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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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Aghaeifar A, Bosch D, Heule R, Williams S, Ehses P, Mauconduit F, Scheffler K. Intra-scan RF power amplifier drift correction. Magn Reson Med 2024; 92:645-659. [PMID: 38469935 DOI: 10.1002/mrm.30078] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2023] [Revised: 12/18/2023] [Accepted: 02/21/2024] [Indexed: 03/13/2024]
Abstract
PURPOSE The drift in radiofrequency (RF) power amplifiers (RFPAs) is assessed and several contributing factors are investigated. Two approaches for prospective correction of drift are proposed and their effectiveness is evaluated. METHODS RFPA drift assessment encompasses both intra-pulse and inter-pulse drift analyses. Scan protocols with varying flip angle (FA), RF length, and pulse repetition time (TR) are used to gauge the influence of these parameters on drift. Directional couplers (DICOs) monitor the forward waveforms of the RFPA outputs. DICOs data is stored for evaluation, allowing calculation of correction factors to adjust RFPAs' transmit voltage. Two correction methods, predictive and run-time, are employed: predictive correction necessitates a calibration scan, while run-time correction calculates factors during the ongoing scan. RESULTS RFPA drift is indeed influenced by the RF duty-cycle, and in the cases examined with a maximum duty-cycle of 66%, the potential drift is approximately 41% or 15%, depending on the specific RFPA revision. Notably, in low transmit voltage scenarios, FA has minimal impact on RFPA drift. The application of predictive and run-time drift correction techniques effectively reduces the average drift from 10.0% to less than 1%, resulting in enhanced MR signal stability. CONCLUSION Utilizing DICO recordings and implementing a feedback mechanism enable the prospective correction of RFPA drift. Having a calibration scan, predictive correction can be utilized with fewer complexity; for enhanced performance, a run-time approach can be employed.
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Affiliation(s)
- Ali Aghaeifar
- High-Field Magnetic Resonance Center, Max Planck Institute for Biological Cybernetics, Tuebingen, Germany
| | - Dario Bosch
- High-Field Magnetic Resonance Center, Max Planck Institute for Biological Cybernetics, Tuebingen, Germany
- Department of Biomedical Magnetic Resonance, University of Tuebingen, Tuebingen, Germany
| | - Rahel Heule
- High-Field Magnetic Resonance Center, Max Planck Institute for Biological Cybernetics, Tuebingen, Germany
- Department of Biomedical Magnetic Resonance, University of Tuebingen, Tuebingen, Germany
- Center for MR Research, University Children's Hospital, Zurich, Switzerland
| | - Sydney Williams
- Imaging Centre of Excellence, University of Glasgow, Glasgow, UK
| | - Philipp Ehses
- MR Physics, German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
| | | | - Klaus Scheffler
- High-Field Magnetic Resonance Center, Max Planck Institute for Biological Cybernetics, Tuebingen, Germany
- Department of Biomedical Magnetic Resonance, University of Tuebingen, Tuebingen, Germany
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Dupuis A, Chen Y, Hansen M, Chow K, Sun JE, Badve C, Ma D, Griswold MA, Boyacioglu R. Quantifying 3D MR fingerprinting (3D-MRF) reproducibility across subjects, sessions, and scanners automatically using MNI atlases. Magn Reson Med 2024; 91:2074-2088. [PMID: 38192239 PMCID: PMC10950529 DOI: 10.1002/mrm.29983] [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: 07/25/2023] [Revised: 12/01/2023] [Accepted: 12/04/2023] [Indexed: 01/10/2024]
Abstract
PURPOSE Quantitative MRI techniques such as MR fingerprinting (MRF) promise more objective and comparable measurements of tissue properties at the point-of-care than weighted imaging. However, few direct cross-modal comparisons of MRF's repeatability and reproducibility versus weighted acquisitions have been performed. This work proposes a novel fully automated pipeline for quantitatively comparing cross-modal imaging performance in vivo via atlas-based sampling. METHODS We acquire whole-brain 3D-MRF, turbo spin echo, and MPRAGE sequences three times each on two scanners across 10 subjects, for a total of 60 multimodal datasets. The proposed automated registration and analysis pipeline uses linear and nonlinear registration to align all qualitative and quantitative DICOM stacks to Montreal Neurological Institute (MNI) 152 space, then samples each dataset's native space through transformation inversion to compare performance within atlas regions across subjects, scanners, and repetitions. RESULTS Voxel values within MRF-derived maps were found to be more repeatable (σT1 = 1.90, σT2 = 3.20) across sessions than vendor-reconstructed MPRAGE (σT1w = 6.04) or turbo spin echo (σT2w = 5.66) images. Additionally, MRF was found to be more reproducible across scanners (σT1 = 2.21, σT2 = 3.89) than either qualitative modality (σT1w = 7.84, σT2w = 7.76). Notably, differences between repeatability and reproducibility of in vivo MRF were insignificant, unlike the weighted images. CONCLUSION MRF data from many sessions and scanners can potentially be treated as a single dataset for harmonized analysis or longitudinal comparisons without the additional regularization steps needed for qualitative modalities.
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Affiliation(s)
- Andrew Dupuis
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio, USA
| | - Yong Chen
- Department of Radiology, Case Western Reserve University, Cleveland, Ohio, USA
- Department of Radiology, University Hospitals, Cleveland, Ohio, USA
| | | | - Kelvin Chow
- Siemens Medical Solutions USA, Inc, Chicago, Illinois, USA
| | - Jessie E.P. Sun
- Department of Radiology, Case Western Reserve University, Cleveland, Ohio, USA
| | - Chaitra Badve
- Department of Radiology, University Hospitals, Cleveland, Ohio, USA
| | - Dan Ma
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio, USA
| | - Mark A. Griswold
- Department of Radiology, Case Western Reserve University, Cleveland, Ohio, USA
| | - Rasim Boyacioglu
- Department of Radiology, Case Western Reserve University, Cleveland, Ohio, USA
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Guan X, Lancione M, Ayton S, Dusek P, Langkammer C, Zhang M. Neuroimaging of Parkinson's disease by quantitative susceptibility mapping. Neuroimage 2024; 289:120547. [PMID: 38373677 DOI: 10.1016/j.neuroimage.2024.120547] [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: 07/30/2023] [Revised: 02/02/2024] [Accepted: 02/17/2024] [Indexed: 02/21/2024] Open
Abstract
Parkinson's disease (PD) is a common neurodegenerative disease, and apart from a few rare genetic causes, its pathogenesis remains largely unclear. Recent scientific interest has been captured by the involvement of iron biochemistry and the disruption of iron homeostasis, particularly within the brain regions specifically affected in PD. The advent of Quantitative Susceptibility Mapping (QSM) has enabled non-invasive quantification of brain iron in vivo by MRI, which has contributed to the understanding of iron-associated pathogenesis and has the potential for the development of iron-based biomarkers in PD. This review elucidates the biochemical underpinnings of brain iron accumulation, details advancements in iron-sensitive MRI technologies, and discusses the role of QSM as a biomarker of iron deposition in PD. Despite considerable progress, several challenges impede its clinical application after a decade of QSM studies. The initiation of multi-site research is warranted for developing robust, interpretable, and disease-specific biomarkers for monitoring PD disease progression.
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Affiliation(s)
- Xiaojun Guan
- Department of Radiology, the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China; Joint Laboratory of Clinical Radiology, the Second Affiliated Hospital, Zhejiang University School of Medicine, No.88 Jiefang Road, Shangcheng District, Hangzhou 31009, China
| | - Marta Lancione
- Laboratory of Medical Physics and Magnetic Resonance, IRCCS Stella Maris Foundation, Pisa, Italy
| | - Scott Ayton
- Florey Institute, The University of Melbourne, Australia
| | - Petr Dusek
- Department of Neurology and Center of Clinical Neuroscience, First Faculty of Medicine, Charles University and General University Hospital in Prague, Prague, Czechia; Department of Radiology, First Faculty of Medicine, Charles University and General University Hospital in Prague, Auenbruggerplatz 22, Prague 8036, Czechia
| | | | - Minming Zhang
- Department of Radiology, the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China; Joint Laboratory of Clinical Radiology, the Second Affiliated Hospital, Zhejiang University School of Medicine, No.88 Jiefang Road, Shangcheng District, Hangzhou 31009, China.
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Wu Y, Wood TC, Derks SHAE, Pruis IJ, van der Voort S, van Zanten SEMV, Smits M, Warnert EAH. Reproducibility of APT-weighted CEST-MRI at 3T in healthy brain and tumor across sessions and scanners. Sci Rep 2023; 13:18115. [PMID: 37872418 PMCID: PMC10593824 DOI: 10.1038/s41598-023-44891-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2023] [Accepted: 10/13/2023] [Indexed: 10/25/2023] Open
Abstract
Amide proton transfer (APT)-weighted chemical exchange saturation transfer (CEST) imaging is a recent MRI technique making its way into clinical application. In this work, we investigated whether APT-weighted CEST imaging can provide reproducible measurements across scan sessions and scanners. Within-session, between-session and between scanner reproducibility was calculated for 19 healthy volunteers and 7 patients with a brain tumor on two 3T MRI scanners. The APT-weighted CEST effect was evaluated by calculating the Lorentzian Difference (LD), magnetization transfer ratio asymmetry (MTRasym), and relaxation-compensated inverse magnetization transfer ratio (MTRREX) averaged in whole brain white matter (WM), enhancing tumor and necrosis. Within subject coefficient of variation (COV) calculations, Bland-Altman plots and mixed effect modeling were performed to assess the repeatability and reproducibility of averaged values. The group median COVs of LD APT were 0.56% (N = 19), 0.84% (N = 6), 0.80% (N = 9) in WM within-session, between-session and between-scanner respectively. The between-session COV of LD APT in enhancing tumor (N = 6) and necrotic core (N = 3) were 4.57% and 5.67%, respectively. There were no significant differences in within session, between session and between scanner comparisons of the APT effect. The COVs of LD and MTRREX were consistently lower than MTRasym in all experiments, both in healthy tissues and tumor. The repeatability and reproducibility of APT-weighted CEST was clinically acceptable across scan sessions and scanners. Although MTRasym is simple to acquire and compute and sufficient to provide robust measurement, it is beneficial to include LD and MTRREX to obtain higher reproducibility for detecting minor signal difference in different tissue types.
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Affiliation(s)
- Yulun Wu
- Department of Radiology & Nuclear Medicine, Erasmus MC, Rotterdam, The Netherlands
- Brain Tumour Centre, Erasmus MC Cancer Institute, Rotterdam, The Netherlands
| | - Tobias C Wood
- Department of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Sophie H A E Derks
- Department of Radiology & Nuclear Medicine, Erasmus MC, Rotterdam, The Netherlands
- Department of Medical Oncology, Erasmus MC-University Medical Centre Rotterdam, Rotterdam, The Netherlands
| | - Ilanah J Pruis
- Department of Radiology & Nuclear Medicine, Erasmus MC, Rotterdam, The Netherlands
| | - Sebastian van der Voort
- Department of Radiology & Nuclear Medicine, Erasmus MC, Rotterdam, The Netherlands
- Medical Delta, Delft, The Netherlands
| | - Sophie E M Veldhuijzen van Zanten
- Department of Radiology & Nuclear Medicine, Erasmus MC, Rotterdam, The Netherlands
- Brain Tumour Centre, Erasmus MC Cancer Institute, Rotterdam, The Netherlands
| | - Marion Smits
- Department of Radiology & Nuclear Medicine, Erasmus MC, Rotterdam, The Netherlands
- Brain Tumour Centre, Erasmus MC Cancer Institute, Rotterdam, The Netherlands
- Medical Delta, Delft, The Netherlands
| | - Esther A H Warnert
- Department of Radiology & Nuclear Medicine, Erasmus MC, Rotterdam, The Netherlands.
- Brain Tumour Centre, Erasmus MC Cancer Institute, Rotterdam, The Netherlands.
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Bordin V, Pirastru A, Bergsland N, Cazzoli M, Baselli G, Baglio F. Optimal echo times for quantitative susceptibility mapping: A test-retest study on basal ganglia and subcortical brain nuclei. Neuroimage 2023; 278:120272. [PMID: 37437701 DOI: 10.1016/j.neuroimage.2023.120272] [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: 04/13/2023] [Revised: 06/16/2023] [Accepted: 07/09/2023] [Indexed: 07/14/2023] Open
Abstract
Quantitative Susceptibility Mapping (QSM) is a recent MRI-technique able to quantify the bulk magnetic susceptibility of myelin, iron, and calcium in the brain. Its variability across different acquisition parameters has prompted the need for standardisation across multiple centres and MRI vendors. However, a high level of agreement between repeated imaging acquisitions is equally important. With this study we aimed to assess the inter-scan repeatability of an optimised multi-echo GRE sequence in 28 healthy volunteers. We extracted and compared the susceptibility measures from the scan and rescan acquisitions across 7 bilateral brain regions (i.e., 14 regions of interest (ROIs)) relevant for neurodegeneration. Repeatability was first assessed while reconstructing QSM with a fixed number of echo times (i.e., 8). Excellent inter-scan repeatability was found for putamen, globus pallidus and caudate nucleus, while good performance characterised the remaining structures. An increased variability was instead noted for small ROIs like red nucleus and substantia nigra. Secondly, we assessed the impact exerted on repeatability by the number of echoes used to derive QSM maps. Results were impacted by this parameter, especially in smaller regions. Larger brain structures, on the other hand, showed more consistent performance. Nevertheless, with either 8 or 7 echoes we managed to obtain good inter-scan repeatability on almost all ROIs. These findings indicate that the designed acquisition/reconstruction protocol has wide applicability, particularly in clinical or research settings involving longitudinal acquisitions (e.g. rehabilitation studies).
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Affiliation(s)
- Valentina Bordin
- Department of Electronics, Information and Bioengineering, Politecnico di Milano, Milan, Italy.
| | - Alice Pirastru
- Department of Electronics, Information and Bioengineering, Politecnico di Milano, Milan, Italy; IRCCS Fondazione Don Carlo Gnocchi ONLUS, Milan, Italy
| | - Niels Bergsland
- IRCCS Fondazione Don Carlo Gnocchi ONLUS, Milan, Italy; Department of Neurology, Buffalo Neuroimaging Analysis Center, School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, NY, United States
| | - Marta Cazzoli
- IRCCS Fondazione Don Carlo Gnocchi ONLUS, Milan, Italy
| | - Giuseppe Baselli
- Department of Electronics, Information and Bioengineering, Politecnico di Milano, Milan, Italy
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Mennecke A, Khakzar KM, German A, Herz K, Fabian MS, Liebert A, Blümcke I, Kasper BS, Nagel AM, Laun FB, Schmidt M, Winkler J, Dörfler A, Zaiss M. 7 tricks for 7 T CEST: Improving the reproducibility of multipool evaluation provides insights into the effects of age and the early stages of Parkinson's disease. NMR IN BIOMEDICINE 2023; 36:e4717. [PMID: 35194865 DOI: 10.1002/nbm.4717] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/26/2021] [Revised: 02/10/2022] [Accepted: 02/21/2022] [Indexed: 05/23/2023]
Abstract
The objective of the current study was to optimize the postprocessing pipeline of 7 T chemical exchange saturation transfer (CEST) imaging for reproducibility and to prove this optimization for the detection of age differences and differences between patients with Parkinson's disease versus normal subjects. The following 7 T CEST MRI experiments were analyzed: repeated measurements of a healthy subject, subjects of two age cohorts (14 older, seven younger subjects), and measurements of 12 patients with Parkinson's disease. A slab-selective, B 1 + -homogeneous parallel transmit protocol was used. The postprocessing, consisting of motion correction, smoothing, B 0 -correction, normalization, denoising, B 1 + -correction and Lorentzian fitting, was optimized regarding the intrasubject and intersubject coefficient of variation (CoV) of the amplitudes of the amide pool and the aliphatic relayed nuclear Overhauser effect (rNOE) pool within the brain. Seven "tricks" for postprocessing accomplished an improvement of the mean voxel CoV of the amide pool and the aliphatic rNOE pool amplitudes of less than 5% and 3%, respectively. These postprocessing steps are: motion correction with interpolation of the motion of low-signal offsets (1) using the amide pool frequency offset image as reference (2), normalization of the Z-spectrum using the outermost saturated measurements (3), B 0 correction of the Z-spectrum with moderate spline smoothing (4), denoising using principal component analysis preserving the 11 highest intensity components (5), B 1 + correction using a linear fit (6) and Lorentzian fitting using the five-pool fit model (7). With the optimized postprocessing pipeline, a significant age effect in the amide pool can be detected. Additionally, for the first time, an aliphatic rNOE contrast between subjects with Parkinson's disease and age-matched healthy controls in the substantia nigra is detected. We propose an optimized postprocessing pipeline for CEST multipool evaluation. It is shown that by the use of these seven "tricks", the reproducibility and, thus, the statistical power of a CEST measurement, can be greatly improved and subtle changes can be detected.
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Affiliation(s)
- Angelika Mennecke
- Institute of Neuroradiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
| | - Katrin M Khakzar
- Institute of Neuroradiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
| | - Alexander German
- Institute of Neuroradiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
| | - Kai Herz
- Max Planck Institute for Biological Cybernetics, Tübingen, Germany
- Department of Biomedical Magnetic Resonance, University of Tuebingen, Tuebingen, Germany
| | - Moritz S Fabian
- Institute of Neuroradiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
| | - Andrzej Liebert
- Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
| | - Ingmar Blümcke
- Institute of Neuropathology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
| | - Burkhard S Kasper
- Department of Neurology, Epilepsy Centre, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
| | - Armin M Nagel
- Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
| | - Frederik B Laun
- Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
| | - Manuel Schmidt
- Institute of Neuroradiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
| | - Jürgen Winkler
- Department of Neurology, Epilepsy Centre, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
| | - Arnd Dörfler
- Institute of Neuroradiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
| | - Moritz Zaiss
- Institute of Neuroradiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
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Benyard B, Nanga RPR, Wilson NE, Thakuri D, Jacobs PS, Swain A, Kumar D, Reddy R. In vivo reproducibility of 3D relayed NOE in the healthy human brain at 7 T. Magn Reson Med 2023; 89:2295-2304. [PMID: 36744726 PMCID: PMC10078808 DOI: 10.1002/mrm.29600] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2022] [Revised: 01/09/2023] [Accepted: 01/11/2023] [Indexed: 02/07/2023]
Abstract
PURPOSE Nuclear Overhauser effect (NOE) is based on dipolar cross-relaxation mechanism that enables the indirect detection of aliphatic protons via the water proton signal. This work focuses on determining the reproducibility of NOE magnetization transfer ratio (NOEMTR ) and isolated or relayed NOE (rNOE) contributions to the NOE MRI of the healthy human brain at 7 Tesla (T). METHODS We optimized theB 1 + $$ {\mathrm{B}}_1^{+} $$ amplitude and length of the saturation pulse by acquiring NOE images with differentB 1 + $$ {\mathrm{B}}_1^{+} $$ values with multiple saturation lengths. Repeated NOE MRI measurements were made on five healthy volunteers by using optimized saturation pulse parameters including correction of B0 andB 1 + $$ {\mathrm{B}}_1^{+} $$ inhomogeneities. To isolate the individual contributions from z-spectra, we have fit the NOE z-spectra using multiple Lorentzians and calculated the total contribution from each pool contributing to the overall NOEMTR contrast. RESULTS We found that a saturation amplitude of 0.72 μT and a length of 3 s provided the highest contrast. We found that the mean NOEMTR value in gray matter (GM) was 26%, and in white matter (WM) was 33.3% across the 3D slab of the brain. The mean rNOE contributions from GM and WM values were 8.9% and 9.6%, which were ∼10% of the corresponding total NOEMTR signal. The intersubject coefficient of variations (CoVs) of NOEMTR from GM and WM were 4.5% and 6.5%, respectively, whereas the CoVs of rNOE were 4.8% and 5.6%, respectively. The intrasubject CoVs of the NOEMTR range was 2.1%-4.2%, and rNOE range was 2.9%-10.5%. CONCLUSION This work has demonstrated an excellent reproducibility of both inter- and intrasubject NOEMTR and rNOE metrics in healthy human brains at 7 T.
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Affiliation(s)
- Blake Benyard
- Center for Metabolic Imaging in Precision Medicine (CAMIPM), Department of Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Ravi Prakash Reddy Nanga
- Center for Metabolic Imaging in Precision Medicine (CAMIPM), Department of Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Neil E. Wilson
- Center for Metabolic Imaging in Precision Medicine (CAMIPM), Department of Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Deepa Thakuri
- Center for Metabolic Imaging in Precision Medicine (CAMIPM), Department of Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Paul S. Jacobs
- Center for Metabolic Imaging in Precision Medicine (CAMIPM), Department of Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Anshuman Swain
- Center for Metabolic Imaging in Precision Medicine (CAMIPM), Department of Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Dushyant Kumar
- Center for Metabolic Imaging in Precision Medicine (CAMIPM), Department of Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Ravinder Reddy
- Center for Metabolic Imaging in Precision Medicine (CAMIPM), Department of Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, USA
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Yin G, Li T, Jin S, Wang N, Li J, Wu C, He H, Wang J. A comprehensive evaluation of multicentric reliability of single-subject cortical morphological networks on traveling subjects. Cereb Cortex 2023:7169131. [PMID: 37197789 DOI: 10.1093/cercor/bhad178] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2023] [Revised: 04/29/2023] [Accepted: 04/30/2023] [Indexed: 05/19/2023] Open
Abstract
Despite the prevalence of research on single-subject cerebral morphological networks in recent years, whether they can offer a reliable way for multicentric studies remains largely unknown. Using two multicentric datasets of traveling subjects, this work systematically examined the inter-site test-retest (TRT) reliabilities of single-subject cerebral morphological networks, and further evaluated the effects of several key factors. We found that most graph-based network measures exhibited fair to excellent reliabilities regardless of different analytical pipelines. Nevertheless, the reliabilities were affected by choices of morphological index (fractal dimension > sulcal depth > gyrification index > cortical thickness), brain parcellation (high-resolution > low-resolution), thresholding method (proportional > absolute), and network type (binarized > weighted). For the factor of similarity measure, its effects depended on the thresholding method used (absolute: Kullback-Leibler divergence > Jensen-Shannon divergence; proportional: Jensen-Shannon divergence > Kullback-Leibler divergence). Furthermore, longer data acquisition intervals and different scanner software versions significantly reduced the reliabilities. Finally, we showed that inter-site reliabilities were significantly lower than intra-site reliabilities for single-subject cerebral morphological networks. Altogether, our findings propose single-subject cerebral morphological networks as a promising approach for multicentric human connectome studies, and offer recommendations on how to determine analytical pipelines and scanning protocols for obtaining reliable results.
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Affiliation(s)
- Guole Yin
- Institute for Brain Research and Rehabilitation, South China Normal University, Guangzhou 510631, China
| | - Ting Li
- Institute of Brain and Psychological Sciences, Sichuan Normal University, Chengdu 610066, China
| | - Suhui Jin
- Institute for Brain Research and Rehabilitation, South China Normal University, Guangzhou 510631, China
| | - Ningkai Wang
- Institute for Brain Research and Rehabilitation, South China Normal University, Guangzhou 510631, China
| | - Junle Li
- Institute for Brain Research and Rehabilitation, South China Normal University, Guangzhou 510631, China
| | - Changwen Wu
- Institute for Brain Research and Rehabilitation, South China Normal University, Guangzhou 510631, China
| | - Hongjian He
- Center for Brain Imaging Science and Technology, College of Biomedical Engineering and Instrumental Science, Zhejiang University, Hangzhou 310058, China
| | - Jinhui Wang
- Institute for Brain Research and Rehabilitation, South China Normal University, Guangzhou 510631, China
- Key Laboratory of Cognition and Education Sciences, Ministry of Education, Beijing 100816, China
- Center for Studies of Psychological Application, South China Normal University, Guangzhou 510000, China
- Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, Guangzhou 510000, China
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10
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Schreiber LM, Lohr D, Baltes S, Vogel U, Elabyad IA, Bille M, Reiter T, Kosmala A, Gassenmaier T, Stefanescu MR, Kollmann A, Aures J, Schnitter F, Pali M, Ueda Y, Williams T, Christa M, Hofmann U, Bauer W, Gerull B, Zernecke A, Ergün S, Terekhov M. Ultra-high field cardiac MRI in large animals and humans for translational cardiovascular research. Front Cardiovasc Med 2023; 10:1068390. [PMID: 37255709 PMCID: PMC10225557 DOI: 10.3389/fcvm.2023.1068390] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2022] [Accepted: 04/04/2023] [Indexed: 06/01/2023] Open
Abstract
A key step in translational cardiovascular research is the use of large animal models to better understand normal and abnormal physiology, to test drugs or interventions, or to perform studies which would be considered unethical in human subjects. Ultrahigh field magnetic resonance imaging (UHF-MRI) at 7 T field strength is becoming increasingly available for imaging of the heart and, when compared to clinically established field strengths, promises better image quality and image information content, more precise functional analysis, potentially new image contrasts, and as all in-vivo imaging techniques, a reduction of the number of animals per study because of the possibility to scan every animal repeatedly. We present here a solution to the dual use problem of whole-body UHF-MRI systems, which are typically installed in clinical environments, to both UHF-MRI in large animals and humans. Moreover, we provide evidence that in such a research infrastructure UHF-MRI, and ideally combined with a standard small-bore UHF-MRI system, can contribute to a variety of spatial scales in translational cardiovascular research: from cardiac organoids, Zebra fish and rodent hearts to large animal models such as pigs and humans. We present pilot data from serial CINE, late gadolinium enhancement, and susceptibility weighted UHF-MRI in a myocardial infarction model over eight weeks. In 14 pigs which were delivered from a breeding facility in a national SARS-CoV-2 hotspot, we found no infection in the incoming pigs. Human scanning using CINE and phase contrast flow measurements provided good image quality of the left and right ventricle. Agreement of functional analysis between CINE and phase contrast MRI was excellent. MRI in arrested hearts or excised vascular tissue for MRI-based histologic imaging, structural imaging of myofiber and vascular smooth muscle cell architecture using high-resolution diffusion tensor imaging, and UHF-MRI for monitoring free radicals as a surrogate for MRI of reactive oxygen species in studies of oxidative stress are demonstrated. We conclude that UHF-MRI has the potential to become an important precision imaging modality in translational cardiovascular research.
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Affiliation(s)
- Laura M. Schreiber
- Department of Cardiovascular Imaging and Chair of Molecular and Cellular Imaging, Comprehensive Heart Failure Center Wuerzburg (CHFC), University Hospital Wuerzburg, Wuerzburg, Germany
| | - David Lohr
- Department of Cardiovascular Imaging and Chair of Molecular and Cellular Imaging, Comprehensive Heart Failure Center Wuerzburg (CHFC), University Hospital Wuerzburg, Wuerzburg, Germany
| | - Steffen Baltes
- Department of Cardiovascular Imaging and Chair of Molecular and Cellular Imaging, Comprehensive Heart Failure Center Wuerzburg (CHFC), University Hospital Wuerzburg, Wuerzburg, Germany
| | - Ulrich Vogel
- Institute for Hygiene and Microbiology, University of Wuerzburg, Wuerzburg, Germany
| | - Ibrahim A. Elabyad
- Department of Cardiovascular Imaging and Chair of Molecular and Cellular Imaging, Comprehensive Heart Failure Center Wuerzburg (CHFC), University Hospital Wuerzburg, Wuerzburg, Germany
| | - Maya Bille
- Department of Cardiovascular Imaging and Chair of Molecular and Cellular Imaging, Comprehensive Heart Failure Center Wuerzburg (CHFC), University Hospital Wuerzburg, Wuerzburg, Germany
| | - Theresa Reiter
- Department of Cardiovascular Imaging and Chair of Molecular and Cellular Imaging, Comprehensive Heart Failure Center Wuerzburg (CHFC), University Hospital Wuerzburg, Wuerzburg, Germany
- Department of Internal Medicine I/Cardiology, University Hospital Wuerzburg, Wuerzburg, Germany
| | - Aleksander Kosmala
- Department of Cardiovascular Imaging and Chair of Molecular and Cellular Imaging, Comprehensive Heart Failure Center Wuerzburg (CHFC), University Hospital Wuerzburg, Wuerzburg, Germany
- Department of Radiology, University Hospital Wuerzburg, Wuerzburg, Germany
| | - Tobias Gassenmaier
- Department of Cardiovascular Imaging and Chair of Molecular and Cellular Imaging, Comprehensive Heart Failure Center Wuerzburg (CHFC), University Hospital Wuerzburg, Wuerzburg, Germany
- Department of Radiology, University Hospital Wuerzburg, Wuerzburg, Germany
| | - Maria R. Stefanescu
- Department of Cardiovascular Imaging and Chair of Molecular and Cellular Imaging, Comprehensive Heart Failure Center Wuerzburg (CHFC), University Hospital Wuerzburg, Wuerzburg, Germany
| | - Alena Kollmann
- Department of Cardiovascular Imaging and Chair of Molecular and Cellular Imaging, Comprehensive Heart Failure Center Wuerzburg (CHFC), University Hospital Wuerzburg, Wuerzburg, Germany
| | - Julia Aures
- Department of Cardiovascular Imaging and Chair of Molecular and Cellular Imaging, Comprehensive Heart Failure Center Wuerzburg (CHFC), University Hospital Wuerzburg, Wuerzburg, Germany
| | - Florian Schnitter
- Department of Internal Medicine I/Cardiology, University Hospital Wuerzburg, Wuerzburg, Germany
| | - Mihaela Pali
- Department of Cardiovascular Imaging and Chair of Molecular and Cellular Imaging, Comprehensive Heart Failure Center Wuerzburg (CHFC), University Hospital Wuerzburg, Wuerzburg, Germany
| | - Yuichiro Ueda
- Institute of Anatomy and Cell Biology, Julius-Maximilians-University, Wuerzburg, Germany
| | - Tatiana Williams
- Department of Cardiovascular Genetics, Comprehensive Heart Failure Center Wuerzburg, University Hospital Wuerzburg, Wuerzburg, Germany
| | - Martin Christa
- Department of Internal Medicine I/Cardiology, University Hospital Wuerzburg, Wuerzburg, Germany
| | - Ulrich Hofmann
- Department of Internal Medicine I/Cardiology, University Hospital Wuerzburg, Wuerzburg, Germany
| | - Wolfgang Bauer
- Department of Internal Medicine I/Cardiology, University Hospital Wuerzburg, Wuerzburg, Germany
| | - Brenda Gerull
- Department of Internal Medicine I/Cardiology, University Hospital Wuerzburg, Wuerzburg, Germany
- Department of Cardiovascular Genetics, Comprehensive Heart Failure Center Wuerzburg, University Hospital Wuerzburg, Wuerzburg, Germany
| | - Alma Zernecke
- Institute of Experimental Biomedicine, University Hospital Wuerzburg, Wuerzburg, Germany
| | - Süleyman Ergün
- Institute of Anatomy and Cell Biology, Julius-Maximilians-University, Wuerzburg, Germany
| | - Maxim Terekhov
- Department of Cardiovascular Imaging and Chair of Molecular and Cellular Imaging, Comprehensive Heart Failure Center Wuerzburg (CHFC), University Hospital Wuerzburg, Wuerzburg, Germany
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11
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Ladd ME, Quick HH, Speck O, Bock M, Doerfler A, Forsting M, Hennig J, Ittermann B, Möller HE, Nagel AM, Niendorf T, Remy S, Schaeffter T, Scheffler K, Schlemmer HP, Schmitter S, Schreiber L, Shah NJ, Stöcker T, Uder M, Villringer A, Weiskopf N, Zaiss M, Zaitsev M. Germany's journey toward 14 Tesla human magnetic resonance. MAGMA (NEW YORK, N.Y.) 2023; 36:191-210. [PMID: 37029886 PMCID: PMC10140098 DOI: 10.1007/s10334-023-01085-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Received: 11/02/2022] [Revised: 03/23/2023] [Accepted: 03/27/2023] [Indexed: 04/09/2023]
Abstract
Multiple sites within Germany operate human MRI systems with magnetic fields either at 7 Tesla or 9.4 Tesla. In 2013, these sites formed a network to facilitate and harmonize the research being conducted at the different sites and make this technology available to a larger community of researchers and clinicians not only within Germany, but also worldwide. The German Ultrahigh Field Imaging (GUFI) network has defined a strategic goal to establish a 14 Tesla whole-body human MRI system as a national research resource in Germany as the next progression in magnetic field strength. This paper summarizes the history of this initiative, the current status, the motivation for pursuing MR imaging and spectroscopy at such a high magnetic field strength, and the technical and funding challenges involved. It focuses on the scientific and science policy process from the perspective in Germany, and is not intended to be a comprehensive systematic review of the benefits and technical challenges of higher field strengths.
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Affiliation(s)
- Mark E Ladd
- Medical Physics in Radiology, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 280, 69120, Heidelberg, Germany.
- Faculty of Medicine, Heidelberg University, Heidelberg, Germany.
- Faculty of Physics and Astronomy, Heidelberg University, Heidelberg, Germany.
- Erwin L. Hahn Institute for MRI, University of Duisburg-Essen, Essen, Germany.
| | - Harald H Quick
- Erwin L. Hahn Institute for MRI, University of Duisburg-Essen, Essen, Germany
- High-Field and Hybrid MR Imaging, University Hospital Essen, Essen, Germany
| | - Oliver Speck
- Department of Biomedical Magnetic Resonance, Otto von Guericke University Magdeburg, Magdeburg, Germany
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany
- Center for Behavioural Brain Sciences, Magdeburg, Germany
- Leibniz Institute for Neurobiology (LIN), Magdeburg, Germany
| | - Michael Bock
- Division of Medical Physics, Department of Diagnostic and Interventional Radiology, Faculty of Medicine, Medical Center, University of Freiburg, Freiburg, Germany
| | - Arnd Doerfler
- Department of Neuroradiology, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nuremberg (FAU), Erlangen, Germany
| | - Michael Forsting
- Institute of Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen, Essen, Germany
| | - Jürgen Hennig
- Division of Medical Physics, Department of Diagnostic and Interventional Radiology, Faculty of Medicine, Medical Center, University of Freiburg, Freiburg, Germany
| | - Bernd Ittermann
- Medical Physics and Metrological Information Technology, Physikalisch-Technische Bundesanstalt (PTB), Berlin, Germany
| | - Harald E Möller
- Methods and Development Group Nuclear Magnetic Resonance, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Armin M Nagel
- Medical Physics in Radiology, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 280, 69120, Heidelberg, Germany
- Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nuremberg (FAU), Erlangen, Germany
| | - Thoralf Niendorf
- Berlin Ultrahigh Field Facility (B.U.F.F.), Max Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany
| | - Stefan Remy
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany
- Leibniz Institute for Neurobiology (LIN), Magdeburg, Germany
| | - Tobias Schaeffter
- Medical Physics and Metrological Information Technology, Physikalisch-Technische Bundesanstalt (PTB), Berlin, Germany
| | - Klaus Scheffler
- Magnetic Resonance Center, Max Planck Institute for Biological Cybernetics, Tübingen, Germany
- Department of Biomedical Magnetic Resonance, University of Tübingen, Tübingen, Germany
| | | | - Sebastian Schmitter
- Medical Physics and Metrological Information Technology, Physikalisch-Technische Bundesanstalt (PTB), Berlin, Germany
| | - Laura Schreiber
- Department of Cardiovascular Imaging, Comprehensive Heart Failure Center, University Hospital Würzburg, Würzburg, Germany
| | - N Jon Shah
- Institute of Neuroscience and Medicine - 4, Forschungszentrum Jülich, Jülich, Germany
| | - Tony Stöcker
- MR Physics, German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
| | - Michael Uder
- Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nuremberg (FAU), Erlangen, Germany
| | - Arno Villringer
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Nikolaus Weiskopf
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Felix Bloch Institute for Solid State Physics, Faculty of Physics and Earth Sciences, Leipzig University, Leipzig, Germany
| | - Moritz Zaiss
- Department of Neuroradiology, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nuremberg (FAU), Erlangen, Germany
| | - Maxim Zaitsev
- Division of Medical Physics, Department of Diagnostic and Interventional Radiology, Faculty of Medicine, Medical Center, University of Freiburg, Freiburg, Germany
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12
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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: 3.0] [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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13
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Straub S, El-Sanosy E, Emmerich J, Sandig FL, Ladd ME, Schlemmer HP. Quantitative magnetic resonance imaging biomarkers for cortical pathology in multiple sclerosis at 7 T. NMR IN BIOMEDICINE 2023; 36:e4847. [PMID: 36259249 DOI: 10.1002/nbm.4847] [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: 04/12/2022] [Revised: 10/08/2022] [Accepted: 10/12/2022] [Indexed: 06/16/2023]
Abstract
Substantial cortical gray matter tissue damage, which correlates with clinical disease severity, has been revealed in multiple sclerosis (MS) using advanced magnetic resonance imaging (MRI) methods at 3 T and the use of ultra-high field, as well as in histopathology studies. While clinical assessment mainly focuses on lesions using T 1 - and T 2 -weighted MRI, quantitative MRI (qMRI) methods are capable of uncovering subtle microstructural changes. The aim of this ultra-high field study is to extract possible future MR biomarkers for the quantitative evaluation of regional cortical pathology. Because of their sensitivity to iron, myelin, and in part specifically to cortical demyelination, T 1 , T 2 , R 2 * , and susceptibility mapping were performed including two novel susceptibility markers; in addition, cortical thickness as well as the volumes of 34 cortical regions were computed. Data were acquired in 20 patients and 16 age- and sex-matched healthy controls. In 18 cortical regions, large to very large effect sizes (Cohen's d ≥ 1) and statistically significant differences in qMRI values between patients and controls were revealed compared with only four regions when using more standard MR measures, namely, volume and cortical thickness. Moreover, a decrease in all susceptibility contrasts ( χ , χ + , χ - ) and R 2 * values indicates that the role of cortical demyelination might outweigh inflammatory processes in the form of iron accumulation in cortical MS pathology, and might also indicate iron loss. A significant association between susceptibility contrasts as well as R 2 * of the caudal middle frontal gyrus and disease duration was found (adjusted R2 : 0.602, p = 0.0011). Quantitative MRI parameters might be more sensitive towards regional cortical pathology compared with the use of conventional markers only and therefore may play a role in early detection of tissue damage in MS in the future.
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Affiliation(s)
- Sina Straub
- Division of Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
- Faculty of Medicine, Heidelberg University, Heidelberg, Germany
| | - Edris El-Sanosy
- Division Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Julian Emmerich
- Division of Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Frederik L Sandig
- Division Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Mark E Ladd
- Division of Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
- Faculty of Medicine, Heidelberg University, Heidelberg, Germany
- Faculty of Physics and Astronomy, Heidelberg University, Heidelberg, Germany
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14
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Marxreiter F, Lambrecht V, Mennecke A, Hanspach J, Jukic J, Regensburger M, Herrler J, German A, Kassubek J, Grön G, Müller HP, Laun FB, Dörfler A, Winkler J, Schmidt MA. Parkinson's disease or multiple system atrophy: potential separation by quantitative susceptibility mapping. Ther Adv Neurol Disord 2023; 16:17562864221143834. [PMID: 36846471 PMCID: PMC9950607 DOI: 10.1177/17562864221143834] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2022] [Accepted: 11/08/2022] [Indexed: 02/24/2023] Open
Abstract
Background Due to the absence of robust biomarkers, and the low sensitivity and specificity of routine imaging techniques, the differential diagnosis between Parkinson's disease (PD) and multiple system atrophy (MSA) is challenging. High-field magnetic resonance imaging (MRI) opened up new possibilities regarding the analysis of pathological alterations associated with neurodegenerative processes. Recently, we have shown that quantitative susceptibility mapping (QSM) enables visualization and quantification of two major histopathologic hallmarks observed in MSA: reduced myelin density and iron accumulation in the basal ganglia of a transgenic murine model of MSA. It is therefore emerging as a promising imaging modality on the differential diagnosis of Parkinsonian syndromes. Objectives To assess QSM on high-field MRI for the differential diagnosis of PD and MSA. Methods We assessed 23 patients (nine PDs and 14 MSAs) and nine controls using QSM on 3T and 7T MRI scanners at two academic centers. Results We observed increased susceptibility in MSA at 3T in prototypical subcortical and brainstem regions. Susceptibility measures of putamen, pallidum, and substantia nigra reached excellent diagnostic accuracy to separate both synucleinopathies. Increase toward 100% sensitivity and specificity was achieved using 7T MRI in a subset of patients. Magnetic susceptibility correlated with age in all groups, but not with disease duration in MSA. Sensitivity and specificity were particularly high for possible MSA, and reached 100% in the putamen. Conclusion Putaminal susceptibility measures, in particular on ultra-high-field MRI, may distinguish MSA patients from both, PD and controls, allowing an early and sensitive diagnosis of MSA.
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Affiliation(s)
| | | | - Angelika Mennecke
- Institute of Neuroradiology, University
Hospital Erlangen, Erlangen, Germany
| | - Jannis Hanspach
- Institute of Radiology, University Hospital
Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen,
Germany
| | - Jelena Jukic
- Department of Molecular Neurology, University
Hospital Erlangen, Erlangen, Germany
| | - Martin Regensburger
- Department of Molecular Neurology, University
Hospital Erlangen, Erlangen, Germany,Center for Rare Diseases, University Hospital
Erlangen, Erlangen, Germany
| | - Juergen Herrler
- Institute of Neuroradiology, University
Hospital Erlangen, Erlangen, Germany,Institute of Radiology, University Hospital
Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen,
Germany
| | - Alexander German
- Institute of Neuroradiology, University
Hospital Erlangen, Erlangen, Germany,Institute of Radiology, University Hospital
Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen,
Germany
| | - Jan Kassubek
- Department of Neurology, Ulm University, Ulm,
Germany
| | - Georg Grön
- Department of Psychiatry and Psychotherapy
III, Ulm University, Ulm, Germany
| | | | - Frederik B. Laun
- Institute of Radiology, University Hospital
Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen,
Germany
| | - Arnd Dörfler
- Institute of Neuroradiology, University
Hospital Erlangen, Erlangen, Germany
| | - Juergen Winkler
- Department of Molecular Neurology, University
Hospital Erlangen, Erlangen, Germany,Center for Rare Diseases, University Hospital
Erlangen, Erlangen, Germany
| | - Manuel A. Schmidt
- Institute of Neuroradiology, University
Hospital Erlangen, Erlangen, Germany
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15
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Jabehdar Maralani P, Chan RW, Lam WW, Oakden W, Oglesby R, Lau A, Mehrabian H, Heyn C, Chan AK, Soliman H, Sahgal A, Stanisz GJ. Chemical Exchange Saturation Transfer MRI: What Neuro-Oncology Clinicians Need To Know. Technol Cancer Res Treat 2023; 22:15330338231208613. [PMID: 37872686 PMCID: PMC10594966 DOI: 10.1177/15330338231208613] [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: 07/11/2023] [Revised: 09/19/2023] [Accepted: 09/28/2023] [Indexed: 10/25/2023] Open
Abstract
Chemical exchange saturation transfer (CEST) is a relatively novel magnetic resonance imaging (MRI) technique with an image contrast designed for in vivo measurement of certain endogenous molecules with protons that are exchangeable with water protons, such as amide proton transfer commonly used for neuro-oncology applications. Recent technological advances have made it feasible to implement CEST on clinical grade scanners within practical acquisition times, creating new opportunities to integrate CEST in clinical workflow. In addition, the majority of CEST applications used in neuro-oncology are performed without the use gadolinium-based contrast agents which are another appealing feature of this technique. This review is written for clinicians involved in neuro-oncologic care (nonphysicists) as the target audience explaining what they need to know as CEST makes its way into practice. The purpose of this article is to (1) review the basic physics and technical principles of CEST MRI, and (2) review the practical applications of CEST in neuro-oncology.
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Affiliation(s)
- Pejman Jabehdar Maralani
- Department of Medical Imaging, University of Toronto, Toronto, ON, Canada
- Physical Sciences, Sunnybrook Research Institute, Toronto, ON, Canada
| | - Rachel W. Chan
- Physical Sciences, Sunnybrook Research Institute, Toronto, ON, Canada
| | - Wilfred W. Lam
- Physical Sciences, Sunnybrook Research Institute, Toronto, ON, Canada
| | - Wendy Oakden
- Physical Sciences, Sunnybrook Research Institute, Toronto, ON, Canada
| | - Ryan Oglesby
- Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada
| | - Angus Lau
- Physical Sciences, Sunnybrook Research Institute, Toronto, ON, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada
| | - Hatef Mehrabian
- Physical Sciences, Sunnybrook Research Institute, Toronto, ON, Canada
| | - Chris Heyn
- Department of Medical Imaging, University of Toronto, Toronto, ON, Canada
| | - Aimee K.M. Chan
- Physical Sciences, Sunnybrook Research Institute, Toronto, ON, Canada
| | - Hany Soliman
- Department of Radiation Oncology, University of Toronto, Toronto, ON, Canada
| | - Arjun Sahgal
- Department of Radiation Oncology, University of Toronto, Toronto, ON, Canada
| | - Greg J. Stanisz
- Physical Sciences, Sunnybrook Research Institute, Toronto, ON, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada
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16
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Seif M, Leutritz T, Schading S, Emmengger T, Curt A, Weiskopf N, Freund P. Reliability of multi-parameter mapping (MPM) in the cervical cord: A multi-center multi-vendor quantitative MRI study. Neuroimage 2022; 264:119751. [PMID: 36384206 DOI: 10.1016/j.neuroimage.2022.119751] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2022] [Revised: 11/07/2022] [Accepted: 11/12/2022] [Indexed: 11/14/2022] Open
Abstract
MRI based multicenter studies which target neurological pathologies affecting the spinal cord and brain - including spinal cord injury (SCI) - require standardized acquisition protocols and image processing methods. We have optimized and applied a multi-parameter mapping (MPM) protocol that simultaneously covers the brain and the cervical cord within a traveling heads study across six clinical centers (Leutritz et al., 2020). The MPM protocol includes quantitative maps (magnetization transfer saturation (MT), proton density (PD), longitudinal (R1), and effective transverse (R2*) relaxation rates) sensitive to myelination, water content, iron concentration, and morphometric measures, such as cross-sectional cord area. Previously, we assessed the repeatability and reproducibility of the brain MPM data acquired in the five healthy participants who underwent two scan-rescans (Leutritz et al., 2020). This study focuses on the cervical cord MPM data derived from the same acquisitions to determine its repeatability and reproducibility in the cervical cord. MPM matrices of the cervical cord were generated and processed using the hMRI and the spinal cord toolbox. To determine reliability of the cervical MPM data, the intra-site (i.e., scan-rescan) coefficient of variation (CoV), inter-site CoV, and bias within region of interests (C1, C2 and C3 levels) were determined. The range of the mean intra- and inter-site CoV of MT, R1 and PD was between 2.5% and 12%, and between 1.1% and 4.0% for the morphometric measures. In conclusion, the cervical MPM data showed a high repeatability and reproducibility for key imaging biomarkers and hence can be employed as a standardized tool in multi-center studies, including clinical trials.
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Affiliation(s)
- Maryam Seif
- Spinal Cord Injury Center, University Hospital Balgrist, University of Zurich, Forchstrasse 340, Zurich 8008, Switzerland; Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.
| | - Tobias Leutritz
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Simon Schading
- Spinal Cord Injury Center, University Hospital Balgrist, University of Zurich, Forchstrasse 340, Zurich 8008, Switzerland
| | - Tim Emmengger
- Spinal Cord Injury Center, University Hospital Balgrist, University of Zurich, Forchstrasse 340, Zurich 8008, Switzerland
| | - Armin Curt
- Spinal Cord Injury Center, University Hospital Balgrist, University of Zurich, Forchstrasse 340, Zurich 8008, Switzerland
| | - Nikolaus Weiskopf
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; Faculty of Physics and Earth Sciences, Felix Bloch Institute for Solid State Physics, Leipzig University, Leipzig, Germany
| | - Patrick Freund
- Spinal Cord Injury Center, University Hospital Balgrist, University of Zurich, Forchstrasse 340, Zurich 8008, Switzerland; Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; Wellcome Centre for Human Neuroimaging, Institute of Neurology, University College London, London, UK
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17
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Lancione M, Bosco P, Costagli M, Nigri A, Aquino D, Carne I, Ferraro S, Giulietti G, Napolitano A, Palesi F, Pavone L, Pirastru A, Savini G, Tagliavini F, Bruzzone MG, Gandini Wheeler-Kingshott CA, Tosetti M, Biagi L. Multi-centre and multi-vendor reproducibility of a standardized protocol for quantitative susceptibility Mapping of the human brain at 3T. Phys Med 2022; 103:37-45. [DOI: 10.1016/j.ejmp.2022.09.012] [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: 06/07/2022] [Revised: 09/12/2022] [Accepted: 09/27/2022] [Indexed: 11/16/2022] Open
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18
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Naji N, Lauzon ML, Seres P, Stolz E, Frayne R, Lebel C, Beaulieu C, Wilman AH. Multisite reproducibility of quantitative susceptibility mapping and effective transverse relaxation rate in deep gray matter at 3 T using locally optimized sequences in 24 traveling heads. NMR IN BIOMEDICINE 2022; 35:e4788. [PMID: 35704837 DOI: 10.1002/nbm.4788] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/01/2022] [Revised: 05/28/2022] [Accepted: 06/05/2022] [Indexed: 06/15/2023]
Abstract
Iron concentration in the human brain plays a crucial role in several neurodegenerative diseases and can be monitored noninvasively using quantitative susceptibility mapping (QSM) and effective transverse relaxation rate (R2 *) mapping from multiecho T2 *-weighted images. Large population studies enable better understanding of pathologies and can benefit from pooling multisite data. However, reproducibility may be compromised between sites and studies using different hardware and sequence protocols. This work investigates QSM and R2 * reproducibility at 3 T using locally optimized sequences from three centers and two vendors, and investigates possible reduction of cross-site variability through postprocessing approaches. Twenty-four healthy subjects traveled between three sites and were scanned twice at each site. Scan-rescan measurements from seven deep gray matter regions were used for assessing within-site and cross-site reproducibility using intraclass correlation coefficient (ICC) and within-subject standard deviation (SDw) measures. In addition, multiple QSM and R2 * postprocessing options were investigated with the aim to minimize cross-site sequence-related variations, including: mask generation approach, echo-timing selection, harmonizing spatial resolution, field map estimation, susceptibility inversion method, and linear field correction for magnitude images. The same-subject cross-site region of interest measurements for QSM and R2 * were highly correlated (R2 ≥ 0.94) and reproducible (mean ICC of 0.89 and 0.82 for QSM and R2 *, respectively). The mean cross-site SDw was 4.16 parts per billion (ppb) for QSM and 1.27 s-1 for R2 *. For within-site measurements of QSM and R2 *, the mean ICC was 0.97 and 0.87 and mean SDw was 2.36 ppb and 0.97 s-1 , respectively. The precision level is regionally dependent and is reduced in the frontal lobe, near brain edges, and in white matter regions. Cross-site QSM variability (mean SDw) was reduced up to 46% through postprocessing approaches, such as masking out less reliable regions, matching available echo timings and spatial resolution, avoiding the use of the nonconsistent magnitude contrast between scans in field estimation, and minimizing streaking artifacts.
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Affiliation(s)
- Nashwan Naji
- Department of Biomedical Engineering, University of Alberta, Edmonton, Alberta, Canada
| | - M Louis Lauzon
- Departments of Radiology and Clinical Neurosciences, Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada
- Seaman Family MR Research Centre, Foothills Medical Centre, Calgary, Alberta, Canada
| | - Peter Seres
- Department of Biomedical Engineering, University of Alberta, Edmonton, Alberta, Canada
| | - Emily Stolz
- Department of Biomedical Engineering, University of Alberta, Edmonton, Alberta, Canada
| | - Richard Frayne
- Departments of Radiology and Clinical Neurosciences, Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada
- Seaman Family MR Research Centre, Foothills Medical Centre, Calgary, Alberta, Canada
| | - Catherine Lebel
- Department of Radiology, Alberta Children's Hospital Research Institute and Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada
| | - Christian Beaulieu
- Department of Biomedical Engineering, University of Alberta, Edmonton, Alberta, Canada
| | - Alan H Wilman
- Department of Biomedical Engineering, University of Alberta, Edmonton, Alberta, Canada
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19
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Jakimovski D, Zivadinov R, Bergsland N, Oh J, Martin M, Shinohara RT, Bakshi R, Calabresi PA, Papinutto N, Pelletier D, Dwyer MG. Multisite MRI reproducibility of lateral ventricular volume using the NAIMS cooperative pilot dataset. J Neuroimaging 2022; 32:910-919. [PMID: 35384119 PMCID: PMC9835837 DOI: 10.1111/jon.12998] [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: 11/18/2021] [Revised: 02/25/2022] [Accepted: 03/20/2022] [Indexed: 01/14/2023] Open
Abstract
BACKGROUND AND PURPOSE The North American Imaging in Multiple Sclerosis (NAIMS) multisite project identified interscanner reproducibility issues with T1-based whole brain volume (WBV). Lateral ventricular volume (LVV) acquired on T2-fluid-attenuated inverse recovery (FLAIR) scans has been proposed as a robust proxy measure. Therefore, we sought to determine the relative magnitude of scanner-induced T2-FLAIR-based LVV and T1-based WBV measurement errors in relation to clinically meaningful changes. METHODS This was a post hoc analysis of the NAIMS pilot dataset in which a relapsing-remitting MS patient with no intrastudy clinical or radiological activity was imaged twice on seven different Siemens scanners across the United States. LVV was determined using the automated NeuroSTREAM technique on T2-FLAIR and WBV was determined with SIENAX on high-resolution T1-MPRAGE. Average LVV and WBV were measured, and absolute intrascanner and interscanner coefficients of variation (CoVs) were calculated. The variabilities were compared to previously established annual pathological and clinically meaningful cutoffs of 0.40% for WBV and of 3.51% for LVV. RESULTS Mean LVV across all seven scan/rescan pairs was 45.87 ± 1.15 ml. Average LVV intrascanner CoV was 1.42% and interscanner CoV was 1.78%, both smaller than the reported annualized clinically meaningful cutoff of 3.51%. In contrast, intra- and interscanner CoVs for WBV (0.99% and 1.15%) were both higher than the established cutoff of 0.40%. Individually, 1/7 intrasite and 2/7 intersite pair-wise LVV comparisons were above the 3.51% cutoff, whereas 4/7 intrasite and 7/7 intersite WBV comparisons were above the 0.40% cutoff. CONCLUSION Fully automated LVV segmentation has higher absolute variability than WBV, but much lower relative variability compared to clinically relevant changes, and may therefore be a meaningful proxy outcome measure of neurodegeneration.
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Affiliation(s)
- Dejan Jakimovski
- Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, New York, USA
| | - Robert Zivadinov
- Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, New York, USA
- Center for Biomedical Imaging at Clinical Translational Research Center, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, New York, USA
| | - Niels Bergsland
- Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, New York, USA
- IRCCS, Fondazione Don Carlo Gnocchi ONLUS, Milan, Italy
| | - Jiwon Oh
- St. Michael's Hospital, University of Toronto, Toronto, Ontario, Canada
| | - Melissa Martin
- Department of Biostatistics and Epidemiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
- Penn Statistics in Imaging and Visualization Center (PennSIVE), Center for Clinical Epidemiology and Biostatistics, Perelman School of Medicine, University of Pennsylvania
- Center for Biomedical Image Computing and Analytics, Department of Radiology, Perelman School of Medicine, University of Pennsylvania
| | - Russell T Shinohara
- Department of Biostatistics and Epidemiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Rohit Bakshi
- Laboratory for Neuroimaging Research, Partners Multiple Sclerosis Center, Departments of Neurology and Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Peter A Calabresi
- Department of Neurology, Johns Hopkins University, Baltimore, Maryland, USA
| | - Nico Papinutto
- UCSF Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, San Francisco, California, USA
| | - Daniel Pelletier
- Department of Neurology, University of Southern California, Los Angeles, California, USA
| | - Michael G Dwyer
- Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, New York, USA
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20
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Glang F, Mueller S, Herz K, Loktyushin A, Scheffler K, Zaiss M. MR-double-zero - Proof-of-concept for a framework to autonomously discover MRI contrasts. JOURNAL OF MAGNETIC RESONANCE (SAN DIEGO, CALIF. : 1997) 2022; 341:107237. [PMID: 35714389 DOI: 10.1016/j.jmr.2022.107237] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/30/2021] [Revised: 04/02/2022] [Accepted: 05/10/2022] [Indexed: 06/15/2023]
Abstract
PURPOSE A framework for supervised design of MR sequences for any given target contrast is proposed, based on fully automatic acquisition and reconstruction of MR data on a real MR scanner. The proposed method does not require any modeling of MR physics and thus allows even unknown contrast mechanisms to be addressed. METHODS A derivative-free optimization algorithm is set up to repeatedly update and execute a parametrized sequence on the MR scanner to acquire data. In each iteration, the acquired data are mapped to a given target contrast by linear regression. RESULTS It is shown that with the proposed framework it is possible to find an MR sequence that yields a predefined target contrast. In the present case, as a proof-of principle, a sequence mapping absolute creatine concentration, which cannot be extracted from T1 or T2-weighted scans directly, is discovered. The sequence was designed in a comparatively short time and with no human interaction. CONCLUSIONS New MR contrasts for mapping a given target can be discovered by derivative-free optimization of parametrized sequences that are directly executed on a real MRI scanner. This is demonstrated by 're-discovery' of a chemical exchange weighted sequence. The proposed method is considered to be a paradigm shift towards autonomous, model-free and target-driven sequence design.
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Affiliation(s)
- Felix Glang
- High-field Magnetic Resonance Center, Max Planck Institute for Biological Cybernetics, Tuebingen, Germany
| | - Sebastian Mueller
- High-field Magnetic Resonance Center, Max Planck Institute for Biological Cybernetics, Tuebingen, Germany; Department of Biomedical Magnetic Resonance, Eberhard Karls University Tuebingen, Tuebingen, Germany
| | - Kai Herz
- High-field Magnetic Resonance Center, Max Planck Institute for Biological Cybernetics, Tuebingen, Germany; Department of Biomedical Magnetic Resonance, Eberhard Karls University Tuebingen, Tuebingen, Germany
| | - Alexander Loktyushin
- High-field Magnetic Resonance Center, Max Planck Institute for Biological Cybernetics, Tuebingen, Germany
| | - Klaus Scheffler
- High-field Magnetic Resonance Center, Max Planck Institute for Biological Cybernetics, Tuebingen, Germany; Department of Biomedical Magnetic Resonance, Eberhard Karls University Tuebingen, Tuebingen, Germany
| | - Moritz Zaiss
- High-field Magnetic Resonance Center, Max Planck Institute for Biological Cybernetics, Tuebingen, Germany; Institute of Neuroradiology, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nürnberg (FAU), Erlangen, Germany.
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21
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Le Ster C, Grant A, Van de Moortele PF, Monreal-Madrigal A, Adriany G, Vignaud A, Mauconduit F, Rabrait-Lerman C, Poser BA, Uğurbil K, Boulant N. Magnetic field strength dependent SNR gain at the center of a spherical phantom and up to 11.7T. Magn Reson Med 2022; 88:2131-2138. [PMID: 35849739 PMCID: PMC9420790 DOI: 10.1002/mrm.29391] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2022] [Revised: 06/06/2022] [Accepted: 06/27/2022] [Indexed: 02/05/2023]
Abstract
PURPOSE The SNR at the center of a spherical phantom of known electrical properties was measured in quasi-identical experimental conditions as a function of magnetic field strength between 3 T and 11.7 T. METHODS The SNR was measured at the center of a spherical water saline phantom with a gradient recalled echo sequence. Measurements were performed at NeuroSpin at 3, 7, and 11.7 T. The phantom was then shipped to Maastricht University and then to the University of Minnesota for additional data points at 7, 9.4, and 10.5 T. Experiments were carried out with the exact same type of birdcage volume coil (except at 3 T, where a similar coil was used) to attempt at isolating the evolution of SNR with field strength alone. Phantom electrical properties were characterized over the corresponding frequency range. RESULTS Electrical properties were found to barely vary over the frequency range. Removing the influence of the flip-angle excitation inhomogeneity was crucial, as expected. After such correction, measurements revealed a gain of SNR growing as B0 1.94 ± 0.16 compared with B0 2.13 according to ultimate intrinsic SNR theory. CONCLUSIONS By using quasi-identical experimental setups (RF volume coil, phantom, electrical properties, and protocol), this work reports experimental data between 3 T and 11.7 T, enabling the comparison with SNR theories in which conductivity and permittivity can be assumed to be constant with respect to field strength. According to ultimate SNR theory, these results can be reasonably extrapolated to the performance of receive arrays with greater than about 32 elements for central SNR in the same spherical phantom.
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Affiliation(s)
- Caroline Le Ster
- University of Paris-Saclay, CEA, CNRS, BAOBAB, NeuroSpin, Gif sur Yvette, France
| | - Andrea Grant
- Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, Minnesota, USA
| | | | | | - Gregor Adriany
- Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, Minnesota, USA
| | - Alexandre Vignaud
- University of Paris-Saclay, CEA, CNRS, BAOBAB, NeuroSpin, Gif sur Yvette, France
| | - Franck Mauconduit
- University of Paris-Saclay, CEA, CNRS, BAOBAB, NeuroSpin, Gif sur Yvette, France
| | | | - Benedikt A Poser
- Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, The Netherlands
| | - Kâmil Uğurbil
- Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, Minnesota, USA
| | - Nicolas Boulant
- University of Paris-Saclay, CEA, CNRS, BAOBAB, NeuroSpin, Gif sur Yvette, France
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22
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Karakuzu A, Biswas L, Cohen-Adad J, Stikov N. Vendor-neutral sequences and fully transparent workflows improve inter-vendor reproducibility of quantitative MRI. Magn Reson Med 2022; 88:1212-1228. [PMID: 35657066 DOI: 10.1002/mrm.29292] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2021] [Revised: 04/18/2022] [Accepted: 04/19/2022] [Indexed: 12/20/2022]
Abstract
PURPOSE We developed an end-to-end workflow that starts with a vendor-neutral acquisition and tested the hypothesis that vendor-neutral sequences decrease inter-vendor variability of T1, magnetization transfer ratio (MTR), and magnetization transfer saturation-index (MTsat) measurements. METHODS We developed and deployed a vendor-neutral 3D spoiled gradient-echo (SPGR) sequence on three clinical scanners by two MRI vendors. We then acquired T1 maps on the ISMRM-NIST system phantom, as well as T1, MTR, and MTsat maps in three healthy participants. We performed hierarchical shift function analysis in vivo to characterize the differences between scanners when the vendor-neutral sequence is used instead of commercial vendor implementations. Inter-vendor deviations were compared for statistical significance to test the hypothesis. RESULTS In the phantom, the vendor-neutral sequence reduced inter-vendor differences from 8% to 19.4% to 0.2% to 5% with an overall accuracy improvement, reducing ground truth T1 deviations from 7% to 11% to 0.2% to 4%. In vivo, we found that the variability between vendors is significantly reduced (p = 0.015) for all maps (T1, MTR, and MTsat) using the vendor-neutral sequence. CONCLUSION We conclude that vendor-neutral workflows are feasible and compatible with clinical MRI scanners. The significant reduction of inter-vendor variability using vendor-neutral sequences has important implications for qMRI research and for the reliability of multicenter clinical trials.
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Affiliation(s)
- Agah Karakuzu
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montréal, Montréal, Quebec, Canada.,Montréal Heart Institute, Montréal, Quebec, Canada
| | - Labonny Biswas
- Sunnybrook Research Institute, University of Toronto, Toronto, Ontario, Canada
| | - Julien Cohen-Adad
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montréal, Montréal, Quebec, Canada.,Functional Neuroimaging Unit, CRIUGM, Université de Montréal, Montréal, Quebec, Canada.,Mila - Quebec AI Institute, Montreal, Quebec, Canada
| | - Nikola Stikov
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montréal, Montréal, Quebec, Canada.,Montréal Heart Institute, Montréal, Quebec, Canada.,Center for Advanced Interdisciplinary Research, Ss. Cyril and Methodius University, Skopje, North Macedonia
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23
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Wang C, Martins-Bach AB, Alfaro-Almagro F, Douaud G, Klein JC, Llera A, Fiscone C, Bowtell R, Elliott LT, Smith SM, Tendler BC, Miller KL. Phenotypic and genetic associations of quantitative magnetic susceptibility in UK Biobank brain imaging. Nat Neurosci 2022; 25:818-831. [PMID: 35606419 PMCID: PMC9174052 DOI: 10.1038/s41593-022-01074-w] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2021] [Accepted: 04/11/2022] [Indexed: 12/17/2022]
Abstract
A key aim in epidemiological neuroscience is identification of markers to assess brain health and monitor therapeutic interventions. Quantitative susceptibility mapping (QSM) is an emerging magnetic resonance imaging technique that measures tissue magnetic susceptibility and has been shown to detect pathological changes in tissue iron, myelin and calcification. We present an open resource of QSM-based imaging measures of multiple brain structures in 35,273 individuals from the UK Biobank prospective epidemiological study. We identify statistically significant associations of 251 phenotypes with magnetic susceptibility that include body iron, disease, diet and alcohol consumption. Genome-wide associations relate magnetic susceptibility to 76 replicating clusters of genetic variants with biological functions involving iron, calcium, myelin and extracellular matrix. These patterns of associations include relationships that are unique to QSM, in particular being complementary to T2* signal decay time measures. These new imaging phenotypes are being integrated into the core UK Biobank measures provided to researchers worldwide, creating the potential to discover new, non-invasive markers of brain health.
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Affiliation(s)
- Chaoyue Wang
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK.
| | - Aurea B Martins-Bach
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Fidel Alfaro-Almagro
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Gwenaëlle Douaud
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Johannes C Klein
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
- Oxford Parkinson's Disease Centre, University of Oxford, Oxford, UK
| | - Alberto Llera
- Donders Institute for Brain, Cognition and Behaviour, Centre for Cognitive Neuroimaging, Nijmegen, the Netherlands
| | - Cristiana Fiscone
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, Nottingham, UK
- Department of Biomedical and Neuromotor Sciences, University of Bologna, Bologna, Italy
| | - Richard Bowtell
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, Nottingham, UK
| | - Lloyd T Elliott
- Department of Statistics and Actuarial Science, Simon Fraser University, Vancouver, British Columbia, Canada
| | - Stephen M Smith
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Benjamin C Tendler
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Karla L Miller
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK.
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24
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Nigri A, Ferraro S, Gandini Wheeler-Kingshott CAM, Tosetti M, Redolfi A, Forloni G, D'Angelo E, Aquino D, Biagi L, Bosco P, Carne I, De Francesco S, Demichelis G, Gianeri R, Lagana MM, Micotti E, Napolitano A, Palesi F, Pirastru A, Savini G, Alberici E, Amato C, Arrigoni F, Baglio F, Bozzali M, Castellano A, Cavaliere C, Contarino VE, Ferrazzi G, Gaudino S, Marino S, Manzo V, Pavone L, Politi LS, Roccatagliata L, Rognone E, Rossi A, Tonon C, Lodi R, Tagliavini F, Bruzzone MG. Quantitative MRI Harmonization to Maximize Clinical Impact: The RIN-Neuroimaging Network. Front Neurol 2022; 13:855125. [PMID: 35493836 PMCID: PMC9047871 DOI: 10.3389/fneur.2022.855125] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2022] [Accepted: 03/17/2022] [Indexed: 11/13/2022] Open
Abstract
Neuroimaging studies often lack reproducibility, one of the cardinal features of the scientific method. Multisite collaboration initiatives increase sample size and limit methodological flexibility, therefore providing the foundation for increased statistical power and generalizable results. However, multisite collaborative initiatives are inherently limited by hardware, software, and pulse and sequence design heterogeneities of both clinical and preclinical MRI scanners and the lack of benchmark for acquisition protocols, data analysis, and data sharing. We present the overarching vision that yielded to the constitution of RIN-Neuroimaging Network, a national consortium dedicated to identifying disease and subject-specific in-vivo neuroimaging biomarkers of diverse neurological and neuropsychiatric conditions. This ambitious goal needs efforts toward increasing the diagnostic and prognostic power of advanced MRI data. To this aim, 23 Italian Scientific Institutes of Hospitalization and Care (IRCCS), with technological and clinical specialization in the neurological and neuroimaging field, have gathered together. Each IRCCS is equipped with high- or ultra-high field MRI scanners (i.e., ≥3T) for clinical or preclinical research or has established expertise in MRI data analysis and infrastructure. The actions of this Network were defined across several work packages (WP). A clinical work package (WP1) defined the guidelines for a minimum standard clinical qualitative MRI assessment for the main neurological diseases. Two neuroimaging technical work packages (WP2 and WP3, for clinical and preclinical scanners) established Standard Operative Procedures for quality controls on phantoms as well as advanced harmonized quantitative MRI protocols for studying the brain of healthy human participants and wild type mice. Under FAIR principles, a web-based e-infrastructure to store and share data across sites was also implemented (WP4). Finally, the RIN translated all these efforts into a large-scale multimodal data collection in patients and animal models with dementia (i.e., case study). The RIN-Neuroimaging Network can maximize the impact of public investments in research and clinical practice acquiring data across institutes and pathologies with high-quality and highly-consistent acquisition protocols, optimizing the analysis pipeline and data sharing procedures.
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Affiliation(s)
- Anna Nigri
- U.O. Neuroradiologia, Fondazione IRCCS Istituto Neurologico Carlo Besta, Milan, Italy
| | - Stefania Ferraro
- U.O. Neuroradiologia, Fondazione IRCCS Istituto Neurologico Carlo Besta, Milan, Italy
- MOE Key Laboratory for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Claudia A. M. Gandini Wheeler-Kingshott
- Unità di Neuroradiologia, IRCCS Mondino Foundation, Pavia, Italy
- NMR Research Unit, Department of Neuroinflammation, Queen Square MS Centre, UCL Queen Square Institute of Neurology, Faculty of Brain Sciences, University College London, London, United Kingdom
- Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy
| | - Michela Tosetti
- Medical Physics and MR Lab, Fondazione IRCCS Stella Maris, Pisa, Italy
| | - Alberto Redolfi
- Laboratory of Neuroinformatics, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Gianluigi Forloni
- Medical Physics and MR Lab, Fondazione IRCCS Stella Maris, Pisa, Italy
| | - Egidio D'Angelo
- Unità di Neuroradiologia, IRCCS Mondino Foundation, Pavia, Italy
- Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy
| | - Domenico Aquino
- U.O. Neuroradiologia, Fondazione IRCCS Istituto Neurologico Carlo Besta, Milan, Italy
| | - Laura Biagi
- Medical Physics and MR Lab, Fondazione IRCCS Stella Maris, Pisa, Italy
| | - Paolo Bosco
- Medical Physics and MR Lab, Fondazione IRCCS Stella Maris, Pisa, Italy
| | - Irene Carne
- Neuroradiology Unit, IRCCS Istituti Clinici Scientifici Maugeri, Pavia, Italy
| | - Silvia De Francesco
- Laboratory of Neuroinformatics, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Greta Demichelis
- U.O. Neuroradiologia, Fondazione IRCCS Istituto Neurologico Carlo Besta, Milan, Italy
| | - Ruben Gianeri
- U.O. Neuroradiologia, Fondazione IRCCS Istituto Neurologico Carlo Besta, Milan, Italy
| | | | - Edoardo Micotti
- Laboratory of Biology of Neurodegenerative Disorders, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Milan, Italy
| | - Antonio Napolitano
- Medical Physics, IRCCS Istituto Ospedale Pediatrico Bambino Gesù, Rome, Italy
| | - Fulvia Palesi
- Unità di Neuroradiologia, IRCCS Mondino Foundation, Pavia, Italy
- Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy
| | | | - Giovanni Savini
- Neuroradiology Unit, IRCCS Humanitas Research Hospital, Milan, Italy
| | - Elisa Alberici
- Neuroradiology Unit, IRCCS Istituti Clinici Scientifici Maugeri, Pavia, Italy
| | - Carmelo Amato
- Unit of Neuroradiology, Oasi Research Institute-IRCCS, Troina, Italy
| | - Filippo Arrigoni
- Neuroimaging Unit, Scientific Institute, IRCCS E. Medea, Bosisio Parini, Italy
| | | | - Marco Bozzali
- Neuroimaging Laboratory, Santa Lucia Foundation, IRCCS, Rome, Italy
| | | | | | - Valeria Elisa Contarino
- Unità di Neuroradiologia, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
| | | | - Simona Gaudino
- Istituto di Radiologia, UOC Radiologia e Neuroradiologia, IRCCS Fondazione Policlinico Universitario Agostino Gemelli, Rome, Italy
| | - Silvia Marino
- IRCCS Centro Neurolesi “Bonino-Pulejo”, Messina, Italy
| | - Vittorio Manzo
- Department of Radiology, Istituto Auxologico Italiano, IRCCS, Milan, Italy
| | | | - Letterio S. Politi
- Neuroradiology Unit, IRCCS Humanitas Research Hospital, Milan, Italy
- Department of Biomedical Sciences, Humanitas University, Milan, Italy
| | - Luca Roccatagliata
- Neuroradiologia IRCCS Ospedale Policlinico San Martino, Genoa, Italy
- Dipartimento di Scienze della Salute Università di Genova, Genoa, Italy
| | - Elisa Rognone
- Unità di Neuroradiologia, IRCCS Mondino Foundation, Pavia, Italy
| | - Andrea Rossi
- Dipartimento di Scienze della Salute Università di Genova, Genoa, Italy
- UO Neuroradiologia, IRCCS Istituto Giannina Gaslini, Genoa, Italy
| | - Caterina Tonon
- Functional and Molecular Neuroimaging Unit, IRCCS Istituto delle Scienze Neurologiche di Bologna, Bologna, Italy
| | - Raffaele Lodi
- Functional and Molecular Neuroimaging Unit, IRCCS Istituto delle Scienze Neurologiche di Bologna, Bologna, Italy
| | - Fabrizio Tagliavini
- Scientific Direction, Fondazione IRCCS Istituto Neurologico Carlo Besta, Milan, Italy
| | - Maria Grazia Bruzzone
- U.O. Neuroradiologia, Fondazione IRCCS Istituto Neurologico Carlo Besta, Milan, Italy
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Perlman O, Farrar CT, Heo HY. MR fingerprinting for semisolid magnetization transfer and chemical exchange saturation transfer quantification. NMR IN BIOMEDICINE 2022; 36:e4710. [PMID: 35141967 PMCID: PMC9808671 DOI: 10.1002/nbm.4710] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/06/2021] [Revised: 01/18/2022] [Accepted: 02/04/2022] [Indexed: 05/11/2023]
Abstract
Chemical exchange saturation transfer (CEST) MRI has positioned itself as a promising contrast mechanism, capable of providing molecular information at sufficient resolution and amplified sensitivity. However, it has not yet become a routinely employed clinical technique, due to a variety of confounding factors affecting its contrast-weighted image interpretation and the inherently long scan time. CEST MR fingerprinting (MRF) is a novel approach for addressing these challenges, allowing simultaneous quantitation of several proton exchange parameters using rapid acquisition schemes. Recently, a number of deep-learning algorithms have been developed to further boost the performance and speed of CEST and semi-solid macromolecule magnetization transfer (MT) MRF. This review article describes the fundamental theory behind semisolid MT/CEST-MRF and its main applications. It then details supervised and unsupervised learning approaches for MRF image reconstruction and describes artificial intelligence (AI)-based pipelines for protocol optimization. Finally, practical considerations are discussed, and future perspectives are given, accompanied by basic demonstration code and data.
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Affiliation(s)
- Or Perlman
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA
| | - Christian T. Farrar
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA
| | - Hye-Young Heo
- Division of MR Research, Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
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Development and evaluation of a numerical simulation approach to predict metal artifacts from passive implants in MRI. MAGNETIC RESONANCE MATERIALS IN PHYSICS BIOLOGY AND MEDICINE 2021; 35:485-497. [PMID: 34655346 PMCID: PMC9188622 DOI: 10.1007/s10334-021-00966-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/16/2021] [Revised: 09/27/2021] [Accepted: 10/01/2021] [Indexed: 11/08/2022]
Abstract
Objective This study presents the development and evaluation of a numerical approach to simulate artifacts of metallic implants in an MR environment that can be applied to improve the testing procedure for MR image artifacts in medical implants according to ASTM F2119. Methods The numerical approach is validated by comparing simulations and measurements of two metallic test objects made of titanium and stainless steel at three different field strengths (1.5T, 3T and 7T). The difference in artifact size and shape between the simulated and measured artifacts were evaluated. A trend analysis of the artifact sizes in relation to the field strength was performed. Results The numerical simulation approach shows high similarity (between 75% and 84%) of simulated and measured artifact sizes of metallic implants. Simulated and measured artifact sizes in relation to the field strength resulted in a calculation guideline to determine and predict the artifact size at one field strength (e.g., 3T or 7T) based on a measurement that was obtained at another field strength only (e.g. 1.5T). Conclusion This work presents a novel tool to improve the MR image artifact testing procedure of passive medical implants. With the help of this tool detailed artifact investigations can be performed, which would otherwise only be possible with substantial measurement effort on different MRI systems and field strengths.
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Reiter T, Lohr D, Hock M, Ankenbrand MJ, Stefanescu MR, Kosmala A, Kaspar M, Juchem C, Terekhov M, Schreiber LM. On the way to routine cardiac MRI at 7 Tesla - a pilot study on consecutive 84 examinations. PLoS One 2021; 16:e0252797. [PMID: 34297720 PMCID: PMC8301632 DOI: 10.1371/journal.pone.0252797] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2020] [Accepted: 05/23/2021] [Indexed: 11/29/2022] Open
Abstract
INTRODUCTION Cardiac magnetic resonance (CMR) at ultrahigh field (UHF) offers the potential of high resolution and fast image acquisition. Both technical and physiological challenges associated with CMR at 7T require specific hardware and pulse sequences. This study aimed to assess the current status and existing, publicly available technology regarding the potential of a clinical application of 7T CMR. METHODS Using a 7T MRI scanner and a commercially available radiofrequency coil, a total of 84 CMR examinations on 72 healthy volunteers (32 males, age 19-70 years, weight 50-103 kg) were obtained. Both electrocardiographic and acoustic triggering were employed. The data were analyzed regarding the diagnostic image quality and the influence of patient and hardware dependent factors. 50 complete short axis stacks and 35 four chamber CINE views were used for left ventricular (LV) and right ventricular (RV), mono-planar LV function, and RV fractional area change (FAC). Twenty-seven data sets included aortic flow measurements that were used to calculate stroke volumes. Subjective acceptance was obtained from all volunteers with a standardized questionnaire. RESULTS Functional analysis showed good functions of LV (mean EF 56%), RV (mean EF 59%) and RV FAC (mean FAC 52%). Flow measurements showed congruent results with both ECG and ACT triggering. No significant influence of experimental parameters on the image quality of the LV was detected. Small fractions of 5.4% of LV and 2.5% of RV segments showed a non-diagnostic image quality. The nominal flip angle significantly influenced the RV image quality. CONCLUSION The results demonstrate that already now a commercially available 7T MRI system, without major methods developments, allows for a solid morphological and functional analysis similar to the clinically established CMR routine approach. This opens the door towards combing routine CMR in patients with development of advanced 7T technology.
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Affiliation(s)
- Theresa Reiter
- Comprehensive Heart Failure Center Wuerzburg (CHFC), Chair of Molecular and Cellular Imaging, Wuerzburg, Germany
- Department of Internal Medicine I, Cardiology, University Hospital Wuerzburg, Wuerzburg, Germany
| | - David Lohr
- Comprehensive Heart Failure Center Wuerzburg (CHFC), Chair of Molecular and Cellular Imaging, Wuerzburg, Germany
| | - Michael Hock
- Comprehensive Heart Failure Center Wuerzburg (CHFC), Chair of Molecular and Cellular Imaging, Wuerzburg, Germany
| | - Markus Johannes Ankenbrand
- Comprehensive Heart Failure Center Wuerzburg (CHFC), Chair of Molecular and Cellular Imaging, Wuerzburg, Germany
| | - Maria Roxana Stefanescu
- Comprehensive Heart Failure Center Wuerzburg (CHFC), Chair of Molecular and Cellular Imaging, Wuerzburg, Germany
| | - Aleksander Kosmala
- Comprehensive Heart Failure Center Wuerzburg (CHFC), Chair of Molecular and Cellular Imaging, Wuerzburg, Germany
- Department of Radiology, University Hospital Wuerzburg, Wuerzburg, Germany
| | - Mathias Kaspar
- Department of Health Services Research, Carl von Ossietzky University of Oldenburg, Oldenburg, Germany
| | - Christoph Juchem
- Departments of Biomedical Engineering and Radiology, Columbia University, New York, New York, United States of America
| | - Maxim Terekhov
- Comprehensive Heart Failure Center Wuerzburg (CHFC), Chair of Molecular and Cellular Imaging, Wuerzburg, Germany
| | - Laura Maria Schreiber
- Comprehensive Heart Failure Center Wuerzburg (CHFC), Chair of Molecular and Cellular Imaging, Wuerzburg, Germany
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Schneider TM, Ma J, Wagner P, Behl N, Nagel AM, Ladd ME, Heiland S, Bendszus M, Straub S. Multiparametric MRI for Characterization of the Basal Ganglia and the Midbrain. Front Neurosci 2021; 15:661504. [PMID: 34234639 PMCID: PMC8255625 DOI: 10.3389/fnins.2021.661504] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2021] [Accepted: 05/17/2021] [Indexed: 12/02/2022] Open
Abstract
Objectives To characterize subcortical nuclei by multi-parametric quantitative magnetic resonance imaging. Materials and Methods: The following quantitative multiparametric MR data of five healthy volunteers were acquired on a 7T MRI system: 3D gradient echo (GRE) data for the calculation of quantitative susceptibility maps (QSM), GRE sequences with and without off-resonant magnetic transfer pulse for magnetization transfer ratio (MTR) calculation, a magnetization−prepared 2 rapid acquisition gradient echo sequence for T1 mapping, and (after a coil change) a density-adapted 3D radial pulse sequence for 23Na imaging. First, all data were co-registered to the GRE data, volumes of interest (VOIs) for 21 subcortical structures were drawn manually for each volunteer, and a combined voxel-wise analysis of the four MR contrasts (QSM, MTR, T1, 23Na) in each structure was conducted to assess the quantitative, MR value-based differentiability of structures. Second, a machine learning algorithm based on random forests was trained to automatically classify the groups of multi-parametric voxel values from each VOI according to their association to one of the 21 subcortical structures. Results The analysis of the integrated multimodal visualization of quantitative MR values in each structure yielded a successful classification among nuclei of the ascending reticular activation system (ARAS), the limbic system and the extrapyramidal system, while classification among (epi-)thalamic nuclei was less successful. The machine learning-based approach facilitated quantitative MR value-based structure classification especially in the group of extrapyramidal nuclei and reached an overall accuracy of 85% regarding all selected nuclei. Conclusion Multimodal quantitative MR enabled excellent differentiation of a wide spectrum of subcortical nuclei with reasonable accuracy and may thus enable sensitive detection of disease and nucleus-specific MR-based contrast alterations in the future.
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Affiliation(s)
- Till M Schneider
- Department of Neuroradiology, University of Heidelberg, Heidelberg, Germany
| | - Jackie Ma
- Department of Artificial Intelligence, Fraunhofer Heinrich Hertz Institute, Berlin, Germany
| | - Patrick Wagner
- Department of Artificial Intelligence, Fraunhofer Heinrich Hertz Institute, Berlin, Germany
| | - Nicolas Behl
- Division of Medical Physics in Radiology, German Cancer Research Center, Heidelberg, Germany
| | - Armin M Nagel
- Division of Medical Physics in Radiology, German Cancer Research Center, Heidelberg, Germany.,Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Mark E Ladd
- Division of Medical Physics in Radiology, German Cancer Research Center, Heidelberg, Germany.,Faculty of Physics and Astronomy and Faculty of Medicine, University of Heidelberg, Heidelberg, Germany
| | - Sabine Heiland
- Department of Neuroradiology, University of Heidelberg, Heidelberg, Germany
| | - Martin Bendszus
- Department of Neuroradiology, University of Heidelberg, Heidelberg, Germany
| | - Sina Straub
- Division of Medical Physics in Radiology, German Cancer Research Center, Heidelberg, Germany
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