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3. Accelerated sodium MRI using undersampled 3D SPARKLING at 7T

Author

Porciuncula Baptista, Renata, Naudin, Mathieu, Giliyar Radhakrishna, Chaithya, Daval-Frérot, Guillaume, Mauconduit, Franck, Haeger, Alexa, Romanzetti, Sandro, Lapert, Marc, Ciuciu, Philippe, Rabrait-Lerman, Cécile, Guillevin, Remy, Vignaud, Alexandre, Boumezbeur, Fawzi, Service NEUROSPIN (NEUROSPIN), Université Paris-Saclay-Direction de Recherche Fondamentale (CEA) (DRF (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA), Building large instruments for neuroimaging: from population imaging to ultra-high magnetic fields (BAOBAB), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Direction de Recherche Fondamentale (CEA) (DRF (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Centre National de la Recherche Scientifique (CNRS), Laboratoire commun Imagerie Métabolique Multi-Noyaux Multi-Organes (I3M), Université de Poitiers-Centre hospitalier universitaire de Poitiers (CHU Poitiers)-Centre National de la Recherche Scientifique (CNRS)-Siemens Healthineers, Digital Services, Digital Technology and Innovation, Data Analysis and Computations Through Imaging Modeling-Mathématiques, Imagerie, Santé (DACTIM-MIS), Laboratoire de Mathématiques et Applications (LMA-Poitiers), Université de Poitiers-Centre National de la Recherche Scientifique (CNRS)-Université de Poitiers-Centre National de la Recherche Scientifique (CNRS), Modèles et inférence pour les données de Neuroimagerie (MIND), IFR49 - Neurospin - CEA, Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Inria Saclay - Ile de France, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Siemens Healthineers [Saint-Denis], Baobab, Département PEGASE [LBBE] (PEGASE), Laboratoire de Biométrie et Biologie Evolutive - UMR 5558 (LBBE), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Centre National de la Recherche Scientifique (CNRS)-Laboratoire de Biométrie et Biologie Evolutive - UMR 5558 (LBBE), Université de Lyon-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Centre National de la Recherche Scientifique (CNRS), Universitätsklinikum RWTH Aachen - University Hospital Aachen [Aachen, Germany] (UKA), Rheinisch-Westfälische Technische Hochschule Aachen University (RWTH), Leducq Foundation (large equipment ERPT program, 360 NEUROVASC7T project), the HPC resources of IDRIS under the allocation 2021-AD011011153 made by GENCI, European Project: 800945,NUMERICS, Ciuciu, Philippe, and International PhD programme in NUMERICal Simulation - NUMERICS - 0000-00-00 - 0000-00-00 - 800945 - VALID

Subjects
SPARKLING, [INFO.INFO-TS] Computer Science [cs]/Signal and Image Processing, [SDV.IB.IMA]Life Sciences [q-bio]/Bioengineering/Imaging, [INFO.INFO-IM] Computer Science [cs]/Medical Imaging, [SDV.NEU.SC]Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC]/Cognitive Sciences, $^{23}$Na, UHF, [SDV.IB.IMA] Life Sciences [q-bio]/Bioengineering/Imaging, [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing, [INFO.INFO-IM]Computer Science [cs]/Medical Imaging, human brain, [SDV.NEU.SC] Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC]/Cognitive Sciences, TSC, compressed sensing
Abstract

Submitted to Magnetic Resonance in Medicine; Purpose: To evaluate the benefits of SPARKLING, a stochastic k-space sampling approach over the deterministic sampling scheme TPI (Twisted Projection Imaging) in the context of accelerated cerebral $^{23}$Na MRI and assessing its impact on tissue sodium concentration (TSC) estimation.Methods: Guided by simulation results, in vitro and in vitro UTE $^{23}$Na MRI datasets were acquired at a 4 mm isotropic resolution from healthy volunteers using both TPI or SPARKLING trajectories with different acceleration factors (AF) on a 7T MR scanner equipped with a 32 channels head coil. Following reconstruction using NUFFT or Proximal Optimized Gradient Method (POGM) algorithms with or without regularization, respectively, the resulting sodium images were compared in terms of effective resolution (FWHM of the PSF), SNR and overall quality. with an in vitro assement of the accuracy of the TSC was performed via external referencing using a 4-point calibration approach. Results: In vivo cerebral sodium images acquired using SPARKLING with an acceleration factor of 32 (TA= 5 min 38 s) are similar to those obtained using TPI at AF=8 (TA= 22 min 34 s) with minimal impact on the accuracy of our TSC quantification. Conclusion: In conditions compatible with clinical examination, undersampled SPARKLING $^{23}$Na MRI can outperform the conventional TPI k-space sampling scheme allowing for shorter acquisition times.

Published
2023

4. Magnetic field strength dependent signal-to-noise ratio gain at the center of a spherical phantom and up to 11.7T

Author

Ster, Caroline Le, Grant, Andrea, Pierre-François Van De Moortele, Monreal-Madrigal, Alejandro, Adriany, Gregor, Vignaud, Alexandre, Mauconduit, Franck, Rabrait-Lerman, Cécile, Poser, Benedikt A., Kâmil Uğurbil, and Boulant, Nicolas

Subjects
signal-to-noise ratio, field strength, volume coil
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 3T and 11.7T. Methods: SNR was measured at the center of a spherical water saline phantom with a GRE sequence. Measurements were performed at NeuroSpin at 3T, 7T and 11.7T. The phantom was then shipped to Maastricht University and then to the University of Minnesota for additional data points at 7T, 9.4T and 10.5T. Experiments were carried out with the exact same type of birdcage volume coil (except at 3T 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 B01.94 ± 0.16 compared to B02.13 according to ultimate intrinsic SNR theory. Conclusion: By using quasi-identical experimental setups (RF volume coil, phantom, electrical properties and protocol), this work reports experimental data between 3T and 11.7T enabling the comparison with SNR theories where conductivity and permittivity can be assumed 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 ~32 elements for central SNR in the same spherical phantom.

Published
2022
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5. Magnetic field strength dependent SNR gain at the center of a spherical phantom and up to 11. 7T

Author

Le Ster, Caroline, primary, Grant, Andrea, additional, Van de Moortele, Pierre‐François, additional, Monreal‐Madrigal, Alejandro, additional, Adriany, Gregor, additional, Vignaud, Alexandre, additional, Mauconduit, Franck, additional, Rabrait‐Lerman, Cécile, additional, Poser, Benedikt A., additional, Uğurbil, Kâmil, additional, and Boulant, Nicolas, additional

Published
2022
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6. What can 7T sodium MRI tell us about cellular energy depletion and neurotransmission in Alzheimer's disease?

Author

Haeger, Alexa, primary, Bottlaender, Michel, additional, Lagarde, Julien, additional, Porciuncula Baptista, Renata, additional, Rabrait‐Lerman, Cécile, additional, Luecken, Volker, additional, Schulz, Jörg B., additional, Vignaud, Alexandre, additional, Sarazin, Marie, additional, Reetz, Kathrin, additional, Romanzetti, Sandro, additional, and Boumezbeur, Fawzi, additional

Published
2021
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9. Simultaneous multi-parametric mapping of total sodium concentration, T1, T2 and ADC at 7 T using a multi-contrast unbalanced SSFP

Author

Leroi, Lisa, primary, Coste, Arthur, additional, de Rochefort, Ludovic, additional, Santin, Mathieu D., additional, Valabregue, Romain, additional, Mauconduit, Franck, additional, Giacomini, Eric, additional, Luong, Michel, additional, Chazel, Edouard, additional, Valette, Julien, additional, Le Bihan, Denis, additional, Poupon, Cyril, additional, Boumezbeur, Fawzi, additional, Rabrait-Lerman, Cécile, additional, and Vignaud, Alexandre, additional

Published
2018
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10. Simultaneous multi-parametric and quantitative estimation of 23Na physical properties at 7 Tesla using QuICS

Author

Leroi, Lisa, Coste, Arthur, Rochefort, Ludovic, Santin, Mathieu, Valabrègue, Romain, Mauconduit, Franck, Hang, Marie-France, Chazel, Edouard, Bernard, Jérémy, Luong, Michel, Giacomini, Eric, Le Bihan, Denis, Poupon, Cyril, Boumezbeur, Fawzi, Rabrait-Lerman, Cécile, Vignaud, Alexandre, Centre de résonance magnétique biologique et médicale (CRMBM), Aix Marseille Université (AMU)-Assistance Publique - Hôpitaux de Marseille (APHM)-Centre National de la Recherche Scientifique (CNRS), Institut du Cerveau et de la Moëlle Epinière = Brain and Spine Institute (ICM), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Center for NeuroImaging Research-Human MRI Neuroimaging core facility for clinical research [ICM Paris] (CENIR), Institut du Cerveau = Paris Brain Institute (ICM), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Siemens Healthcare, Service NEUROSPIN (NEUROSPIN), Université Paris-Saclay-Direction de Recherche Fondamentale (CEA) (DRF (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA), Lab-STICC_CNRS_CID_DECIDE, Laboratoire des sciences et techniques de l'information, de la communication et de la connaissance (Lab-STICC), Université européenne de Bretagne - European University of Brittany (UEB)-École Nationale d'Ingénieurs de Brest (ENIB)-Université de Bretagne Sud (UBS)-Université de Brest (UBO)-Télécom Bretagne-Institut Brestois du Numérique et des Mathématiques (IBNM), Université de Brest (UBO)-École Nationale Supérieure de Techniques Avancées Bretagne (ENSTA Bretagne)-Institut Mines-Télécom [Paris] (IMT)-Centre National de la Recherche Scientifique (CNRS)-Université européenne de Bretagne - European University of Brittany (UEB)-École Nationale d'Ingénieurs de Brest (ENIB)-Université de Bretagne Sud (UBS)-Université de Brest (UBO)-Télécom Bretagne-Institut Brestois du Numérique et des Mathématiques (IBNM), Université de Brest (UBO)-École Nationale Supérieure de Techniques Avancées Bretagne (ENSTA Bretagne)-Institut Mines-Télécom [Paris] (IMT)-Centre National de la Recherche Scientifique (CNRS), Laboratoire d'Imagerie et de Spectroscopie (LRMN), Commissariat à l'énergie atomique et aux énergies alternatives (CEA), Assistance Publique - Hôpitaux de Marseille (APHM)-Aix Marseille Université (AMU)-Centre National de la Recherche Scientifique (CNRS), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-CHU Pitié-Salpêtrière [AP-HP], Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), Centre de Neuro-Imagerie de Recherche (CENIR), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-CHU Pitié-Salpêtrière [AP-HP], Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU), Direction de Recherche Fondamentale (CEA) (DRF (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay, École Nationale d'Ingénieurs de Brest (ENIB)-Université de Bretagne Sud (UBS)-Université de Brest (UBO)-Télécom Bretagne-Institut Brestois du Numérique et des Mathématiques (IBNM), Université de Brest (UBO)-Université européenne de Bretagne - European University of Brittany (UEB)-École Nationale Supérieure de Techniques Avancées Bretagne (ENSTA Bretagne)-Institut Mines-Télécom [Paris] (IMT)-Centre National de la Recherche Scientifique (CNRS)-École Nationale d'Ingénieurs de Brest (ENIB)-Université de Bretagne Sud (UBS)-Université de Brest (UBO)-Télécom Bretagne-Institut Brestois du Numérique et des Mathématiques (IBNM), Université de Brest (UBO)-Université européenne de Bretagne - European University of Brittany (UEB)-École Nationale Supérieure de Techniques Avancées Bretagne (ENSTA Bretagne)-Institut Mines-Télécom [Paris] (IMT)-Centre National de la Recherche Scientifique (CNRS), BERNARD, Monique, and Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU)

Subjects
[SDV.IB.IMA] Life Sciences [q-bio]/Bioengineering/Imaging, [SDV.IB.IMA]Life Sciences [q-bio]/Bioengineering/Imaging, [INFO.INFO-IM] Computer Science [cs]/Medical Imaging, [INFO.INFO-IM]Computer Science [cs]/Medical Imaging
Abstract

International audience; Quantifying physical properties of sodium could be of benefit to assess more specifically changes in cellular homeostasis accompanying neuroinflammatory or neurodegenerative diseases. This work aimed at adapting for ^\textrm23Na MRI at 7 Tesla the Quantitative Imaging using Configuration States (QuICS) method, primarily developped for ^\textrm1H MRI. We demonstrate the possibility to not only estimate accurately the T_\textrm1, T_\textrm2, FA, M_\textrm0 and ADC simultaneously for ^\textrm23Na at physiological concentration at UHF, but to acquire 3D maps for all of them.

Published
2017

11. Characterization of altered neuroenergetic patterns in Alzheimer's Disease using combined FDG‐PET and sodium MRI.

Author

Haeger, Alexa, Fuchs, Annalena, Romanzetti, Sandro, Bottlaender, Michel, Boumezbeur, Fawzi, Lagarde, Julien, Rabrait‐Lerman, Cécile, Holtbernd, Florian, Sarazin, Marie, Winz, Oliver, Heinzel, Alexander, Mottaghy, Felix M., Schulz, Jörg B., and Reetz, Kathrin

Abstract

Background: [18F]‐2‐fluoro‐2‐deoxy‐D‐glucose (FDG) positron emission tomography (PET) is applied to delineate cerebral glucose metabolic patterns in Alzheimer's disease (AD). Sodium MR imaging (23Na‐MRI) can reveal alterations in tissue sodium concentration (TSC) in the brain, potentially reflecting mitochondrial dysfunction and impaired cellular energy state. This initial study aims at investigating disease‐specific topographical associations between glucose metabolism assessed via FDG‐PET and regional TSC from 23Na‐MRI, thus improving our understanding of neuroenergetics alteration in AD. Method: 20 patients with a biological biomarker‐based diagnosis of prodromal/mild AD (mean age 68±7.5; 8 females; CDR 0.75±0.57, MMSE 23.9±4.2) received an FDG‐PET, 23Na‐MRI and 1H‐MRI at 3T magnetic field (Siemens Prisma). A variable flip angle method was used to obtain TSC maps (Coste et al., 2019). To control for inter‐individual differences, FDG‐PET and TSC images were intensity‐normalized to the brainstem to create normalized glucose metabolism (nFDG) and normalized TSC maps (nTSC) (de Souza et al., 2011; Nugent et al., 2020), respectively. The Hammersmith and VolBrain Segmentation atlases were applied for region‐of‐interest analysis and to create correlation matrices between nFDG, nTSC and normalized local brain volume. Result: Regional nTSC negatively correlated with nFDG in AD patients mainly in temporal lobe structures and superior frontal gyri, indicating that decreased glucose metabolism was associated with increased TSC and vice versa. As expected, regional volume was positively correlated with nFDG in regions of the temporal lobe. When performing partial correlation controlling for volume, negative correlation clusters between nTSC and nFDG remained significant for superior frontal gyri and the anterior temporal lobes (Figure 1). Conclusion: For the first time, the association between local glucose consumption rates and sodium concentrations were investigated in AD using combined FDG‐PET and 23Na‐MRI at 3T. Consistently to our recent findings of increased TSC in AD patients (Haeger et al., 2021), the negative correlations between nTSC and nFDG values in temporal and frontal brain regions, are confirming the interplay between reduced energy metabolism and sodium increase in AD, the exact nature of which remains to be determined. References: Coste [...]. Magnetic Resonance Imaging 2019. Haeger [...]. Alzheimer's & Dementia 2021. Nugent [...]. Scientific Reports 2020. de Souza [...]. Brain 2011. [ABSTRACT FROM AUTHOR]

Published
2023
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13. Tissue sodium concentration and sodium T1 mapping of the human brain at 3 T using a Variable Flip Angle method.

Author

Coste, Arthur, Boumezbeur, Fawzi, Vignaud, Alexandre, Madelin, Guillaume, Reetz, Kathrin, Le Bihan, Denis, Rabrait-Lerman, Cécile, and Romanzetti, Sandro

Subjects
*BRAIN imaging, *BRAIN mapping, *MAGNETIC resonance imaging of the brain, *TISSUE engineering, *CLINICAL trials
Abstract

Abstract Purpose The state-of-the-art method to quantify sodium concentrations in vivo consists in a fully relaxed 3D spin-density (SD) weighted acquisition. Nevertheless, most sodium MRI clinical studies use short-TR SD acquisitions to reduce acquisition durations. We present a clinically viable implementation of the Variable Flip Angle (VFA) method for robust and clinically viable quantification of total sodium concentration (TSC) and longitudinal relaxation rates in vivo in human brain at 3 T. Methods Two non-Cartesian steady-state spoiled ultrashort echo time (UTE) scans, performed at optimized flip angles, repetition time and pulse length determined under specific absorption rate constraints, are used to simultaneously compute T 1 and total sodium concentration (TSC) maps using the VFA method. Images are reconstructed using the non-uniform Fast Fourier Transform algorithm and TSC maps are corrected for possible inhomogeneity of coil transmission and reception profiles. Fractioned acquisitions are used to correct for potential patient motion. TSC quantifications obtained using the VFA method are validated at first in comparison with a fully-relaxed SD acquisition in a calibration phantom. The robustness of similar VFA acquisitions are compared to the short-TR SD approach in vivo on seven healthy volunteers. Results The VFA method resulted in consistent TSC and T 1 estimates across our cohort of healthy subjects, with mean TSC of 38.1 ± 5.0 mmol/L and T 1 of 39.2 ± 4.4 ms. These results are in agreement with previously reported values in literature TSC estimations and with the predictions of a 2-compartment model. However, the short-TR SD acquisition systematically underestimated the sodium concentration with a mean TSC of 31 ± 4.5 mmol/L. Conclusion The VFA method can be applied successfully to image sodium at 3 T in about 20 min and provides robust and intrinsically T 1 -corrected TSC maps. [ABSTRACT FROM AUTHOR]

Published
2019
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