilaterally, except for the bilateral globi pallidi. However, the volumes measured using the three software packages showed significant mean differences for most brain regions, with consistent systematic biases and wide limits of agreement in the Bland-Altman analyses. The pallidum showed the largest effect size in the comparisons between NQ and FS (5.20-6.93) and between NQ and HAD (2.01-6.17), while the cortical gray matter showed the largest effect size in the comparisons between FS and HAD (0.79-1.91). These differences and variations between the software packages were also observed in the subset analyses of 45 patients without AD and 33 patients with AD. Conclusions: Despite their favorable reliability, the software-based brain volume measurements showed significant differences and systematic biases in most regions. Thus, these volumetric measurements should be interpreted based on the type of volumetric software used, particularly for smaller structures. Moreover, users should consider the replaceability-related limitations when using these packages in real-world practice.
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Affiliation(s)
- Kwang Ho Choi
- Department of Thoracic and Cardiovascular Surgery, Research Institute for Convergence of Biomedical Science and Technology, Pusan National University Yangsan Hospital, Pusan National University School of Medicine, 20 Geumo-ro, Mulgeum-eup, Yangsan-si 50612, Republic of Korea
| | - Young Jin Heo
- Department of Radiology, Busan Paik Hospital, Inje University College of Medicine, 75, Bokji-ro, Busanjin-gu, Busan 47392, Republic of Korea
| | - Hye Jin Baek
- Department of Radiology, Gyeongsang National University School of Medicine and Gyeongsang National University Changwon Hospital, 11 Samjeongja-ro, Seongsan-gu, Changwon 51472, Republic of Korea
- Miracle Radiology Clinic, 201 Songpa-daero, Songpa-gu, Seoul 05854, Republic of Korea
| | - Jun-Ho Kim
- Department of Electrical and Electronic Engineering, Yonsei University, Seoul 03722, Republic of Korea
| | - Jeong Yoon Jang
- Division of Cardiology, Department of Internal Medicine, Gyeongsang National University School of Medicine and Gyeongsang National University Changwon Hospital, 11 Samjeongja-ro, Seongsan-gu, Changwon 51472, Republic of Korea
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Gomez DEP, Polimeni JR, Lewis LD. The temporal specificity of BOLD fMRI is systematically related to anatomical and vascular features of the human brain. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.02.01.578428. [PMID: 38352610 PMCID: PMC10862860 DOI: 10.1101/2024.02.01.578428] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/22/2024]
Abstract
The ability to detect fast responses with functional MRI depends on the speed of hemodynamic responses to neural activity, because hemodynamic responses act as a temporal low-pass filter smoothing out rapid changes. However, hemodynamic responses (their shape and timing) are highly variable across the brain and across stimuli. This heterogeneity of responses implies that the temporal specificity of fMRI signals, or the ability of fMRI to preserve fast information, should also vary substantially across the cortex. In this work we investigated how local differences in hemodynamic response timing impact the temporal specificity of fMRI. We conducted our research using ultra-high field (7T) fMRI at high spatiotemporal resolution, using the primary visual cortex (V1) as a model area for investigation. We used visual stimuli oscillating at slow and fast frequencies to probe the temporal specificity of individual voxels. As expected, we identified substantial variability in temporal specificity, with some voxels preserving their responses to fast neural activity more effectively than others. We investigated which voxels had the highest temporal specificity and related those to anatomical and vascular features of V1. We found that low temporal specificity is only weakly explained by the presence of large veins or cerebral cortical depth. Notably, however, temporal specificity depended strongly on a voxel's position along the anterior-posterior anatomical axis of V1, with voxels within the calcarine sulcus being capable of preserving close to 25% of their amplitude as the frequency of stimulation increased from 0.05-Hz to 0.20-Hz, and voxels nearest to the occipital pole preserving less than 18%. These results indicate that detection biases in high-resolution fMRI will depend on the anatomical and vascular features of the area being imaged, and that these biases will differ depending on the timing of the underlying neuronal activity. Importantly, this spatial heterogeneity of temporal specificity suggests that it could be exploited to achieve higher specificity in some locations, and that tailored data analysis strategies may help improve the detection and interpretation of fast fMRI responses.
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Affiliation(s)
- Daniel E. P. Gomez
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, United States
- Department of Radiology, Harvard Medical School, Boston, MA, United States
- Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA, United States
| | - Jonathan R. Polimeni
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, United States
- Department of Radiology, Harvard Medical School, Boston, MA, United States
- Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, United States
| | - Laura D. Lewis
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, United States
- Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA, United States
- Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, MA, United States
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Zhang K, Triphan SMF, Wielpütz MO, Ziener CH, Ladd ME, Schlemmer HP, Kauczor HU, Kurz FT, Sedlaczek O. Simultaneous T 1, T 2 and T 2⁎ mapping of the liver with multi-shot MI-SAGE. Magn Reson Imaging 2024; 105:75-81. [PMID: 37939972 DOI: 10.1016/j.mri.2023.11.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2023] [Accepted: 11/04/2023] [Indexed: 11/10/2023]
Abstract
PURPOSE To apply multi-shot high-resolution multi inversion spin and gradient echo (MI-SAGE) acquisition for simultaneous liver T1, T2 and T2* mapping. METHODS Inversion prepared spin- and gradient-echo EPI was developed with ascending slice order across measurements for efficient acquisition with T1, T2, and T2⁎ weighting. Multi-shot EPI was also implemented to minimize distortion and blurring while enabling high in-plane resolution. A dictionary-matching approach was used to fit the images to quantitative parameter maps, which were compared to T1 measured by modified Look-Locker (MOLLI), T1 measured by variable flip angle (VFA), T2 measured by multiple echo time-based Half Fourier Single-shot Turbo spin-Echo (HASTE), T2 measured by radial turbo-spin-echo (rTSE) and T2⁎ measured by multiple gradient echo (MGRE) sequences. RESULTS The multi-shot variant of the sequence achieved higher in-plane resolution of 1.7 × 1.7 mm2 with good image quality in 28 s. Derived quantitative maps showed comparable values to conventional mapping methods. As measured in phantom and in vivo, MOLLI, MESE and MGRE give closest values to MISAGE. VFA, HASTE and rTSE show obvious overestimation. CONCLUSIONS The proposed multi-shot inversion prepared spin- and gradient-echo EPI sequence allows for high-resolution quantitative T1, T2 and T2 liver tissue characterization in a single breath-hold scan.
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Affiliation(s)
- Ke Zhang
- Department of Diagnostic & Interventional Radiology, Heidelberg University Hospital, Heidelberg, Germany; Translational Lung Research Center (TLRC), German Center for Lung Research (DZL), Heidelberg, Germany; Department of Diagnostic & Interventional Radiology with Nuclear Medicine, Thoraxklinik at Heidelberg University Hospital, Heidelberg, Germany
| | - Simon M F Triphan
- Department of Diagnostic & Interventional Radiology, Heidelberg University Hospital, Heidelberg, Germany; Translational Lung Research Center (TLRC), German Center for Lung Research (DZL), Heidelberg, Germany; Department of Diagnostic & Interventional Radiology with Nuclear Medicine, Thoraxklinik at Heidelberg University Hospital, Heidelberg, Germany
| | - Mark O Wielpütz
- Department of Diagnostic & Interventional Radiology, Heidelberg University Hospital, Heidelberg, Germany; Translational Lung Research Center (TLRC), German Center for Lung Research (DZL), Heidelberg, Germany; Department of Diagnostic & Interventional Radiology with Nuclear Medicine, Thoraxklinik at Heidelberg University Hospital, Heidelberg, Germany
| | - Christian H Ziener
- Divison of Radiology, German Cancer Research Center, Heidelberg, Germany
| | - Mark E Ladd
- Divison of Medical Physics in Radiology, German Cancer Research Center, Heidelberg, Germany; Faculty of Physics and Astronomy, Heidelberg University, Heidelberg, Germany; Faculty of Medicine, Heidelberg University, Heidelberg, Germany
| | | | - Hans-Ulrich Kauczor
- Department of Diagnostic & Interventional Radiology, Heidelberg University Hospital, Heidelberg, Germany; Translational Lung Research Center (TLRC), German Center for Lung Research (DZL), Heidelberg, Germany; Department of Diagnostic & Interventional Radiology with Nuclear Medicine, Thoraxklinik at Heidelberg University Hospital, Heidelberg, Germany
| | - Felix T Kurz
- Divison of Radiology, German Cancer Research Center, Heidelberg, Germany
| | - Oliver Sedlaczek
- Department of Diagnostic & Interventional Radiology, Heidelberg University Hospital, Heidelberg, Germany; Translational Lung Research Center (TLRC), German Center for Lung Research (DZL), Heidelberg, Germany; Department of Diagnostic & Interventional Radiology with Nuclear Medicine, Thoraxklinik at Heidelberg University Hospital, Heidelberg, Germany; Divison of Radiology, German Cancer Research Center, Heidelberg, Germany.
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Malekian V, Graedel NN, Hickling A, Aghaeifar A, Dymerska B, Corbin N, Josephs O, Maguire EA, Callaghan MF. Mitigating susceptibility-induced distortions in high-resolution 3DEPI fMRI at 7T. Neuroimage 2023; 279:120294. [PMID: 37517572 PMCID: PMC10951962 DOI: 10.1016/j.neuroimage.2023.120294] [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: 05/12/2023] [Revised: 07/08/2023] [Accepted: 07/22/2023] [Indexed: 08/01/2023] Open
Abstract
Geometric distortion is a major limiting factor for spatial specificity in high-resolution fMRI using EPI readouts and is exacerbated at higher field strengths due to increased B0 field inhomogeneity. Prominent correction schemes are based on B0 field-mapping or acquiring reverse phase-encoded (reversed-PE) data. However, to date, comparisons of these techniques in the context of fMRI have only been performed on 2DEPI data, either at lower field or lower resolution. In this study, we investigate distortion compensation in the context of sub-millimetre 3DEPI data at 7T. B0 field-mapping and reversed-PE distortion correction techniques were applied to both partial coverage BOLD-weighted and whole brain MT-weighted 3DEPI data with matched distortion. Qualitative assessment showed overall improvement in cortical alignment for both correction techniques in both 3DEPI fMRI and whole-brain MT-3DEPI datasets. The distortion-corrected MT-3DEPI images were quantitatively evaluated by comparing cortical alignment with an anatomical reference using dice coefficient (DC) and correlation ratio (CR) measures. These showed that B0 field-mapping and reversed-PE methods both improved correspondence between the MT-3DEPI and anatomical data, with more substantial improvements consistently obtained using the reversed-PE approach. Regional analyses demonstrated that the largest benefit of distortion correction, and in particular of the reversed-PE approach, occurred in frontal and temporal regions where susceptibility-induced distortions are known to be greatest, but had not led to complete signal dropout. In conclusion, distortion correction based on reversed-PE data has shown the greater capacity for achieving faithful alignment with anatomical data in the context of high-resolution fMRI at 7T using 3DEPI.
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Affiliation(s)
- Vahid Malekian
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, UK.
| | - Nadine N Graedel
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, UK
| | - Alice Hickling
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, UK
| | - Ali Aghaeifar
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, UK; MR Research Collaborations, Siemens Healthcare Limited, Frimley, UK
| | - Barbara Dymerska
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, UK
| | - Nadège Corbin
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, UK; Centre de Résonance Magnétique des Systèmes Biologiques, CNRS-University Bordeaux, Bordeaux, France
| | - Oliver Josephs
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, UK
| | - Eleanor A Maguire
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, UK
| | - Martina F Callaghan
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, UK
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Domingos C, Fouto AR, Nunes RG, Ruiz-Tagle A, Esteves I, Silva NA, Vilela P, Gil-Gouveia R, Figueiredo P. Impact of susceptibility-induced distortion correction on perfusion imaging by pCASL with a segmented 3D GRASE readout. Magn Reson Imaging 2023:S0730-725X(23)00104-2. [PMID: 37343905 DOI: 10.1016/j.mri.2023.06.010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2023] [Revised: 05/18/2023] [Accepted: 06/17/2023] [Indexed: 06/23/2023]
Abstract
PURPOSE The consensus for the clinical implementation of arterial spin labeling (ASL) perfusion imaging recommends a segmented 3D Gradient and Spin-Echo (GRASE) readout for optimal signal-to-noise-ratio(SNR). The correction of the associated susceptibility-induced geometric distortions has been shown to improve diagnostic precision, but its impact on ASL data has not been systematically assessed and it is not consistently part of pre-processing pipelines. Here, we investigate the effects of susceptibility-induced distortion correction on perfusion imaging by pseudo-continuous ASL (pCASL) with a segmented 3D GRASE readout. METHODS Data acquired from 28 women using pCASL with 3D GRASE at 3T was analyzed using three pre-processing options: without distortion correction, with distortion correction, and with spatial smoothing (without distortion correction) matched to control for blurring effects induced by distortion correction. Maps of temporal SNR (tSNR) and relative perfusion were analyzed in eight regions-of-interest (ROIs) across the brain. RESULTS Distortion correction significantly affected tSNR and relative perfusion across the brain. Increases in tSNR were like those produced by matched spatial smoothing in most ROIs, indicating that they were likely due to blurring effects. However, that was not the case in the frontal and temporal lobes, where we also found increased relative perfusion with distortion correction even compared with matched spatial smoothing. These effects were found in both controls and patients, with no interactions with the participant group. CONCLUSION Correction of Susceptibility-induced distortions significantly impacts ASL perfusion imaging using a segmented 3D GRASE readout, and this step should therefore be considered in ASL pre-processing pipelines. This is of special importance in clinical studies, reporting perfusion across ROIs defined on relatively undistorted images and when conducting group analyses requiring the alignment of images across different subjects.
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Affiliation(s)
- Catarina Domingos
- Institute for Systems and Robotics - Lisboa and Department of Bioengineering, Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal; Agência Regional para o Desenvolvimento da Investigação, Tecnologia e Inovação, Funchal, Portugal.
| | - Ana R Fouto
- Institute for Systems and Robotics - Lisboa and Department of Bioengineering, Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal
| | - Rita G Nunes
- Institute for Systems and Robotics - Lisboa and Department of Bioengineering, Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal
| | - Amparo Ruiz-Tagle
- Institute for Systems and Robotics - Lisboa and Department of Bioengineering, Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal
| | - Inês Esteves
- Institute for Systems and Robotics - Lisboa and Department of Bioengineering, Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal
| | | | - Pedro Vilela
- Neurology Department, Hospital da Luz, Lisbon, Portugal
| | - Raquel Gil-Gouveia
- Neurology Department, Hospital da Luz, Lisbon, Portugal.; Center for Interdisciplinary Research in Health, Universidade Católica Portuguesa, Lisbon, Portugal
| | - Patrícia Figueiredo
- Institute for Systems and Robotics - Lisboa and Department of Bioengineering, Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal
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10
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Wang J, Nasr S, Roe AW, Polimeni JR. Critical factors in achieving fine-scale functional MRI: Removing sources of inadvertent spatial smoothing. Hum Brain Mapp 2022; 43:3311-3331. [PMID: 35417073 PMCID: PMC9248309 DOI: 10.1002/hbm.25867] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2021] [Revised: 03/04/2022] [Accepted: 03/30/2022] [Indexed: 11/09/2022] Open
Abstract
Ultra‐high Field (≥7T) functional magnetic resonance imaging (UHF‐fMRI) provides opportunities to resolve fine‐scale features of functional architecture such as cerebral cortical columns and layers, in vivo. While the nominal resolution of modern fMRI acquisitions may appear to be sufficient to resolve these features, several common data preprocessing steps can introduce unwanted spatial blurring, especially those that require interpolation of the data. These resolution losses can impede the detection of the fine‐scale features of interest. To examine quantitatively and systematically the sources of spatial resolution losses occurring during preprocessing, we used synthetic fMRI data and real fMRI data from the human visual cortex—the spatially interdigitated human V2 “thin” and “thick” stripes. The pattern of these cortical columns lies along the cortical surface and thus can be best appreciated using surface‐based fMRI analysis. We used this as a testbed for evaluating strategies that can reduce spatial blurring of fMRI data. Our results show that resolution losses can be mitigated at multiple points in preprocessing pathway. We show that unwanted blur is introduced at each step of volume transformation and surface projection, and can be ameliorated by replacing multi‐step transformations with equivalent single‐step transformations. Surprisingly, the simple approaches of volume upsampling and of cortical mesh refinement also helped to reduce resolution losses caused by interpolation. Volume upsampling also serves to improve motion estimation accuracy, which helps to reduce blur. Moreover, we demonstrate that the level of spatial blurring is nonuniform over the brain—knowledge which is critical for interpreting data in high‐resolution fMRI studies. Importantly, our study provides recommendations for reducing unwanted blurring during preprocessing as well as methods that enable quantitative comparisons between preprocessing strategies. These findings highlight several underappreciated sources of a spatial blur. Individually, the factors that contribute to spatial blur may appear to be minor, but in combination, the cumulative effects can hinder the interpretation of fine‐scale fMRI and the detectability of these fine‐scale features of functional architecture.
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Affiliation(s)
- Jianbao Wang
- Department of Neurosurgery of the Second Affiliated Hospital, Interdisciplinary Institute of Neuroscience and Technology, School of Medicine, Zhejiang University, Hangzhou, China.,Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA
| | - Shahin Nasr
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA.,Department of Radiology, Harvard Medical School, Charlestown, Massachusetts, USA
| | - Anna Wang Roe
- Department of Neurosurgery of the Second Affiliated Hospital, Interdisciplinary Institute of Neuroscience and Technology, School of Medicine, Zhejiang University, Hangzhou, China.,Key Laboratory for Biomedical Engineering of Ministry of Education, Zhejiang University, Hangzhou, China
| | - Jonathan R Polimeni
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA.,Department of Radiology, Harvard Medical School, Charlestown, Massachusetts, USA.,Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
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11
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Automated Brain Volumetry in Patients With Memory Impairment: Comparison of Conventional and Ultrafast 3D T1-weighted MRI Sequences Using Two Software Packages. AJR Am J Roentgenol 2022; 218:1062-1073. [DOI: 10.2214/ajr.21.27043] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/14/2023]
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12
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Chai Y, Li L, Wang Y, Huber L, Poser BA, Duyn J, Bandettini PA. Magnetization transfer weighted EPI facilitates cortical depth determination in native fMRI space. Neuroimage 2021; 242:118455. [PMID: 34364993 PMCID: PMC8520138 DOI: 10.1016/j.neuroimage.2021.118455] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2021] [Revised: 07/23/2021] [Accepted: 08/03/2021] [Indexed: 11/25/2022] Open
Abstract
The increased availability of ultra-high field scanners provides an opportunity to perform fMRI at sub-millimeter spatial scales and enables in vivo probing of laminar function in the human brain. In most previous studies, the definition of cortical layers, or depths, is based on an anatomical reference image that is collected by a different acquisition sequence and exhibits different geometric distortion compared to the functional images. Here, we propose to generate the anatomical image with the fMRI acquisition technique by incorporating magnetization transfer (MT) weighted imaging. Small flip angle binomial pulse trains are used as MT preparation, with a flexible duration (several to tens of milliseconds), which can be applied before each EPI segment without constraining the acquisition length (segment or slice number). The method's feasibility was demonstrated at 7T for coverage of either a small slab or the near-whole brain at 0.8 mm isotropic resolution. Tissue contrast was found to be similar to that obtained with a state-of-art anatomical reference based on MP2RAGE. This MT-weighted EPI image allows an automatic reconstruction of the cortical surface to support laminar analysis in native fMRI space, obviating the need for distortion correction and registration.
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Affiliation(s)
- Yuhui Chai
- Section on Functional Imaging Methods, Laboratory of Brain and Cognition, NIMH, NIH, Bethesda 20892, MD, United States.
| | - Linqing Li
- Functional MRI Core, NIMH, NIH, Bethesda, MD, United States
| | - Yicun Wang
- Advanced MRI Section, Laboratory of Functional and Molecular Imaging, NINDS, NIH, Bethesda, MD, United States
| | - Laurentius Huber
- Maastricht Brain Imaging Center, Faculty of Psychology and Neuroscience, University of Maastricht, the Netherlands
| | - Benedikt A Poser
- Maastricht Brain Imaging Center, Faculty of Psychology and Neuroscience, University of Maastricht, the Netherlands
| | - Jeff Duyn
- Advanced MRI Section, Laboratory of Functional and Molecular Imaging, NINDS, NIH, Bethesda, MD, United States
| | - Peter A Bandettini
- Section on Functional Imaging Methods, Laboratory of Brain and Cognition, NIMH, NIH, Bethesda 20892, MD, United States; Functional MRI Core, NIMH, NIH, Bethesda, MD, United States
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13
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Manhard MK, Stockmann J, Liao C, Park D, Han S, Fair M, van den Boomen M, Polimeni J, Bilgic B, Setsompop K. A multi-inversion multi-echo spin and gradient echo echo planar imaging sequence with low image distortion for rapid quantitative parameter mapping and synthetic image contrasts. Magn Reson Med 2021; 86:866-880. [PMID: 33764563 PMCID: PMC8793364 DOI: 10.1002/mrm.28761] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2020] [Revised: 02/02/2021] [Accepted: 02/12/2021] [Indexed: 02/06/2023]
Abstract
PURPOSE Brain imaging exams typically take 10-20 min and involve multiple sequential acquisitions. A low-distortion whole-brain echo planar imaging (EPI)-based approach was developed to efficiently encode multiple contrasts in one acquisition, allowing for calculation of quantitative parameter maps and synthetic contrast-weighted images. METHODS Inversion prepared spin- and gradient-echo EPI was developed with slice-order shuffling across measurements for efficient acquisition with T1 , T2 , and T 2 ∗ weighting. A dictionary-matching approach was used to fit the images to quantitative parameter maps, which in turn were used to create synthetic weighted images with typical clinical contrasts. Dynamic slice-optimized multi-coil shimming with a B0 shim array was used to reduce B0 inhomogeneity and, therefore, image distortion by >50%. Multi-shot EPI was also implemented to minimize distortion and blurring while enabling high in-plane resolution. A low-rank reconstruction approach was used to mitigate errors from shot-to-shot phase variation. RESULTS The slice-optimized shimming approach was combined with in-plane parallel-imaging acceleration of 4× to enable single-shot EPI with more than eight-fold distortion reduction. The proposed sequence efficiently obtained 40 contrasts across the whole-brain in just over 1 min at 1.2 × 1.2 × 3 mm resolution. The multi-shot variant of the sequence achieved higher in-plane resolution of 1 × 1 × 4 mm with good image quality in 4 min. Derived quantitative maps showed comparable values to conventional mapping methods. CONCLUSION The approach allows fast whole-brain imaging with quantitative parameter maps and synthetic weighted contrasts. The slice-optimized multi-coil shimming and multi-shot reconstruction approaches result in minimal EPI distortion, giving the sequence the potential to be used in rapid screening applications.
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Affiliation(s)
- Mary Kate Manhard
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
- Department of Radiology, Harvard Medical School, Boston, MA, USA
| | - Jason Stockmann
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
- Department of Radiology, Harvard Medical School, Boston, MA, USA
| | - Congyu Liao
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
- Department of Radiology, Harvard Medical School, Boston, MA, USA
| | - Daniel Park
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
| | - Sohyun Han
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
- Center for Neuroscience Imaging Research, Institute for Basic Science (IBS), Suwon, Korea, Republic of
| | - Merlin Fair
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
- Department of Radiology, Harvard Medical School, Boston, MA, USA
| | - Maaike van den Boomen
- Department of Radiology, Harvard Medical School, Boston, MA, USA
- Department of Radiology, University Medical Center Groningen, University of Groningen, Groningen, Netherlands
| | - Jon Polimeni
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
- Department of Radiology, Harvard Medical School, Boston, MA, USA
- Harvard-MIT Division of Health Sciences and Technology, Cambridge, MA, USA
| | - Berkin Bilgic
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
- Department of Radiology, Harvard Medical School, Boston, MA, USA
| | - Kawin Setsompop
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
- Department of Radiology, Harvard Medical School, Boston, MA, USA
- Harvard-MIT Division of Health Sciences and Technology, Cambridge, MA, USA
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14
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Cole M, Murray K, St‐Onge E, Risk B, Zhong J, Schifitto G, Descoteaux M, Zhang Z. Surface-Based Connectivity Integration: An atlas-free approach to jointly study functional and structural connectivity. Hum Brain Mapp 2021; 42:3481-3499. [PMID: 33956380 PMCID: PMC8249904 DOI: 10.1002/hbm.25447] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2020] [Revised: 03/03/2021] [Accepted: 04/06/2021] [Indexed: 01/29/2023] Open
Abstract
There has been increasing interest in jointly studying structural connectivity (SC) and functional connectivity (FC) derived from diffusion and functional MRI. Previous connectome integration studies almost exclusively required predefined atlases. However, there are many potential atlases to choose from and this choice heavily affects all subsequent analyses. To avoid such an arbitrary choice, we propose a novel atlas-free approach, named Surface-Based Connectivity Integration (SBCI), to more accurately study the relationships between SC and FC throughout the intra-cortical gray matter. SBCI represents both SC and FC in a continuous manner on the white surface, avoiding the need for prespecified atlases. The continuous SC is represented as a probability density function and is smoothed for better facilitation of its integration with FC. To infer the relationship between SC and FC, three novel sets of SC-FC coupling (SFC) measures are derived. Using data from the Human Connectome Project, we introduce the high-quality SFC measures produced by SBCI and demonstrate the use of these measures to study sex differences in a cohort of young adults. Compared with atlas-based methods, this atlas-free framework produces more reproducible SFC features and shows greater predictive power in distinguishing biological sex. This opens promising new directions for all connectomics studies.
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Affiliation(s)
- Martin Cole
- Department of Biostatistics and Computational BiologyUniversity of RochesterRochesterNew YorkUSA
| | - Kyle Murray
- Department of Physics and AstronomyUniversity of RochesterRochesterNew YorkUSA
| | - Etienne St‐Onge
- Sherbrooke Connectivity Imaging Laboratory (SCIL)Université de SherbrookeQuébecCanada
| | - Benjamin Risk
- Department of Biostatistics and BioinformaticsEmory UniversityAtlantaGeorgiaUSA
| | - Jianhui Zhong
- Department of Physics and AstronomyUniversity of RochesterRochesterNew YorkUSA
- Department of Imaging SciencesUniversity of RochesterRochesterNew YorkUSA
| | - Giovanni Schifitto
- Department of Imaging SciencesUniversity of RochesterRochesterNew YorkUSA
- Department of NeurologyUniversity of RochesterRochesterNew YorkUSA
| | - Maxime Descoteaux
- Sherbrooke Connectivity Imaging Laboratory (SCIL)Université de SherbrookeQuébecCanada
| | - Zhengwu Zhang
- Department of Statistics and Operations ResearchUniversity of North Carolina at Chapel HillNorth CarolinaUSA
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15
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Little G, Beaulieu C. Automated cerebral cortex segmentation based solely on diffusion tensor imaging for investigating cortical anisotropy. Neuroimage 2021; 237:118105. [PMID: 33933593 DOI: 10.1016/j.neuroimage.2021.118105] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2020] [Revised: 04/14/2021] [Accepted: 04/16/2021] [Indexed: 10/21/2022] Open
Abstract
To extract Diffusion Tensor Imaging (DTI) parameters from the human cortex, the inner and outer boundaries of the cortex are usually defined on 3D-T1-weighted images and then applied to the co-registered DTI. However, this analysis requires the acquisition of an additional high-resolution structural image that may not be practical in various imaging studies. Here an automatic cortical boundary segmentation method was developed to work directly only on the native DTI images by using fractional anisotropy (FA) maps and mean diffusion weighted images (DWI), the latter with acceptable gray-white matter image contrast. This new method was compared to the conventional cortical segmentations generated from high-resolution T1 structural images in 5 participants. In addition, the proposed method was applied to 15 healthy young adults (10 cross-sectional, 5 test-retest) to measure FA, MD, and radiality of the primary eigenvector across the cortex on whole-brain 1.5 mm isotropic images acquired in 3.5 min at 3T. The proposed method generated reasonable segmentations of the cortical boundaries for all individuals and large proportions of the proposed method segmentations (more than 85%) were within ±1 mm from those generated with the conventional approach on higher resolution T1 structural images. Both FA (~0.15) and MD (~0.77 × 10-3 mm2/s) extracted halfway between the cortical boundaries were relatively stable across the cortex, although focal regions such as the posterior bank of the central sulcus, anterior insula, and medial temporal lobe showed higher FA. The primary eigenvectors were primarily oriented radially to the middle cortical surface, but there were tangential orientations in the sulcal fundi as well as in the posterior bank of the central sulcus. The proposed method demonstrates the feasibility and accuracy of cortical analysis in native DTI space while avoiding the acquisition of other imaging contrasts like 3D T1-weighted scans.
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Affiliation(s)
- Graham Little
- Department of Biomedical Engineering, University of Alberta, 1098 Research Transition Facility, 8308-114 Street, Edmonton, Alberta T6G 2V2, Canada.
| | - Christian Beaulieu
- Department of Biomedical Engineering, University of Alberta, 1098 Research Transition Facility, 8308-114 Street, Edmonton, Alberta T6G 2V2, Canada.
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16
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Sanchez Panchuelo RM, Mougin O, Turner R, Francis ST. Quantitative T1 mapping using multi-slice multi-shot inversion recovery EPI. Neuroimage 2021; 234:117976. [PMID: 33781969 PMCID: PMC8204273 DOI: 10.1016/j.neuroimage.2021.117976] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2020] [Revised: 02/27/2021] [Accepted: 03/13/2021] [Indexed: 11/12/2022] Open
Abstract
An efficient multi-slice inversion–recovery EPI (MS-IR-EPI) sequence for fast, high spatial resolution, quantitative T1 mapping is presented, using a segmented simultaneous multi-slice acquisition, combined with slice order shifting across multiple acquisitions. The segmented acquisition minimises the effective TE and readout duration compared to a single-shot EPI scheme, reducing geometric distortions to provide high quality T1 maps with a narrow point-spread function. The precision and repeatability of MS-IR-EPI T1 measurements are assessed using both T1-calibrated and T2-calibrated ISMRM/NIST phantom spheres at 3 and 7 T and compared with single slice IR and MP2RAGE methods. Magnetization transfer (MT) effects of the spectrally-selective fat-suppression (FS) pulses required for in vivo imaging are shown to shorten the measured in-vivo T1 values. We model the effect of these fat suppression pulses on T1 measurements and show that the model can remove their MT contribution from the measured T1, thus providing accurate T1 quantification. High spatial resolution T1 maps of the human brain generated with MS-IR-EPI at 7 T are compared with those generated with the widely implemented MP2RAGE sequence. Our MS-IR-EPI sequence provides high SNR per unit time and sharper T1 maps than MP2RAGE, demonstrating the potential for ultra-high resolution T1 mapping and the improved discrimination of functionally relevant cortical areas in the human brain.
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Affiliation(s)
- Rosa M Sanchez Panchuelo
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, Nottingham, United Kingdom; NIHR Nottingham Biomedical Research Centre, University of Nottingham, Nottingham, United Kingdom.
| | - Olivier Mougin
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, Nottingham, United Kingdom
| | - Robert Turner
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, Nottingham, United Kingdom; Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Susan T Francis
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, Nottingham, United Kingdom; NIHR Nottingham Biomedical Research Centre, University of Nottingham, Nottingham, United Kingdom
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17
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Leppert IR, Andrews DA, Campbell JSW, Park DJ, Pike GB, Polimeni JR, Tardif CL. Efficient whole-brain tract-specific T 1 mapping at 3T with slice-shuffled inversion-recovery diffusion-weighted imaging. Magn Reson Med 2021; 86:738-753. [PMID: 33749017 DOI: 10.1002/mrm.28734] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2020] [Revised: 12/31/2020] [Accepted: 01/25/2021] [Indexed: 02/06/2023]
Abstract
PURPOSE Most voxels in white matter contain multiple fiber populations with different orientations and levels of myelination. Conventional T1 mapping measures 1 T1 value per voxel, representing a weighted average of the multiple tract T1 times. Inversion-recovery diffusion-weighted imaging (IR-DWI) allows the T1 times of multiple tracts in a voxel to be disentangled, but the scan time is prohibitively long. Recently, slice-shuffled IR-DWI implementations have been proposed to significantly reduce scan time. In this work, we demonstrate that we can measure tract-specific T1 values in the whole brain using simultaneous multi-slice slice-shuffled IR-DWI at 3T. METHODS We perform simulations to evaluate the accuracy and precision of our crossing fiber IR-DWI signal model for various fiber parameters. The proposed sequence and signal model are tested in a phantom consisting of crossing asparagus pieces doped with gadolinium to vary T1 , and in 2 human subjects. RESULTS Our simulations show that tract-specific T1 times can be estimated within 5% of the nominal fiber T1 values. Tract-specific T1 values were resolved in subvoxel 2 fiber crossings in the asparagus phantom. Tract-specific T1 times were resolved in 2 different tract crossings in the human brain where myelination differences have previously been reported; the crossing of the cingulum and genu of the corpus callosum and the crossing of the corticospinal tract and pontine fibers. CONCLUSION Whole-brain tract-specific T1 mapping is feasible using slice-shuffled IR-DWI at 3T. This technique has the potential to improve the microstructural characterization of specific tracts implicated in neurodevelopment, aging, and demyelinating disorders.
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Affiliation(s)
- Ilana R Leppert
- McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, Montreal, Quebec, Canada
| | - Daniel A Andrews
- McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, Montreal, Quebec, Canada.,Department of Biomedical Engineering, McGill University, Montreal, Quebec, Canada
| | - Jennifer S W Campbell
- McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, Montreal, Quebec, Canada
| | - Daniel J Park
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA
| | - G Bruce Pike
- Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada.,Department of Radiology and Department of Clinical Neuroscience, University of Calgary, Calgary, Alberta, Canada
| | - Jonathan R Polimeni
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA.,Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA.,Department of Radiology, Harvard Medical School, Boston, Massachusetts, USA
| | - Christine L Tardif
- McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, Montreal, Quebec, Canada.,Department of Biomedical Engineering, McGill University, Montreal, Quebec, Canada.,Department of Neurology and Neurosurgery, McGill University, Montreal, Quebec, Canada
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18
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Tootell RBH, Nasr S. Scotopic Vision Is Selectively Processed in Thick-Type Columns in Human Extrastriate Cortex. Cereb Cortex 2021; 31:1163-1181. [PMID: 33073288 PMCID: PMC7786355 DOI: 10.1093/cercor/bhaa284] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2020] [Revised: 07/25/2020] [Accepted: 08/17/2020] [Indexed: 11/26/2022] Open
Abstract
In humans, visual stimuli can be perceived across an enormous range of light levels. Evidence suggests that different neural mechanisms process different subdivisions of this range. For instance, in the retina, stimuli presented at very low (scotopic) light levels activate rod photoreceptors, whereas cone photoreceptors are activated relatively more at higher (photopic) light levels. Similarly, different retinal ganglion cells are activated by scotopic versus photopic stimuli. However, in the brain, it remains unknown whether scotopic versus photopic information is: 1) processed in distinct channels, or 2) neurally merged. Using high-resolution functional magnetic resonance imaging at 7 T, we confirmed the first hypothesis. We first localized thick versus thin-type columns within areas V2, V3, and V4, based on photopic selectivity to motion versus color, respectively. Next, we found that scotopic stimuli selectively activated thick- (compared to thin-) type columns in V2 and V3 (in measurements of both overlap and amplitude) and V4 (based on overlap). Finally, we found stronger resting-state functional connections between scotopically dominated area MT with thick- (compared to thin-) type columns in areas V2, V3, and V4. We conclude that scotopic stimuli are processed in partially segregated parallel streams, emphasizing magnocellular influence, from retina through middle stages of visual cortex.
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Affiliation(s)
- Roger B H Tootell
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA 02114, USA.,Department of Radiology, Harvard Medical School, Boston, MA 02115, USA
| | - Shahin Nasr
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA 02114, USA.,Department of Radiology, Harvard Medical School, Boston, MA 02115, USA
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19
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Stirnberg R, Stöcker T. Segmented K-space blipped-controlled aliasing in parallel imaging for high spatiotemporal resolution EPI. Magn Reson Med 2020; 85:1540-1551. [PMID: 32936488 DOI: 10.1002/mrm.28486] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2020] [Revised: 07/29/2020] [Accepted: 07/30/2020] [Indexed: 12/16/2022]
Abstract
PURPOSE A segmented k-space blipped-controlled aliasing in parallel imaging (skipped-CAIPI) sampling strategy for EPI is proposed, which allows for a flexible choice of EPI factor and phase encode bandwidth independent of the controlled aliasing in parallel imaging (CAIPI) sampling pattern. THEORY AND METHODS With previously proposed approaches, exactly two EPI trajectories were possible given a specific CAIPI pattern, either with slice gradient blips (blipped-CAIPI) or following a shot-selective CAIPI approach (higher resolution). Recently, interleaved multi-shot segmentation along shot-selective CAIPI trajectories has been applied for high-resolution anatomical imaging. For more flexibility and a broader range of applications, we propose segmentation along any blipped-CAIPI trajectory. Thus, all EPI factors and phase encode bandwidths available with traditional segmented EPI can be combined with controlled aliasing. RESULTS Temporal SNR maps of moderate-to-high-resolution time series acquisitions at varying undersampling factors demonstrate beneficial sampling alternatives to blipped-CAIPI or shot-selective CAIPI. Rapid high-resolution scans furthermore demonstrate SNR-efficient and motion-robust structural imaging with almost arbitrary EPI factor and minimal noise penalty. CONCLUSION Skipped-CAIPI sampling increases protocol flexibility for high spatiotemporal resolution EPI. In terms of SNR and efficiency, high-resolution functional or structural scans benefit vastly from a free choice of the CAIPI pattern. Even at moderate resolutions, the independence of sampling pattern, TE, and image matrix size is valuable for optimized functional protocol design. Although demonstrated with 3D-EPI, skipped-CAIPI is also applicable with simultaneous multislice EPI.
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Affiliation(s)
| | - Tony Stöcker
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany.,Department of Physics and Astronomy, University of Bonn, Bonn, Germany
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20
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Beckett AJS, Dadakova T, Townsend J, Huber L, Park S, Feinberg DA. Comparison of BOLD and CBV using 3D EPI and 3D GRASE for cortical layer functional MRI at 7 T. Magn Reson Med 2020; 84:3128-3145. [PMID: 32557752 DOI: 10.1002/mrm.28347] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2019] [Revised: 05/12/2020] [Accepted: 05/14/2020] [Indexed: 01/27/2023]
Abstract
PURPOSE Functional MRI (fMRI) at the mesoscale of cortical layers and columns requires both sensitivity and specificity, the latter of which can be compromised if the imaging method is affected by vascular artifacts, particularly cortical draining veins at the pial surface. Recent studies have shown that cerebral blood volume (CBV) imaging is more specific to the actual laminar locus of neural activity than BOLD imaging using standard gradient-echo EPI sequences. Gradient and spin-echo (GRASE) BOLD imaging has also shown greater specificity when compared with standard gradient-echo EPI BOLD. Here we directly compare CBV and BOLD contrasts in high-resolution imaging of the primary motor cortex for laminar functional MRI in four combinations of signal labeling, CBV using slice-selective slab-inversion vascular space occupancy (VASO) and BOLD, each with 3D gradient-echo EPI and zoomed 3D-GRASE image readouts. METHODS Activations were measured using each sequence and contrast combination during a motor task. Activation profiles across cortical depth were measured to assess the sensitivity and specificity (pial bias) of each method. RESULTS Both CBV imaging using gradient-echo 3D-EPI and BOLD imaging using 3D-GRASE show similar specificity and sensitivity and are therefore useful tools for mesoscopic functional MRI in the human cortex. The combination of GRASE and VASO did not demonstrate high levels of sensitivity, nor show increased specificity. CONCLUSION Three-dimensional EPI with VASO contrast and 3D-GRASE with BOLD contrast both demonstrate sufficient sensitivity and specificity for laminar functional MRI to be used by neuroscientists in a wide range of investigations of depth-dependent neural circuitry in the human brain.
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Affiliation(s)
- Alexander J S Beckett
- Helen Wills Neuroscience Institute, University of California, Berkeley, California, USA.,Advanced MRI Technologies, Sebastopol, California, USA
| | - Tetiana Dadakova
- Helen Wills Neuroscience Institute, University of California, Berkeley, California, USA
| | - Jennifer Townsend
- Helen Wills Neuroscience Institute, University of California, Berkeley, California, USA.,Advanced MRI Technologies, Sebastopol, California, USA
| | - Laurentius Huber
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, the Netherlands
| | - Suhyung Park
- Helen Wills Neuroscience Institute, University of California, Berkeley, California, USA.,Advanced MRI Technologies, Sebastopol, California, USA
| | - David A Feinberg
- Helen Wills Neuroscience Institute, University of California, Berkeley, California, USA.,Advanced MRI Technologies, Sebastopol, California, USA
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21
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Layer-Specific Contributions to Imagined and Executed Hand Movements in Human Primary Motor Cortex. Curr Biol 2020; 30:1721-1725.e3. [PMID: 32220318 DOI: 10.1016/j.cub.2020.02.046] [Citation(s) in RCA: 29] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2019] [Revised: 01/10/2020] [Accepted: 02/17/2020] [Indexed: 11/23/2022]
Abstract
The human ability to imagine motor actions without executing them (i.e., motor imagery) is crucial to a number of cognitive functions, including motor planning and learning, and has been shown to improve response times and accuracy of subsequent motor actions [1, 2]. Although these behavioral findings suggest the possibility that imagined movements directly influence primary motor cortex (M1), how this might occur remains unknown [3]. Here, we use a non-blood-oxygen-level-dependent (BOLD) method for collecting fMRI data, called vascular space occupancy (VASO) [4, 5], to measure neural activations across cortical laminae in M1 while participants either tapped their thumb and forefinger together or simply imagined doing so. We report that, whereas executed movements (i.e., finger tapping) evoked neural responses in both the superficial layers of M1 that receive cortical input and the deep layers of M1 that send output to the spinal cord to support movement, imagined movements evoked responses in superficial cortical layers only. Furthermore, we found that finger tapping preceded by both imagined and executed movements showed a reduced response in the superficial layers (repetition suppression) coupled with a heightened response in the deep layers (repetition enhancement). Taken together, our results provide evidence for a mechanism whereby imagined movements can directly affect motor performance and might explain how neural repetition effects lead to improvements in behavior (e.g., repetition priming).
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Bause J, Polimeni JR, Stelzer J, In MH, Ehses P, Kraemer-Fernandez P, Aghaeifar A, Lacosse E, Pohmann R, Scheffler K. Impact of prospective motion correction, distortion correction methods and large vein bias on the spatial accuracy of cortical laminar fMRI at 9.4 Tesla. Neuroimage 2020; 208:116434. [DOI: 10.1016/j.neuroimage.2019.116434] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2019] [Revised: 11/08/2019] [Accepted: 12/02/2019] [Indexed: 01/24/2023] Open
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Norbeck O, Sprenger T, Avventi E, Rydén H, Kits A, Berglund J, Skare S. Optimizing 3D EPI for rapid T
1
‐weighted imaging. Magn Reson Med 2020; 84:1441-1455. [DOI: 10.1002/mrm.28222] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2019] [Revised: 01/14/2020] [Accepted: 01/29/2020] [Indexed: 01/17/2023]
Affiliation(s)
- Ola Norbeck
- Department of Neuroradiology Karolinska University Hospital Stockholm Sweden
- Department of Clinical Neuroscience Karolinska Institutet Stockholm Sweden
| | - Tim Sprenger
- MR Applied Science Laboratory Europe, GE Healthcare Stockholm Sweden
| | - Enrico Avventi
- Department of Neuroradiology Karolinska University Hospital Stockholm Sweden
- Department of Clinical Neuroscience Karolinska Institutet Stockholm Sweden
| | - Henric Rydén
- Department of Neuroradiology Karolinska University Hospital Stockholm Sweden
- Department of Clinical Neuroscience Karolinska Institutet Stockholm Sweden
| | - Annika Kits
- Department of Neuroradiology Karolinska University Hospital Stockholm Sweden
- Department of Clinical Neuroscience Karolinska Institutet Stockholm Sweden
| | - Johan Berglund
- Department of Clinical Neuroscience Karolinska Institutet Stockholm Sweden
| | - Stefan Skare
- Department of Neuroradiology Karolinska University Hospital Stockholm Sweden
- Department of Clinical Neuroscience Karolinska Institutet Stockholm Sweden
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Bilgic B, Chatnuntawech I, Manhard MK, Tian Q, Liao C, Iyer SS, Cauley SF, Huang SY, Polimeni JR, Wald LL, Setsompop K. Highly accelerated multishot echo planar imaging through synergistic machine learning and joint reconstruction. Magn Reson Med 2019; 82:1343-1358. [PMID: 31106902 PMCID: PMC6626584 DOI: 10.1002/mrm.27813] [Citation(s) in RCA: 27] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2018] [Revised: 04/22/2019] [Accepted: 04/22/2019] [Indexed: 12/13/2022]
Abstract
PURPOSE To introduce a combined machine learning (ML)- and physics-based image reconstruction framework that enables navigator-free, highly accelerated multishot echo planar imaging (msEPI) and demonstrate its application in high-resolution structural and diffusion imaging. METHODS Single-shot EPI is an efficient encoding technique, but does not lend itself well to high-resolution imaging because of severe distortion artifacts and blurring. Although msEPI can mitigate these artifacts, high-quality msEPI has been elusive because of phase mismatch arising from shot-to-shot variations which preclude the combination of the multiple-shot data into a single image. We utilize deep learning to obtain an interim image with minimal artifacts, which permits estimation of image phase variations attributed to shot-to-shot changes. These variations are then included in a joint virtual coil sensitivity encoding (JVC-SENSE) reconstruction to utilize data from all shots and improve upon the ML solution. RESULTS Our combined ML + physics approach enabled Rinplane × multiband (MB) = 8- × 2-fold acceleration using 2 EPI shots for multiecho imaging, so that whole-brain T2 and T2 * parameter maps could be derived from an 8.3-second acquisition at 1 × 1 × 3-mm3 resolution. This has also allowed high-resolution diffusion imaging with high geometrical fidelity using 5 shots at Rinplane × MB = 9- × 2-fold acceleration. To make these possible, we extended the state-of-the-art MUSSELS reconstruction technique to simultaneous multislice encoding and used it as an input to our ML network. CONCLUSION Combination of ML and JVC-SENSE enabled navigator-free msEPI at higher accelerations than previously possible while using fewer shots, with reduced vulnerability to poor generalizability and poor acceptance of end-to-end ML approaches.
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Affiliation(s)
- Berkin Bilgic
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, USA
- Department of Radiology, Harvard Medical School, Boston, MA, USA
- Harvard-MIT Health Sciences and Technology, MIT, Cambridge, MA, USA
| | - Itthi Chatnuntawech
- National Nanotechnology Center, National Science and Technology Development Agency, Pathum Thani, Thailand
| | - Mary Kate Manhard
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, USA
- Department of Radiology, Harvard Medical School, Boston, MA, USA
| | - Qiyuan Tian
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, USA
- Department of Radiology, Harvard Medical School, Boston, MA, USA
| | - Congyu Liao
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, USA
- Department of Radiology, Harvard Medical School, Boston, MA, USA
| | - Siddharth S. Iyer
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, USA
- Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Stephen F. Cauley
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, USA
- Department of Radiology, Harvard Medical School, Boston, MA, USA
| | - Susie Y. Huang
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, USA
- Department of Radiology, Harvard Medical School, Boston, MA, USA
- Harvard-MIT Health Sciences and Technology, MIT, Cambridge, MA, USA
| | - Jonathan R. Polimeni
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, USA
- Department of Radiology, Harvard Medical School, Boston, MA, USA
- Harvard-MIT Health Sciences and Technology, MIT, Cambridge, MA, USA
| | - Lawrence L. Wald
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, USA
- Department of Radiology, Harvard Medical School, Boston, MA, USA
- Harvard-MIT Health Sciences and Technology, MIT, Cambridge, MA, USA
| | - Kawin Setsompop
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, USA
- Department of Radiology, Harvard Medical School, Boston, MA, USA
- Harvard-MIT Health Sciences and Technology, MIT, Cambridge, MA, USA
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Brainstem neuroimaging of nociception and pain circuitries. Pain Rep 2019; 4:e745. [PMID: 31579846 PMCID: PMC6727990 DOI: 10.1097/pr9.0000000000000745] [Citation(s) in RCA: 34] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2019] [Revised: 03/22/2019] [Accepted: 03/24/2019] [Indexed: 01/09/2023] Open
Abstract
The brainstem is known to be an important brain area for nociception and pain processing, and both relaying and coordinating signaling between the cerebrum, cerebellum, and spinal cord. Although preclinical models of pain have characterized the many roles that brainstem nuclei play in nociceptive processing, the degree to which these circuitries extend to humans is not as well known. Unfortunately, the brainstem is also a very challenging region to evaluate in humans with neuroimaging. The challenges for human brainstem imaging arise from the location of this elongated brain structure, proximity to cardiorespiratory noise sources, and the size of its constituent nuclei. These challenges can require dedicated approaches to brainstem imaging, which should be adopted when study hypotheses are focused on brainstem processing of nociception or modulation of pain perception. In fact, our review will highlight many pain neuroimaging studies that have reported some brainstem involvement in nociceptive processing and chronic pain pathology. However, we note that with recent advances in neuroimaging leading to improved spatial and temporal resolution, more studies are needed that take advantage of data collection and analysis methods focused on the challenges of brainstem neuroimaging.
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Non-BOLD contrast for laminar fMRI in humans: CBF, CBV, and CMRO2. Neuroimage 2019; 197:742-760. [DOI: 10.1016/j.neuroimage.2017.07.041] [Citation(s) in RCA: 78] [Impact Index Per Article: 15.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2017] [Revised: 07/10/2017] [Accepted: 07/19/2017] [Indexed: 12/22/2022] Open
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Functional Involvement of Human Periaqueductal Gray and Other Midbrain Nuclei in Cognitive Control. J Neurosci 2019; 39:6180-6189. [PMID: 31160537 DOI: 10.1523/jneurosci.2043-18.2019] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2019] [Revised: 05/22/2019] [Accepted: 05/28/2019] [Indexed: 12/16/2022] Open
Abstract
Recent theoretical advances have motivated the hypothesis that the periaqueductal gray (PAG) participates in behaviors that involve changes in the autonomic control of visceromotor activity, including during cognitively demanding tasks. We used ultra-high-field (7 tesla) fMRI to measure human brain activity at 1.1 mm resolution while participants completed a working memory task. Consistent with prior work, participants were less accurate and responded more slowly with increasing memory load-signs of increasing task difficulty. Whole-brain fMRI analysis revealed increased activity in multiple cortical areas with increasing working memory load, including frontal and parietal cortex, dorsal cingulate, supplementary motor area, and anterior insula. Several dopamine-rich midbrain nuclei, such as the substantia nigra and ventral tegmental area, also exhibited load-dependent increases in activation. To investigate PAG involvement during cognitive engagement, we developed an automated method for segmenting and spatially normalizing the PAG. Analyses using cross-validated linear support vector machines showed that the PAG discriminated high versus low working memory load conditions with 95% accuracy in individual subjects based on activity increases in lateral and ventrolateral PAG. Effect sizes in the PAG were comparable in magnitude to those in many of the cortical areas. These findings suggest that cognitive control is not only associated with cortical activity in the frontal and parietal lobes, but also with increased activity in the subcortical PAG and other midbrain regions involved in the regulation of autonomic nervous system function.SIGNIFICANCE STATEMENT Functional neuroimaging in humans has shown that cognitive control engages multiple corticostriatal networks and brainstem nuclei, but theoretical advances suggest that the periaqueductal gray (PAG) should also be engaged during cognitively demanding tasks. Recent advances in ultra-high-field fMRI provided an opportunity to obtain the first evidence that increased activation of intermediate and rostral portions of lateral and ventrolateral PAG columns in humans is modulated by cognitive load. These findings suggest that cognitive control is not solely mediated by activity in the cortex, but that midbrain structures important for autonomic regulation also play a crucial role in higher-order cognition.
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Kay K, Jamison KW, Vizioli L, Zhang R, Margalit E, Ugurbil K. A critical assessment of data quality and venous effects in sub-millimeter fMRI. Neuroimage 2019; 189:847-869. [PMID: 30731246 PMCID: PMC7737092 DOI: 10.1016/j.neuroimage.2019.02.006] [Citation(s) in RCA: 56] [Impact Index Per Article: 11.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2018] [Revised: 02/02/2019] [Accepted: 02/04/2019] [Indexed: 01/07/2023] Open
Abstract
Advances in hardware, pulse sequences, and reconstruction techniques have made it possible to perform functional magnetic resonance imaging (fMRI) at sub-millimeter resolution while maintaining high spatial coverage and acceptable signal-to-noise ratio. Here, we examine whether sub-millimeter fMRI can be used as a routine method for obtaining accurate measurements of fine-scale local neural activity. We conducted fMRI in human visual cortex during a simple event-related visual experiment (7 T, gradient-echo EPI, 0.8-mm isotropic voxels, 2.2-s sampling rate, 84 slices), and developed analysis and visualization tools to assess the quality of the data. Our results fall along three lines of inquiry. First, we find that the acquired fMRI images, combined with appropriate surface-based processing, provide reliable and accurate measurements of fine-scale blood oxygenation level dependent (BOLD) activity patterns. Second, we show that the highly folded structure of cortex causes substantial biases on spatial resolution and data visualization. Third, we examine the well-recognized issue of venous contributions to fMRI signals. In a systematic assessment of large sections of cortex measured at a fine scale, we show that time-averaged T2*-weighted EPI intensity is a simple, robust marker of venous effects. These venous effects are unevenly distributed across cortex, are more pronounced in gyri and outer cortical depths, and are, to a certain degree, in consistent locations across subjects relative to cortical folding. Furthermore, we show that these venous effects are strongly correlated with BOLD responses evoked by the experiment. We conclude that sub-millimeter fMRI can provide robust information about fine-scale BOLD activity patterns, but special care must be exercised in visualizing and interpreting these patterns, especially with regards to the confounding influence of the brain's vasculature. To help translate these methodological findings to neuroscience research, we provide practical suggestions for both high-resolution and standard-resolution fMRI studies.
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Affiliation(s)
- Kendrick Kay
- Center for Magnetic Resonance Research (CMRR), Department of Radiology, University of Minnesota, USA.
| | - Keith W Jamison
- Center for Magnetic Resonance Research (CMRR), Department of Radiology, University of Minnesota, USA
| | - Luca Vizioli
- Center for Magnetic Resonance Research (CMRR), Department of Radiology, University of Minnesota, USA
| | - Ruyuan Zhang
- Center for Magnetic Resonance Research (CMRR), Department of Radiology, University of Minnesota, USA
| | - Eshed Margalit
- Stanford Neurosciences Institute, Stanford University, USA
| | - Kamil Ugurbil
- Center for Magnetic Resonance Research (CMRR), Department of Radiology, University of Minnesota, USA
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29
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Shrestha M, Nöth U, Deichmann R. Improved signal-to-noise ratio in EPI sequences with highly asymmetric spin echo and highly asymmetric STEAM preparations (HASE-EPI and HASTEAM-EPI). MAGNETIC RESONANCE MATERIALS IN PHYSICS BIOLOGY AND MEDICINE 2019; 32:549-558. [DOI: 10.1007/s10334-019-00749-z] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/19/2018] [Revised: 03/12/2019] [Accepted: 03/13/2019] [Indexed: 12/20/2022]
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Blazejewska AI, Fischl B, Wald LL, Polimeni JR. Intracortical smoothing of small-voxel fMRI data can provide increased detection power without spatial resolution losses compared to conventional large-voxel fMRI data. Neuroimage 2019; 189:601-614. [PMID: 30690157 DOI: 10.1016/j.neuroimage.2019.01.054] [Citation(s) in RCA: 30] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2018] [Revised: 12/17/2018] [Accepted: 01/19/2019] [Indexed: 10/27/2022] Open
Abstract
Continued improvement in MRI acquisition technology has made functional MRI (fMRI) with small isotropic voxel sizes down to 1 mm and below more commonly available. Although many conventional fMRI studies seek to investigate regional patterns of cortical activation for which conventional voxel sizes of 3 mm and larger provide sufficient spatial resolution, smaller voxels can help avoid contamination from adjacent white matter (WM) and cerebrospinal fluid (CSF), and thereby increase the specificity of fMRI to signal changes within the gray matter. Unfortunately, temporal signal-to-noise ratio (tSNR), a metric of fMRI sensitivity, is reduced in high-resolution acquisitions, which offsets the benefits of small voxels. Here we introduce a framework that combines small, isotropic fMRI voxels acquired at 7 T field strength with a novel anatomically-informed, surface mesh-navigated spatial smoothing that can provide both higher detection power and higher resolution than conventional voxel sizes. Our smoothing approach uses a family of intracortical surface meshes and allows for kernels of various shapes and sizes, including curved 3D kernels that adapt to and track the cortical folding pattern. Our goal is to restrict smoothing to the cortical gray matter ribbon and avoid noise contamination from CSF and signal dilution from WM via partial volume effects. We found that the intracortical kernel that maximizes tSNR does not maximize percent signal change (ΔS/S), and therefore the kernel configuration that optimizes detection power cannot be determined from tSNR considerations alone. However, several kernel configurations provided a favorable balance between boosting tSNR and ΔS/S, and allowed a 1.1-mm isotropic fMRI acquisition to have higher performance after smoothing (in terms of both detection power and spatial resolution) compared to an unsmoothed 3.0-mm isotropic fMRI acquisition. Overall, the results of this study support the strategy of acquiring voxels smaller than the cortical thickness, even for studies not requiring high spatial resolution, and smoothing them down within the cortical ribbon with a kernel of an appropriate shape to achieve the best performance-thus decoupling the choice of fMRI voxel size from the spatial resolution requirements of the particular study. The improvement of this new intracortical smoothing approach over conventional surface-based smoothing is expected to be modest for conventional resolutions, however the improvement is expected to increase with higher resolutions. This framework can also be applied to anatomically-informed intracortical smoothing of higher-resolution data (e.g. along columns and layers) in studies with prior information about the spatial structure of activation.
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Affiliation(s)
- Anna I Blazejewska
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Boston, MA, USA; Department of Radiology, Harvard Medical School, Boston, MA, USA.
| | - Bruce Fischl
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Boston, MA, USA; Department of Radiology, Harvard Medical School, Boston, MA, USA; Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Lawrence L Wald
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Boston, MA, USA; Department of Radiology, Harvard Medical School, Boston, MA, USA; Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Jonathan R Polimeni
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Boston, MA, USA; Department of Radiology, Harvard Medical School, Boston, MA, USA; Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, USA
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31
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Raslau FD, Lin LY, Andersen AH, Powell DK, Smith CD, Escott EJ. Peeking into the Black Box of Coregistration in Clinical fMRI: Which Registration Methods Are Used and How Well Do They Perform? AJNR Am J Neuroradiol 2018; 39:2332-2339. [PMID: 30361428 DOI: 10.3174/ajnr.a5846] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2018] [Accepted: 08/25/2018] [Indexed: 11/07/2022]
Abstract
BACKGROUND AND PURPOSE Interpretation of fMRI depends on accurate functional-to-structural alignment. This study explores registration methods used by FDA-approved software for clinical fMRI and aims to answer the following question: What is the degree of misalignment when registration is not performed, and how well do current registration methods perform? MATERIALS AND METHODS This retrospective study of presurgical fMRI for brain tumors compares nonregistered images and 5 registration cost functions: Hellinger, mutual information, normalized mutual information, correlation ratio, and local Pearson correlation. To adjudicate the accuracy of coregistration, we edge-enhanced echo-planar maps and rated them for alignment with structural anatomy. Lesion-to-activation distances were measured to evaluate the effects of different cost functions. RESULTS Transformation parameters were congruent among Hellinger, mutual information, normalized mutual information, and the correlation ratio but divergent from the local Pearson correlation. Edge-enhanced images validated the local Pearson correlation as the most accurate. Hellinger worsened misalignment in 59% of cases, primarily exaggerating the inferior translation; no cases were worsened by the local Pearson correlation. Three hundred twenty lesion-to-activation distances from 25 patients were analyzed among nonregistered images, Hellinger, and the local Pearson correlation. ANOVA analysis revealed significant differences in the coronal (P < .001) and sagittal (P = .04) planes. If registration is not performed, 8% of cases may have a >3-mm discrepancy and up to a 5.6-mm lesion-to-activation distance difference. If a poor registration method is used, 23% of cases may have a >3-mm discrepancy and up to a 6.9-mm difference. CONCLUSIONS The local Pearson correlation is a special-purpose cost function specifically designed for T2*-T1 coregistration and should be more widely incorporated into software tools as a better method for coregistration in clinical fMRI.
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Affiliation(s)
- F D Raslau
- From the Departments of Radiology (F.D.R., L.Y.L., E.J.E., C.D.S.)
| | - L Y Lin
- From the Departments of Radiology (F.D.R., L.Y.L., E.J.E., C.D.S.)
| | | | | | - C D Smith
- From the Departments of Radiology (F.D.R., L.Y.L., E.J.E., C.D.S.)
- Neurology (C.D.S.)
- Neuroscience (A.H.A., D.K.P., C.D.S.)
| | - E J Escott
- From the Departments of Radiology (F.D.R., L.Y.L., E.J.E., C.D.S.)
- Otolaryngology-Head & Neck Surgery (E.J.E.), University of Kentucky, Lexington, Kentucky
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Bydder M, Zaaraoui W, Ridley B, Soubrier M, Bertinetti M, Confort-Gouny S, Schad L, Guye M, Ranjeva JP. Dynamic 23Na MRI - A non-invasive window on neuroglial-vascular mechanisms underlying brain function. Neuroimage 2018; 184:771-780. [PMID: 30292814 DOI: 10.1016/j.neuroimage.2018.09.071] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2018] [Revised: 09/21/2018] [Accepted: 09/25/2018] [Indexed: 11/17/2022] Open
Abstract
A novel magnetic resonance imaging (MRI) acquisition and reconstruction method for obtaining a series of dynamic sodium 23Na-MRI acquisitions was designed to non-invasively assess the signal variations of brain sodium during a hand motor task in 14 healthy human volunteers on an ultra high field (7T) MR scanner. Regions undergoing activation and deactivation were identified with reference to conventional task-related BOLD functional MRI (fMRI). Activation observed in the left central regions, the supplementary motor areas and the left cerebellum induced an increase in the sodium signal observed at ultra short echo time and a decrease in the 23Na signal observed at long echo time. Based on a simple model of two distinct sodium pools (namely, restricted and mobile sodium), the ultra short echo time measures the totality of sodium whereas the long echo time is mainly sensitive to mobile sodium. This activation pattern is consistent with previously described processes related to an influx of Na+ into the intracellular compartments and a moderate increase in the cerebral blood volume (CBV). In contrast, deactivation observed in the right central regions ipsilateral to the movement, the precuneus and the left cerebellum induced a slight decrease in sodium signal at ultra short echo time and an increase of sodium signal at longer echo times. This inhibitory pattern is compatible with a slight decrease in CBV and an efflux of intracellular Na+ to the extracellular compartments that may reflect neural dendritic spine and astrocytic shrinkage, and an increase of sodium in the extracellular fraction. In conclusion, cerebral dynamic 23Na MRI experiments can provide access to the ionic transients following a functional task occurring within the neuro-glial-vascular ensemble. This has the potential to open up a novel non-invasive window on the mechanisms underlying brain function.
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Affiliation(s)
- Mark Bydder
- Aix-Marseille Univ, CNRS, CRMBM, Marseille, France; APHM, University Hospital Timone, CEMEREM, Marseille, France
| | - Wafaa Zaaraoui
- Aix-Marseille Univ, CNRS, CRMBM, Marseille, France; APHM, University Hospital Timone, CEMEREM, Marseille, France
| | - Ben Ridley
- Aix-Marseille Univ, CNRS, CRMBM, Marseille, France; APHM, University Hospital Timone, CEMEREM, Marseille, France
| | - Manon Soubrier
- Aix-Marseille Univ, CNRS, CRMBM, Marseille, France; APHM, University Hospital Timone, CEMEREM, Marseille, France
| | - Marie Bertinetti
- Aix-Marseille Univ, CNRS, CRMBM, Marseille, France; APHM, University Hospital Timone, CEMEREM, Marseille, France
| | - Sylviane Confort-Gouny
- Aix-Marseille Univ, CNRS, CRMBM, Marseille, France; APHM, University Hospital Timone, CEMEREM, Marseille, France
| | - Lothar Schad
- Computer Assisted Clinical Medicine, Centre for Biomedicine and Medical Technology Mannheim, Heidelberg University, Mannheim, Germany
| | - Maxime Guye
- Aix-Marseille Univ, CNRS, CRMBM, Marseille, France; APHM, University Hospital Timone, CEMEREM, Marseille, France
| | - Jean-Philippe Ranjeva
- Aix-Marseille Univ, CNRS, CRMBM, Marseille, France; APHM, University Hospital Timone, CEMEREM, Marseille, France.
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Huber L, Tse DHY, Wiggins CJ, Uludağ K, Kashyap S, Jangraw DC, Bandettini PA, Poser BA, Ivanov D. Ultra-high resolution blood volume fMRI and BOLD fMRI in humans at 9.4 T: Capabilities and challenges. Neuroimage 2018; 178:769-779. [PMID: 29890330 PMCID: PMC6100753 DOI: 10.1016/j.neuroimage.2018.06.025] [Citation(s) in RCA: 35] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2018] [Revised: 05/23/2018] [Accepted: 06/07/2018] [Indexed: 12/31/2022] Open
Abstract
Functional mapping of cerebral blood volume (CBV) changes has the potential to reveal brain activity with high localization specificity at the level of cortical layers and columns. Non-invasive CBV imaging using Vascular Space Occupancy (VASO) at ultra-high magnetic field strengths promises high spatial specificity but poses unique challenges in human applications. As such, 9.4 T B1+ and B0 inhomogeneities limit efficient blood tagging, while the specific absorption rate (SAR) constraints limit the application of VASO-specific RF pulses. Moreover, short T2* values at 9.4 T require short readout duration, and long T1 values at 9.4 T can cause blood-inflow contaminations. In this study, we investigated the applicability of layer-dependent CBV-fMRI at 9.4 T in humans. We addressed the aforementioned challenges by combining multiple technical advancements: temporally alternating pTx B1+ shimming parameters, advanced adiabatic RF-pulses, 3D-EPI signal readout, optimized GRAPPA acquisition and reconstruction, and stability-optimized RF channel combination. We found that a combination of suitable advanced methodology alleviates the challenges and potential artifacts, and that VASO fMRI provides reliable measures of CBV change across cortical layers in humans at 9.4 T. The localization specificity of CBV-fMRI, combined with the high sensitivity of 9.4 T, makes this method an important tool for future studies investigating cortical micro-circuitry in humans.
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Affiliation(s)
- Laurentius Huber
- Section on Functional Imaging Methods, Laboratory of Brain and Cognition, NIMH, NIH, Bethesda, MD, USA.
| | - Desmond H Y Tse
- Maastricht Brain Imaging Center, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, The Netherlands; Centre for Advanced Imaging, University of Queensland, Australia
| | | | - Kâmil Uludağ
- Maastricht Brain Imaging Center, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, The Netherlands
| | - Sriranga Kashyap
- Maastricht Brain Imaging Center, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, The Netherlands
| | - David C Jangraw
- Section on Functional Imaging Methods, Laboratory of Brain and Cognition, NIMH, NIH, Bethesda, MD, USA
| | - Peter A Bandettini
- Section on Functional Imaging Methods, Laboratory of Brain and Cognition, NIMH, NIH, Bethesda, MD, USA; FMRIF, NIMH, NIH, Bethesda, MD, USA
| | - Benedikt A Poser
- Maastricht Brain Imaging Center, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, The Netherlands
| | - Dimo Ivanov
- Maastricht Brain Imaging Center, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, The Netherlands
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34
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Distortion-matched T1 maps and unbiased T1-weighted images as anatomical reference for high-resolution fMRI. Neuroimage 2018; 176:41-55. [DOI: 10.1016/j.neuroimage.2018.04.026] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2018] [Revised: 04/05/2018] [Accepted: 04/10/2018] [Indexed: 11/20/2022] Open
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Keuken MC, Isaacs BR, Trampel R, van der Zwaag W, Forstmann BU. Visualizing the Human Subcortex Using Ultra-high Field Magnetic Resonance Imaging. Brain Topogr 2018; 31:513-545. [PMID: 29497874 PMCID: PMC5999196 DOI: 10.1007/s10548-018-0638-7] [Citation(s) in RCA: 30] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2017] [Accepted: 01/28/2018] [Indexed: 12/15/2022]
Abstract
With the recent increased availability of ultra-high field (UHF) magnetic resonance imaging (MRI), substantial progress has been made in visualizing the human brain, which can now be done in extraordinary detail. This review provides an extensive overview of the use of UHF MRI in visualizing the human subcortex for both healthy and patient populations. The high inter-subject variability in size and location of subcortical structures limits the usability of atlases in the midbrain. Fortunately, the combined results of this review indicate that a large number of subcortical areas can be visualized in individual space using UHF MRI. Current limitations and potential solutions of UHF MRI for visualizing the subcortex are also discussed.
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Affiliation(s)
- M C Keuken
- Integrative Model-Based Cognitive Neuroscience Research Unit, University of Amsterdam, Postbus 15926, 1001NK, Amsterdam, The Netherlands.
- Cognitive Psychology Unit, Institute of Psychology and Leiden Institute for Brain and Cognition, Leiden University, Leiden, The Netherlands.
| | - B R Isaacs
- Integrative Model-Based Cognitive Neuroscience Research Unit, University of Amsterdam, Postbus 15926, 1001NK, Amsterdam, The Netherlands
- Maastricht University Medical Center, Maastricht, The Netherlands
| | - R Trampel
- Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | | | - B U Forstmann
- Integrative Model-Based Cognitive Neuroscience Research Unit, University of Amsterdam, Postbus 15926, 1001NK, Amsterdam, The Netherlands
- Netherlands Institute for Neuroscience, An Institute of the Royal Netherlands Academy of Arts and Sciences, Amsterdam, The Netherlands
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Gulban OF, Schneider M, Marquardt I, Haast RAM, De Martino F. A scalable method to improve gray matter segmentation at ultra high field MRI. PLoS One 2018; 13:e0198335. [PMID: 29874295 PMCID: PMC5991408 DOI: 10.1371/journal.pone.0198335] [Citation(s) in RCA: 25] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2018] [Accepted: 05/17/2018] [Indexed: 11/19/2022] Open
Abstract
High-resolution (functional) magnetic resonance imaging (MRI) at ultra high magnetic fields (7 Tesla and above) enables researchers to study how anatomical and functional properties change within the cortical ribbon, along surfaces and across cortical depths. These studies require an accurate delineation of the gray matter ribbon, which often suffers from inclusion of blood vessels, dura mater and other non-brain tissue. Residual segmentation errors are commonly corrected by browsing the data slice-by-slice and manually changing labels. This task becomes increasingly laborious and prone to error at higher resolutions since both work and error scale with the number of voxels. Here we show that many mislabeled, non-brain voxels can be corrected more efficiently and semi-automatically by representing three-dimensional anatomical images using two-dimensional histograms. We propose both a uni-modal (based on first spatial derivative) and multi-modal (based on compositional data analysis) approach to this representation and quantify the benefits in 7 Tesla MRI data of nine volunteers. We present an openly accessible Python implementation of these approaches and demonstrate that editing cortical segmentations using two-dimensional histogram representations as an additional post-processing step aids existing algorithms and yields improved gray matter borders. By making our data and corresponding expert (ground truth) segmentations openly available, we facilitate future efforts to develop and test segmentation algorithms on this challenging type of data.
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Affiliation(s)
- Omer Faruk Gulban
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, The Netherlands
| | - Marian Schneider
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, The Netherlands
| | - Ingo Marquardt
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, The Netherlands
| | - Roy A. M. Haast
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, The Netherlands
- Maastricht Centre for Systems Biology, Maastricht University, Maastricht, The Netherlands
| | - Federico De Martino
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, The Netherlands
- Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, United States of America
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Kashyap S, Ivanov D, Havlicek M, Poser BA, Uludağ K. Impact of acquisition and analysis strategies on cortical depth-dependent fMRI. Neuroimage 2018; 168:332-344. [DOI: 10.1016/j.neuroimage.2017.05.022] [Citation(s) in RCA: 62] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2016] [Revised: 03/31/2017] [Accepted: 05/11/2017] [Indexed: 01/19/2023] Open
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Polimeni JR, Renvall V, Zaretskaya N, Fischl B. Analysis strategies for high-resolution UHF-fMRI data. Neuroimage 2018; 168:296-320. [PMID: 28461062 PMCID: PMC5664177 DOI: 10.1016/j.neuroimage.2017.04.053] [Citation(s) in RCA: 64] [Impact Index Per Article: 10.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2016] [Revised: 04/21/2017] [Accepted: 04/22/2017] [Indexed: 12/22/2022] Open
Abstract
Functional MRI (fMRI) benefits from both increased sensitivity and specificity with increasing magnetic field strength, making it a key application for Ultra-High Field (UHF) MRI scanners. Most UHF-fMRI studies utilize the dramatic increases in sensitivity and specificity to acquire high-resolution data reaching sub-millimeter scales, which enable new classes of experiments to probe the functional organization of the human brain. This review article surveys advanced data analysis strategies developed for high-resolution fMRI at UHF. These include strategies designed to mitigate distortion and artifacts associated with higher fields in ways that attempt to preserve spatial resolution of the fMRI data, as well as recently introduced analysis techniques that are enabled by these extremely high-resolution data. Particular focus is placed on anatomically-informed analyses, including cortical surface-based analysis, which are powerful techniques that can guide each step of the analysis from preprocessing to statistical analysis to interpretation and visualization. New intracortical analysis techniques for laminar and columnar fMRI are also reviewed and discussed. Prospects for single-subject individualized analyses are also presented and discussed. Altogether, there are both specific challenges and opportunities presented by UHF-fMRI, and the use of proper analysis strategies can help these valuable data reach their full potential.
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Affiliation(s)
- Jonathan R Polimeni
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Harvard Medical School, Massachusetts General Hospital, Charlestown, MA, United States; Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, United States.
| | - Ville Renvall
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Harvard Medical School, Massachusetts General Hospital, Charlestown, MA, United States; Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, Espoo, Finland
| | - Natalia Zaretskaya
- Centre for Integrative Neuroscience, Department of Psychology, University of Tübingen, Tübingen, Germany; Max Planck Institute for Biological Cybernetics, Tübingen, Germany
| | - Bruce Fischl
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Harvard Medical School, Massachusetts General Hospital, Charlestown, MA, United States; Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA, United States
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39
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How to choose the right MR sequence for your research question at 7 T and above? Neuroimage 2018; 168:119-140. [DOI: 10.1016/j.neuroimage.2017.04.044] [Citation(s) in RCA: 40] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2016] [Revised: 04/18/2017] [Accepted: 04/19/2017] [Indexed: 12/29/2022] Open
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40
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Dohmatob E, Varoquaux G, Thirion B. Inter-subject Registration of Functional Images: Do We Need Anatomical Images? Front Neurosci 2018; 12:64. [PMID: 29497357 PMCID: PMC5819565 DOI: 10.3389/fnins.2018.00064] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2017] [Accepted: 01/26/2018] [Indexed: 01/29/2023] Open
Abstract
In Echo-Planar Imaging (EPI)-based Magnetic Resonance Imaging (MRI), inter-subject registration typically uses the subject's T1-weighted (T1w) anatomical image to learn deformations of the subject's brain onto a template. The estimated deformation fields are then applied to the subject's EPI scans (functional or diffusion-weighted images) to warp the latter to a template space. Historically, such indirect T1w-based registration was motivated by the lack of clear anatomical details in low-resolution EPI images: a direct registration of the EPI scans to template space would be futile. A central prerequisite in such indirect methods is that the anatomical (aka the T1w) image of each subject is well aligned with their EPI images via rigid coregistration. We provide experimental evidence that things have changed: nowadays, there is a decent amount of anatomical contrast in high-resolution EPI data. That notwithstanding, EPI distortions due to B0 inhomogeneities cannot be fully corrected. Residual uncorrected distortions induce non-rigid deformations between the EPI scans and the same subject's anatomical scan. In this manuscript, we contribute a computationally cheap pipeline that leverages the high spatial resolution of modern EPI scans for direct inter-subject matching. Our pipeline is direct and does not rely on the T1w scan to estimate the inter-subject deformation. Results on a large dataset show that this new pipeline outperforms the classical indirect T1w-based registration scheme, across a variety of post-registration quality-assessment metrics including: Normalized Mutual Information, relative variance (variance-to-mean ratio), and to a lesser extent, improved peaks of group-level General Linear Model (GLM) activation maps.
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Affiliation(s)
- Elvis Dohmatob
- Parietal Team, INRIA, CEA, Université Paris-Saclay, Gif-sur-Yvette, France
| | - Gael Varoquaux
- Parietal Team, INRIA, CEA, Université Paris-Saclay, Gif-sur-Yvette, France
| | - Bertrand Thirion
- Parietal Team, INRIA, CEA, Université Paris-Saclay, Gif-sur-Yvette, France
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Huber L, Ivanov D, Handwerker DA, Marrett S, Guidi M, Uludağ K, Bandettini PA, Poser BA. Techniques for blood volume fMRI with VASO: From low-resolution mapping towards sub-millimeter layer-dependent applications. Neuroimage 2018; 164:131-143. [PMID: 27867088 PMCID: PMC5436958 DOI: 10.1016/j.neuroimage.2016.11.039] [Citation(s) in RCA: 67] [Impact Index Per Article: 11.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2016] [Revised: 10/24/2016] [Accepted: 11/14/2016] [Indexed: 12/24/2022] Open
Abstract
Quantitative cerebral blood volume (CBV) fMRI has the potential to overcome several specific limitations of BOLD fMRI. It provides direct physiological interpretability and promises superior localization specificity in applications of sub-millimeter resolution fMRI applications at ultra-high magnetic fields (7T and higher). Non-invasive CBV fMRI using VASO (vascular space occupancy), however, is inherently limited with respect to its data acquisition efficiency, restricting its imaging coverage and achievable spatial and temporal resolution. This limitation may be reduced with recent advanced acceleration and reconstruction strategies that allow two-dimensional acceleration, such as in simultaneous multi-slice (SMS) 2D-EPI or 3D-EPI in combination with CAIPIRINHA field-of-view shifting. In this study, we sought to determine the functional sensitivity and specificity of these readout strategies with VASO over a broad range of spatial resolutions; spanning from low spatial resolution (3mm) whole-cortex to sub-millimeter (0.75mm) slab-of-cortex (for cortical layer-dependent applications). In the thermal-noise-dominated regime of sub-millimeter resolutions, 3D-EPI-VASO provides higher temporal stability and sensitivity to detect changes in CBV compared to 2D-EPI-VASO. In this regime, 3D-EPI-VASO unveils task activation located in the cortical laminae with little contamination from surface veins, in contrast to the cortical surface weighting of GE-BOLD fMRI. In the physiological-noise-dominated regime of lower resolutions, however, 2D-SMS-VASO shows superior performance compared to 3D-EPI-VASO. Due to its superior sensitivity at a layer-dependent level, 3D-EPI VASO promises to play an important role in future neuroscientific applications of layer-dependent fMRI.
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Affiliation(s)
- Laurentius Huber
- Section on Functional Imaging Methods, Laboratory of Brain and Cognition, NIMH, NIH, Bethesda, MD, USA.
| | - Dimo Ivanov
- Maastricht Brain Imaging Centre, Faculty of Psychology and Neurosciencve, Maastricht University, Maastricht, The Netherlands
| | - Daniel A Handwerker
- Section on Functional Imaging Methods, Laboratory of Brain and Cognition, NIMH, NIH, Bethesda, MD, USA
| | | | - Maria Guidi
- Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Kâmil Uludağ
- Maastricht Brain Imaging Centre, Faculty of Psychology and Neurosciencve, Maastricht University, Maastricht, The Netherlands
| | - Peter A Bandettini
- Section on Functional Imaging Methods, Laboratory of Brain and Cognition, NIMH, NIH, Bethesda, MD, USA; FMRIF, NIMH, NIH, Bethesda, MD, USA
| | - Benedikt A Poser
- Maastricht Brain Imaging Centre, Faculty of Psychology and Neurosciencve, Maastricht University, Maastricht, The Netherlands
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Huber L, Handwerker DA, Jangraw DC, Chen G, Hall A, Stüber C, Gonzalez-Castillo J, Ivanov D, Marrett S, Guidi M, Goense J, Poser BA, Bandettini PA. High-Resolution CBV-fMRI Allows Mapping of Laminar Activity and Connectivity of Cortical Input and Output in Human M1. Neuron 2017; 96:1253-1263.e7. [PMID: 29224727 DOI: 10.1016/j.neuron.2017.11.005] [Citation(s) in RCA: 186] [Impact Index Per Article: 26.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2017] [Revised: 09/25/2017] [Accepted: 11/02/2017] [Indexed: 10/18/2022]
Abstract
Layer-dependent fMRI allows measurements of information flow in cortical circuits, as afferent and efferent connections terminate in different cortical layers. However, it is unknown to what level human fMRI is specific and sensitive enough to reveal directional functional activity across layers. To answer this question, we developed acquisition and analysis methods for blood-oxygen-level-dependent (BOLD) and cerebral-blood-volume (CBV)-based laminar fMRI and used these to discriminate four different tasks in the human motor cortex (M1). In agreement with anatomical data from animal studies, we found evidence for somatosensory and premotor input in superficial layers of M1 and for cortico-spinal motor output in deep layers. Laminar resting-state fMRI showed directional functional connectivity of M1 with somatosensory and premotor areas. Our findings demonstrate that CBV-fMRI can be used to investigate cortical activity in humans with unprecedented detail, allowing investigations of information flow between brain regions and outperforming conventional BOLD results that are often buried under vascular biases.
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Affiliation(s)
| | | | | | | | | | - Carsten Stüber
- Department of Radiology, Weill Cornell Medical College, New York, NY 10044, USA; Department of Neurology, Yale School of Medicine, Yale University, New Haven, CT 06511, USA
| | | | - Dimo Ivanov
- Maastricht Brain Imaging Centre, Maastricht University, Maastricht 6229, the Netherlands
| | | | - Maria Guidi
- NMR Group, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig 04103, Germany
| | - Jozien Goense
- School of Psychology and Institute of Neuroscience and Psychology, University of Glasgow, Glasgow G12 8QB, UK
| | - Benedikt A Poser
- Maastricht Brain Imaging Centre, Maastricht University, Maastricht 6229, the Netherlands
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43
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Cohen O, Polimeni JR. Optimized inversion-time schedules for quantitative T 1 measurements based on high-resolution multi-inversion EPI. Magn Reson Med 2017; 79:2101-2112. [PMID: 28845547 DOI: 10.1002/mrm.26889] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2017] [Revised: 08/02/2017] [Accepted: 08/04/2017] [Indexed: 01/07/2023]
Abstract
PURPOSE Demonstrate an optimized multi-inversion echo-planar imaging technique to accelerate quantitative T1 mapping by judicious selection of inversion times for each slice. METHODS Slice ordering is optimized to maximize discrimination between tissues with different T1 values. The optimized slice orderings are tested in the International Society for Magnetic Resonance in Medicine/National Institute of Standards and Technology phantom and compared with an unoptimized 21-measurement acquisition. The utility of the method is demonstrated in a healthy subject in vivo at 3 T and validated with a gold-standard inversion-recovery sequence. The in vivo precision of our technique was tested by repeated scans of the same subject within a scan session and across scan sessions, occurring 28 days apart. RESULTS Phantom measurements yielded good agreement (R2 = 0.99) between the T1 estimates from the proposed optimized protocol, reference values from the National Institute of Standards and Technology phantom and gold-standard inversion-recovery values, as well as a negligible estimation bias that was slightly lower than that from the unoptimized 21-measurement protocol (0.74 versus 19 ms). The range of values for the scan-rescan coefficient of variation was 0.86 to 0.93 (within session) and 0.83 to 0.92 (across sessions) across all scan durations tested. CONCLUSIONS Optimized slice orderings allow faster quantitative T1 mapping. The optimized sequence yielded accurate and precise T1 maps. Magn Reson Med 79:2101-2112, 2018. © 2017 International Society for Magnetic Resonance in Medicine.
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Affiliation(s)
- Ouri Cohen
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA.,Department of Radiology, Harvard Medical School, Boston, Massachusetts, USA
| | - Jonathan R Polimeni
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA.,Department of Radiology, Harvard Medical School, Boston, Massachusetts, USA.,Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
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44
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Caballero-Gaudes C, Reynolds RC. Methods for cleaning the BOLD fMRI signal. Neuroimage 2017; 154:128-149. [PMID: 27956209 PMCID: PMC5466511 DOI: 10.1016/j.neuroimage.2016.12.018] [Citation(s) in RCA: 325] [Impact Index Per Article: 46.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2016] [Revised: 12/05/2016] [Accepted: 12/08/2016] [Indexed: 01/13/2023] Open
Abstract
Blood oxygen-level-dependent functional magnetic resonance imaging (BOLD fMRI) has rapidly become a popular technique for the investigation of brain function in healthy individuals, patients as well as in animal studies. However, the BOLD signal arises from a complex mixture of neuronal, metabolic and vascular processes, being therefore an indirect measure of neuronal activity, which is further severely corrupted by multiple non-neuronal fluctuations of instrumental, physiological or subject-specific origin. This review aims to provide a comprehensive summary of existing methods for cleaning the BOLD fMRI signal. The description is given from a methodological point of view, focusing on the operation of the different techniques in addition to pointing out the advantages and limitations in their application. Since motion-related and physiological noise fluctuations are two of the main noise components of the signal, techniques targeting their removal are primarily addressed, including both data-driven approaches and using external recordings. Data-driven approaches, which are less specific in the assumed model and can simultaneously reduce multiple noise fluctuations, are mainly based on data decomposition techniques such as principal and independent component analysis. Importantly, the usefulness of strategies that benefit from the information available in the phase component of the signal, or in multiple signal echoes is also highlighted. The use of global signal regression for denoising is also addressed. Finally, practical recommendations regarding the optimization of the preprocessing pipeline for the purpose of denoising and future venues of research are indicated. Through the review, we summarize the importance of signal denoising as an essential step in the analysis pipeline of task-based and resting state fMRI studies.
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Affiliation(s)
| | - Richard C Reynolds
- Scientific and Statistical Computing Core, National Institute of Mental Health, National Institutes of Health, Department of Health and Human Services, USA
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45
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Stannarius R. Magnetic resonance imaging of granular materials. THE REVIEW OF SCIENTIFIC INSTRUMENTS 2017; 88:051806. [PMID: 28571451 DOI: 10.1063/1.4983135] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/07/2023]
Abstract
Magnetic Resonance Imaging (MRI) has become one of the most important tools to screen humans in medicine; virtually every modern hospital is equipped with a Nuclear Magnetic Resonance (NMR) tomograph. The potential of NMR in 3D imaging tasks is by far greater, but there is only "a handful" of MRI studies of particulate matter. The method is expensive, time-consuming, and requires a deep understanding of pulse sequences, signal acquisition, and processing. We give a short introduction into the physical principles of this imaging technique, describe its advantages and limitations for the screening of granular matter, and present a number of examples of different application purposes, from the exploration of granular packing, via the detection of flow and particle diffusion, to real dynamic measurements. Probably, X-ray computed tomography is preferable in most applications, but fast imaging of single slices with modern MRI techniques is unmatched, and the additional opportunity to retrieve spatially resolved flow and diffusion profiles without particle tracking is a unique feature.
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Affiliation(s)
- Ralf Stannarius
- Institute of Experimental Physics, Otto-von-Guericke-University, Universitätsplatz 2, D-39106 Magdeburg, Germany
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46
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Fan Q, Nummenmaa A, Polimeni JR, Witzel T, Huang SY, Wedeen VJ, Rosen BR, Wald LL. HIgh b-value and high Resolution Integrated Diffusion (HIBRID) imaging. Neuroimage 2017; 150:162-176. [PMID: 28188913 PMCID: PMC5501959 DOI: 10.1016/j.neuroimage.2017.02.002] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2016] [Revised: 02/01/2017] [Accepted: 02/01/2017] [Indexed: 11/28/2022] Open
Abstract
The parameter selection for diffusion MRI experiments is dominated by the "k-q tradeoff" whereby the Signal to Noise Ratio (SNR) of the images is traded for either high spatial resolution (determined by the maximum k-value collected) or high diffusion sensitivity (effected by b-value or the q vector) but usually not both. Furthermore, different brain regions (such as gray matter and white matter) likely require different tradeoffs between these parameters due to the size of the structures to be visualized or the length-scale of the microstructure being probed. In this case, it might be advantageous to combine information from two scans - a scan with high q but low k (high angular resolution in diffusion but low spatial resolution in the image domain) to provide maximal information about white matter fiber crossing, and one low q but high k (low angular resolution but high spatial resolution) for probing the cortex. In this study, we propose a method, termed HIgh b-value and high Resolution Integrated Diffusion (HIBRID) imaging, for acquiring and combining the information from these two complementary types of scan with the goal of studying diffusion in the cortex without compromising white matter fiber information. The white-gray boundary and pial surface obtained from anatomical scans are incorporated as prior information to guide the fusion. We study the complementary advantages of the fused datasets, and assess the quality of the HIBRID data compared to either alone.
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Affiliation(s)
- Qiuyun Fan
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Harvard Medical School, Massachusetts General Hospital, Charlestown, MA, USA
| | - Aapo Nummenmaa
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Harvard Medical School, Massachusetts General Hospital, Charlestown, MA, USA
| | - Jonathan R Polimeni
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Harvard Medical School, Massachusetts General Hospital, Charlestown, MA, USA; Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Thomas Witzel
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Harvard Medical School, Massachusetts General Hospital, Charlestown, MA, USA
| | - Susie Y Huang
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Harvard Medical School, Massachusetts General Hospital, Charlestown, MA, USA
| | - Van J Wedeen
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Harvard Medical School, Massachusetts General Hospital, Charlestown, MA, USA
| | - Bruce R Rosen
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Harvard Medical School, Massachusetts General Hospital, Charlestown, MA, USA; Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Lawrence L Wald
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Harvard Medical School, Massachusetts General Hospital, Charlestown, MA, USA; Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, USA.
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47
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High resolution data analysis strategies for mesoscale human functional MRI at 7 and 9.4T. Neuroimage 2017; 164:48-58. [PMID: 28416453 PMCID: PMC5745233 DOI: 10.1016/j.neuroimage.2017.03.058] [Citation(s) in RCA: 53] [Impact Index Per Article: 7.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2016] [Revised: 02/22/2017] [Accepted: 03/28/2017] [Indexed: 01/22/2023] Open
Abstract
The advent of ultra-high field functional magnetic resonance imaging (fMRI) has greatly facilitated submillimeter resolution acquisitions (voxel volume below (1 mm³)), allowing the investigation of cortical columns and cortical depth dependent (i.e. laminar) structures in the human brain. Advanced data analysis techniques are essential to exploit the information in high resolution functional measures. In this article, we use recent, exemplary 9.4 T human functional and anatomical data to review the advantages and disadvantages of (1) pooling high resolution data across regions of interest for cortical depth profile analysis, (2) pooling across cortical depths for mapping patches of cortex while discarding depth-dependent (i.e. columnar) effects, and (3) isotropic sampling without pooling to assess individual voxel’s responses. A set of cortical depth meshes may be a solution to sampling information tangentially while keeping correspondence across depths. For quantitative analysis of the spatial organization in fine-grained structures, a cortical grid approach is advantageous. We further extend this general framework by combining it with a previously introduced cortical layer volume-preserving (equi-volume) approach. This framework can readily accommodate the research questions which allow for spatial smoothing within or across layers. We demonstrate and discuss that equi-volume sampling yields a slight advantage over equidistant sampling given the current limitations of fMRI voxel size, participant motion, coregistration and segmentation. Our 9.4 T human anatomical and functional data indicate the advantage over lower fields including 7 T and demonstrate the practical applicability of T2* and T2-weighted fMRI acquisitions. High resolution regular cortical grids are advantageous for local applications. Equi-volume sampling is slightly advantageous over equidistant sampling in-vivo. Isotropic submillimeter cortical sampling without spatial pooling requires high SNR. 9.4 T human T2 and T2* BOLD fMRI are practically feasible and provide high SNR. 9.4 T T2*-weighted 0.35 mm iso. res. anatomical images for laminar contrast in vivo.
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De Martino F, Yacoub E, Kemper V, Moerel M, Uludağ K, De Weerd P, Ugurbil K, Goebel R, Formisano E. The impact of ultra-high field MRI on cognitive and computational neuroimaging. Neuroimage 2017; 168:366-382. [PMID: 28396293 DOI: 10.1016/j.neuroimage.2017.03.060] [Citation(s) in RCA: 73] [Impact Index Per Article: 10.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2016] [Revised: 03/20/2017] [Accepted: 03/29/2017] [Indexed: 01/14/2023] Open
Abstract
The ability to measure functional brain responses non-invasively with ultra high field MRI (7 T and above) represents a unique opportunity in advancing our understanding of the human brain. Compared to lower fields (3 T and below), ultra high field MRI has an increased sensitivity, which can be used to acquire functional images with greater spatial resolution, and greater specificity of the blood oxygen level dependent (BOLD) signal to the underlying neuronal responses. Together, increased resolution and specificity enable investigating brain functions at a submillimeter scale, which so far could only be done with invasive techniques. At this mesoscopic spatial scale, perception, cognition and behavior can be probed at the level of fundamental units of neural computations, such as cortical columns, cortical layers, and subcortical nuclei. This represents a unique and distinctive advantage that differentiates ultra high from lower field imaging and that can foster a tighter link between fMRI and computational modeling of neural networks. So far, functional brain mapping at submillimeter scale has focused on the processing of sensory information and on well-known systems for which extensive information is available from invasive recordings in animals. It remains an open challenge to extend this methodology to uniquely human functions and, more generally, to systems for which animal models may be problematic. To succeed, the possibility to acquire high-resolution functional data with large spatial coverage, the availability of computational models of neural processing as well as accurate biophysical modeling of neurovascular coupling at mesoscopic scale all appear necessary.
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Affiliation(s)
- Federico De Martino
- Department of Cognitive Neurosciences, Faculty of Psychology and Neuroscience, Maastricht University, Oxfordlaan 55, 6229 ER Maastricht, The Netherlands; Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, 2021 sixth street SE, 55455 Minneapolis, MN, USA.
| | - Essa Yacoub
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, 2021 sixth street SE, 55455 Minneapolis, MN, USA
| | - Valentin Kemper
- Department of Cognitive Neurosciences, Faculty of Psychology and Neuroscience, Maastricht University, Oxfordlaan 55, 6229 ER Maastricht, The Netherlands
| | - Michelle Moerel
- Department of Cognitive Neurosciences, Faculty of Psychology and Neuroscience, Maastricht University, Oxfordlaan 55, 6229 ER Maastricht, The Netherlands; Maastricht Center for System Biology, Maastricht University, Universiteitssingel 60, 6229 ER Maastricht, The Netherlands
| | - Kâmil Uludağ
- Department of Cognitive Neurosciences, Faculty of Psychology and Neuroscience, Maastricht University, Oxfordlaan 55, 6229 ER Maastricht, The Netherlands
| | - Peter De Weerd
- Department of Cognitive Neurosciences, Faculty of Psychology and Neuroscience, Maastricht University, Oxfordlaan 55, 6229 ER Maastricht, The Netherlands
| | - Kamil Ugurbil
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, 2021 sixth street SE, 55455 Minneapolis, MN, USA
| | - Rainer Goebel
- Department of Cognitive Neurosciences, Faculty of Psychology and Neuroscience, Maastricht University, Oxfordlaan 55, 6229 ER Maastricht, The Netherlands
| | - Elia Formisano
- Department of Cognitive Neurosciences, Faculty of Psychology and Neuroscience, Maastricht University, Oxfordlaan 55, 6229 ER Maastricht, The Netherlands; Maastricht Center for System Biology, Maastricht University, Universiteitssingel 60, 6229 ER Maastricht, The Netherlands
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Sclocco R, Beissner F, Bianciardi M, Polimeni JR, Napadow V. Challenges and opportunities for brainstem neuroimaging with ultrahigh field MRI. Neuroimage 2017; 168:412-426. [PMID: 28232189 DOI: 10.1016/j.neuroimage.2017.02.052] [Citation(s) in RCA: 82] [Impact Index Per Article: 11.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2016] [Revised: 01/30/2017] [Accepted: 02/19/2017] [Indexed: 12/19/2022] Open
Abstract
The human brainstem plays a central role in connecting the cerebrum, the cerebellum and the spinal cord to one another, hosting relay nuclei for afferent and efferent signaling, and providing source nuclei for several neuromodulatory systems that impact central nervous system function. While the investigation of the brainstem with functional or structural magnetic resonance imaging has been hampered for years due to this brain structure's physiological and anatomical characteristics, the field has seen significant advances in recent years thanks to the broader adoption of ultrahigh-field (UHF) MRI scanning. In the present review, we focus on the advantages offered by UHF in the context of brainstem imaging, as well as the challenges posed by the investigation of this complex brain structure in terms of data acquisition and analysis. We also illustrate how UHF MRI can shed new light on the neuroanatomy and neurophysiology underlying different brainstem-based circuitries, such as the central autonomic network and neurotransmitter/neuromodulator systems, discuss existing and foreseeable clinical applications to better understand diseases such as chronic pain and Parkinson's disease, and explore promising future directions for further improvements in brainstem imaging using UHF MRI techniques.
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Affiliation(s)
- Roberta Sclocco
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, CNY 149-2301, 13th St. Charlestown, Boston, MA 02129, USA; Department of Radiology, Logan University, Chesterfield, MO, USA.
| | - Florian Beissner
- Somatosensory and Autonomic Therapy Research, Institute for Neuroradiology, Hannover Medical School, Hannover, Germany
| | - Marta Bianciardi
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, CNY 149-2301, 13th St. Charlestown, Boston, MA 02129, USA
| | - Jonathan R Polimeni
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, CNY 149-2301, 13th St. Charlestown, Boston, MA 02129, USA; Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Vitaly Napadow
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, CNY 149-2301, 13th St. Charlestown, Boston, MA 02129, USA; Department of Radiology, Logan University, Chesterfield, MO, USA
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Turner R, De Haan D. Bridging the gap between system and cell: The role of ultra-high field MRI in human neuroscience. PROGRESS IN BRAIN RESEARCH 2017; 233:179-220. [DOI: 10.1016/bs.pbr.2017.05.005] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
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