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Hübner S, Tambalo S, Novello L, Hilbert T, Kober T, Jovicich J. Advancing Thalamic Nuclei Segmentation: The Impact of Compressed Sensing on MRI Processing. Hum Brain Mapp 2024; 45:e70120. [PMID: 39722224 DOI: 10.1002/hbm.70120] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2024] [Revised: 12/09/2024] [Accepted: 12/13/2024] [Indexed: 12/28/2024] Open
Abstract
The thalamus is a collection of gray matter nuclei that play a crucial role in sensorimotor processing and modulation of cortical activity. Characterizing thalamic nuclei non-invasively with structural MRI is particularly relevant for patient populations with Parkinson's disease, epilepsy, dementia, and schizophrenia. However, severe head motion in these populations poses a significant challenge for in vivo mapping of thalamic nuclei. Recent advancements have leveraged the compressed sensing (CS) framework to accelerate structural MRI acquisition times in MPRAGE sequence variants, while fast segmentation tools like FastSurfer have reduced processing times in neuroimaging research. In this study, we evaluated thalamic nuclei segmentations derived from six different MPRAGE variants with varying degrees of CS acceleration (from about 9 to about 1-min acquisitions). Thalamic segmentations were initialized from either FastSurfer or FreeSurfer, and the robustness of the thalamic nuclei segmentation tool to different initialization inputs was evaluated. Our findings show minimal sequence effects with no systematic bias, and low volume variability across sequences for the whole thalamus and major thalamic nuclei. Notably, CS-accelerated sequences produced less variable volumes compared to non-CS sequences. Additionally, segmentations of thalamic nuclei initialized from FastSurfer and FreeSurfer were highly comparable. We provide the first evidence supporting that a good segmentation quality of thalamic nuclei with CS T1-weighted image acceleration in a clinical 3T MRI system is possible. Our findings encourage future applications of fast T1-weighted MRI to study deep gray matter. CS-accelerated sequences and rapid segmentation methods are promising tools for future studies aiming to characterize thalamic nuclei in vivo at 3T in both healthy individuals and clinical populations.
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Affiliation(s)
- Sebastian Hübner
- Center for Mind/Brain Sciences-CIMeC, University of Trento, Rovereto, Italy
| | - Stefano Tambalo
- Center for Mind/Brain Sciences-CIMeC, University of Trento, Rovereto, Italy
| | - Lisa Novello
- Center for Mind/Brain Sciences-CIMeC, University of Trento, Rovereto, Italy
- Data Science for Health, Fondazione Bruno Kessler, Trento, Italy
| | - Tom Hilbert
- Advanced Clinical Imaging Technology, Siemens Healthineers International AG, Lausanne, Switzerland
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- Signal Processing Laboratory 5 (LTS5), Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Tobias Kober
- Advanced Clinical Imaging Technology, Siemens Healthineers International AG, Lausanne, Switzerland
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- Signal Processing Laboratory 5 (LTS5), Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Jorge Jovicich
- Center for Mind/Brain Sciences-CIMeC, University of Trento, Rovereto, Italy
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Aichour R, Emorine T, Oubaya N, Megdiche I, Créange A, Lecler A, Kober T, Massire A, Bapst B. Improved MR Detection of Optic Nerve Demyelination With MP2RAGE-FLAWS Compared With T2-Weighted Fat-Saturated Sequences. Invest Radiol 2024:00004424-990000000-00271. [PMID: 39602823 DOI: 10.1097/rli.0000000000001140] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2024]
Abstract
OBJECTIVES Nonenhanced T1-w sequences such as magnetization-prepared 2 rapid acquisition gradient echo (MP2RAGE) and derived fluid and white matter suppression (FLAWS) have demonstrated high performance for detecting brain parenchymal and cervical spine demyelinating lesions in multiple sclerosis. However, their potential for identifying optic nerve (ON) demyelination remains unexplored. The aim of this study was to evaluate the performance of compressed sensing-accelerated (CS) MP2RAGE-FLAWS imaging for detection of ON demyelination lesions compared with T2-w fat-saturated (FS) TSE imaging in a clinical setting. MATERIALS AND METHODS We conducted a retrospective study of magnetic resonance scans acquired on patients with central nervous system demyelinating disorders between January and December 2022. Inclusion criteria were the acquisition in the same session of a brain CS-MP2RAGE-FLAWS imaging and a combination of axial + coronal T2-w FS orbital sequences. A 4-step radiological analysis-including blinded and consensus readings-assessed ON lesion detection. The reference standard was the final reading session of radiologists using the entire patient file. Sensitivities and specificities of both sequences were computed and compared using McNemar χ2 tests. RESULTS Thirty-nine patients (mean age: 43 ± 14 years; 25 women) were analyzed, including 34 with multiple sclerosis, 2 with MOGAD (myelin oligodendrocyte glycoprotein antibody-associated disease), 1 with NMOSD (neuromyelitis optica spectrum disorder), and 2 with indeterminate demyelinating disease. Among the 78 ONs analyzed, 64 lesions were detected with CS-MP2RAGE-FLAWS as opposed to 37 with 2D T2-w FS imaging, corresponding to a total of 41 and 27 affected nerves, respectively. CS-MP2RAGE-FLAWS exhibited higher sensitivity for overall detection of ON lesions compared with 2D T2-w FS imaging (97.5% vs 67.5%, P = 0.001) without reducing the specificity. Improved lesion detectability with CS-MP2RAGE-FLAWS was significant compared with 2D T2-w FS in intraorbital and intracanalicular segments (respectively, 92.3% vs 50% and 96.3% vs 66.7%; P < 0.05). There was no difference in sensitivity (P = 0.69) or specificity (P = 0.99) regarding the intracranial segment analysis. CONCLUSIONS CS-MP2RAGE-FLAWS sequence improves ON lesion detection compared with conventional 2D T2-w FS, especially in the intraorbital segment, while simultaneously providing whole-brain and cervical spinal cord imaging at no additional time cost.
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Affiliation(s)
- Randa Aichour
- From the Department of Neuroradiology, AP-HP, Henri Mondor University Hospital, Créteil, France (R.A., T.E., I.M., B.B.); University Paris Est Créteil, INSERM, IMRB, Créteil, France (N.O.); Department of Public Health, AP-HP, Henri Mondor University Hospital, Créteil, France (N.O.); EA 4391, Université Paris Est Créteil, Créteil, France (A.C., B.B.); Department of Neurology, AP-HP, Henri Mondor University Hospital, Créteil, France (A.C.); Department of Neuroradiology, A. Rothschild Foundation Hospital, Paris, France (A.L.); Paris Cité University, Paris, France (A.L.); Advanced Clinical Imaging Technology, Siemens Healthineers International AG, Lausanne, Switzerland (T.K.); Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland (T.K.); Signal Processing Laboratory (LTS 5), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland (T.K.); and Siemens Healthcare SAS, Courbevoie, France (A.M.)
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Gil N, Tabari A, Lo WC, Clifford B, Lang M, Awan K, Gaudet K, Splitthoff DN, Polak D, Cauley S, Huang SY. Quantitative evaluation of Scout Accelerated Motion Estimation and Reduction (SAMER) MPRAGE for morphometric analysis of brain tissue in patients undergoing evaluation for memory loss. Neuroimage 2024; 300:120865. [PMID: 39349147 PMCID: PMC11498920 DOI: 10.1016/j.neuroimage.2024.120865] [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: 02/04/2024] [Revised: 09/20/2024] [Accepted: 09/23/2024] [Indexed: 10/02/2024] Open
Abstract
BACKGROUND Three-dimensional (3D) T1-weighted MRI sequences such as the magnetization prepared rapid gradient echo (MPRAGE) sequence are important for assessing regional cortical atrophy in the clinical evaluation of dementia but have long acquisition times and are prone to motion artifact. The recently developed Scout Accelerated Motion Estimation and Reduction (SAMER) retrospective motion correction method addresses motion artifact within clinically-acceptable computation times and has been validated through qualitative evaluation in inpatient and emergency settings. METHODS We evaluated the quantitative accuracy of morphometric analysis of SAMER motion-corrected compared to non-motion-corrected MPRAGE images by estimating cortical volume and thickness across neuroanatomical regions in two subject groups: (1) healthy volunteers and (2) patients undergoing evaluation for dementia. In part (1), we used a set of 108 MPRAGE reconstructed images derived from 12 healthy volunteers to systematically assess the effectiveness of SAMER in correcting varying degrees of motion corruption, ranging from mild to severe. In part (2), 29 patients who were scheduled for brain MRI with memory loss protocol and had motion corruption on their clinical MPRAGE scans were prospectively enrolled. RESULTS In part (1), SAMER resulted in effective correction of motion-induced cortical volume and thickness reductions. We observed systematic increases in the estimated cortical volume and thickness across all neuroanatomical regions and a relative reduction in percent error values compared to reference standard scans of up to 66 % for the cerebral white matter volume. In part (2), SAMER resulted in statistically significant volume increases across anatomical regions, with the most pronounced increases seen in the parietal and temporal lobes, and general reductions in percent error relative to reference standard clinical scans. CONCLUSION SAMER improves the accuracy of morphometry through systematic increases and recovery of the estimated cortical volume and cortical thickness following motion correction, which may affect the evaluation of regional cortical atrophy in patients undergoing evaluation for dementia.
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Affiliation(s)
- Nelson Gil
- Department of Radiology, Massachusetts General Hospital, Boston, MA, USA; Harvard Medical School, Boston, MA, USA.
| | - Azadeh Tabari
- Department of Radiology, Massachusetts General Hospital, Boston, MA, USA; Harvard Medical School, Boston, MA, USA
| | | | | | - Min Lang
- Department of Radiology, Massachusetts General Hospital, Boston, MA, USA; Harvard Medical School, Boston, MA, USA
| | - Komal Awan
- Department of Radiology, Massachusetts General Hospital, Boston, MA, USA; Harvard Medical School, Boston, MA, USA
| | - Kyla Gaudet
- Department of Radiology, Massachusetts General Hospital, Boston, MA, USA; Harvard Medical School, Boston, MA, USA
| | | | | | - Stephen Cauley
- Harvard Medical School, Boston, MA, USA; Department of Radiology, A. A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
| | - Susie Y Huang
- Department of Radiology, Massachusetts General Hospital, Boston, MA, USA; Harvard Medical School, Boston, MA, USA
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Rowley CD, Nelson MC, Campbell JSW, Leppert IR, Pike GB, Tardif CL. Fast magnetization transfer saturation imaging of the brain using MP2RAGE T 1 mapping. Magn Reson Med 2024; 92:1540-1555. [PMID: 38703017 DOI: 10.1002/mrm.30143] [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: 09/15/2023] [Revised: 03/26/2024] [Accepted: 04/17/2024] [Indexed: 05/06/2024]
Abstract
PURPOSE Magnetization transfer saturation (MTsat) mapping is commonly used to examine the macromolecular content of brain tissue. This study compared variable flip angle (VFA) T1 mapping against compressed-sensing MP2RAGE (csMP2RAGE) T1 mapping for accelerating MTsat imaging. METHODS VFA, MP2RAGE, and csMP2RAGE were compared against inversion-recovery T1 in an aqueous phantom at 3 T. The same 1-mm VFA, MP2RAGE, and csMP2RAGE protocols were acquired in 4 healthy subjects to compare T1 and MTsat. Bloch-McConnell simulations were used to investigate differences between the phantom and in vivo T1 results. Ten healthy controls were imaged twice with the csMP2RAGE MTsat protocol to quantify repeatability. RESULTS The MP2RAGE and csMP2RAGE protocols were 13.7% and 32.4% faster than the VFA protocol, respectively. At these scan times, all approaches provided strong repeatability and accurate T1 times (< 5% difference) in the phantom, but T1 accuracy was more impacted by T2 for VFA than for MP2RAGE. In vivo, VFA estimated longer T1 times than MP2RAGE and csMP2RAGE. Simulations suggest that the differences in the T1 measured using VFA, MP2RAGE, and inversion recovery could be explained by the magnetization-transfer effects. In the test-retest experiment, we found that the csMP2RAGE has a minimum detectable change of 2.3% for T1 mapping and 7.8% for MTsat imaging. CONCLUSIONS We demonstrated that MP2RAGE can be used in place of VFA T1 mapping in an MTsat protocol. Furthermore, a shorter scan time and high repeatability can be achieved using the csMP2RAGE sequence.
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Affiliation(s)
- Christopher D Rowley
- McConnell Brain Imaging Center, Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada
- Department of Neurology and Neurosurgery, McGill University, Montreal, Quebec, Canada
- Department of Physics and Astronomy, McMaster University, Hamilton, Ontario, Canada
| | - Mark C Nelson
- McConnell Brain Imaging Center, Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada
| | - Jennifer S W Campbell
- McConnell Brain Imaging Center, Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada
| | - Ilana R Leppert
- McConnell Brain Imaging Center, Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada
| | - G Bruce Pike
- Department of Radiology and Clinical Neuroscience, Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada
| | - Christine L Tardif
- McConnell Brain Imaging Center, Montreal Neurological Institute and Hospital, McGill University, Montreal, Quebec, Canada
- Department of Neurology and Neurosurgery, McGill University, Montreal, Quebec, Canada
- Department of Biomedical Engineering, McGill University, Montreal, Quebec, Canada
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Licht C, Reichert S, Bydder M, Zapp J, Corella S, Guye M, Zöllner FG, Schad LR, Rapacchi S. Low-rank reconstruction for simultaneous double half-echo 23Na and undersampled 23Na multi-quantum coherences MRI. Magn Reson Med 2024; 92:1440-1455. [PMID: 38725430 DOI: 10.1002/mrm.30132] [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: 11/20/2023] [Revised: 03/05/2024] [Accepted: 04/08/2024] [Indexed: 07/23/2024]
Abstract
PURPOSE To develop a new sequence to simultaneously acquire Cartesian sodium (23Na) MRI and accelerated Cartesian single (SQ) and triple quantum (TQ) sodium MRI of in vivo human brain at 7 T by leveraging two dedicated low-rank reconstruction frameworks. THEORY AND METHODS The Double Half-Echo technique enables short echo time Cartesian 23Na MRI and acquires two k-space halves, reconstructed by a low-rank coupling constraint. Additionally, three-dimensional (3D) 23Na Multi-Quantum Coherences (MQC) MRI requires multi-echo sampling paired with phase-cycling, exhibiting a redundant multidimensional space. Simultaneous Autocalibrating and k-Space Estimation (SAKE) were used to reconstruct highly undersampled 23Na MQC MRI. Reconstruction performance was assessed against five-dimensional (5D) CS, evaluating structural similarity index (SSIM), root mean squared error (RMSE), signal-to-noise ratio (SNR), and quantification of tissue sodium concentration and TQ/SQ ratio in silico, in vitro, and in vivo. RESULTS The proposed sequence enabled the simultaneous acquisition of fully sampled 23Na MRI while leveraging prospective undersampling for 23Na MQC MRI. SAKE improved TQ image reconstruction regarding SSIM by 6% and reduced RMSE by 35% compared to 5D CS in vivo. Thanks to prospective undersampling, the spatial resolution of 23Na MQC MRI was enhanced from8 × 8 × 15 $$ 8\times 8\times 15 $$ mm3 to8 × 8 × 8 $$ 8\times 8\times 8 $$ mm3 while reducing acquisition time from2 × 31 $$ 2\times 31 $$ min to2 × 23 $$ 2\times 23 $$ min. CONCLUSION The proposed sequence, coupled with low-rank reconstructions, provides an efficient framework for comprehensive whole-brain sodium MRI, combining TSC, T2*, and TQ/SQ ratio estimations. Additionally, low-rank matrix completion enables the reconstruction of highly undersampled 23Na MQC MRI, allowing for accelerated acquisition or enhanced spatial resolution.
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Affiliation(s)
- Christian Licht
- Computer Assisted Clinical Medicine, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
- Mannheim Institute for Intelligent Systems in Medicine, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Simon Reichert
- Computer Assisted Clinical Medicine, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
- Mannheim Institute for Intelligent Systems in Medicine, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Mark Bydder
- Aix-Marseille Univ, CNRS, CRMBM, Marseille, France
| | - Jascha Zapp
- Computer Assisted Clinical Medicine, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
- Mannheim Institute for Intelligent Systems in Medicine, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Shirley Corella
- Aix-Marseille Univ, CNRS, CRMBM, Marseille, France
- APHM, CEMEREM, Hôpital Universitaire Timone, Marseille, France
| | - Maxime Guye
- Aix-Marseille Univ, CNRS, CRMBM, Marseille, France
- APHM, CEMEREM, Hôpital Universitaire Timone, Marseille, France
| | - Frank G Zöllner
- Computer Assisted Clinical Medicine, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
- Mannheim Institute for Intelligent Systems in Medicine, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Lothar R Schad
- Computer Assisted Clinical Medicine, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
- Mannheim Institute for Intelligent Systems in Medicine, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Stanislas Rapacchi
- Aix-Marseille Univ, CNRS, CRMBM, Marseille, France
- APHM, CEMEREM, Hôpital Universitaire Timone, Marseille, France
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Ravano V, Andelova M, Piredda GF, Sommer S, Caneschi S, Roccaro L, Krasensky J, Kudrna M, Uher T, Corredor-Jerez RA, Disselhorst JA, Maréchal B, Hilbert T, Thiran JP, Richiardi J, Horakova D, Vaneckova M, Kober T. Microstructural characterization of multiple sclerosis lesion phenotypes using multiparametric longitudinal analysis. J Neurol 2024; 271:5944-5957. [PMID: 39003428 PMCID: PMC11377637 DOI: 10.1007/s00415-024-12568-x] [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: 02/06/2024] [Revised: 07/01/2024] [Accepted: 07/05/2024] [Indexed: 07/15/2024]
Abstract
BACKGROUND AND OBJECTIVES In multiple sclerosis (MS), slowly expanding lesions were shown to be associated with worse disability and prognosis. Their timely detection from cross-sectional data at early disease stages could be clinically relevant to inform treatment planning. Here, we propose to use multiparametric, quantitative MRI to allow a better cross-sectional characterization of lesions with different longitudinal phenotypes. METHODS We analysed T1 and T2 relaxometry maps from a longitudinal cohort of MS patients. Lesions were classified as enlarging, shrinking, new or stable based on their longitudinal volumetric change using a newly developed automated technique. Voxelwise deviations were computed as z-scores by comparing individual patient data to T1, T2 and T2/T1 normative values from healthy subjects. We studied the distribution of microstructural properties inside lesions and within perilesional tissue. RESULTS AND CONCLUSIONS Stable lesions exhibited the highest T1 and T2 z-scores in lesion tissue, while the lowest values were observed for new lesions. Shrinking lesions presented the highest T1 z-scores in the first perilesional ring while enlarging lesions showed the highest T2 z-scores in the same region. Finally, a classification model was trained to predict the longitudinal lesion type based on microstructural metrics and feature importance was assessed. Z-scores estimated in lesion and perilesional tissue from T1, T2 and T2/T1 quantitative maps carry discriminative and complementary information to classify longitudinal lesion phenotypes, hence suggesting that multiparametric MRI approaches are essential for a better understanding of the pathophysiological mechanisms underlying disease activity in MS lesions.
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Affiliation(s)
- Veronica Ravano
- Advanced Clinical Imaging Technology, Siemens Healthineers International AG, Lausanne, Geneva and Zurich, Switzerland.
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.
- LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.
| | - Michaela Andelova
- Department of Neurology and Center of Clinical Neuroscience, First Faculty of Medicine, Charles University and General University, Prague, Czech Republic
| | - Gian Franco Piredda
- Advanced Clinical Imaging Technology, Siemens Healthineers International AG, Lausanne, Geneva and Zurich, Switzerland
| | - Stefan Sommer
- Advanced Clinical Imaging Technology, Siemens Healthineers International AG, Lausanne, Geneva and Zurich, Switzerland
- Swiss Center for Muscoloskeletal Imaging (SCMI) Balgrist Campus, Zurich, Switzerland
| | - Samuele Caneschi
- Advanced Clinical Imaging Technology, Siemens Healthineers International AG, Lausanne, Geneva and Zurich, Switzerland
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Lucia Roccaro
- Advanced Clinical Imaging Technology, Siemens Healthineers International AG, Lausanne, Geneva and Zurich, Switzerland
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Jan Krasensky
- Department of Radiology, First Faculty of Medicine, Charles University and General University Hospital, Prague, Czech Republic
| | - Matej Kudrna
- Department of Radiology, First Faculty of Medicine, Charles University and General University Hospital, Prague, Czech Republic
| | - Tomas Uher
- Department of Neurology and Center of Clinical Neuroscience, First Faculty of Medicine, Charles University and General University, Prague, Czech Republic
| | - Ricardo A Corredor-Jerez
- Advanced Clinical Imaging Technology, Siemens Healthineers International AG, Lausanne, Geneva and Zurich, Switzerland
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Jonathan A Disselhorst
- Advanced Clinical Imaging Technology, Siemens Healthineers International AG, Lausanne, Geneva and Zurich, Switzerland
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Bénédicte Maréchal
- Advanced Clinical Imaging Technology, Siemens Healthineers International AG, Lausanne, Geneva and Zurich, Switzerland
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Tom Hilbert
- Advanced Clinical Imaging Technology, Siemens Healthineers International AG, Lausanne, Geneva and Zurich, Switzerland
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | | | - Jonas Richiardi
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Dana Horakova
- Department of Neurology and Center of Clinical Neuroscience, First Faculty of Medicine, Charles University and General University, Prague, Czech Republic
| | - Manuela Vaneckova
- Department of Radiology, First Faculty of Medicine, Charles University and General University Hospital, Prague, Czech Republic
| | - Tobias Kober
- Advanced Clinical Imaging Technology, Siemens Healthineers International AG, Lausanne, Geneva and Zurich, Switzerland
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
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Tazza F, Boffa G, Schiavi S, Lapucci C, Piredda GF, Cipriano E, Zacà D, Roccatagliata L, Hilbert T, Kober T, Inglese M, Costagli M. Multiparametric Characterization and Spatial Distribution of Different MS Lesion Phenotypes. AJNR Am J Neuroradiol 2024; 45:1166-1174. [PMID: 38816021 PMCID: PMC11383400 DOI: 10.3174/ajnr.a8271] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2023] [Accepted: 03/01/2024] [Indexed: 06/01/2024]
Abstract
BACKGROUND AND PURPOSE MS lesions exhibit varying degrees of axonal and myelin damage. A comprehensive description of lesion phenotypes could contribute to an improved radiologic evaluation of smoldering inflammation and remyelination processes. This study aimed to identify in vivo distinct MS lesion types using quantitative susceptibility mapping and susceptibility mapping-weighted imaging and to characterize them through T1-relaxometry, myelin mapping, and diffusion MR imaging. The spatial distribution of lesion phenotypes in relation to ventricular CSF was investigated. MATERIALS AND METHODS MS lesions of 53 individuals were categorized into iso- or hypointense lesions, hyperintense lesions, and paramagnetic rim lesions, on the basis of their appearance on quantitative susceptibility mapping alone, according to published criteria, and with the additional support of susceptibility mapping-weighted imaging. Susceptibility values, T1-relaxation times, myelin and free water fractions, intracellular volume fraction, and the orientation dispersion index were compared among lesion phenotypes. The distance of the geometric center of each lesion from the ventricular CSF was calculated. RESULTS Eight hundred ninety-six MS lesions underwent the categorization process using quantitative susceptibility mapping and susceptibility mapping-weighted imaging. The novel use of susceptibility mapping-weighted images, which revealed additional microvasculature details, led us to re-allocate several lesions to different categories, resulting in a 35.6% decrease in the number of paramagnetic rim lesions, a 22.5% decrease in hyperintense lesions, and a 17.2% increase in iso- or hypointense lesions, with respect to the categorization based on quantitative susceptibility mapping only. The outcome of the categorization based on the joint use of quantitative susceptibility mapping and susceptibility mapping-weighted imaging was that 44.4% of lesions were iso- or hypointense lesions, 47.9% were hyperintense lesions, and 7.7% were paramagnetic rim lesions. A worsening gradient was observed from iso- or hypointense lesions to hyperintense lesions to paramagnetic rim lesions in T1-relaxation times, myelin water fraction, free water fraction, and intracellular volume fraction. Paramagnetic rim lesions were located closer to ventricular CSF than iso- or hypointense lesions. The volume of hyperintense lesions was associated with a more severe disease course. CONCLUSIONS Quantitative susceptibility mapping and susceptibility mapping-weighted imaging allow in vivo classification of MS lesions into different phenotypes, characterized by different levels of axonal and myelin loss and spatial distribution. Hyperintense lesions and paramagnetic rim lesions, which have the most severe microstructural damage, were more often observed in the periventricular WM and were associated with a more severe disease course.
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Affiliation(s)
- Francesco Tazza
- From the Departments of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (F.T., G.B., S.S., E.C., M.I., M.C.), University of Genoa, Genoa, Italy
| | - Giacomo Boffa
- From the Departments of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (F.T., G.B., S.S., E.C., M.I., M.C.), University of Genoa, Genoa, Italy
| | - Simona Schiavi
- From the Departments of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (F.T., G.B., S.S., E.C., M.I., M.C.), University of Genoa, Genoa, Italy
| | - Caterina Lapucci
- Istituto di Ricovero e Cura a Carattere Scientifico (C.L., L.R., M.I., M.C.), Ospedale Policlinico San Martino, Genoa, Italy
| | - Gian Franco Piredda
- Advanced Clinical Imaging Technology (G.F.P., T.H., T.K.), Siemens Healthineers International AG, Lausanne, Switzerland
| | - Emilio Cipriano
- From the Departments of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (F.T., G.B., S.S., E.C., M.I., M.C.), University of Genoa, Genoa, Italy
| | | | - Luca Roccatagliata
- Istituto di Ricovero e Cura a Carattere Scientifico (C.L., L.R., M.I., M.C.), Ospedale Policlinico San Martino, Genoa, Italy
- Department of Health Sciences (L.R.), University of Genoa, Genoa, Italy
| | - Tom Hilbert
- Advanced Clinical Imaging Technology (G.F.P., T.H., T.K.), Siemens Healthineers International AG, Lausanne, Switzerland
- Department of Radiology (T.H., T.K.), Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- LTS5 (T.H., T.K.), École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Tobias Kober
- Advanced Clinical Imaging Technology (G.F.P., T.H., T.K.), Siemens Healthineers International AG, Lausanne, Switzerland
- Department of Radiology (T.H., T.K.), Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- LTS5 (T.H., T.K.), École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Matilde Inglese
- From the Departments of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (F.T., G.B., S.S., E.C., M.I., M.C.), University of Genoa, Genoa, Italy
- Istituto di Ricovero e Cura a Carattere Scientifico (C.L., L.R., M.I., M.C.), Ospedale Policlinico San Martino, Genoa, Italy
| | - Mauro Costagli
- From the Departments of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (F.T., G.B., S.S., E.C., M.I., M.C.), University of Genoa, Genoa, Italy
- Istituto di Ricovero e Cura a Carattere Scientifico (C.L., L.R., M.I., M.C.), Ospedale Policlinico San Martino, Genoa, Italy
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8
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Bapst B, Massire A, Mauconduit F, Gras V, Boulant N, Dufour J, Bodini B, Stankoff B, Luciani A, Vignaud A. Pushing MP2RAGE boundaries: Ultimate time-efficient parameterization combined with exhaustive T 1 synthetic contrasts. Magn Reson Med 2024; 91:1608-1624. [PMID: 38102807 DOI: 10.1002/mrm.29948] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2023] [Revised: 11/09/2023] [Accepted: 11/12/2023] [Indexed: 12/17/2023]
Abstract
PURPOSE MP2RAGE parameter optimization is redefined to allow more time-efficient MR acquisitions, whereas the T1 -based synthetic imaging framework is used to obtain on-demand T1 -weighted contrasts. Our aim was to validate this concept on healthy volunteers and patients with multiple sclerosis, using plug-and-play parallel-transmission brain imaging at 7 T. METHODS A "time-efficient" MP2RAGE sequence was designed with optimized parameters including TI and TR set as small as possible. Extended phase graph formalism was used to set flip-angle values to maximize the gray-to-white-matter contrast-to-noise ratio (CNR). Several synthetic contrasts (UNI, EDGE, FGATIR, FLAWSMIN , FLAWSHCO ) were generated online based on the acquired T1 maps. Experimental validation was performed on 4 healthy volunteers at various spatial resolutions. Clinical applicability was evaluated on 6 patients with multiple sclerosis, scanned with both time-efficient and conventional MP2RAGE parameterizations. RESULTS The proposed time-efficient MP2RAGE protocols reduced acquisition time by 40%, 30%, and 19% for brain imaging at (1 mm)3 , (0.80 mm)3 and (0.65 mm)3 , respectively, when compared with conventional parameterizations. They also provided all synthetic contrasts and comparable contrast-to-noise ratio on UNI images. The flexibility in parameter selection allowed us to obtain a whole-brain (0.45 mm)3 acquisition in 19 min 56 s. On patients with multiple sclerosis, a (0.67 mm)3 time-efficient acquisition enhanced cortical lesion visualization compared with a conventional (0.80 mm)3 protocol, while decreasing the scan time by 15%. CONCLUSION The proposed optimization, associated with T1 -based synthetic contrasts, enabled substantial decrease of the acquisition time or higher spatial resolution scans for a given time budget, while generating all typical brain contrasts derived from MP2RAGE.
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Affiliation(s)
- Blanche Bapst
- University of Paris-Saclay, CEA, CNRS, BAOBAB, NeuroSpin, Gif-sur-Yvette, France
- Department of Neuroradiology, AP-HP, Henri Mondor University Hospital, Créteil, France
- EA 4391, Université Paris Est Créteil, Créteil, France
| | | | - Franck Mauconduit
- University of Paris-Saclay, CEA, CNRS, BAOBAB, NeuroSpin, Gif-sur-Yvette, France
| | - Vincent Gras
- University of Paris-Saclay, CEA, CNRS, BAOBAB, NeuroSpin, Gif-sur-Yvette, France
| | - Nicolas Boulant
- University of Paris-Saclay, CEA, CNRS, BAOBAB, NeuroSpin, Gif-sur-Yvette, France
| | - Juliette Dufour
- Sorbonne Université, Paris Brain Institute, ICM, CNRS, Inserm, Paris, France
| | - Benedetta Bodini
- Sorbonne Université, Paris Brain Institute, ICM, CNRS, Inserm, Paris, France
| | - Bruno Stankoff
- Sorbonne Université, Paris Brain Institute, ICM, CNRS, Inserm, Paris, France
| | - Alain Luciani
- Department of Medical Imaging, Henri Mondor University Hospital, Créteil, France
| | - Alexandre Vignaud
- University of Paris-Saclay, CEA, CNRS, BAOBAB, NeuroSpin, Gif-sur-Yvette, France
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9
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Ravano V, Piredda GF, Krasensky J, Andelova M, Uher T, Srpova B, Havrdova EK, Vodehnalova K, Horakova D, Nytrova P, Disselhorst JA, Hilbert T, Maréchal B, Thiran JP, Kober T, Richiardi J, Vaneckova M. Tract-wise microstructural analysis informs on current and future disability in early multiple sclerosis. J Neurol 2024; 271:631-641. [PMID: 37819462 PMCID: PMC10827809 DOI: 10.1007/s00415-023-12023-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2023] [Revised: 09/21/2023] [Accepted: 09/24/2023] [Indexed: 10/13/2023]
Abstract
OBJECTIVES Microstructural characterization of patients with multiple sclerosis (MS) has been shown to correlate better with disability compared to conventional radiological biomarkers. Quantitative MRI provides effective means to characterize microstructural brain tissue changes both in lesions and normal-appearing brain tissue. However, the impact of the location of microstructural alterations in terms of neuronal pathways has not been thoroughly explored so far. Here, we study the extent and the location of tissue changes probed using quantitative MRI along white matter (WM) tracts extracted from a connectivity atlas. METHODS We quantified voxel-wise T1 tissue alterations compared to normative values in a cohort of 99 MS patients. For each WM tract, we extracted metrics reflecting tissue alterations both in lesions and normal-appearing WM and correlated these with cross-sectional disability and disability evolution after 2 years. RESULTS In early MS patients, T1 alterations in normal-appearing WM correlated better with disability evolution compared to cross-sectional disability. Further, the presence of lesions in supratentorial tracts was more strongly associated with cross-sectional disability, while microstructural alterations in infratentorial pathways yielded higher correlations with disability evolution. In progressive patients, all major WM pathways contributed similarly to explaining disability, and correlations with disability evolution were generally poor. CONCLUSIONS We showed that microstructural changes evaluated in specific WM pathways contribute to explaining future disability in early MS, hence highlighting the potential of tract-wise analyses in monitoring disease progression. Further, the proposed technique allows to estimate WM tract-specific microstructural characteristics in clinically compatible acquisition times, without the need for advanced diffusion imaging.
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Affiliation(s)
- Veronica Ravano
- Advanced Clinical Imaging Technology, Siemens Healthineers International AG, Lausanne, Switzerland.
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.
- LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.
| | - Gian Franco Piredda
- Advanced Clinical Imaging Technology, Siemens Healthineers International AG, Lausanne, Switzerland
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Jan Krasensky
- Department of Radiology, First Faculty of Medicine, Charles University and General University Hospital, Prague, Czech Republic
| | - Michaela Andelova
- Department of Neurology and Center of Clinical Neuroscience, First Faculty of Medicine, Charles University and General University Hospital, Prague, Czech Republic
| | - Tomas Uher
- Department of Neurology and Center of Clinical Neuroscience, First Faculty of Medicine, Charles University and General University Hospital, Prague, Czech Republic
| | - Barbora Srpova
- Department of Neurology and Center of Clinical Neuroscience, First Faculty of Medicine, Charles University and General University Hospital, Prague, Czech Republic
| | - Eva Kubala Havrdova
- Department of Neurology and Center of Clinical Neuroscience, First Faculty of Medicine, Charles University and General University Hospital, Prague, Czech Republic
| | - Karolina Vodehnalova
- Department of Neurology and Center of Clinical Neuroscience, First Faculty of Medicine, Charles University and General University Hospital, Prague, Czech Republic
| | - Dana Horakova
- Department of Neurology and Center of Clinical Neuroscience, First Faculty of Medicine, Charles University and General University Hospital, Prague, Czech Republic
| | - Petra Nytrova
- Department of Neurology and Center of Clinical Neuroscience, First Faculty of Medicine, Charles University and General University Hospital, Prague, Czech Republic
| | - Jonathan A Disselhorst
- Advanced Clinical Imaging Technology, Siemens Healthineers International AG, Lausanne, Switzerland
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Tom Hilbert
- Advanced Clinical Imaging Technology, Siemens Healthineers International AG, Lausanne, Switzerland
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Bénédicte Maréchal
- Advanced Clinical Imaging Technology, Siemens Healthineers International AG, Lausanne, Switzerland
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Jean-Philippe Thiran
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Tobias Kober
- Advanced Clinical Imaging Technology, Siemens Healthineers International AG, Lausanne, Switzerland
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Jonas Richiardi
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Manuela Vaneckova
- Department of Radiology, First Faculty of Medicine, Charles University and General University Hospital, Prague, Czech Republic
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10
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Kadalie E, Trotier AJ, Corbin N, Miraux S, Ribot EJ. Rapid whole brain 3D T 2 mapping respiratory-resolved Double-Echo Steady State (DESS) sequence with improved repeatability. Magn Reson Med 2024; 91:221-236. [PMID: 37794821 DOI: 10.1002/mrm.29847] [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: 03/03/2023] [Revised: 08/11/2023] [Accepted: 08/11/2023] [Indexed: 10/06/2023]
Abstract
PURPOSE To propose a quantitative 3D double-echo steady-state (DESS) sequence that offers rapid and repeatable T2 mapping of the human brain using different encoding schemes that account for respiratory B0 variation. METHODS A retrospective self-gating module was firstly implemented into the standard DESS sequence in order to suppress the respiratory artifact via data binning. A compressed-sensing trajectory (CS-DESS) was then optimized to accelerate the acquisition. Finally, a spiral Cartesian encoding (SPICCS-DESS) was incorporated to further disrupt the coherent respiratory artifact. These different versions were compared to a standard DESS sequence (fully DESS) by assessing the T2 distribution and repeatability in different brain regions of eight volunteers at 3 T. RESULTS The respiratory artifact correction was determined to be optimal when the data was binned into seven respiratory phases. Compared to the fully DESS, T2 distribution was improved for the CS-DESS and SPICCS-DESS with interquartile ranges reduced significantly by a factor ranging from 2 to 12 in the caudate, putamen, and thalamus regions. In the gray and white matter areas, average absolute test-retest T2 differences across all volunteers were respectively 3.5 ± 2% and 3.1 ± 2.1% for the SPICCS-DESS, 4.6 ± 4.6% and 4.9 ± 5.1% for the CS-DESS, and 15% ± 13% and 7.3 ± 5.6% for the fully DESS. The SPICCS-DESS sequence's acquisition time could be reduced by half (<4 min) while maintaining its efficient T2 mapping. CONCLUSION The respiratory-resolved SPICCS-DESS sequence offers rapid, robust, and repeatable 3D T2 mapping of the human brain, which can be especially effective for longitudinal monitoring of cerebral pathologies.
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Affiliation(s)
- Emile Kadalie
- Univ. Bordeaux, CNRS, Centre de Résonance Magnétique des Systèmes Biologiques (CRMSB), UMR 5536, F-33000, Bordeaux, France
| | - Aurélien J Trotier
- Univ. Bordeaux, CNRS, Centre de Résonance Magnétique des Systèmes Biologiques (CRMSB), UMR 5536, F-33000, Bordeaux, France
| | - Nadège Corbin
- Univ. Bordeaux, CNRS, Centre de Résonance Magnétique des Systèmes Biologiques (CRMSB), UMR 5536, F-33000, Bordeaux, France
| | - Sylvain Miraux
- Univ. Bordeaux, CNRS, Centre de Résonance Magnétique des Systèmes Biologiques (CRMSB), UMR 5536, F-33000, Bordeaux, France
| | - Emeline J Ribot
- Univ. Bordeaux, CNRS, Centre de Résonance Magnétique des Systèmes Biologiques (CRMSB), UMR 5536, F-33000, Bordeaux, France
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11
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Elliott ML, Nielsen JA, Hanford LC, Hamadeh A, Hilbert T, Kober T, Dickerson BC, Hyman BT, Mair RW, Eldaief MC, Buckner RL. Precision Brain Morphometry Using Cluster Scanning. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.12.23.23300492. [PMID: 38234845 PMCID: PMC10793507 DOI: 10.1101/2023.12.23.23300492] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/19/2024]
Abstract
Measurement error limits the statistical power to detect group differences and longitudinal change in structural MRI morphometric measures (e.g., hippocampal volume, prefrontal thickness). Recent advances in scan acceleration enable extremely fast T1-weighted scans (~1 minute) to achieve morphometric errors that are close to the errors in longer traditional scans. As acceleration allows multiple scans to be acquired in rapid succession, it becomes possible to pool estimates to increase measurement precision, a strategy known as "cluster scanning." Here we explored brain morphometry using cluster scanning in a test-retest study of 40 individuals (12 younger adults, 18 cognitively unimpaired older adults, and 10 adults diagnosed with mild cognitive impairment or Alzheimer's Dementia). Morphometric errors from a single compressed sensing (CS) 1.0mm scan with 6x acceleration (CSx6) were, on average, 12% larger than a traditional scan using the Alzheimer's Disease Neuroimaging Initiative (ADNI) protocol. Pooled estimates from four clustered CSx6 acquisitions led to errors that were 34% smaller than ADNI despite having a shorter total acquisition time. Given a fixed amount of time, a gain in measurement precision can thus be achieved by acquiring multiple rapid scans instead of a single traditional scan. Errors were further reduced when estimates were pooled from eight CSx6 scans (51% smaller than ADNI). Neither pooling across a break nor pooling across multiple scan resolutions boosted this benefit. We discuss the potential of cluster scanning to improve morphometric precision, boost statistical power, and produce more sensitive disease progression biomarkers.
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Affiliation(s)
- Maxwell L Elliott
- Department of Psychology, Center for Brain Science, Harvard University, Cambridge, MA 02138, USA
| | - Jared A Nielsen
- Department of Psychology, Neuroscience Center, Brigham Young University, Provo, UT, 84602, USA
| | - Lindsay C Hanford
- Department of Psychology, Center for Brain Science, Harvard University, Cambridge, MA 02138, USA
| | - Aya Hamadeh
- Baylor College of Medicine, Houston, TX 77030
| | - Tom Hilbert
- Advanced Clinical Imaging Technology, Siemens Healthineers International AG, Lausanne, Switzerland
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Tobias Kober
- Advanced Clinical Imaging Technology, Siemens Healthineers International AG, Lausanne, Switzerland
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Bradford C Dickerson
- Frontotemporal Disorders Unit
- Alzheimer's Disease Research Center
- Athinoula A. Martinos Center for Biomedical Imaging
- Department of Neurology, Massachusetts General Hospital & Harvard Medical School
- Department of Psychiatry, Massachusetts General Hospital & Harvard Medical School, Charlestown, MA 02129, USA
| | - Bradley T Hyman
- Alzheimer's Disease Research Center
- Department of Neurology, Massachusetts General Hospital & Harvard Medical School
| | - Ross W Mair
- Department of Psychology, Center for Brain Science, Harvard University, Cambridge, MA 02138, USA
- Athinoula A. Martinos Center for Biomedical Imaging
| | - Mark C Eldaief
- Frontotemporal Disorders Unit
- Alzheimer's Disease Research Center
- Department of Neurology, Massachusetts General Hospital & Harvard Medical School
- Department of Psychiatry, Massachusetts General Hospital & Harvard Medical School, Charlestown, MA 02129, USA
| | - Randy L Buckner
- Department of Psychology, Center for Brain Science, Harvard University, Cambridge, MA 02138, USA
- Alzheimer's Disease Research Center
- Athinoula A. Martinos Center for Biomedical Imaging
- Department of Psychiatry, Massachusetts General Hospital & Harvard Medical School, Charlestown, MA 02129, USA
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12
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Rowley CD, Campbell JSW, Leppert IR, Nelson MC, Pike GB, Tardif CL. Optimization of acquisition parameters for cortical inhomogeneous magnetization transfer (ihMT) imaging using a rapid gradient echo readout. Magn Reson Med 2023; 90:1762-1775. [PMID: 37332194 DOI: 10.1002/mrm.29754] [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: 02/14/2023] [Revised: 04/25/2023] [Accepted: 05/22/2023] [Indexed: 06/20/2023]
Abstract
PURPOSE Imaging biomarkers with increased myelin specificity are needed to better understand the complex progression of neurological disorders. Inhomogeneous magnetization transfer (ihMT) imaging is an emergent technique that has a high degree of specificity for myelin content but suffers from low signal to-noise ratio (SNR). This study used simulations to determine optimal sequence parameters for ihMT imaging for use in high-resolution cortical mapping. METHODS MT-weighted cortical image intensity and ihMT SNR were simulated using modified Bloch equations for a range of sequence parameters. The acquisition time was limited to 4.5 min/volume. A custom MT-weighted RAGE sequence with center-out k-space encoding was used to enhance SNR at 3 T. Pulsed MT imaging was studied over a range of saturation parameters, and the impact of the turbo factor on the effective ihMT resolution was investigated. 1 mm isotropic ihMTsat maps were generated in 25 healthy adults. RESULTS Greater SNR was observed for larger number of bursts consisting of 6-8 saturation pulses each, combined with a high readout turbo factor. However, that protocol suffered from a point spread function that was more than twice the nominal resolution. For high-resolution cortical imaging, we selected a protocol with a higher effective resolution at the cost of a lower SNR. We present the first group-average ihMTsat whole-brain map at 1 mm isotropic resolution. CONCLUSION This study presents the impact of saturation and excitation parameters on ihMTsat SNR and resolution. We demonstrate the feasibility of high-resolution cortical myelin imaging using ihMTsat in less than 20 min.
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Affiliation(s)
- Christopher D Rowley
- McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Québec, Canada
- Department of Neurology and Neurosurgery, McGill University, Montreal, Québec, Canada
| | - Jennifer S W Campbell
- McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Québec, Canada
| | - Ilana R Leppert
- McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Québec, Canada
| | - Mark C Nelson
- McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Québec, Canada
- Department of Neurology and Neurosurgery, McGill University, Montreal, Québec, Canada
| | - G Bruce Pike
- Hotchkiss Brain Institute and Departments of Radiology and Clinical Neuroscience, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
| | - Christine L Tardif
- McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, Québec, Canada
- Department of Neurology and Neurosurgery, McGill University, Montreal, Québec, Canada
- Department of Biomedical Engineering, McGill University, Montreal, Québec, Canada
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13
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Beaumont J, Fripp J, Raniga P, Acosta O, Ferre JC, McMahon K, Trinder J, Kober T, Gambarota G. Multi T1-weighted contrast imaging and T1 mapping with compressed sensing FLAWS at 3 T. MAGMA (NEW YORK, N.Y.) 2023; 36:823-836. [PMID: 36847989 DOI: 10.1007/s10334-023-01071-5] [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: 11/15/2022] [Revised: 01/26/2023] [Accepted: 02/10/2023] [Indexed: 03/01/2023]
Abstract
OBJECTIVE The Fluid And White matter Suppression (FLAWS) MRI sequence provides multiple T1-weighted contrasts of the brain in a single acquisition. However, the FLAWS acquisition time is approximately 8 min with a standard GRAPPA 3 acceleration factor at 3 T. This study aims at reducing the FLAWS acquisition time by providing a new sequence optimization based on a Cartesian phyllotaxis k-space undersampling and a compressed sensing (CS) reconstruction. This study also aims at showing that T1 mapping can be performed with FLAWS at 3 T. MATERIALS AND METHODS The CS FLAWS parameters were determined using a method based on a profit function maximization under constraints. The FLAWS optimization and T1 mapping were assessed with in-silico, in-vitro and in-vivo (10 healthy volunteers) experiments conducted at 3 T. RESULTS In-silico, in-vitro and in-vivo experiments showed that the proposed CS FLAWS optimization allows the acquisition time of a 1 mm-isotropic full-brain scan to be reduced from [Formula: see text] to [Formula: see text] without decreasing image quality. In addition, these experiments demonstrate that T1 mapping can be performed with FLAWS at 3 T. DISCUSSION The results obtained in this study suggest that the recent advances in FLAWS imaging allow to perform multiple T1-weighted contrast imaging and T1 mapping in a single [Formula: see text] sequence acquisition.
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Affiliation(s)
- Jeremy Beaumont
- Univ Rennes, CRLCC Eugene Marquis, Inserm, LTSI-UMR1099, LTSI, Campus de Beaulieu, Université de Rennes 1, 35042, Rennes, France.
- The Australian e-Health Research Centre, CSIRO, Brisbane, QLD, Australia.
| | - Jurgen Fripp
- The Australian e-Health Research Centre, CSIRO, Brisbane, QLD, Australia
| | - Parnesh Raniga
- The Australian e-Health Research Centre, CSIRO, Brisbane, QLD, Australia
| | - Oscar Acosta
- Univ Rennes, CRLCC Eugene Marquis, Inserm, LTSI-UMR1099, LTSI, Campus de Beaulieu, Université de Rennes 1, 35042, Rennes, France
| | - Jean-Christophe Ferre
- Univ Rennes, Inria, CNRS, Inserm, IRISA, EMPENN ERL U-1228, Rennes, France
- Department of Neuroradiology, CHU Rennes, Rennes, France
| | - Katie McMahon
- School of Clinical Sciences, Centre for Biomedical Technologies, Queensland University of Technology (QUT), Brisbane, QLD, Australia
- Herston Imaging Research Facility, Royal Brisbane and Women's Hospital, Brisbane, QLD, Australia
| | - Julie Trinder
- The Australian e-Health Research Centre, CSIRO, Brisbane, QLD, Australia
| | - Tobias Kober
- Advanced Clinical Imaging Technology, Siemens Healthcare, Lausanne, Switzerland
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- LTS5, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Giulio Gambarota
- Univ Rennes, CRLCC Eugene Marquis, Inserm, LTSI-UMR1099, LTSI, Campus de Beaulieu, Université de Rennes 1, 35042, Rennes, France
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14
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Testud B, Fabiani N, Demortière S, Mchinda S, Medina NL, Pelletier J, Guye M, Audoin B, Stellmann JP, Callot V. Contribution of the MP2RAGE 7T Sequence in MS Lesions of the Cervical Spinal Cord. AJNR Am J Neuroradiol 2023; 44:1101-1107. [PMID: 37562829 PMCID: PMC10494945 DOI: 10.3174/ajnr.a7964] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2023] [Accepted: 07/06/2023] [Indexed: 08/12/2023]
Abstract
BACKGROUND AND PURPOSE The detection of spinal cord lesions in patients with MS is challenging. Recently, the 3D MP2RAGE sequence demonstrated its usefulness at 3T. Benefiting from the high spatial resolution provided by ultra-high-field MR imaging systems, we aimed to evaluate the contribution of the 3D MP2RAGE sequence acquired at 7T for the detection of MS lesions in the cervical spine. MATERIALS AND METHODS Seventeen patients with MS participated in this study. They were examined at both 3T and 7T. The MR imaging examination included a Magnetic Imaging in MS (MAGNIMS) protocol with an axial T2*-WI gradient recalled-echo sequence ("optimized MAGNIMS protocol") and a 0.9-mm isotropic 3D MP2RAGE sequence at 3T, as well as a 0.7-mm isotropic and 0.3-mm in-plane-resolution anisotropic 3D MP2RAGE sequences at 7T. Each data set was read by a consensus of radiologists, neurologists, and neuroscientists. The number of lesions and their topography, as well as the visibility of the lesions from one set to another, were carefully analyzed. RESULTS A total of 55 lesions were detected. The absolute number of visible lesions differed among the 4 sequences (linear mixed effect ANOVA, P = .020). The highest detection was observed for the two 7T sequences with 51 lesions each (92.7% of the total). The optimized 3T MAGNIMS protocol and the 3T MP2RAGE isotropic sequence detected 41 (74.5%) and 35 lesions (63.6%), respectively. CONCLUSIONS The 7T MP2RAGE sequences detected more lesions than the 3T sets. Isotropic and anisotropic acquisitions performed comparably. Ultra-high-resolution sequences obtained at 7T improve the identification and delineation of lesions of the cervical spinal cord in MS.
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Affiliation(s)
- B Testud
- From the Center for Magnetic Resonance in Biology and Medicine (B.T., N.F., S.D., S.M., N.L.M., J.P., M.G., B.A., J.P.S., V.C.), Aix-Marseille University, Centre national de la recherche scientifique, Marseille, France
- Assistance Publique-Hopitaux de Marseille (B.T., N.F., S.D., S.M., N.L.M., J,P., M.G., B.A., J.P.S., V.C.), Hôpital Universitaire Timone, CEMEREM, Marseille, France
| | - N Fabiani
- From the Center for Magnetic Resonance in Biology and Medicine (B.T., N.F., S.D., S.M., N.L.M., J.P., M.G., B.A., J.P.S., V.C.), Aix-Marseille University, Centre national de la recherche scientifique, Marseille, France
- Assistance Publique-Hopitaux de Marseille (B.T., N.F., S.D., S.M., N.L.M., J,P., M.G., B.A., J.P.S., V.C.), Hôpital Universitaire Timone, CEMEREM, Marseille, France
| | - S Demortière
- From the Center for Magnetic Resonance in Biology and Medicine (B.T., N.F., S.D., S.M., N.L.M., J.P., M.G., B.A., J.P.S., V.C.), Aix-Marseille University, Centre national de la recherche scientifique, Marseille, France
- Assistance Publique-Hopitaux de Marseille (B.T., N.F., S.D., S.M., N.L.M., J,P., M.G., B.A., J.P.S., V.C.), Hôpital Universitaire Timone, CEMEREM, Marseille, France
- Department of Neurology (S.D., J.P., B.A.), Assistance Publique-Hopitaux de Marseille, Hôpital Universitaire Timone, Marseille, France
| | - S Mchinda
- From the Center for Magnetic Resonance in Biology and Medicine (B.T., N.F., S.D., S.M., N.L.M., J.P., M.G., B.A., J.P.S., V.C.), Aix-Marseille University, Centre national de la recherche scientifique, Marseille, France
- Assistance Publique-Hopitaux de Marseille (B.T., N.F., S.D., S.M., N.L.M., J,P., M.G., B.A., J.P.S., V.C.), Hôpital Universitaire Timone, CEMEREM, Marseille, France
| | - N L Medina
- From the Center for Magnetic Resonance in Biology and Medicine (B.T., N.F., S.D., S.M., N.L.M., J.P., M.G., B.A., J.P.S., V.C.), Aix-Marseille University, Centre national de la recherche scientifique, Marseille, France
- Assistance Publique-Hopitaux de Marseille (B.T., N.F., S.D., S.M., N.L.M., J,P., M.G., B.A., J.P.S., V.C.), Hôpital Universitaire Timone, CEMEREM, Marseille, France
| | - J Pelletier
- From the Center for Magnetic Resonance in Biology and Medicine (B.T., N.F., S.D., S.M., N.L.M., J.P., M.G., B.A., J.P.S., V.C.), Aix-Marseille University, Centre national de la recherche scientifique, Marseille, France
- Assistance Publique-Hopitaux de Marseille (B.T., N.F., S.D., S.M., N.L.M., J,P., M.G., B.A., J.P.S., V.C.), Hôpital Universitaire Timone, CEMEREM, Marseille, France
- Department of Neurology (S.D., J.P., B.A.), Assistance Publique-Hopitaux de Marseille, Hôpital Universitaire Timone, Marseille, France
| | - M Guye
- From the Center for Magnetic Resonance in Biology and Medicine (B.T., N.F., S.D., S.M., N.L.M., J.P., M.G., B.A., J.P.S., V.C.), Aix-Marseille University, Centre national de la recherche scientifique, Marseille, France
- Assistance Publique-Hopitaux de Marseille (B.T., N.F., S.D., S.M., N.L.M., J,P., M.G., B.A., J.P.S., V.C.), Hôpital Universitaire Timone, CEMEREM, Marseille, France
| | - B Audoin
- From the Center for Magnetic Resonance in Biology and Medicine (B.T., N.F., S.D., S.M., N.L.M., J.P., M.G., B.A., J.P.S., V.C.), Aix-Marseille University, Centre national de la recherche scientifique, Marseille, France
- Assistance Publique-Hopitaux de Marseille (B.T., N.F., S.D., S.M., N.L.M., J,P., M.G., B.A., J.P.S., V.C.), Hôpital Universitaire Timone, CEMEREM, Marseille, France
- Department of Neurology (S.D., J.P., B.A.), Assistance Publique-Hopitaux de Marseille, Hôpital Universitaire Timone, Marseille, France
| | - J P Stellmann
- From the Center for Magnetic Resonance in Biology and Medicine (B.T., N.F., S.D., S.M., N.L.M., J.P., M.G., B.A., J.P.S., V.C.), Aix-Marseille University, Centre national de la recherche scientifique, Marseille, France
- Assistance Publique-Hopitaux de Marseille (B.T., N.F., S.D., S.M., N.L.M., J,P., M.G., B.A., J.P.S., V.C.), Hôpital Universitaire Timone, CEMEREM, Marseille, France
| | - V Callot
- From the Center for Magnetic Resonance in Biology and Medicine (B.T., N.F., S.D., S.M., N.L.M., J.P., M.G., B.A., J.P.S., V.C.), Aix-Marseille University, Centre national de la recherche scientifique, Marseille, France
- Assistance Publique-Hopitaux de Marseille (B.T., N.F., S.D., S.M., N.L.M., J,P., M.G., B.A., J.P.S., V.C.), Hôpital Universitaire Timone, CEMEREM, Marseille, France
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15
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Elliott ML, Hanford LC, Hamadeh A, Hilbert T, Kober T, Dickerson BC, Mair RW, Eldaief MC, Buckner RL. Brain morphometry in older adults with and without dementia using extremely rapid structural scans. Neuroimage 2023; 276:120173. [PMID: 37201641 PMCID: PMC10330834 DOI: 10.1016/j.neuroimage.2023.120173] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2023] [Revised: 04/25/2023] [Accepted: 05/15/2023] [Indexed: 05/20/2023] Open
Abstract
T1-weighted structural MRI is widely used to measure brain morphometry (e.g., cortical thickness and subcortical volumes). Accelerated scans as fast as one minute or less are now available but it is unclear if they are adequate for quantitative morphometry. Here we compared the measurement properties of a widely adopted 1.0 mm resolution scan from the Alzheimer's Disease Neuroimaging Initiative (ADNI = 5'12'') with two variants of highly accelerated 1.0 mm scans (compressed-sensing, CSx6 = 1'12''; and wave-controlled aliasing in parallel imaging, WAVEx9 = 1'09'') in a test-retest study of 37 older adults aged 54 to 86 (including 19 individuals diagnosed with a neurodegenerative dementia). Rapid scans produced highly reliable morphometric measures that largely matched the quality of morphometrics derived from the ADNI scan. Regions of lower reliability and relative divergence between ADNI and rapid scan alternatives tended to occur in midline regions and regions with susceptibility-induced artifacts. Critically, the rapid scans yielded morphometric measures similar to the ADNI scan in regions of high atrophy. The results converge to suggest that, for many current uses, extremely rapid scans can replace longer scans. As a final test, we explored the possibility of a 0'49'' 1.2 mm CSx6 structural scan, which also showed promise. Rapid structural scans may benefit MRI studies by shortening the scan session and reducing cost, minimizing opportunity for movement, creating room for additional scan sequences, and allowing for the repetition of structural scans to increase precision of the estimates.
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Affiliation(s)
- Maxwell L Elliott
- Department of Psychology, Center for Brain Science, Harvard University, 52 Oxford Street, Northwest Laboratory 280.10, Cambridge, MA 02138, USA.
| | - Lindsay C Hanford
- Department of Psychology, Center for Brain Science, Harvard University, 52 Oxford Street, Northwest Laboratory 280.10, Cambridge, MA 02138, USA
| | - Aya Hamadeh
- Baylor College of Medicine, Houston, TX 77030, USA
| | - Tom Hilbert
- Advanced Clinical Imaging Technology, Siemens Healthineers International AG, Lausanne, Switzerland; Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland; LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Tobias Kober
- Advanced Clinical Imaging Technology, Siemens Healthineers International AG, Lausanne, Switzerland; Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland; LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Bradford C Dickerson
- Frontotemporal Disorders Unit, Massachusetts General Hospital, USA; Alzheimer's Disease Research Center, Massachusetts General Hospital, USA; Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, USA; Department of Neurology, Massachusetts General Hospital & Harvard Medical School, USA; Department of Psychiatry, Massachusetts General Hospital & Harvard Medical School, Charlestown, MA 02129, USA
| | - Ross W Mair
- Department of Psychology, Center for Brain Science, Harvard University, 52 Oxford Street, Northwest Laboratory 280.10, Cambridge, MA 02138, USA; Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, USA
| | - Mark C Eldaief
- Frontotemporal Disorders Unit, Massachusetts General Hospital, USA; Alzheimer's Disease Research Center, Massachusetts General Hospital, USA; Department of Neurology, Massachusetts General Hospital & Harvard Medical School, USA; Department of Psychiatry, Massachusetts General Hospital & Harvard Medical School, Charlestown, MA 02129, USA
| | - Randy L Buckner
- Department of Psychology, Center for Brain Science, Harvard University, 52 Oxford Street, Northwest Laboratory 280.10, Cambridge, MA 02138, USA; Alzheimer's Disease Research Center, Massachusetts General Hospital, USA; Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, USA; Department of Psychiatry, Massachusetts General Hospital & Harvard Medical School, Charlestown, MA 02129, USA
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16
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Piredda GF, Caneschi S, Hilbert T, Bonanno G, Joseph A, Egger K, Peter J, Klöppel S, Jehli E, Grieder M, Slotboom J, Seiffge D, Goeldlin M, Hoepner R, Willems T, Vulliemoz S, Seeck M, Venkategowda PB, Corredor Jerez RA, Maréchal B, Thiran JP, Wiest R, Kober T, Radojewski P. Submillimeter T 1 atlas for subject-specific abnormality detection at 7T. Magn Reson Med 2023; 89:1601-1616. [PMID: 36478417 DOI: 10.1002/mrm.29540] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2022] [Revised: 10/14/2022] [Accepted: 11/07/2022] [Indexed: 12/12/2022]
Abstract
PURPOSE Studies at 3T have shown that T1 relaxometry enables characterization of brain tissues at the single-subject level by comparing individual physical properties to a normative atlas. In this work, an atlas of normative T1 values at 7T is introduced with 0.6 mm isotropic resolution and its clinical potential is explored in comparison to 3T. METHODS T1 maps were acquired in two separate healthy cohorts scanned at 3T and 7T. Using transfer learning, a template-based brain segmentation algorithm was adapted to ultra-high field imaging data. After segmenting brain tissues, volumes were normalized into a common space, and an atlas of normative T1 values was established by modeling the T1 inter-subject variability. A method for single-subject comparisons restricted to white matter and subcortical structures was developed by computing Z-scores. The comparison was applied to eight patients scanned at both field strengths for proof of concept. RESULTS The proposed method for morphometry delivered segmentation masks without statistically significant differences from those derived with the original pipeline at 3T and achieved accurate segmentation at 7T. The established normative atlas allowed characterizing tissue alterations in single-subject comparisons at 7T, and showed greater anatomical details compared with 3T results. CONCLUSION A high-resolution quantitative atlas with an adapted pipeline was introduced and validated. Several case studies on different clinical conditions showed the feasibility, potential and limitations of high-resolution single-subject comparisons based on quantitative MRI atlases. This method in conjunction with 7T higher resolution broadens the range of potential applications of quantitative MRI in clinical practice.
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Affiliation(s)
- Gian Franco Piredda
- Advanced Clinical Imaging Technology, Siemens Healthineers International AG, Lausanne, Switzerland.,Human Neuroscience Platform, Fondation Campus Biotech Geneva, Geneva, Switzerland.,CIBM-AIT, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Samuele Caneschi
- Advanced Clinical Imaging Technology, Siemens Healthineers International AG, Lausanne, Switzerland.,Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.,LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Tom Hilbert
- Advanced Clinical Imaging Technology, Siemens Healthineers International AG, Lausanne, Switzerland.,Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.,LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Gabriele Bonanno
- Advanced Clinical Imaging Technology, Siemens Healthineers International AG, Bern, Switzerland.,Translational Imaging Center (TIC), Swiss Institute for Translational and Entrepreneurial Medicine, Bern, Switzerland.,Magnetic Resonance Methodology, Institute of Diagnostic and Interventional Neuroradiology, University of Bern, Bern, Switzerland
| | - Arun Joseph
- Advanced Clinical Imaging Technology, Siemens Healthineers International AG, Bern, Switzerland.,Translational Imaging Center (TIC), Swiss Institute for Translational and Entrepreneurial Medicine, Bern, Switzerland.,Magnetic Resonance Methodology, Institute of Diagnostic and Interventional Neuroradiology, University of Bern, Bern, Switzerland
| | - Karl Egger
- Department of Neuroradiology, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Jessica Peter
- University Hospital of Old Age Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland
| | - Stefan Klöppel
- University Hospital of Old Age Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland
| | - Elisabeth Jehli
- Translational Research Center, University Hospital of Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland.,Department of Neurosurgery, University Hospital of Zurich, Zurich, Switzerland
| | - Matthias Grieder
- Translational Research Center, University Hospital of Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland
| | - Johannes Slotboom
- Support Center for Advanced Neuroimaging, Institute for Diagnostic and Interventional Neuroradiology, Inselspital, University of Bern, Bern, Switzerland
| | - David Seiffge
- Department of Neurology, University Hospital Bern, Inselspital, University of Bern, Bern, Switzerland
| | - Martina Goeldlin
- Department of Neurology, University Hospital Bern, Inselspital, University of Bern, Bern, Switzerland
| | - Robert Hoepner
- Department of Neurology, University Hospital Bern, Inselspital, University of Bern, Bern, Switzerland
| | - Tom Willems
- Institute of Psychology, University of Bern, Bern, Switzerland
| | - Serge Vulliemoz
- EEG and Epilepsy Unit, Department of Clinical Neurosciences, Geneva University Hospitals and Faculty of Medicine, Geneva, Switzerland
| | - Margitta Seeck
- EEG and Epilepsy Unit, Department of Clinical Neurosciences, Geneva University Hospitals and Faculty of Medicine, Geneva, Switzerland
| | | | - Ricardo A Corredor Jerez
- Advanced Clinical Imaging Technology, Siemens Healthineers International AG, Lausanne, Switzerland.,Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.,LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Bénédicte Maréchal
- Advanced Clinical Imaging Technology, Siemens Healthineers International AG, Lausanne, Switzerland.,Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.,LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Jean-Philippe Thiran
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.,LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Roland Wiest
- Translational Imaging Center (TIC), Swiss Institute for Translational and Entrepreneurial Medicine, Bern, Switzerland.,Support Center for Advanced Neuroimaging, Institute for Diagnostic and Interventional Neuroradiology, Inselspital, University of Bern, Bern, Switzerland
| | - Tobias Kober
- Advanced Clinical Imaging Technology, Siemens Healthineers International AG, Lausanne, Switzerland.,Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.,LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Piotr Radojewski
- Translational Imaging Center (TIC), Swiss Institute for Translational and Entrepreneurial Medicine, Bern, Switzerland.,Support Center for Advanced Neuroimaging, Institute for Diagnostic and Interventional Neuroradiology, Inselspital, University of Bern, Bern, Switzerland
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17
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Dokumacı AS, Aitken FR, Sedlacik J, Bridgen P, Tomi‐Tricot R, Mooiweer R, Vecchiato K, Wilkinson T, Casella C, Giles S, Hajnal JV, Malik SJ, O'Muircheartaigh J, Carmichael DW. Simultaneous Optimization of MP2RAGE T 1 -weighted (UNI) and FLuid And White matter Suppression (FLAWS) brain images at 7T using Extended Phase Graph (EPG) Simulations. Magn Reson Med 2023; 89:937-950. [PMID: 36352772 PMCID: PMC10100108 DOI: 10.1002/mrm.29479] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2022] [Revised: 09/16/2022] [Accepted: 09/16/2022] [Indexed: 11/11/2022]
Abstract
PURPOSE The MP2RAGE sequence is typically optimized for either T1 -weighted uniform image (UNI) or gray matter-dominant fluid and white matter suppression (FLAWS) contrast images. Here, the purpose was to optimize an MP2RAGE protocol at 7 Tesla to provide UNI and FLAWS images simultaneously in a clinically applicable acquisition time at <0.7 mm isotropic resolution. METHODS Using the extended phase graph formalism, the signal evolution of the MP2RAGE sequence was simulated incorporating T2 relaxation, diffusion, RF spoiling, and B1 + variability. Flip angles and TI were optimized at different TRs (TRMP2RAGE ) to produce an optimal contrast-to-noise ratio for UNI and FLAWS images. Simulation results were validated by comparison to MP2RAGE brain scans of 5 healthy subjects, and a final protocol at TRMP2RAGE = 4000 ms was applied in 19 subjects aged 8-62 years with and without epilepsy. RESULTS FLAWS contrast images could be obtained while maintaining >85% of the optimal UNI contrast-to-noise ratio. Using TI1 /TI2 /TRMP2RAGE of 650/2280/4000 ms, 6/8 partial Fourier in the inner phase-encoding direction, and GRAPPA factor = 4 in the other, images with 0.65 mm isotropic resolution were produced in <7.5 min. The contrast-to-noise ratio was around 20% smaller at TRMP2RAGE = 4000 ms compared to that at TRMP2RAGE = 5000 ms; however, the 20% shorter duration makes TRMP2RAGE = 4000 ms a good candidate for clinical applications example, pediatrics. CONCLUSION FLAWS and UNI images could be obtained in a single scan with 0.65 mm isotropic resolution, providing a set of high-contrast images and full brain coverage in a clinically applicable scan time. Images with excellent anatomical detail were demonstrated over a wide age range using the optimized parameter set.
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Affiliation(s)
- Ayşe Sıla Dokumacı
- Biomedical Engineering DepartmentSchool of Biomedical Engineering and Imaging Sciences, King's College London
LondonUnited Kingdom
- London Collaborative Ultra high field System (LoCUS)LondonUnited Kingdom
| | - Fraser R. Aitken
- Biomedical Engineering DepartmentSchool of Biomedical Engineering and Imaging Sciences, King's College London
LondonUnited Kingdom
- London Collaborative Ultra high field System (LoCUS)LondonUnited Kingdom
| | - Jan Sedlacik
- London Collaborative Ultra high field System (LoCUS)LondonUnited Kingdom
- Radiology DepartmentGreat Ormond Street Hospital for ChildrenLondonUnited Kingdom
| | - Pip Bridgen
- Biomedical Engineering DepartmentSchool of Biomedical Engineering and Imaging Sciences, King's College London
LondonUnited Kingdom
- London Collaborative Ultra high field System (LoCUS)LondonUnited Kingdom
| | - Raphael Tomi‐Tricot
- Biomedical Engineering DepartmentSchool of Biomedical Engineering and Imaging Sciences, King's College London
LondonUnited Kingdom
- London Collaborative Ultra high field System (LoCUS)LondonUnited Kingdom
- MR Research CollaborationsSiemens Healthcare LimitedCamberleyUnited Kingdom
| | - Ronald Mooiweer
- Biomedical Engineering DepartmentSchool of Biomedical Engineering and Imaging Sciences, King's College London
LondonUnited Kingdom
- MR Research CollaborationsSiemens Healthcare LimitedCamberleyUnited Kingdom
| | - Katy Vecchiato
- London Collaborative Ultra high field System (LoCUS)LondonUnited Kingdom
- Department of Forensic and Neurodevelopmental SciencesInstitute of Psychiatry, Psychology and Neuroscience, King's College LondonLondonUnited Kingdom
- Centre for the Developing BrainSchool of Biomedical Engineering and Imaging Sciences, King's College LondonLondonUnited Kingdom
| | - Tom Wilkinson
- Biomedical Engineering DepartmentSchool of Biomedical Engineering and Imaging Sciences, King's College London
LondonUnited Kingdom
- London Collaborative Ultra high field System (LoCUS)LondonUnited Kingdom
| | - Chiara Casella
- London Collaborative Ultra high field System (LoCUS)LondonUnited Kingdom
- Centre for the Developing BrainSchool of Biomedical Engineering and Imaging Sciences, King's College LondonLondonUnited Kingdom
| | - Sharon Giles
- Biomedical Engineering DepartmentSchool of Biomedical Engineering and Imaging Sciences, King's College London
LondonUnited Kingdom
- London Collaborative Ultra high field System (LoCUS)LondonUnited Kingdom
| | - Joseph V. Hajnal
- Biomedical Engineering DepartmentSchool of Biomedical Engineering and Imaging Sciences, King's College London
LondonUnited Kingdom
- London Collaborative Ultra high field System (LoCUS)LondonUnited Kingdom
| | - Shaihan J. Malik
- Biomedical Engineering DepartmentSchool of Biomedical Engineering and Imaging Sciences, King's College London
LondonUnited Kingdom
- London Collaborative Ultra high field System (LoCUS)LondonUnited Kingdom
| | - Jonathan O'Muircheartaigh
- London Collaborative Ultra high field System (LoCUS)LondonUnited Kingdom
- Department of Forensic and Neurodevelopmental SciencesInstitute of Psychiatry, Psychology and Neuroscience, King's College LondonLondonUnited Kingdom
- Centre for the Developing BrainSchool of Biomedical Engineering and Imaging Sciences, King's College LondonLondonUnited Kingdom
- MRC Centre for Neurodevelopmental Disorders, King's College LondonLondonUnited Kingdom
| | - David W. Carmichael
- Biomedical Engineering DepartmentSchool of Biomedical Engineering and Imaging Sciences, King's College London
LondonUnited Kingdom
- London Collaborative Ultra high field System (LoCUS)LondonUnited Kingdom
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18
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Abstract
ABSTRACT This review summarizes the existing techniques and methods used to generate synthetic contrasts from magnetic resonance imaging data focusing on musculoskeletal magnetic resonance imaging. To that end, the different approaches were categorized into 3 different methodological groups: mathematical image transformation, physics-based, and data-driven approaches. Each group is characterized, followed by examples and a brief overview of their clinical validation, if present. Finally, we will discuss the advantages, disadvantages, and caveats of synthetic contrasts, focusing on the preservation of image information, validation, and aspects of the clinical workflow.
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19
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Abstract
Cerebral small vessel disease (cSVD) is a major cause of stroke and dementia. This review summarizes recent developments in advanced neuroimaging of cSVD with a focus on clinical and research applications. In the first section, we highlight how advanced structural imaging techniques, including diffusion magnetic resonance imaging (MRI), enable improved detection of tissue damage, including characterization of tissue appearing normal on conventional MRI. These techniques enable progression to be monitored and may be useful as surrogate endpoint in clinical trials. Quantitative MRI, including iron and myelin imaging, provides insights into tissue composition on the molecular level. In the second section, we cover how advanced MRI techniques can demonstrate functional or dynamic abnormalities of the blood vessels, which could be targeted in mechanistic research and early-stage intervention trials. Such techniques include the use of dynamic contrast enhanced MRI to measure blood-brain barrier permeability, and MRI methods to assess cerebrovascular reactivity. In the third section, we discuss how the increased spatial resolution provided by ultrahigh field MRI at 7 T allows imaging of perforating arteries, and flow velocity and pulsatility within them. The advanced MRI techniques we describe are providing novel pathophysiological insights in cSVD and allow improved quantification of disease burden and progression. They have application in clinical trials, both in assessing novel therapeutic mechanisms, and as a sensitive endpoint to assess efficacy of interventions on parenchymal tissue damage. We also discuss challenges of these advanced techniques and suggest future directions for research.
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Affiliation(s)
- Hilde van den Brink
- Department of Neurology and
Neurosurgery, University Medical Center Utrecht Brain Center, Utrecht University,
Utrecht, The Netherlands
| | - Fergus N Doubal
- Centre for Clinical Brain Sciences, UK
Dementia Research Institute, University of Edinburgh, Edinburgh, UK
| | - Marco Duering
- Medical Image Analysis Center (MIAC AG)
and qbig, Department of Biomedical Engineering, University of Basel, Basel,
Switzerland,Marco Duering, Medical Image Analysis
Center (MIAC AG) and qbig, Department of Biomedical Engineering, University of
Basel, Marktgasse 8, Basel, CH-4051, Switzerland.
; @MarcoDuering
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20
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Ferraro PM, Gualco L, Costagli M, Schiavi S, Ponzano M, Signori A, Massa F, Pardini M, Castellan L, Levrero F, Zacà D, Piredda GF, Hilbert T, Kober T, Roccatagliata L. Compressed sensing (CS) MP2RAGE versus standard MPRAGE: A comparison of derived brain volume measurements. Phys Med 2022; 103:166-174. [DOI: 10.1016/j.ejmp.2022.10.023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/04/2022] [Revised: 09/16/2022] [Accepted: 10/23/2022] [Indexed: 11/11/2022] Open
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21
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La Rosa F, Beck ES, Maranzano J, Todea R, van Gelderen P, de Zwart JA, Luciano NJ, Duyn JH, Thiran J, Granziera C, Reich DS, Sati P, Bach Cuadra M. Multiple sclerosis cortical lesion detection with deep learning at ultra-high-field MRI. NMR IN BIOMEDICINE 2022; 35:e4730. [PMID: 35297114 PMCID: PMC9539569 DOI: 10.1002/nbm.4730] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/18/2021] [Revised: 02/23/2022] [Accepted: 03/14/2022] [Indexed: 05/16/2023]
Abstract
Manually segmenting multiple sclerosis (MS) cortical lesions (CLs) is extremely time consuming, and past studies have shown only moderate inter-rater reliability. To accelerate this task, we developed a deep-learning-based framework (CLAIMS: Cortical Lesion AI-Based Assessment in Multiple Sclerosis) for the automated detection and classification of MS CLs with 7 T MRI. Two 7 T datasets, acquired at different sites, were considered. The first consisted of 60 scans that include 0.5 mm isotropic MP2RAGE acquired four times (MP2RAGE×4), 0.7 mm MP2RAGE, 0.5 mm T2 *-weighted GRE, and 0.5 mm T2 *-weighted EPI. The second dataset consisted of 20 scans including only 0.75 × 0.75 × 0.9 mm3 MP2RAGE. CLAIMS was first evaluated using sixfold cross-validation with single and multi-contrast 0.5 mm MRI input. Second, the performance of the model was tested on 0.7 mm MP2RAGE images after training with either 0.5 mm MP2RAGE×4, 0.7 mm MP2RAGE, or alternating the two. Third, its generalizability was evaluated on the second external dataset and compared with a state-of-the-art technique based on partial volume estimation and topological constraints (MSLAST). CLAIMS trained only with MP2RAGE×4 achieved results comparable to those of the multi-contrast model, reaching a CL true positive rate of 74% with a false positive rate of 30%. Detection rate was excellent for leukocortical and subpial lesions (83%, and 70%, respectively), whereas it reached 53% for intracortical lesions. The correlation between disability measures and CL count was similar for manual and CLAIMS lesion counts. Applying a domain-scanner adaptation approach and testing CLAIMS on the second dataset, the performance was superior to MSLAST when considering a minimum lesion volume of 6 μL (lesion-wise detection rate of 71% versus 48%). The proposed framework outperforms previous state-of-the-art methods for automated CL detection across scanners and protocols. In the future, CLAIMS may be useful to support clinical decisions at 7 T MRI, especially in the field of diagnosis and differential diagnosis of MS patients.
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Affiliation(s)
- Francesco La Rosa
- Signal Processing Laboratory (LTS5)Ecole Polytechnique Fédérale de Lausanne (EPFL)Lausanne
- CIBM Center for Biomedical Imaging
- Translational Neuroradiology SectionNational Institute of Neurological Disorders and Stroke, National Institutes of HealthBethesdaMD
| | - Erin S. Beck
- Translational Neuroradiology SectionNational Institute of Neurological Disorders and Stroke, National Institutes of HealthBethesdaMD
- Department of NeurologyIcahn School of Medicine at Mount SinaiNew YorkNYUSA
| | - Josefina Maranzano
- Department of AnatomyUniversity of Quebec in Trois‐RivièresTrois‐RivièresQuebecCanada
- McConnell Brain Imaging Center, Department of Neurology and NeurosurgeryMontreal Neurological Institute and Hospital, McGill UniversityMontrealQuebecCanada
| | - Ramona‐Alexandra Todea
- Department of Neuroradiology, Clinic of Radiology and Nuclear MedicineUniversity Hospital of BaselBaselSwitzerland
| | - Peter van Gelderen
- Advanced MRI SectionNational Institute of Neurological Disorders and Stroke, National Institutes of HealthBethesdaMDUSA
| | - Jacco A. de Zwart
- Advanced MRI SectionNational Institute of Neurological Disorders and Stroke, National Institutes of HealthBethesdaMDUSA
| | - Nicholas J. Luciano
- Translational Neuroradiology SectionNational Institute of Neurological Disorders and Stroke, National Institutes of HealthBethesdaMD
| | - Jeff H. Duyn
- Advanced MRI SectionNational Institute of Neurological Disorders and Stroke, National Institutes of HealthBethesdaMDUSA
| | - Jean‐Philippe Thiran
- Signal Processing Laboratory (LTS5)Ecole Polytechnique Fédérale de Lausanne (EPFL)Lausanne
- CIBM Center for Biomedical Imaging
- Radiology DepartmentLausanne University and University HospitalSwitzerland
| | - Cristina Granziera
- Translational Imaging in Neurology (ThINk) Basel, Department of Medicine and Biomedical EngineeringUniversity Hospital Basel and University of BaselBaselSwitzerland
- Neurologic Clinic and Policlinic, Departments of Medicine, Clinical Research and Biomedical EngineeringUniversity Hospital Basel and University of BaselBaselSwitzerland
| | - Daniel S. Reich
- Translational Neuroradiology SectionNational Institute of Neurological Disorders and Stroke, National Institutes of HealthBethesdaMD
| | - Pascal Sati
- Translational Neuroradiology SectionNational Institute of Neurological Disorders and Stroke, National Institutes of HealthBethesdaMD
- Department of NeurologyCedars‐Sinai Medical CenterLos AngelesCAUSA
| | - Meritxell Bach Cuadra
- CIBM Center for Biomedical Imaging
- Radiology DepartmentLausanne University and University HospitalSwitzerland
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22
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Trotier AJ, Dilharreguy B, Anandra S, Corbin N, Lefrançois W, Ozenne V, Miraux S, Ribot EJ. The Compressed Sensing MP2RAGE as a Surrogate to the MPRAGE for Neuroimaging at 3 T. Invest Radiol 2022; 57:366-378. [PMID: 35030106 PMCID: PMC9390231 DOI: 10.1097/rli.0000000000000849] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2021] [Accepted: 11/08/2021] [Indexed: 11/26/2022]
Abstract
OBJECTIVES The magnetization-prepared 2 rapid acquisition gradient echo (MP2RAGE) sequence provides quantitative T1 maps in addition to high-contrast morphological images. Advanced acceleration techniques such as compressed sensing (CS) allow its acquisition time to be compatible with clinical applications. To consider its routine use in future neuroimaging protocols, the repeatability of the segmented brain structures was evaluated and compared with the standard morphological sequence (magnetization-prepared rapid gradient echo [MPRAGE]). The repeatability of the T1 measurements was also assessed. MATERIALS AND METHODS Thirteen healthy volunteers were scanned either 3 or 4 times at several days of interval, on a 3 T clinical scanner, with the 2 sequences (CS-MP2RAGE and MPRAGE), set with the same spatial resolution (0.8-mm isotropic) and scan duration (6 minutes 21 seconds). The reconstruction time of the CS-MP2RAGE outputs (including the 2 echo images, the MP2RAGE image, and the T1 map) was 3 minutes 33 seconds, using an open-source in-house algorithm implemented in the Gadgetron framework.Both precision and variability of volume measurements obtained from CAT12 and VolBrain were assessed. The T1 accuracy and repeatability were measured on phantoms and on humans and were compared with literature.Volumes obtained from the CS-MP2RAGE and the MPRAGE images were compared using Student t tests (P < 0.05 was considered significant). RESULTS The CS-MP2RAGE acquisition provided morphological images of the same quality and higher contrasts than the standard MPRAGE images. Similar intravolunteer variabilities were obtained with the CS-MP2RAGE and the MPRAGE segmentations. In addition, high-resolution T1 maps were obtained from the CS-MP2RAGE. T1 times of white and gray matters and several deep gray nuclei are consistent with the literature and show very low variability (<1%). CONCLUSIONS The CS-MP2RAGE can be used in future protocols to rapidly obtain morphological images and quantitative T1 maps in 3-dimensions while maintaining high repeatability in volumetry and relaxation times.
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Affiliation(s)
- Aurélien J. Trotier
- From the Centre de Résonance Magnétique des Systèmes Biologiques, UMR5536, CNRS/Université de Bordeaux
| | - Bixente Dilharreguy
- Biomedical Imaging Facility (pIBIO), UMS3767, CNRS/Université de Bordeaux, Bordeaux, France
| | - Serge Anandra
- Biomedical Imaging Facility (pIBIO), UMS3767, CNRS/Université de Bordeaux, Bordeaux, France
| | - Nadège Corbin
- From the Centre de Résonance Magnétique des Systèmes Biologiques, UMR5536, CNRS/Université de Bordeaux
- UCL Queen Square Institute of Neurology, Wellcome Centre for Human Neuroimaging, University College of London, London, United Kingdom
| | - William Lefrançois
- From the Centre de Résonance Magnétique des Systèmes Biologiques, UMR5536, CNRS/Université de Bordeaux
| | - Valery Ozenne
- From the Centre de Résonance Magnétique des Systèmes Biologiques, UMR5536, CNRS/Université de Bordeaux
| | - Sylvain Miraux
- From the Centre de Résonance Magnétique des Systèmes Biologiques, UMR5536, CNRS/Université de Bordeaux
| | - Emeline J. Ribot
- From the Centre de Résonance Magnétique des Systèmes Biologiques, UMR5536, CNRS/Université de Bordeaux
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23
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Vaneckova M, Piredda GF, Andelova M, Krasensky J, Uher T, Srpova B, Havrdova EK, Vodehnalova K, Horakova D, Hilbert T, Maréchal B, Fartaria MJ, Ravano V, Kober T. Periventricular gradient of T 1 tissue alterations in multiple sclerosis. Neuroimage Clin 2022; 34:103009. [PMID: 35561554 PMCID: PMC9112026 DOI: 10.1016/j.nicl.2022.103009] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2022] [Revised: 03/24/2022] [Accepted: 04/12/2022] [Indexed: 01/12/2023]
Abstract
T1 relaxation times alterations were assessed based on a study-specific atlas. T1 alterations depend on distance from lateral ventricles (“periventricular gradient”). Gradient parameters correlate better with disability compared to conventional MRI.
Objective Pathology in multiple sclerosis is not homogenously distributed. Recently, it has been shown that structures adjacent to CSF are more severely affected. A gradient of brain tissue involvement was shown with more severe pathology in periventricular areas and in proximity to brain surfaces such as the subarachnoid spaces and ependyma, and hence termed the “surface–in” gradient. Here, we study whether (i) the surface-in gradient of periventricular tissue alteration measured by T1 relaxometry is already present in early multiple sclerosis patients, (ii) how it differs between early and progressive multiple sclerosis patients, and (iii) whether the gradient-derived metrics in normal-appearing white matter and lesions correlate better with physical disability than conventional MRI-based metrics. Methods Forty-seven patients with early multiple sclerosis, 52 with progressive multiple sclerosis, and 92 healthy controls were included in the study. Isotropic 3D T1 relaxometry maps were obtained using the Magnetization-Prepared 2 Rapid Acquisition Gradient Echoes sequence at 3 T. After spatially normalizing the T1 maps into a study-specific common space, T1 inter-subject variability within the healthy cohort was modelled voxel-wise, yielding a normative T1 atlas. Individual comparisons of each multiple sclerosis patient against the atlas were performed by computing z-scores. Equidistant bands of voxels were defined around the ventricles in the supratentorial white matter; the z-scores in these bands were analysed and compared between the early and progressive multiple sclerosis cohorts. Correlations between both conventional and z-score-gradient-derived MRI metrics and the Expanded Disability Status Scale were assessed. Results Patients with early and progressive multiple sclerosis demonstrated a periventricular gradient of T1 relaxation time z-scores. In progressive multiple sclerosis, z-score-derived metrics reflecting the gradient of tissue abnormality in normal-appearing white matter were more strongly correlated with disability (maximal rho = 0.374) than the conventional lesion volume and count (maximal rho = 0.189 and 0.21 respectively). In early multiple sclerosis, the gradient of normal-appearing white matter volume with z-scores > 2 at baseline correlated with clinical disability assessed at two years follow-up. Conclusion Our results suggest that the surface-in white matter gradient of tissue alteration is detectable with T1 relaxometry and is already present at clinical disease onset. The periventricular gradients correlate with clinical disability. The periventricular gradient in normal-appearing white matter may thus qualify as a promising biomarker for monitoring of disease activity from an early stage in all phenotypes of multiple sclerosis.
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Affiliation(s)
- Manuela Vaneckova
- Department of Radiology, First Faculty of Medicine, Charles University and General University Hospital, Prague, Czech Republic.
| | - Gian Franco Piredda
- Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland; Department of Radiology, Lausanne University Hospital and University of Lausanne, Switzerland; Signal Processing Laboratory (LTS 5), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Michaela Andelova
- Department of Neurology and Center of Clinical Neuroscience, First Faculty of Medicine, Charles University and General University Hospital, Prague, Czech Republic
| | - Jan Krasensky
- Department of Radiology, First Faculty of Medicine, Charles University and General University Hospital, Prague, Czech Republic
| | - Tomas Uher
- Department of Neurology and Center of Clinical Neuroscience, First Faculty of Medicine, Charles University and General University Hospital, Prague, Czech Republic
| | - Barbora Srpova
- Department of Neurology and Center of Clinical Neuroscience, First Faculty of Medicine, Charles University and General University Hospital, Prague, Czech Republic
| | - Eva Kubala Havrdova
- Department of Neurology and Center of Clinical Neuroscience, First Faculty of Medicine, Charles University and General University Hospital, Prague, Czech Republic
| | - Karolina Vodehnalova
- Department of Neurology and Center of Clinical Neuroscience, First Faculty of Medicine, Charles University and General University Hospital, Prague, Czech Republic
| | - Dana Horakova
- Department of Neurology and Center of Clinical Neuroscience, First Faculty of Medicine, Charles University and General University Hospital, Prague, Czech Republic
| | - Tom Hilbert
- Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland; Department of Radiology, Lausanne University Hospital and University of Lausanne, Switzerland; Signal Processing Laboratory (LTS 5), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Bénédicte Maréchal
- Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland; Department of Radiology, Lausanne University Hospital and University of Lausanne, Switzerland; Signal Processing Laboratory (LTS 5), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Mário João Fartaria
- Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland; Department of Radiology, Lausanne University Hospital and University of Lausanne, Switzerland; Signal Processing Laboratory (LTS 5), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Veronica Ravano
- Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland; Department of Radiology, Lausanne University Hospital and University of Lausanne, Switzerland; Signal Processing Laboratory (LTS 5), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Tobias Kober
- Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland; Department of Radiology, Lausanne University Hospital and University of Lausanne, Switzerland; Signal Processing Laboratory (LTS 5), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
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24
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3-Dimensional Fluid and White Matter Suppression Magnetic Resonance Imaging Sequence Accelerated With Compressed Sensing Improves Multiple Sclerosis Cervical Spinal Cord Lesion Detection Compared With Standard 2-Dimensional Imaging. Invest Radiol 2022; 57:575-584. [PMID: 35318971 DOI: 10.1097/rli.0000000000000874] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
OBJECTIVES Fluid and white matter suppression (FLAWS) is a recently proposed magnetic resonance sequence derived from magnetization-prepared 2 rapid acquisition gradient-echo providing 2 coregistered datasets with white matter- and cerebrospinal fluid-suppressed signal, enabling synthetic imaging with amplified contrast. Although these features are high potential for brain multiple sclerosis (MS) imaging, spinal cord has never been evaluated with this sequence to date. The objective of this work was therefore to assess diagnostic performance and self-confidence provided by compressed-sensing (CS) 3-dimensional (3D) FLAWS for cervical MS lesion detection on a head scan that includes the cervical cord without changing standard procedures. MATERIALS AND METHODS Prospective 3 T scans (MS first diagnosis or follow-up) acquired between 2019 and 2020 were retrospectively analyzed. All patients underwent 3D CS-FLAWS (duration: 5 minutes 40 seconds), axial T2 turbo spin echo covering cervical spine from cervicomedullary junction to the same inferior level as FLAWS, and sagittal cervical T2/short tau inversion recovery imaging. Two readers performed a 2-stage double-blind reading, followed by consensus reading. Wilcoxon tests were used to compare the number of detected spinal cord lesions and the reader's diagnostic self-confidence when using FLAWS versus the reference 2D T2-weighted imaging. RESULTS Fifty-eight patients were included (mean age, 40 ± 13 years, 46 women, 7 ± 6 years mean disease duration). The CS-FLAWS detected significantly more lesions than the reference T2-weighted imaging (197 vs 152 detected lesions, P < 0.001), with a sensitivity of 98% (T2-weighted imaging sensitivity: 90%) after consensual reading. Considering the subgroup of patients who underwent sagittal T2 + short tau inversion recovery imaging (Magnetic Resonance Imaging for Multiple Sclerosis subgroup), +250% lesions were detected with FLAWS (63 vs 25 lesions detected, P < 0.001). Mean reading self-confidence was significantly better with CS-FLAWS (median, 5 [interquartile range, 1] [no doubt for diagnosis] vs 4 [interquartile range, 1] [high confidence]; P < 0.001). CONCLUSIONS Imaging with CS-FLAWS provides an improved cervical spinal cord exploration for MS with increased self-confidence compared with conventional T2-weighted imaging, in a clinically acceptable time.
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25
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Berg RC, Leutritz T, Weiskopf N, Preibisch C. Multi-parameter quantitative mapping of R1, R2*, PD, and MTsat is reproducible when accelerated with Compressed SENSE. Neuroimage 2022; 253:119092. [PMID: 35288281 DOI: 10.1016/j.neuroimage.2022.119092] [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: 10/12/2021] [Revised: 03/07/2022] [Accepted: 03/08/2022] [Indexed: 10/18/2022] Open
Abstract
Multi-parameter mapping (MPM) magnetic resonance imaging (MRI) provides quantitative estimates of the longitudinal and effective transverse relaxation rates R1 and R2*, proton density (PD), and magnetization transfer saturation (MTsat). Thereby, MPM enables better comparability across sites and time than conventional weighted MRI. However, for MPM, several contrasts must be acquired, resulting in prolonged measurement durations and thus preventing MPM's application in clinical routines. State-of-the-art imaging acceleration techniques such as Compressed SENSE (CS), a combination of compressed sensing and sensitivity encoding, can be used to reduce the scan time of MPM. However, the accuracy and precision of the resulting quantitative parameter maps have not been systematically evaluated. In this study, we therefore investigated the effect of CS acceleration on the fidelity and reproducibility of MPM acquisitions. In five healthy volunteers and in a phantom, we compared MPM metrics acquired without imaging acceleration, with the standard acceleration (SENSE factor 2.5), and with Compressed SENSE with acceleration factors 4 and 6 using a 32-channel head coil. We evaluated the reproducibility and repeatability of accelerated MPM using data from three scan sessions in gray and white matter volumes-of-interest (VOIs). Accelerated MPM provided precise and accurate quantitative parameter maps. For most parameters, the results of the CS-accelerated protocols correlated more strongly with the non-accelerated protocol than the standard SENSE-accelerated protocols. Furthermore, for most VOIs and contrasts, coefficients of variation were lower when calculated from data acquired with different imaging accelerations within a single scan session than from data acquired in different scan sessions. These results suggest that MPM with Compressed SENSE acceleration factors up to at least 6 yields reproducible quantitative parameter maps that are highly comparable to those acquired without imaging acceleration. Compressed SENSE can thus be used to considerably reduce the scan duration of R1, R2*, PD, and MTsat mapping, and is highly promising for clinical applications of MPM.
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Affiliation(s)
- Ronja C Berg
- Technical University of Munich, School of Medicine, Klinikum rechts der Isar, Department of Diagnostic and Interventional Neuroradiology, Munich, Germany; Technical University of Munich, School of Medicine, Klinikum rechts der Isar, Department of Neurology, Munich, Germany.
| | - Tobias Leutritz
- Max Planck Institute for Human Cognitive and Brain Sciences, Department of Neurophysics, Leipzig, Germany.
| | - Nikolaus Weiskopf
- Max Planck Institute for Human Cognitive and Brain Sciences, Department of Neurophysics, Leipzig, Germany; Felix Bloch Institute for Solid State Physics, Faculty of Physics and Earth Sciences, Leipzig University, Leipzig, Germany.
| | - Christine Preibisch
- Technical University of Munich, School of Medicine, Klinikum rechts der Isar, Department of Diagnostic and Interventional Neuroradiology, Munich, Germany; Technical University of Munich, School of Medicine, Klinikum rechts der Isar, Department of Neurology, Munich, Germany; Technical University of Munich, School of Medicine, Klinikum rechts der Isar, TUM Neuroimaging Center, Munich, Germany.
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26
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Clifford B, Conklin J, Huang SY, Feiweier T, Hosseini Z, Goncalves Filho ALM, Tabari A, Demir S, Lo WC, Longo MGF, Lev M, Schaefer P, Rapalino O, Setsompop K, Bilgic B, Cauley S. An artificial intelligence-accelerated 2-minute multi-shot echo planar imaging protocol for comprehensive high-quality clinical brain imaging. Magn Reson Med 2021; 87:2453-2463. [PMID: 34971463 DOI: 10.1002/mrm.29117] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2021] [Revised: 10/29/2021] [Accepted: 11/22/2021] [Indexed: 02/06/2023]
Abstract
PURPOSE We introduce and validate an artificial intelligence (AI)-accelerated multi-shot echo-planar imaging (msEPI)-based method that provides T1w, T2w, T 2 ∗ , T2-FLAIR, and DWI images with high SNR, high tissue contrast, low specific absorption rates (SAR), and minimal distortion in 2 minutes. METHODS The rapid imaging technique combines a novel machine learning (ML) scheme to limit g-factor noise amplification and improve SNR, a magnetization transfer preparation module to provide clinically desirable contrast, and high per-shot EPI undersampling factors to reduce distortion. The ML training and image reconstruction incorporates a tunable parameter for controlling the level of denoising/smoothness. The performance of the reconstruction method is evaluated across various acceleration factors, contrasts, and SNR conditions. The 2-minute protocol is directly compared to a 10-minute clinical reference protocol through deployment in a clinical setting, where five representative cases with pathology are examined. RESULTS Optimization of custom msEPI sequences and protocols was performed to balance acquisition efficiency and image quality compared to the five-fold longer clinical reference. Training data from 16 healthy subjects across multiple contrasts and orientations were used to produce ML networks at various acceleration levels. The flexibility of the ML reconstruction was demonstrated across SNR levels, and an optimized regularization was determined through radiological review. Network generalization toward novel pathology, unobserved during training, was illustrated in five clinical case studies with clinical reference images provided for comparison. CONCLUSION The rapid 2-minute msEPI-based protocol with tunable ML reconstruction allows for advantageous trade-offs between acquisition speed, SNR, and tissue contrast when compared to the five-fold slower standard clinical reference exam.
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Affiliation(s)
- Bryan Clifford
- Siemens Medical Solutions USA, Boston, Massachusetts, USA
| | - John Conklin
- Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Susie Y Huang
- Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts, USA
| | | | | | | | - Azadeh Tabari
- Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Serdest Demir
- Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Wei-Ching Lo
- Siemens Medical Solutions USA, Boston, Massachusetts, USA
| | | | - Michael Lev
- Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Pam Schaefer
- Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Otto Rapalino
- Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Kawin Setsompop
- Department of Radiology and Department of Electrical Engineering, Stanford University, Stanford, California, USA
| | - Berkin Bilgic
- Department of Radiology, A. A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Stephen Cauley
- Department of Radiology, A. A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA
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27
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Nguyen TH, Vaussy A, Le Gaudu V, Aboab J, Espinoza S, Curajos I, Heron E, Habas C. The brainstem in multiple sclerosis: MR identification of tracts and nuclei damage. Insights Imaging 2021; 12:151. [PMID: 34674050 PMCID: PMC8531176 DOI: 10.1186/s13244-021-01101-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2021] [Accepted: 08/23/2021] [Indexed: 01/04/2023] Open
Abstract
Objective To evaluate the 3D Fast Gray Acquisition T1 Inversion Recovery (FGATIR) sequence for MRI identification of brainstem tracts and nuclei damage in multiple sclerosis (MS) patients. Methods From april to december 2020, 10 healthy volunteers and 50 patients with remitted-relapsing MS (58% female, mean age 36) underwent MR imaging in the Neuro-imaging department of the C.H.N.O. des Quinze-Vingts, Paris, France. MRI was achieved on a 3 T system (MAGNETOM Skyra) using a 64-channel coil. 3D FGATIR sequence was first performed on healthy volunteers to classify macroscopically identifiable brainstem structures. Then, FGATIR was assessed in MS patients to locate brainstem lesions detected with Proton Density/T2w (PD/T2w) sequence. Results In healthy volunteers, FGATIR allowed a precise visualization of tracts and nuclei according to their myelin density. Including FGATIR in MR follow-up of MS patients helped to identify structures frequently involved in the inflammatory process. Most damaged tracts were the superior cerebellar peduncle and the transverse fibers of the pons. Most frequently affected nuclei were the vestibular nuclei, the trigeminal tract, the facial nerve and the solitary tract. Conclusion Combination of FGATIR and PD/T2w sequences opened prospects to define MS elective injury in brainstem tracts and nuclei, with particular lesion features suggesting variations of the inflammatory process within brainstem structures. In a further study, hypersignal quantification and microstructure information should be evaluated using relaxometry and diffusion tractography. Technical improvements would bring novel parameters to train an artificial neural network for accurate automated labeling of MS lesions within the brainstem.
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Affiliation(s)
- Thien Huong Nguyen
- Department of Neuro Imaging, C.H.N.O. des Quinze- Vingts, Paris, France.
| | | | - Violette Le Gaudu
- Department of Neuro Imaging, C.H.N.O. des Quinze- Vingts, Paris, France
| | - Jennifer Aboab
- Department of Internal Medicine, C.H.N.O. des Quinze-Vingts, Paris, France
| | - Sophie Espinoza
- Department of Neuro Imaging, C.H.N.O. des Quinze- Vingts, Paris, France
| | - Irina Curajos
- Department of Neuro Imaging, C.H.N.O. des Quinze- Vingts, Paris, France
| | - Emmanuel Heron
- Department of Internal Medicine, C.H.N.O. des Quinze-Vingts, Paris, France
| | - Christophe Habas
- Department of Neuro Imaging, C.H.N.O. des Quinze- Vingts, Paris, France
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28
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Forodighasemabadi A, Rasoanandrianina H, El Mendili MM, Guye M, Callot V. An optimized MP2RAGE sequence for studying both brain and cervical spinal cord in a single acquisition at 3T. Magn Reson Imaging 2021; 84:18-26. [PMID: 34517015 DOI: 10.1016/j.mri.2021.08.011] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2021] [Revised: 08/25/2021] [Accepted: 08/25/2021] [Indexed: 11/30/2022]
Abstract
Magnetization Prepared 2 Rapid Acquisition Gradient Echo (MP2RAGE) is a T1 mapping technique that has been used broadly on brain and recently on cervical spinal cord (cSC). The growing interest for combined investigation of brain and SC in numerous pathologies of the central nervous system such as multiple sclerosis (MS), amyotrophic lateral sclerosis (ALS) and traumatic injuries, now brings about the need for optimization with regards to this specific investigation. This implies large spatial coverage with high spatial resolution and short acquisition time, high CNR and low B1+ sensitivity, as well as high reproducibility and robust post-processing tools for T1 quantification in different regions of brain and SC. In this work, a dedicated protocol (referred to as Pr-BSC) has been optimized for simultaneous brain and cSC T1 MP2RAGE acquisition at 3T. After computer simulation optimization, the protocol was applied for in vivo validation experiments and compared to previously published state of the art protocols focusing on either the brain (Pr-B) or the cSC (Pr-SC). Reproducibility and in-ROI standard deviations were assessed on healthy volunteers in the perspective of future clinical use. The mean T1 values, obtained by the Pr-BSC, in brain white, gray and deep gray matters were: (mean ± in-ROI SD) 792 ± 27 ms, 1339 ± 139 ms and 1136 ± 88 ms, respectively. In cSC, T1 values for white matter corticospinal, posterior sensory, lateral sensory and rubro/reticulospinal tracts were 902 ± 41 ms, 920 ± 35 ms, 903 ± 46 ms, 891 ± 41 ms, respectively, and 954 ± 32 ms for anterior and intermediate gray matter. The Pr-BSC protocol showed excellent agreement with previously proposed Pr-B on brain and Pr-SC on cSC, with very high inter-scan reproducibility (coefficients of variation of 0.52 ± 0.36% and 1.12 ± 0.62% on brain and cSC, respectively). This optimized protocol covering both brain and cSC with a sub-millimetric isotropic spatial resolution in one acquisition of less than 8 min, opens up great perspectives for clinical applications focusing on degenerative tissue such as encountered in MS and ALS.
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Affiliation(s)
- Arash Forodighasemabadi
- Aix-Marseille Univ, CNRS, CRMBM, Marseille, France; APHM, Hopital Universitaire Timone, CEMEREM, Marseille, France; Aix-Marseille Univ, Université Gustave Eiffel, LBA, Marseille, France; iLab-Spine International Associated Laboratory, Marseille-Montreal, France, Canada
| | - Henitsoa Rasoanandrianina
- Aix-Marseille Univ, CNRS, CRMBM, Marseille, France; APHM, Hopital Universitaire Timone, CEMEREM, Marseille, France; Aix-Marseille Univ, Université Gustave Eiffel, LBA, Marseille, France; iLab-Spine International Associated Laboratory, Marseille-Montreal, France, Canada
| | - Mohamed Mounir El Mendili
- Aix-Marseille Univ, CNRS, CRMBM, Marseille, France; APHM, Hopital Universitaire Timone, CEMEREM, Marseille, France
| | - Maxime Guye
- Aix-Marseille Univ, CNRS, CRMBM, Marseille, France; APHM, Hopital Universitaire Timone, CEMEREM, Marseille, France
| | - Virginie Callot
- Aix-Marseille Univ, CNRS, CRMBM, Marseille, France; APHM, Hopital Universitaire Timone, CEMEREM, Marseille, France; iLab-Spine International Associated Laboratory, Marseille-Montreal, France, Canada.
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29
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Yarach U, Saekho S, Setsompop K, Suwannasak A, Boonsuth R, Wantanajittikul K, Angkurawaranon S, Angkurawaranon C, Sangpin P. Feasibility of accelerated 3D T1-weighted MRI using compressed sensing: application to quantitative volume measurements of human brain structures. MAGNETIC RESONANCE MATERIALS IN PHYSICS BIOLOGY AND MEDICINE 2021; 34:915-927. [PMID: 34181119 DOI: 10.1007/s10334-021-00939-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/25/2021] [Revised: 06/09/2021] [Accepted: 06/23/2021] [Indexed: 12/26/2022]
Abstract
OBJECTIVE Scan time reduction is necessary for volumetric acquisitions to improve workflow productivity and to reduce motion artifacts during MRI procedures. We explored the possibility that Compressed Sensing-4 (CS-4) can be employed with 3D-turbo-field-echo T1-weighted (3D-TFE-T1W) sequence without compromising subcortical measurements on clinical 1.5 T MRI. MATERIALS AND METHODS Thirty-three healthy volunteers (24 females, 9 males) underwent imaging scans on a 1.5 T MRI equipped with a 12-channel head coil. 3D-TFE-T1W for whole-brain coverage was performed with different acceleration factors, including SENSE-2, SENSE-4, CS-4. Freesurfer, FSL's FIRST, and volBrain packages were utilized for subcortical segmentation. All processed data were assessed using the Wilcoxon signed-rank test. RESULTS The results obtained from SENSE-2 were considered as references. For SENSE-4, the maximum signal-to-noise ratio (SNR) drop was detected in the Accumbens (51.96%). For CS-4, the maximum SNR drop was detected in the Amygdala (10.55%). Since the SNR drop in CS-4 is relatively small, the SNR in all of the subcortical volumes obtained from SENSE-2 and CS-4 are not statistically different (P > 0.05), and their Pearson's correlation coefficients are larger than 0.90. The maximum biases of SENSE-4 and CS-4 were found in the Thalamus with the mean of differences of 1.60 ml and 0.18 ml, respectively. CONCLUSION CS-4 provided sufficient quality of 3D-TFE-T1W images for 1.5 T MRI equipped with a 12-channel receiver coil. Subcortical volumes obtained from the CS-4 images are consistent among different post-processing packages.
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Affiliation(s)
- Uten Yarach
- Department of Radiologic Technology, Faculty of Associated Medical Sciences, Chiang Mai University, 110 Intavaroros Rd. Sripoom, Chiang Mai, 50200, Thailand.
| | - Suwit Saekho
- Department of Radiologic Technology, Faculty of Associated Medical Sciences, Chiang Mai University, 110 Intavaroros Rd. Sripoom, Chiang Mai, 50200, Thailand
| | - Kawin Setsompop
- Department of Radiology, Stanford University, Stanford, CA, USA.,Department of Electrical Engineering, Stanford University, Stanford, CA, USA
| | - Atita Suwannasak
- Department of Radiologic Technology, Faculty of Associated Medical Sciences, Chiang Mai University, 110 Intavaroros Rd. Sripoom, Chiang Mai, 50200, Thailand
| | - Ratthaporn Boonsuth
- Department of Radiologic Technology, Faculty of Associated Medical Sciences, Chiang Mai University, 110 Intavaroros Rd. Sripoom, Chiang Mai, 50200, Thailand
| | - Kittichai Wantanajittikul
- Department of Radiologic Technology, Faculty of Associated Medical Sciences, Chiang Mai University, 110 Intavaroros Rd. Sripoom, Chiang Mai, 50200, Thailand
| | - Salita Angkurawaranon
- Department of Radiology, Faculty of Medicine, Chiang Mai University, Chiang Mai, Thailand
| | - Chaisiri Angkurawaranon
- Department of Family Medicine, Faculty of Medicine, Chiang Mai University, Chiang Mai, Thailand
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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: 13] [Impact Index Per Article: 3.3] [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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31
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Schmaranzer F, Afacan O, Lerch TD, Kim YJ, Siebenrock KA, Ith M, Cullmann JL, Kober T, Klarhoefer M, Tannast M, Bixby SD, Novais EN, Jung B. Magnetization-prepared 2 Rapid Gradient-Echo MRI for B 1 Insensitive 3D T1 Mapping of Hip Cartilage: An Experimental and Clinical Validation. Radiology 2021; 299:150-158. [PMID: 33620288 DOI: 10.1148/radiol.2021200085] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
Background Often used for T1 mapping of hip cartilage, three-dimensional (3D) dual-flip-angle (DFA) techniques are highly sensitive to flip angle variations related to B1 inhomogeneities. The authors hypothesized that 3D magnetization-prepared 2 rapid gradient-echo (MP2RAGE) MRI would help provide more accurate T1 mapping of hip cartilage at 3.0 T than would 3D DFA techniques. Purpose To compare 3D MP2RAGE MRI with 3D DFA techniques using two-dimensional (2D) inversion recovery T1 mapping as a standard of reference for hip cartilage T1 mapping in phantoms, healthy volunteers, and participants with hip pain. Materials and Methods T1 mapping at 3.0 T was performed in phantoms and in healthy volunteers using 3D MP2RAGE MRI and 3D DFA techniques with B1 field mapping for flip angle correction. Participants with hip pain prospectively (July 2019-January 2020) underwent indirect MR arthrography (with intravenous administration of 0.2 mmol/kg of gadoterate meglumine), including 3D MP2RAGE MRI. A 2D inversion recovery-based sequence served as a T1 reference in phantoms and in participants with hip pain. In healthy volunteers, cartilage T1 was compared between 3D MP2RAGE MRI and 3D DFA techniques. Paired t tests and Bland-Altman analysis were performed. Results Eleven phantoms, 10 healthy volunteers (median age, 27 years; range, 26-30 years; five men), and 20 participants with hip pain (mean age, 34 years ± 10 [standard deviation]; 17 women) were evaluated. In phantoms, T1 bias from 2D inversion recovery was lower for 3D MP2RAGE MRI than for 3D DFA techniques (mean, 3 msec ± 11 vs 253 msec ± 85; P < .001), and, unlike 3D DFA techniques, the deviation found with MP2RAGE MRI did not correlate with increasing B1 deviation. In healthy volunteers, regional cartilage T1 difference (109 msec ± 163; P = .008) was observed only for the 3D DFA technique. In participants with hip pain, the mean T1 bias of 3D MP2RAGE MRI from 2D inversion recovery was -23 msec ± 31 (P < .001). Conclusion Compared with three-dimensional (3D) dual-flip-angle techniques, 3D magnetization-prepared 2 rapid gradient-echo MRI enabled more accurate T1 mapping of hip cartilage, was less affected by B1 inhomogeneities, and showed high accuracy against a T1 reference in participants with hip pain. © RSNA, 2021.
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Affiliation(s)
- Florian Schmaranzer
- From the Department of Diagnostic, Interventional and Pediatric Radiology (F.S., T.D.L., M.I., J.L.C., B.J.) and Department of Orthopaedic Surgery (K.A.S., M.T.), Inselspital, University Hospital Bern, University of Bern, Freiburgstrasse, 3010 Bern, Switzerland; Departments of Orthopaedic Surgery (F.S., Y.J.K., E.N.N.) and Radiology (O.A., S.D.B.), Boston Children's Hospital, Harvard Medical School, Boston, Mass; Advanced Clinical Imaging Technology, Siemens Healthcare, Lausanne, Switzerland (T.K.); Department of Radiology, Lausanne University Hospital, University of Lausanne, Lausanne, Switzerland (T.K.); LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland (T.K.); Siemens Healthcare, Zürich, Switzerland (M.K.); and Department of Orthopaedic Surgery, Cantonal Hospital, University of Fribourg, Fribourg, Switzerland (M.T.)
| | - Onur Afacan
- From the Department of Diagnostic, Interventional and Pediatric Radiology (F.S., T.D.L., M.I., J.L.C., B.J.) and Department of Orthopaedic Surgery (K.A.S., M.T.), Inselspital, University Hospital Bern, University of Bern, Freiburgstrasse, 3010 Bern, Switzerland; Departments of Orthopaedic Surgery (F.S., Y.J.K., E.N.N.) and Radiology (O.A., S.D.B.), Boston Children's Hospital, Harvard Medical School, Boston, Mass; Advanced Clinical Imaging Technology, Siemens Healthcare, Lausanne, Switzerland (T.K.); Department of Radiology, Lausanne University Hospital, University of Lausanne, Lausanne, Switzerland (T.K.); LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland (T.K.); Siemens Healthcare, Zürich, Switzerland (M.K.); and Department of Orthopaedic Surgery, Cantonal Hospital, University of Fribourg, Fribourg, Switzerland (M.T.)
| | - Till D Lerch
- From the Department of Diagnostic, Interventional and Pediatric Radiology (F.S., T.D.L., M.I., J.L.C., B.J.) and Department of Orthopaedic Surgery (K.A.S., M.T.), Inselspital, University Hospital Bern, University of Bern, Freiburgstrasse, 3010 Bern, Switzerland; Departments of Orthopaedic Surgery (F.S., Y.J.K., E.N.N.) and Radiology (O.A., S.D.B.), Boston Children's Hospital, Harvard Medical School, Boston, Mass; Advanced Clinical Imaging Technology, Siemens Healthcare, Lausanne, Switzerland (T.K.); Department of Radiology, Lausanne University Hospital, University of Lausanne, Lausanne, Switzerland (T.K.); LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland (T.K.); Siemens Healthcare, Zürich, Switzerland (M.K.); and Department of Orthopaedic Surgery, Cantonal Hospital, University of Fribourg, Fribourg, Switzerland (M.T.)
| | - Young-Jo Kim
- From the Department of Diagnostic, Interventional and Pediatric Radiology (F.S., T.D.L., M.I., J.L.C., B.J.) and Department of Orthopaedic Surgery (K.A.S., M.T.), Inselspital, University Hospital Bern, University of Bern, Freiburgstrasse, 3010 Bern, Switzerland; Departments of Orthopaedic Surgery (F.S., Y.J.K., E.N.N.) and Radiology (O.A., S.D.B.), Boston Children's Hospital, Harvard Medical School, Boston, Mass; Advanced Clinical Imaging Technology, Siemens Healthcare, Lausanne, Switzerland (T.K.); Department of Radiology, Lausanne University Hospital, University of Lausanne, Lausanne, Switzerland (T.K.); LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland (T.K.); Siemens Healthcare, Zürich, Switzerland (M.K.); and Department of Orthopaedic Surgery, Cantonal Hospital, University of Fribourg, Fribourg, Switzerland (M.T.)
| | - Klaus A Siebenrock
- From the Department of Diagnostic, Interventional and Pediatric Radiology (F.S., T.D.L., M.I., J.L.C., B.J.) and Department of Orthopaedic Surgery (K.A.S., M.T.), Inselspital, University Hospital Bern, University of Bern, Freiburgstrasse, 3010 Bern, Switzerland; Departments of Orthopaedic Surgery (F.S., Y.J.K., E.N.N.) and Radiology (O.A., S.D.B.), Boston Children's Hospital, Harvard Medical School, Boston, Mass; Advanced Clinical Imaging Technology, Siemens Healthcare, Lausanne, Switzerland (T.K.); Department of Radiology, Lausanne University Hospital, University of Lausanne, Lausanne, Switzerland (T.K.); LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland (T.K.); Siemens Healthcare, Zürich, Switzerland (M.K.); and Department of Orthopaedic Surgery, Cantonal Hospital, University of Fribourg, Fribourg, Switzerland (M.T.)
| | - Michael Ith
- From the Department of Diagnostic, Interventional and Pediatric Radiology (F.S., T.D.L., M.I., J.L.C., B.J.) and Department of Orthopaedic Surgery (K.A.S., M.T.), Inselspital, University Hospital Bern, University of Bern, Freiburgstrasse, 3010 Bern, Switzerland; Departments of Orthopaedic Surgery (F.S., Y.J.K., E.N.N.) and Radiology (O.A., S.D.B.), Boston Children's Hospital, Harvard Medical School, Boston, Mass; Advanced Clinical Imaging Technology, Siemens Healthcare, Lausanne, Switzerland (T.K.); Department of Radiology, Lausanne University Hospital, University of Lausanne, Lausanne, Switzerland (T.K.); LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland (T.K.); Siemens Healthcare, Zürich, Switzerland (M.K.); and Department of Orthopaedic Surgery, Cantonal Hospital, University of Fribourg, Fribourg, Switzerland (M.T.)
| | - Jennifer L Cullmann
- From the Department of Diagnostic, Interventional and Pediatric Radiology (F.S., T.D.L., M.I., J.L.C., B.J.) and Department of Orthopaedic Surgery (K.A.S., M.T.), Inselspital, University Hospital Bern, University of Bern, Freiburgstrasse, 3010 Bern, Switzerland; Departments of Orthopaedic Surgery (F.S., Y.J.K., E.N.N.) and Radiology (O.A., S.D.B.), Boston Children's Hospital, Harvard Medical School, Boston, Mass; Advanced Clinical Imaging Technology, Siemens Healthcare, Lausanne, Switzerland (T.K.); Department of Radiology, Lausanne University Hospital, University of Lausanne, Lausanne, Switzerland (T.K.); LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland (T.K.); Siemens Healthcare, Zürich, Switzerland (M.K.); and Department of Orthopaedic Surgery, Cantonal Hospital, University of Fribourg, Fribourg, Switzerland (M.T.)
| | - Tobias Kober
- From the Department of Diagnostic, Interventional and Pediatric Radiology (F.S., T.D.L., M.I., J.L.C., B.J.) and Department of Orthopaedic Surgery (K.A.S., M.T.), Inselspital, University Hospital Bern, University of Bern, Freiburgstrasse, 3010 Bern, Switzerland; Departments of Orthopaedic Surgery (F.S., Y.J.K., E.N.N.) and Radiology (O.A., S.D.B.), Boston Children's Hospital, Harvard Medical School, Boston, Mass; Advanced Clinical Imaging Technology, Siemens Healthcare, Lausanne, Switzerland (T.K.); Department of Radiology, Lausanne University Hospital, University of Lausanne, Lausanne, Switzerland (T.K.); LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland (T.K.); Siemens Healthcare, Zürich, Switzerland (M.K.); and Department of Orthopaedic Surgery, Cantonal Hospital, University of Fribourg, Fribourg, Switzerland (M.T.)
| | - Markus Klarhoefer
- From the Department of Diagnostic, Interventional and Pediatric Radiology (F.S., T.D.L., M.I., J.L.C., B.J.) and Department of Orthopaedic Surgery (K.A.S., M.T.), Inselspital, University Hospital Bern, University of Bern, Freiburgstrasse, 3010 Bern, Switzerland; Departments of Orthopaedic Surgery (F.S., Y.J.K., E.N.N.) and Radiology (O.A., S.D.B.), Boston Children's Hospital, Harvard Medical School, Boston, Mass; Advanced Clinical Imaging Technology, Siemens Healthcare, Lausanne, Switzerland (T.K.); Department of Radiology, Lausanne University Hospital, University of Lausanne, Lausanne, Switzerland (T.K.); LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland (T.K.); Siemens Healthcare, Zürich, Switzerland (M.K.); and Department of Orthopaedic Surgery, Cantonal Hospital, University of Fribourg, Fribourg, Switzerland (M.T.)
| | - Moritz Tannast
- From the Department of Diagnostic, Interventional and Pediatric Radiology (F.S., T.D.L., M.I., J.L.C., B.J.) and Department of Orthopaedic Surgery (K.A.S., M.T.), Inselspital, University Hospital Bern, University of Bern, Freiburgstrasse, 3010 Bern, Switzerland; Departments of Orthopaedic Surgery (F.S., Y.J.K., E.N.N.) and Radiology (O.A., S.D.B.), Boston Children's Hospital, Harvard Medical School, Boston, Mass; Advanced Clinical Imaging Technology, Siemens Healthcare, Lausanne, Switzerland (T.K.); Department of Radiology, Lausanne University Hospital, University of Lausanne, Lausanne, Switzerland (T.K.); LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland (T.K.); Siemens Healthcare, Zürich, Switzerland (M.K.); and Department of Orthopaedic Surgery, Cantonal Hospital, University of Fribourg, Fribourg, Switzerland (M.T.)
| | - Sarah D Bixby
- From the Department of Diagnostic, Interventional and Pediatric Radiology (F.S., T.D.L., M.I., J.L.C., B.J.) and Department of Orthopaedic Surgery (K.A.S., M.T.), Inselspital, University Hospital Bern, University of Bern, Freiburgstrasse, 3010 Bern, Switzerland; Departments of Orthopaedic Surgery (F.S., Y.J.K., E.N.N.) and Radiology (O.A., S.D.B.), Boston Children's Hospital, Harvard Medical School, Boston, Mass; Advanced Clinical Imaging Technology, Siemens Healthcare, Lausanne, Switzerland (T.K.); Department of Radiology, Lausanne University Hospital, University of Lausanne, Lausanne, Switzerland (T.K.); LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland (T.K.); Siemens Healthcare, Zürich, Switzerland (M.K.); and Department of Orthopaedic Surgery, Cantonal Hospital, University of Fribourg, Fribourg, Switzerland (M.T.)
| | - Eduardo N Novais
- From the Department of Diagnostic, Interventional and Pediatric Radiology (F.S., T.D.L., M.I., J.L.C., B.J.) and Department of Orthopaedic Surgery (K.A.S., M.T.), Inselspital, University Hospital Bern, University of Bern, Freiburgstrasse, 3010 Bern, Switzerland; Departments of Orthopaedic Surgery (F.S., Y.J.K., E.N.N.) and Radiology (O.A., S.D.B.), Boston Children's Hospital, Harvard Medical School, Boston, Mass; Advanced Clinical Imaging Technology, Siemens Healthcare, Lausanne, Switzerland (T.K.); Department of Radiology, Lausanne University Hospital, University of Lausanne, Lausanne, Switzerland (T.K.); LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland (T.K.); Siemens Healthcare, Zürich, Switzerland (M.K.); and Department of Orthopaedic Surgery, Cantonal Hospital, University of Fribourg, Fribourg, Switzerland (M.T.)
| | - Bernd Jung
- From the Department of Diagnostic, Interventional and Pediatric Radiology (F.S., T.D.L., M.I., J.L.C., B.J.) and Department of Orthopaedic Surgery (K.A.S., M.T.), Inselspital, University Hospital Bern, University of Bern, Freiburgstrasse, 3010 Bern, Switzerland; Departments of Orthopaedic Surgery (F.S., Y.J.K., E.N.N.) and Radiology (O.A., S.D.B.), Boston Children's Hospital, Harvard Medical School, Boston, Mass; Advanced Clinical Imaging Technology, Siemens Healthcare, Lausanne, Switzerland (T.K.); Department of Radiology, Lausanne University Hospital, University of Lausanne, Lausanne, Switzerland (T.K.); LTS5, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland (T.K.); Siemens Healthcare, Zürich, Switzerland (M.K.); and Department of Orthopaedic Surgery, Cantonal Hospital, University of Fribourg, Fribourg, Switzerland (M.T.)
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La Rosa F, Abdulkadir A, Fartaria MJ, Rahmanzadeh R, Lu PJ, Galbusera R, Barakovic M, Thiran JP, Granziera C, Cuadra MB. Multiple sclerosis cortical and WM lesion segmentation at 3T MRI: a deep learning method based on FLAIR and MP2RAGE. NEUROIMAGE-CLINICAL 2020; 27:102335. [PMID: 32663798 PMCID: PMC7358270 DOI: 10.1016/j.nicl.2020.102335] [Citation(s) in RCA: 39] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/28/2020] [Revised: 06/16/2020] [Accepted: 06/26/2020] [Indexed: 01/22/2023]
Abstract
The presence of cortical lesions in multiple sclerosis patients has emerged as an important biomarker of the disease. They appear in the earliest stages of the illness and have been shown to correlate with the severity of clinical symptoms. However, cortical lesions are hardly visible in conventional magnetic resonance imaging (MRI) at 3T, and thus their automated detection has been so far little explored. In this study, we propose a fully-convolutional deep learning approach, based on the 3D U-Net, for the automated segmentation of cortical and white matter lesions at 3T. For this purpose, we consider a clinically plausible MRI setting consisting of two MRI contrasts only: one conventional T2-weighted sequence (FLAIR), and one specialized T1-weighted sequence (MP2RAGE). We include 90 patients from two different centers with a total of 728 and 3856 gray and white matter lesions, respectively. We show that two reference methods developed for white matter lesion segmentation are inadequate to detect small cortical lesions, whereas our proposed framework is able to achieve a detection rate of 76% for both cortical and white matter lesions with a false positive rate of 29% in comparison to manual segmentation. Further results suggest that our framework generalizes well for both types of lesion in subjects acquired in two hospitals with different scanners.
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Affiliation(s)
- Francesco La Rosa
- Signal Processing Laboratory (LTS5), École Polytechnique Fédérale de Lausanne, Switzerland; Medical Image Analysis Laboratory, Center for Biomedical Imaging (CIBM), University of Lausanne, Switzerland; Department of Radiology, Lausanne University Hospital and University of Lausanne, Switzerland.
| | - Ahmed Abdulkadir
- University Hospital of Old Age Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland; Center for Biomedical Image Computing and Analytics at the Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Mário João Fartaria
- Signal Processing Laboratory (LTS5), École Polytechnique Fédérale de Lausanne, Switzerland; Department of Radiology, Lausanne University Hospital and University of Lausanne, Switzerland; Advanced Clinical Imaging Technology, Siemens Healthcare AG, Lausanne, Switzerland
| | - Reza Rahmanzadeh
- Translational Imaging in Neurology Basel, Department of Medicine and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland; Neurologic Clinic and Policlinic, Departments of Medicine, University Hospital Basel and University of Basel, Basel, Switzerland
| | - Po-Jui Lu
- Translational Imaging in Neurology Basel, Department of Medicine and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland; Neurologic Clinic and Policlinic, Departments of Medicine, University Hospital Basel and University of Basel, Basel, Switzerland
| | - Riccardo Galbusera
- Translational Imaging in Neurology Basel, Department of Medicine and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland; Neurologic Clinic and Policlinic, Departments of Medicine, University Hospital Basel and University of Basel, Basel, Switzerland
| | - Muhamed Barakovic
- Translational Imaging in Neurology Basel, Department of Medicine and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland; Neurologic Clinic and Policlinic, Departments of Medicine, University Hospital Basel and University of Basel, Basel, Switzerland
| | - Jean-Philippe Thiran
- Signal Processing Laboratory (LTS5), École Polytechnique Fédérale de Lausanne, Switzerland; Department of Radiology, Lausanne University Hospital and University of Lausanne, Switzerland
| | - Cristina Granziera
- Translational Imaging in Neurology Basel, Department of Medicine and Biomedical Engineering, University Hospital Basel and University of Basel, Basel, Switzerland; Neurologic Clinic and Policlinic, Departments of Medicine, University Hospital Basel and University of Basel, Basel, Switzerland
| | - Merixtell Bach Cuadra
- Signal Processing Laboratory (LTS5), École Polytechnique Fédérale de Lausanne, Switzerland; Medical Image Analysis Laboratory, Center for Biomedical Imaging (CIBM), University of Lausanne, Switzerland; Department of Radiology, Lausanne University Hospital and University of Lausanne, Switzerland
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Demortière S, Lehmann P, Pelletier J, Audoin B, Callot V. Improved Cervical Cord Lesion Detection with 3D-MP2RAGE Sequence in Patients with Multiple Sclerosis. AJNR Am J Neuroradiol 2020; 41:1131-1134. [PMID: 32439640 DOI: 10.3174/ajnr.a6567] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2019] [Accepted: 03/23/2020] [Indexed: 12/18/2022]
Abstract
Spinal cord lesions have a real diagnostic and prognostic role in multiple sclerosis. Thus, optimizing their detection on MR imaging has become a central issue with direct therapeutic impact. In this study, we compared the 3D-MP2RAGE sequence with the conventional Magnetic Resonance Imaging in Multiple Sclerosis (MAGNIMS) set for cervical cord lesion detection in 28 patients with multiple sclerosis. 3D-MP2RAGE allowed better detection of cervical lesions (+62%) in this population, with better confidence, due to optimized contrast and high spatial resolution.
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Affiliation(s)
- S Demortière
- From the Centre d'exploration métabolique par résonance magnétique (S.D., P.L., J.P., B.A., V.C.).,Departments of Neurology (S.D., J.P., B.A.)
| | - P Lehmann
- From the Centre d'exploration métabolique par résonance magnétique (S.D., P.L., J.P., B.A., V.C.).,Neuroradiology (P.L.), Assistance Publique-Hôpitaux de Marseille, Hôpital Universitaire Timone, Marseille, France
| | - J Pelletier
- From the Centre d'exploration métabolique par résonance magnétique (S.D., P.L., J.P., B.A., V.C.).,Departments of Neurology (S.D., J.P., B.A.)
| | - B Audoin
- From the Centre d'exploration métabolique par résonance magnétique (S.D., P.L., J.P., B.A., V.C.).,Departments of Neurology (S.D., J.P., B.A.)
| | - V Callot
- From the Centre d'exploration métabolique par résonance magnétique (S.D., P.L., J.P., B.A., V.C.) .,Center for Magnetic Resonance in Biology and Medicine (V.C.), Aix-Marseille University, National Centre for Scientific Research, Marseille, France
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