1
|
Kofler A, Kerkering KM, Goschel L, Fillmer A, Kolbitsch C. Quantitative MR Image Reconstruction Using Parameter-Specific Dictionary Learning With Adaptive Dictionary-Size and Sparsity-Level Choice. IEEE Trans Biomed Eng 2024; 71:388-399. [PMID: 37540614 DOI: 10.1109/tbme.2023.3300090] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/06/2023]
Abstract
OBJECTIVE We propose a method for the reconstruction of parameter-maps in Quantitative Magnetic Resonance Imaging (QMRI). METHODS Because different quantitative parameter-maps differ from each other in terms of local features, we propose a method where the employed dictionary learning (DL) and sparse coding (SC) algorithms automatically estimate the optimal dictionary-size and sparsity level separately for each parameter-map. We evaluated the method on a T1-mapping QMRI problem in the brain using the BrainWeb data as well as in-vivo brain images acquired on an ultra-high field 7 T scanner. We compared it to a model-based acceleration for parameter mapping (MAP) approach, other sparsity-based methods using total variation (TV), Wavelets (Wl), and Shearlets (Sh) to a method which uses DL and SC to reconstruct qualitative images, followed by a non-linear (DL+Fit). RESULTS Our algorithm surpasses MAP, TV, Wl, and Sh in terms of RMSE and PSNR. It yields better or comparable results to DL+Fit by additionally significantly accelerating the reconstruction by a factor of approximately seven. CONCLUSION The proposed method outperforms the reported methods of comparison and yields accurate T1-maps. Although presented for T1-mapping in the brain, our method's structure is general and thus most probably also applicable for the the reconstruction of other quantitative parameters in other organs. SIGNIFICANCE From a clinical perspective, the obtained T1-maps could be utilized to differentiate between healthy subjects and patients with Alzheimer's disease. From a technical perspective, the proposed unsupervised method could be employed to obtain ground-truth data for the development of data-driven methods based on supervised learning.
Collapse
|
2
|
Dell'Orco A, Riemann LT, Ellison SLR, Aydin S, Göschel L, Tietze A, Scheel M, Fillmer A. Macromolecule modelling for improved metabolite quantification using short echo time brain 1 H MRS at 3 T and 7 T: The PRaMM Model. bioRxiv 2023:2023.11.16.567383. [PMID: 38014000 PMCID: PMC10680753 DOI: 10.1101/2023.11.16.567383] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/29/2023]
Abstract
Purpose To improve reliability of metabolite quantification at both, 3 T and 7 T, we propose a novel parametrized macromolecules quantification model (PRaMM) for brain 1 H MRS, in which the ratios of macromolecule peak intensities are used as soft constraints. Methods Full- and metabolite-nulled spectra were acquired in three different brain regions with different ratios of grey and white matter from six healthy volunteers, at both 3 T and 7 T. Metabolite-nulled spectra were used to identify highly correlated macromolecular signal contributions and estimate the ratios of their intensities. These ratios were then used as soft constraints in the proposed PRaMM model for quantification of full spectra. The PRaMM model was validated by comparison with a single component macromolecule model and a macromolecule subtraction technique. Moreover, the influence of the PRaMM model on the repeatability and reproducibility compared to those other methods was investigated. Results The developed PRaMM model performed better than the two other approaches in all three investigated brain regions. Several estimates of metabolite concentration and their Cramér-Rao lower bounds were affected by the PRaMM model reproducibility, and repeatability of the achieved concentrations were tested by evaluating the method on a second repeated acquisitions dataset. While the observed effects on both metrics were not significant, the fit quality metrics were improved for the PRaMM method (p≤0.0001). Minimally detectable changes are in the range 0.5 - 1.9 mM and percent coefficients of variations are lower than 10% for almost all the clinically relevant metabolites. Furthermore, potential overparameterization was ruled out. Conclusion Here, the PRaMM model, a method for an improved quantification of metabolites was developed, and a method to investigate the role of the MM background and its individual components from a clinical perspective is proposed.
Collapse
|
3
|
Göschel L, Kurz L, Dell'Orco A, Köbe T, Körtvélyessy P, Fillmer A, Aydin S, Riemann LT, Wang H, Ittermann B, Grittner U, Flöel A. 7T amygdala and hippocampus subfields in volumetry-based associations with memory: A 3-year follow-up study of early Alzheimer's disease. Neuroimage Clin 2023; 38:103439. [PMID: 37253284 PMCID: PMC10236463 DOI: 10.1016/j.nicl.2023.103439] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2023] [Revised: 05/09/2023] [Accepted: 05/15/2023] [Indexed: 06/01/2023]
Abstract
INTRODUCTION The hippocampus is the most prominent single region of interest (ROI) for the diagnosis and prediction of Alzheimer's disease (AD). However, its suitability in the earliest stages of cognitive decline, i.e., subjective cognitive decline (SCD), remains uncertain which warrants the pursuit of alternative or complementary regions. The amygdala might be a promising candidate, given its implication in memory as well as other psychiatric disorders, e.g. depression and anxiety, which are prevalent in SCD. In this 7 tesla (T) magnetic resonance imaging (MRI) study, we aimed to compare the contribution of volumetric measurements of the hippocampus, the amygdala, and their respective subfields, for early diagnosis and prediction in an AD-related study population. METHODS Participants from a longitudinal study were grouped into SCD (n = 29), mild cognitive impairment (MCI, n = 23), AD (n = 22) and healthy control (HC, n = 31). All participants underwent 7T MRI at baseline and extensive neuropsychological testing at up to three visits (baseline n = 105, 1-year n = 78, 3-year n = 39). Analysis of covariance (ANCOVA) was used to assess group differences of baseline volumes of the amygdala and the hippocampus and their subfields. Linear mixed models were used to estimate the effects of baseline volumes on yearly changes of a z-scaled memory score. All models were adjusted to age, sex and education. RESULTS Compared to the HC group, individuals with SCD showed smaller amygdala ROI volumes (range across subfields -11% to -1%), but not hippocampus ROI volumes (-2% to 1%) except for the hippocampus-amygdala-transition-area (-7%). However, cross-sectional associations between baseline memory and volumes were smaller for amygdala ROIs (std. ß [95% CI] ranging between 0.16 [0.08; 0.25] and 0.46 [0.31; 0.60]) than hippocampus ROIs (between 0.32 [0.19; 0.44] and 0.53 [0.40; 0.67]). Further, the association of baseline volumes with yearly memory change in the HC and SCD groups was similarly weak for amygdala ROIs and hippocampus ROIs. In the MCI group, volumes of amygdala ROIs were associated with a relevant yearly memory decline [95% CI] ranging between -0.12 [-0.24; 0.00] and -0.26 [-0.42; -0.09] for individuals with 20% smaller volumes than the HC group. However, effects were stronger for hippocampus ROIs with a corresponding yearly memory decline ranging between -0.21 [-0.35; -0.07] and -0.31 [-0.50; -0.13]. CONCLUSION Volumes of amygdala ROIs, as determined by 7T MRI, might contribute to objectively and non-invasively identify patients with SCD, and thus aid early diagnosis and treatment of individuals at risk to develop dementia due to AD, however associations with other psychiatric disorders should be evaluated in further studies. The amygdala's value in the prediction of longitudinal memory changes in the SCD group remains questionable. Primarily in patients with MCI, memory decline over 3 years appears to be more strongly associated with volumes of hippocampus ROIs than amygdala ROIs.
Collapse
Affiliation(s)
- Laura Göschel
- Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Neurology, Charitéplatz 1, 10117 Berlin, Germany; Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, NCRC - Neuroscience Clinical Research Center, Charitéplatz 1, 10117 Berlin, Germany.
| | - Lea Kurz
- Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Neurology, Charitéplatz 1, 10117 Berlin, Germany; Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, NCRC - Neuroscience Clinical Research Center, Charitéplatz 1, 10117 Berlin, Germany
| | - Andrea Dell'Orco
- Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Neurology, Charitéplatz 1, 10117 Berlin, Germany; Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, NCRC - Neuroscience Clinical Research Center, Charitéplatz 1, 10117 Berlin, Germany; Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Neuroradiology, Charitéplatz 1, 10117 Berlin, Germany
| | - Theresa Köbe
- Deutsches Zentrum für Luft- und Raumfahrt e.V. Projektträger (DLR-PT), Berlin, Germany
| | - Peter Körtvélyessy
- Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Neurology, Charitéplatz 1, 10117 Berlin, Germany; German Center for Neurodegenerative Diseases (DZNE), site Magdeburg, Leipziger Strasse 44, 39120 Magdeburg, Germany
| | - Ariane Fillmer
- Physikalisch-Technische Bundesanstalt (PTB), Braunschweig and Berlin, Germany
| | - Semiha Aydin
- Physikalisch-Technische Bundesanstalt (PTB), Braunschweig and Berlin, Germany
| | - Layla Tabea Riemann
- Physikalisch-Technische Bundesanstalt (PTB), Braunschweig and Berlin, Germany; Institute for Applied Medical Informatics, University Hospital Hamburg-Eppendorf, Hamburg, Germany
| | - Hui Wang
- Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Neurology, Charitéplatz 1, 10117 Berlin, Germany; Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, NCRC - Neuroscience Clinical Research Center, Charitéplatz 1, 10117 Berlin, Germany; Department of Neurology and Pain Treatment, Immanuel Klinik Rüdersdorf, University Hospital of the Brandenburg Medical School Theodor Fontane, Rüdersdorf bei Berlin, Germany
| | - Bernd Ittermann
- Physikalisch-Technische Bundesanstalt (PTB), Braunschweig and Berlin, Germany
| | - Ulrike Grittner
- Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Institute of Biometry and Clinical Epidemiology, Charitéplatz 1, 10117 Berlin, Germany
| | - Agnes Flöel
- Department of Neurology, University Medicine Greifswald, Greifswald, Germany; German Center for Neurodegenerative Diseases (DZNE), Standort Rostock/Greifswald, Germany
| |
Collapse
|
4
|
Kant IMJ, de Bresser J, van Montfort SJT, Witkamp TD, Walraad B, Spies CD, Hendrikse J, van Dellen E, Slooter AJC, Winterer G, Pischon T, Boraschi D, Schneider R, N#x00FC;rnberg P, Norman Zacharias MP, Morgeli R, Olbert M, Lachmann G, Borchers F, Ofosu K, Yurek F, Wolf A, Gallinat J, Hendrikse J, Slooter A, van Dellen E, Stamatakis E, Preller J, Menon D, Moreno-Lopez L, Winzeck S, Feinkohl I, Italiani P, Melillo D, Camera GD, Krause R, Heidtke K, Kuhn S, Kronabel M, Dscietzig TB, Armbruster FP, Hafen B, Ruppert J, Bocher A, Helmschrodt A, Weyer M, Hartmann K, Diehl I, Weber S, Fillmer A, Ittermann B. Postoperative delirium is associated with grey matter brain volume loss. Brain Commun 2023; 5:fcad013. [PMID: 36819940 PMCID: PMC9933897 DOI: 10.1093/braincomms/fcad013] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2022] [Revised: 08/12/2022] [Accepted: 01/26/2023] [Indexed: 02/03/2023] Open
Abstract
Delirium is associated with long-term cognitive dysfunction and with increased brain atrophy. However, it is unclear whether these problems result from or predisposes to delirium. We aimed to investigate preoperative to postoperative brain changes, as well as the role of delirium in these changes over time. We investigated the effects of surgery and postoperative delirium with brain MRIs made before and 3 months after major elective surgery in 299 elderly patients, and an MRI with a 3 months follow-up MRI in 48 non-surgical control participants. To study the effects of surgery and delirium, we compared brain volumes, white matter hyperintensities and brain infarcts between baseline and follow-up MRIs, using multiple regression analyses adjusting for possible confounders. Within the patients group, 37 persons (12%) developed postoperative delirium. Surgical patients showed a greater decrease in grey matter volume than non-surgical control participants [linear regression: B (95% confidence interval) = -0.65% of intracranial volume (-1.01 to -0.29, P < 0.005)]. Within the surgery group, delirium was associated with a greater decrease in grey matter volume [B (95% confidence interval): -0.44% of intracranial volume (-0.82 to -0.06, P = 0.02)]. Furthermore, within the patients, delirium was associated with a non-significantly increased risk of a new postoperative brain infarct [logistic regression: odds ratio (95% confidence interval): 2.8 (0.7-11.1), P = 0.14]. Our study was the first to investigate the association between delirium and preoperative to postoperative brain volume changes, suggesting that delirium is associated with increased progression of grey matter volume loss.
Collapse
Affiliation(s)
- Ilse M J Kant
- Department of Intensive Care Medicine and University Medical Center Utrecht Brain Center, University Medical Center Utrecht, Utrecht University, Utrecht 3584 CX, The Netherlands,Department of Information Technology and Digital Innovation, Leiden University Medical Center, Leiden 2333 ZA, The Netherlands
| | - Jeroen de Bresser
- Department of Radiology, Leiden University Medical Center, Leiden 2333 ZA, The Netherlands
| | - Simone J T van Montfort
- Department of Intensive Care Medicine and University Medical Center Utrecht Brain Center, University Medical Center Utrecht, Utrecht University, Utrecht 3584 CX, The Netherlands
| | - Theodoor D Witkamp
- Department of Radiology and University Medical Center Utrecht Brain Center, University Medical Center Utrecht, Utrecht University, Utrecht 3584 CX, The Netherlands
| | - Bob Walraad
- Department of Intensive Care Medicine and University Medical Center Utrecht Brain Center, University Medical Center Utrecht, Utrecht University, Utrecht 3584 CX, The Netherlands
| | - Claudia D Spies
- Department of Anesthesiology and Operative Intensive Care Medicine (CCM, CVK), Charité – Universitätsmedizin Berlin, Berlin 10117, Germany
| | - Jeroen Hendrikse
- Department of Radiology and University Medical Center Utrecht Brain Center, University Medical Center Utrecht, Utrecht University, Utrecht 3584 CX, The Netherlands
| | - Edwin van Dellen
- Department of Intensive Care Medicine and University Medical Center Utrecht Brain Center, University Medical Center Utrecht, Utrecht University, Utrecht 3584 CX, The Netherlands,Department of Psychiatry and University Medical Center Utrecht Brain Center, University Medical Center Utrecht, Utrecht University, Utrecht 3584 CX, The Netherlands
| | - Arjen J C Slooter
- Correspondence to: Arjen Slooter Department of Intensive Care Medicine University Medical Center Utrecht Brain Center Utrecht University, Heidelberglaan 100 Utrecht 3584 CX, The Netherlands E-mail:
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
Collapse
|
5
|
Göschel L, Fillmer A, Dell'Orco A, Melin J, Aydin S, Kurz L, Riemann LT, Wang H, Ittermann B, Rujescu D, Pendrill L, Köbe T, Flöel A. Associations between the glial marker myo‐inositol measured by 7T MRS and other AD‐relevant measures. Alzheimers Dement 2022. [DOI: 10.1002/alz.069340] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Affiliation(s)
- Laura Göschel
- Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt‐Universität zu Berlin, Department of Neurology Charitéplatz 1 Berlin Germany
- Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt‐Universität zu Berlin, NeuroCure Clinical Research Center Charitéplatz 1 Berlin Germany
| | - Ariane Fillmer
- Physikalisch‐Technische Bundesanstalt (PTB) Braunschweig and Berlin Germany
| | - Andrea Dell'Orco
- Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt‐Universität zu Berlin, Department of Neurology Charitéplatz 1 Berlin Germany
- Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt‐Universität zu Berlin, NeuroCure Clinical Research Center Charitéplatz 1 Berlin Germany
- Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt‐Universität zu Berlin, Department of Neuroradiology Charitéplatz 1 Berlin Germany
| | - Jeanette Melin
- RISE, Research Institutes of Sweden, Division Safety and Transport, Measurement Science and Technology Göteborg Sweden
| | - Semiha Aydin
- Physikalisch‐Technische Bundesanstalt (PTB) Braunschweig and Berlin Germany
| | - Lea Kurz
- Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt‐Universität zu Berlin, Department of Neurology Charitéplatz 1 Berlin Germany
- Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt‐Universität zu Berlin, NeuroCure Clinical Research Center Charitéplatz 1 Berlin Germany
| | | | - Hui Wang
- Department of Neurology and pain treatment, Immanuel Klinik Rüdersdorf, University Hospital of the Brandenburg Medical School Theodor Fontane Rüdersdorf bei Berlin Germany
| | - Bernd Ittermann
- Physikalisch‐Technische Bundesanstalt (PTB) Braunschweig and Berlin Germany
| | - Dan Rujescu
- Medical University of Vienna, Department of Psychiatry Währiger Gürtel 18‐20 Vienna Austria
| | - Leslie Pendrill
- RISE, Research Institutes of Sweden, Division Safety and Transport, Measurement Science and Technology Göteborg Sweden
| | - Theresa Köbe
- German Center for Neurodegenerative Diseases (DZNE) Dresden Germany
| | - Agnes Flöel
- German Centre for Neurodegenerative Diseases (DZNE), Standort Rostock/Greifswald Greifswald Germany
- Department of Neurology, University Medicine Greifswald Greifswald Germany
| |
Collapse
|
6
|
Riemann LT, Aigner CS, Mekle R, Speck O, Rose G, Ittermann B, Schmitter S, Fillmer A. Fourier-based decomposition for simultaneous 2-voxel MRS acquisition with 2SPECIAL. Magn Reson Med 2022; 88:1978-1993. [PMID: 35906900 DOI: 10.1002/mrm.29369] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2022] [Revised: 05/17/2022] [Accepted: 05/31/2022] [Indexed: 11/06/2022]
Abstract
PURPOSE To simultaneously acquire spectroscopic signals from two MRS voxels using a multi-banded 2 spin-echo, full-intensity acquired localized (2SPECIAL) sequence, and to decompose the signal to their respective regions by a novel voxel-GRAPPA (vGRAPPA) decomposition approach for in vivo brain applications at 7 T. METHODS A wideband, uniform rate, smooth truncation (WURST) multi-banded pulse was incorporated into SPECIAL to implement 2SPECIAL for simultaneous multi-voxel spectroscopy (sMVS). To decompose the acquired data, the voxel-GRAPPA decomposition algorithm is introduced, and its performance is compared to the SENSE-based decomposition. Furthermore, the limitations of two-voxel excitation concerning the multi-banded adiabatic inversion pulse, as well as of the combined B0 shim and B1 + adjustments, are evaluated. RESULTS It was successfully shown that the 2SPECIAL sequence enables sMVS without a significant loss in SNR while reducing the total scan time by 21.6% compared to two consecutive acquisitions. The proposed voxel-GRAPPA algorithm properly reassigns the signal components to their respective origin region and shows no significant differences to the well-established SENSE-based algorithm in terms of leakage (both <10%) or Cramér-Rao lower bounds (CRLB) for in vivo applications, while not requiring the acquisition of additional sensitivity maps and thus decreasing motion sensitivity. CONCLUSION The use of 2SPECIAL in combination with the novel voxel-GRAPPA decomposition technique allows a substantial reduction of measurement time compared to the consecutive acquisition of two single voxels without a significant decrease in spectral quality or metabolite quantification accuracy and thus provides a new option for multiple-voxel applications.
Collapse
Affiliation(s)
- Layla Tabea Riemann
- Physikalisch-Technische Bundesanstalt (PTB), Braunschweig und Berlin, Germany
| | | | - Ralf Mekle
- Center for Stroke Research Berlin, Charité-Universitätsmedizin, Berlin, Germany
| | - Oliver Speck
- Biomedical Magnetic Resonance, Otto-von-Guericke University, Magdeburg, Germany.,Research Campus STIMULATE, Magdeburg, Germany
| | - Georg Rose
- Research Campus STIMULATE, Magdeburg, Germany.,Institut für Medizintechnik, Otto-von-Guericke University, Magdeburg, Germany
| | - Bernd Ittermann
- Physikalisch-Technische Bundesanstalt (PTB), Braunschweig und Berlin, Germany
| | - Sebastian Schmitter
- Physikalisch-Technische Bundesanstalt (PTB), Braunschweig und Berlin, Germany.,Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, Minnesota.,Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Ariane Fillmer
- Physikalisch-Technische Bundesanstalt (PTB), Braunschweig und Berlin, Germany
| |
Collapse
|
7
|
Quaglia M, Cano S, Fillmer A, Flöel A, Giangrande C, Göschel L, Lehmann S, Melin J, Teunissen CE. The NeuroMET project: Metrology and innovation for early diagnosis and accurate stratification of patients with neurodegenerative diseases. Alzheimers Dement 2021. [DOI: 10.1002/alz.053655] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Affiliation(s)
- Milena Quaglia
- NML at LGC Ltd Teddington United Kingdom
- LGC Limited Teddington United Kingdom
| | - Stefan Cano
- Modus Outcomes Letchworth Garden City United Kingdom
| | | | - Agnes Flöel
- NeuroCure Clinical Research Center, Charité ‐ Universitätsmedizin Berlin Berlin Germany
| | | | - Laura Göschel
- Charité‐Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt‐Universität zu Berlin, and Berlin Institute of Health, NeuroCure Clinical Research Center, Department of Neurology Berlin Germany
| | - Sylvain Lehmann
- Laboratoire de Biochimie Protéomique Clinique‐CHU Montpellier Montpellier France
| | | | - Charlotte E. Teunissen
- VU University Medical Center, Alzheimer Center VUMC, Neurocampus Amsterdam Netherlands
- Amsterdam UMC, VU University Amsterdam Netherlands
| |
Collapse
|
8
|
Prinz C, Starke L, Ramspoth TF, Kerkering J, Martos Riaño V, Paul J, Neuenschwander M, Oder A, Radetzki S, Adelhoefer S, Ramos Delgado P, Aravina M, Millward JM, Fillmer A, Paul F, Siffrin V, von Kries JP, Niendorf T, Nazaré M, Waiczies S. Pentafluorosulfanyl (SF 5) as a Superior 19F Magnetic Resonance Reporter Group: Signal Detection and Biological Activity of Teriflunomide Derivatives. ACS Sens 2021; 6:3948-3956. [PMID: 34666481 PMCID: PMC8630787 DOI: 10.1021/acssensors.1c01024] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2021] [Accepted: 09/24/2021] [Indexed: 12/30/2022]
Abstract
Fluorine (19F) magnetic resonance imaging (MRI) is severely limited by a low signal-to noise ratio (SNR), and tapping it for 19F drug detection in vivo still poses a significant challenge. However, it bears the potential for label-free theranostic imaging. Recently, we detected the fluorinated dihydroorotate dehydrogenase (DHODH) inhibitor teriflunomide (TF) noninvasively in an animal model of multiple sclerosis (MS) using 19F MR spectroscopy (MRS). In the present study, we probed distinct modifications to the CF3 group of TF to improve its SNR. This revealed SF5 as a superior alternative to the CF3 group. The value of the SF5 bioisostere as a 19F MRI reporter group within a biological or pharmacological context is by far underexplored. Here, we compared the biological and pharmacological activities of different TF derivatives and their 19F MR properties (chemical shift and relaxation times). The 19F MR SNR efficiency of three MRI methods revealed that SF5-substituted TF has the highest 19F MR SNR efficiency in combination with an ultrashort echo-time (UTE) MRI method. Chemical modifications did not reduce pharmacological or biological activity as shown in the in vitro dihydroorotate dehydrogenase enzyme and T cell proliferation assays. Instead, SF5-substituted TF showed an improved capacity to inhibit T cell proliferation, indicating better anti-inflammatory activity and its suitability as a viable bioisostere in this context. This study proposes SF5 as a novel superior 19F MR reporter group for the MS drug teriflunomide.
Collapse
Affiliation(s)
- Christian Prinz
- Berlin
Ultrahigh Field Facility (B.U.F.F.), Max
Delbrück Center for Molecular Medicine in the Helmholtz Association, Robert Rössle Straße
10, 13125 Berlin, Germany
- Experimental
and Clinical Research Center, a joint cooperation between the Charité
- Universitätsmedizin Berlin and the Max Delbrück Center
for Molecular Medicine in the Helmholtz Association, Robert Rössle Straße 10, 13125 Berlin, Germany
| | - Ludger Starke
- Berlin
Ultrahigh Field Facility (B.U.F.F.), Max
Delbrück Center for Molecular Medicine in the Helmholtz Association, Robert Rössle Straße
10, 13125 Berlin, Germany
| | - Tizian-Frank Ramspoth
- Medicinal
Chemistry, Leibniz-Institut für Molekulare
Pharmakologie (FMP), Robert Rössle Straße 10, 13125 Berlin, Germany
| | - Janis Kerkering
- Experimental
and Clinical Research Center, a joint cooperation between the Charité
- Universitätsmedizin Berlin and the Max Delbrück Center
for Molecular Medicine in the Helmholtz Association, Robert Rössle Straße 10, 13125 Berlin, Germany
| | - Vera Martos Riaño
- Medicinal
Chemistry, Leibniz-Institut für Molekulare
Pharmakologie (FMP), Robert Rössle Straße 10, 13125 Berlin, Germany
| | - Jérôme Paul
- Medicinal
Chemistry, Leibniz-Institut für Molekulare
Pharmakologie (FMP), Robert Rössle Straße 10, 13125 Berlin, Germany
| | - Martin Neuenschwander
- Screening
Unit, Leibniz-Institut für Molekulare
Pharmakologie (FMP), Robert Rössle Straße 10, 13125 Berlin, Germany
| | - Andreas Oder
- Screening
Unit, Leibniz-Institut für Molekulare
Pharmakologie (FMP), Robert Rössle Straße 10, 13125 Berlin, Germany
| | - Silke Radetzki
- Screening
Unit, Leibniz-Institut für Molekulare
Pharmakologie (FMP), Robert Rössle Straße 10, 13125 Berlin, Germany
| | - Siegfried Adelhoefer
- Berlin
Ultrahigh Field Facility (B.U.F.F.), Max
Delbrück Center for Molecular Medicine in the Helmholtz Association, Robert Rössle Straße
10, 13125 Berlin, Germany
| | - Paula Ramos Delgado
- Berlin
Ultrahigh Field Facility (B.U.F.F.), Max
Delbrück Center for Molecular Medicine in the Helmholtz Association, Robert Rössle Straße
10, 13125 Berlin, Germany
- Experimental
and Clinical Research Center, a joint cooperation between the Charité
- Universitätsmedizin Berlin and the Max Delbrück Center
for Molecular Medicine in the Helmholtz Association, Robert Rössle Straße 10, 13125 Berlin, Germany
| | - Mariya Aravina
- Berlin
Ultrahigh Field Facility (B.U.F.F.), Max
Delbrück Center for Molecular Medicine in the Helmholtz Association, Robert Rössle Straße
10, 13125 Berlin, Germany
| | - Jason M. Millward
- Berlin
Ultrahigh Field Facility (B.U.F.F.), Max
Delbrück Center for Molecular Medicine in the Helmholtz Association, Robert Rössle Straße
10, 13125 Berlin, Germany
- Experimental
and Clinical Research Center, a joint cooperation between the Charité
- Universitätsmedizin Berlin and the Max Delbrück Center
for Molecular Medicine in the Helmholtz Association, Robert Rössle Straße 10, 13125 Berlin, Germany
| | - Ariane Fillmer
- Physikalisch-Technische
Bundesanstalt (PTB), Abbestraße 2-12, 10587 Berlin, Germany
| | - Friedemann Paul
- Experimental
and Clinical Research Center, a joint cooperation between the Charité
- Universitätsmedizin Berlin and the Max Delbrück Center
for Molecular Medicine in the Helmholtz Association, Robert Rössle Straße 10, 13125 Berlin, Germany
- Charité
− Universitätsmedizin Berlin, corporate member of Freie
Universität Berlin, Humboldt-Universität zu Berlin,
and Berlin Institute of Health (BIH), Charitéplatz 1, 10117 Berlin, Germany
| | - Volker Siffrin
- Experimental
and Clinical Research Center, a joint cooperation between the Charité
- Universitätsmedizin Berlin and the Max Delbrück Center
for Molecular Medicine in the Helmholtz Association, Robert Rössle Straße 10, 13125 Berlin, Germany
| | - Jens-Peter von Kries
- Screening
Unit, Leibniz-Institut für Molekulare
Pharmakologie (FMP), Robert Rössle Straße 10, 13125 Berlin, Germany
| | - Thoralf Niendorf
- Berlin
Ultrahigh Field Facility (B.U.F.F.), Max
Delbrück Center for Molecular Medicine in the Helmholtz Association, Robert Rössle Straße
10, 13125 Berlin, Germany
- Experimental
and Clinical Research Center, a joint cooperation between the Charité
- Universitätsmedizin Berlin and the Max Delbrück Center
for Molecular Medicine in the Helmholtz Association, Robert Rössle Straße 10, 13125 Berlin, Germany
| | - Marc Nazaré
- Medicinal
Chemistry, Leibniz-Institut für Molekulare
Pharmakologie (FMP), Robert Rössle Straße 10, 13125 Berlin, Germany
| | - Sonia Waiczies
- Berlin
Ultrahigh Field Facility (B.U.F.F.), Max
Delbrück Center for Molecular Medicine in the Helmholtz Association, Robert Rössle Straße
10, 13125 Berlin, Germany
- Experimental
and Clinical Research Center, a joint cooperation between the Charité
- Universitätsmedizin Berlin and the Max Delbrück Center
for Molecular Medicine in the Helmholtz Association, Robert Rössle Straße 10, 13125 Berlin, Germany
| |
Collapse
|
9
|
Riemann LT, Aigner CS, Ellison SLR, Brühl R, Mekle R, Schmitter S, Speck O, Rose G, Ittermann B, Fillmer A. Assessment of measurement precision in single-voxel spectroscopy at 7 T: Toward minimal detectable changes of metabolite concentrations in the human brain in vivo. Magn Reson Med 2021; 87:1119-1135. [PMID: 34783376 DOI: 10.1002/mrm.29034] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2021] [Revised: 09/14/2021] [Accepted: 09/16/2021] [Indexed: 12/13/2022]
Abstract
PURPOSE To introduce a study design and statistical analysis framework to assess the repeatability, reproducibility, and minimal detectable changes (MDCs) of metabolite concentrations determined by in vivo MRS. METHODS An unbalanced nested study design was chosen to acquire in vivo MRS data within different repeatability and reproducibility scenarios. A spin-echo, full-intensity acquired localized (SPECIAL) sequence was employed at 7 T utlizing three different inversion pulses: a hyperbolic secant (HS), a gradient offset independent adiabaticity (GOIA), and a wideband, uniform rate, smooth truncation (WURST) pulse. Metabolite concentrations, Cramér-Rao lower bounds (CRLBs) and coefficients of variation (CVs) were calculated. Both Bland-Altman analysis and a restricted maximum-likelihood estimation (REML) analysis were performed to estimate the different variance contributions of the repeatability and reproducibility of the measured concentration. A Bland-Altmann analysis of the spectral shape was performed to assess the variance of the spectral shape, independent of quantification model influences. RESULTS For the used setup, minimal detectable changes of brain metabolite concentrations were found to be between 0.40 µmol/g and 2.23 µmol/g. CRLBs account for only 16 % to 74 % of the total variance of the metabolite concentrations. The application of gradient-modulated inversion pulses in SPECIAL led to slightly improved repeatability, but overall reproducibility appeared to be limited by differences in positioning, calibration, and other day-to-day variations throughout different sessions. CONCLUSION A framework is introduced to estimate the precision of metabolite concentrations obtained by MRS in vivo, and the minimal detectable changes for 13 metabolite concentrations measured at 7 T using SPECIAL are obtained.
Collapse
Affiliation(s)
| | | | | | - Rüdiger Brühl
- Physikalisch-Technische Bundesanstalt, Braunschweig und Berlin, Germany
| | - Ralf Mekle
- Center for Stroke Research Berlin, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | | | - Oliver Speck
- Biomedical Magnetic Resonance, Otto-von-Guericke University, Magdeburg, Germany.,Research Campus STIMULATE, Magdeburg, Germany
| | - Georg Rose
- Research Campus STIMULATE, Magdeburg, Germany.,Institut für Medizintechnik, Otto-von-Guericke University, Magdeburg, Germany
| | - Bernd Ittermann
- Physikalisch-Technische Bundesanstalt, Braunschweig und Berlin, Germany
| | - Ariane Fillmer
- Physikalisch-Technische Bundesanstalt, Braunschweig und Berlin, Germany
| |
Collapse
|
10
|
Hui SCN, Mikkelsen M, Zöllner HJ, Ahluwalia V, Alcauter S, Baltusis L, Barany DA, Barlow LR, Becker R, Berman JI, Berrington A, Bhattacharyya PK, Blicher JU, Bogner W, Brown MS, Calhoun VD, Castillo R, Cecil KM, Choi YB, Chu WCW, Clarke WT, Craven AR, Cuypers K, Dacko M, de la Fuente-Sandoval C, Desmond P, Domagalik A, Dumont J, Duncan NW, Dydak U, Dyke K, Edmondson DA, Ende G, Ersland L, Evans CJ, Fermin ASR, Ferretti A, Fillmer A, Gong T, Greenhouse I, Grist JT, Gu M, Harris AD, Hat K, Heba S, Heckova E, Hegarty JP, Heise KF, Honda S, Jacobson A, Jansen JFA, Jenkins CW, Johnston SJ, Juchem C, Kangarlu A, Kerr AB, Landheer K, Lange T, Lee P, Levendovszky SR, Limperopoulos C, Liu F, Lloyd W, Lythgoe DJ, Machizawa MG, MacMillan EL, Maddock RJ, Manzhurtsev AV, Martinez-Gudino ML, Miller JJ, Mirzakhanian H, Moreno-Ortega M, Mullins PG, Nakajima S, Near J, Noeske R, Nordhøy W, Oeltzschner G, Osorio-Duran R, Otaduy MCG, Pasaye EH, Peeters R, Peltier SJ, Pilatus U, Polomac N, Porges EC, Pradhan S, Prisciandaro JJ, Puts NA, Rae CD, Reyes-Madrigal F, Roberts TPL, Robertson CE, Rosenberg JT, Rotaru DG, O'Gorman Tuura RL, Saleh MG, Sandberg K, Sangill R, Schembri K, Schrantee A, Semenova NA, Singel D, Sitnikov R, Smith J, Song Y, Stark C, Stoffers D, Swinnen SP, Tain R, Tanase C, Tapper S, Tegenthoff M, Thiel T, Thioux M, Truong P, van Dijk P, Vella N, Vidyasagar R, Vovk A, Wang G, Westlye LT, Wilbur TK, Willoughby WR, Wilson M, Wittsack HJ, Woods AJ, Wu YC, Xu J, Lopez MY, Yeung DKW, Zhao Q, Zhou X, Zupan G, Edden RAE. Frequency drift in MR spectroscopy at 3T. Neuroimage 2021; 241:118430. [PMID: 34314848 PMCID: PMC8456751 DOI: 10.1016/j.neuroimage.2021.118430] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2021] [Revised: 06/18/2021] [Accepted: 07/22/2021] [Indexed: 11/17/2022] Open
Abstract
PURPOSE Heating of gradient coils and passive shim components is a common cause of instability in the B0 field, especially when gradient intensive sequences are used. The aim of the study was to set a benchmark for typical drift encountered during MR spectroscopy (MRS) to assess the need for real-time field-frequency locking on MRI scanners by comparing field drift data from a large number of sites. METHOD A standardized protocol was developed for 80 participating sites using 99 3T MR scanners from 3 major vendors. Phantom water signals were acquired before and after an EPI sequence. The protocol consisted of: minimal preparatory imaging; a short pre-fMRI PRESS; a ten-minute fMRI acquisition; and a long post-fMRI PRESS acquisition. Both pre- and post-fMRI PRESS were non-water suppressed. Real-time frequency stabilization/adjustment was switched off when appropriate. Sixty scanners repeated the protocol for a second dataset. In addition, a three-hour post-fMRI MRS acquisition was performed at one site to observe change of gradient temperature and drift rate. Spectral analysis was performed using MATLAB. Frequency drift in pre-fMRI PRESS data were compared with the first 5:20 minutes and the full 30:00 minutes of data after fMRI. Median (interquartile range) drifts were measured and showed in violin plot. Paired t-tests were performed to compare frequency drift pre- and post-fMRI. A simulated in vivo spectrum was generated using FID-A to visualize the effect of the observed frequency drifts. The simulated spectrum was convolved with the frequency trace for the most extreme cases. Impacts of frequency drifts on NAA and GABA were also simulated as a function of linear drift. Data from the repeated protocol were compared with the corresponding first dataset using Pearson's and intraclass correlation coefficients (ICC). RESULTS Of the data collected from 99 scanners, 4 were excluded due to various reasons. Thus, data from 95 scanners were ultimately analyzed. For the first 5:20 min (64 transients), median (interquartile range) drift was 0.44 (1.29) Hz before fMRI and 0.83 (1.29) Hz after. This increased to 3.15 (4.02) Hz for the full 30 min (360 transients) run. Average drift rates were 0.29 Hz/min before fMRI and 0.43 Hz/min after. Paired t-tests indicated that drift increased after fMRI, as expected (p < 0.05). Simulated spectra convolved with the frequency drift showed that the intensity of the NAA singlet was reduced by up to 26%, 44 % and 18% for GE, Philips and Siemens scanners after fMRI, respectively. ICCs indicated good agreement between datasets acquired on separate days. The single site long acquisition showed drift rate was reduced to 0.03 Hz/min approximately three hours after fMRI. DISCUSSION This study analyzed frequency drift data from 95 3T MRI scanners. Median levels of drift were relatively low (5-min average under 1 Hz), but the most extreme cases suffered from higher levels of drift. The extent of drift varied across scanners which both linear and nonlinear drifts were observed.
Collapse
Affiliation(s)
- Steve C N Hui
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA; F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Mark Mikkelsen
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA; F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Helge J Zöllner
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA; F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Vishwadeep Ahluwalia
- GSU/GT Center for Advanced Brain Imaging, Georgia Institute of Technology, Atlanta, GA USA
| | - Sarael Alcauter
- Instituto de Neurobiología, Universidad Nacional Autónoma de México, Queretaro, Mexico
| | - Laima Baltusis
- Center for Cognitive and Neurobiological Imaging, Stanford University, Stanford, CA USA
| | - Deborah A Barany
- Department of Kinesiology, University of Georgia, and Augusta University/University of Georgia Medical Partnership, Athens, GA USA
| | - Laura R Barlow
- Department of Radiology, Faculty of Medicine, The University of British Columbia, Vancouver, Canada
| | - Robert Becker
- Center for Innovative Psychiatry and Psychotherapy Research, Department Neuroimaging, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Jeffrey I Berman
- Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA USA
| | - Adam Berrington
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, Nottingham, UK
| | | | - Jakob Udby Blicher
- Center of Functionally Integrative Neuroscience, Aarhus University, Aarhus, Denmark
| | - Wolfgang Bogner
- Department of Biomedical Imaging and Image-guided Therapy, High-Field MR Center, Medical University of Vienna, Vienna, Austria
| | - Mark S Brown
- Department of Radiology, Medical Physics, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Vince D Calhoun
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, and Emory University, Atlanta, GA USA
| | - Ryan Castillo
- NeuRA Imaging, Neuroscience Research Australia, Randwick, Australia
| | - Kim M Cecil
- Department of Radiology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH USA
| | - Yeo Bi Choi
- Department of Psychological and Brain Sciences, Dartmouth College, Hanover, NH USA
| | - Winnie C W Chu
- Department of Imaging and Interventional Radiology, The Chinese University of Hong Kong, Hong Kong, China
| | - William T Clarke
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Alexander R Craven
- Department of Biological and Medical Psychology, University of Bergen, Haukeland University Hospital, Bergen, Norway
| | - Koen Cuypers
- REVAL Rehabilitation Research Institute (REVAL), Hasselt University, Diepenbeek, Belgium; Department of Movement Sciences, KU Leuven, Leuven, Belgium
| | - Michael Dacko
- Department of Radiology, Medical Physics, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Camilo de la Fuente-Sandoval
- Laboratory of Experimental Psychiatry & Neuropsychiatry Department, Instituto Nacional de Neurología y Neurocirugía, Mexico City, Mexico
| | - Patricia Desmond
- Department of Radiology, University of Melbourne/ Royal Melbourne Hospital, Melbourne, Australia
| | - Aleksandra Domagalik
- Brain Imaging Core Facility, Malopolska Centre of Biotechnology, Jagiellonian University, Kraków, Poland
| | - Julien Dumont
- Univ. Lille, CNRS, Inserm, CHU Lille, Institut Pasteur de Lille, US 41 - UMS 2014 - PLBS, F-59000 Lille, France
| | - Niall W Duncan
- Graduate Institute of Mind, Brain and Consciousness, Taipei Medical University, Taipei, Taiwan
| | - Ulrike Dydak
- School of Health Sciences, Purdue University, West Lafayette, IN USA
| | - Katherine Dyke
- School of Psychology, University of Nottingham, Nottingham, UK
| | - David A Edmondson
- Department of Radiology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH USA
| | - Gabriele Ende
- Center for Innovative Psychiatry and Psychotherapy Research, Department Neuroimaging, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Lars Ersland
- Department of Clinical Engineering, University of Bergen, Haukeland University Hospital, Bergen, Norway
| | | | - Alan S R Fermin
- Center for Brain, Mind and KANSEI Sciences Research, Hiroshima University, Hiroshima, Japan
| | - Antonio Ferretti
- Department of Neuroscience, Imaging and Clinical Sciences, University "G. d'Annunzio" of Chieti-Pescara, Chieti, Italy
| | - Ariane Fillmer
- Physikalisch-Technische Bundesanstalt (PTB), Braunschweig und Berlin, Germany
| | - Tao Gong
- Department of Imaging and Nuclear Medicine, Shandong Medical Imaging Research Institute, Shandong University, Jinan, China
| | - Ian Greenhouse
- Department of Human Physiology, University of Oregon, Eugene, OR USA
| | - James T Grist
- Department of Physiology, Anatomy, and Genetics, Oxford Centre for Magnetic Resonance / Department of Radiology, The Churchill Hospital, The University of Oxford, Oxford, UK
| | - Meng Gu
- Department of Radiology, Stanford University, Stanford, CA, USA
| | - Ashley D Harris
- Department of Radiology, University of Calgary, Calgary, Canada
| | - Katarzyna Hat
- Consciousness Lab, Institute of Psychology, Jagiellonian University, Kraków, Poland
| | - Stefanie Heba
- Department of Neurology, BG University Hospital Bergmannsheil, Bochum, Germany
| | - Eva Heckova
- Department of Biomedical Imaging and Image-guided Therapy, High-Field MR Center, Medical University of Vienna, Vienna, Austria
| | - John P Hegarty
- Department of Psychiatry & Behavioral Sciences, Stanford University, Stanford, CA, USA
| | | | - Shiori Honda
- Department of Neuropsychiatry, Keio University School of Medicine, Tokyo, Japan
| | - Aaron Jacobson
- Department of Radiology / Psychiatry, University of California San Diego, San Diego, CA USA
| | - Jacobus F A Jansen
- Department of Radiology and Nuclear Medicine, Maastricht University Medical Center, Maastricht, The Netherlands
| | | | - Stephen J Johnston
- Psychology Department / Clinical Imaging Facility, Swansea University, Swansea, UK
| | - Christoph Juchem
- Departments of Biomedical Engineering and Radiology, Columbia University, New York, NY USA
| | - Alayar Kangarlu
- Department of Psychiatry, Columbia University Irving Medical Center/New York State Psychiatric Institute, New York, NY USA
| | - Adam B Kerr
- Center for Cognitive and Neurobiological Imaging, Stanford University, Stanford, CA USA
| | - Karl Landheer
- Departments of Biomedical Engineering and Radiology, Columbia University, New York, NY USA
| | - Thomas Lange
- Department of Radiology, Medical Physics, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Phil Lee
- Department of Radiology / Hoglund Biomedical Imaging Center, University of Kansas Medical Center, Kansas City, KS USA
| | | | - Catherine Limperopoulos
- Developing Brain Institute, Diagnostic Imaging and Radiology, Children's National Hospital, Washington, DC USA
| | - Feng Liu
- Department of Psychiatry, Columbia University Irving Medical Center/New York State Psychiatric Institute, New York, NY USA
| | - William Lloyd
- Division of Informatics, Imaging & Data Sciences, University of Manchester, Manchester, UK
| | - David J Lythgoe
- Department of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Maro G Machizawa
- Center for Brain, Mind and KANSEI Sciences Research, Hiroshima University, Hiroshima, Japan
| | - Erin L MacMillan
- Department of Radiology, Faculty of Medicine, The University of British Columbia, Vancouver, Canada; Philips Canada, Markham, ON, Canada
| | - Richard J Maddock
- Department of Psychiatry and Behavioral Sciences, University of California Davis, Imaging Research Center, Davis, CA USA
| | - Andrei V Manzhurtsev
- Department of Radiology, Clinical and Research Institute of Emergency Pediatric Surgery and Trauma, Moscow, Russia; Emanuel Institute of Biochemical Physics of the Russian Academy of Sciences, Moscow, Russia
| | - María L Martinez-Gudino
- Departamento de Imágenes Cerebrales, Instituto Nacional de Psiquiatría Ramón de la Fuente Muñiz, Mexico City, Mexico
| | - Jack J Miller
- Department of Physics, University of Oxford, Oxford, UK; The MR Research Centre & The PET Research Centre, Aarhus University, Aarhus, DK
| | - Heline Mirzakhanian
- Department of Radiology / Psychiatry, University of California San Diego, San Diego, CA USA
| | - Marta Moreno-Ortega
- Department of Psychiatry, Columbia University Irving Medical Center/New York State Psychiatric Institute, New York, NY USA
| | - Paul G Mullins
- Bangor Imaging Unit, Department of Psychology, Bangor University, Bangor, Wales, UK
| | - Shinichiro Nakajima
- Department of Neuropsychiatry, Keio University School of Medicine, Tokyo, Japan
| | - Jamie Near
- Douglas Mental Health University Institute and Department of Psychiatry, McGill University, Montreal, Canada
| | | | - Wibeke Nordhøy
- NORMENT, Division of Mental Health and Addiction and Department of Diagnostic Physics, Division of Radiology and Nuclear Medicine, Oslo University Hospital / Department of Psychology, University of Oslo, Oslo, Norway
| | - Georg Oeltzschner
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA; F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Raul Osorio-Duran
- Departamento de Imágenes Cerebrales, Instituto Nacional de Psiquiatría Ramón de la Fuente Muñiz, Mexico City, Mexico
| | - Maria C G Otaduy
- LIM44, Instituto e Departamento de Radiologia, Faculdade de Medicina, Universidade de Sao Paulo, Sao Paulo, SP, Brazil
| | - Erick H Pasaye
- Instituto de Neurobiología, Universidad Nacional Autónoma de México, Queretaro, Mexico
| | - Ronald Peeters
- Department of Imaging & Pathology, Department of Radiology, University Hospitals Leuven, KU Leuven, Leuven, Belgium
| | - Scott J Peltier
- Functional MRI Laboratory, University of Michigan, Ann Arbor, MI USA
| | - Ulrich Pilatus
- Institute of Neuroradiology, Goethe-University Frankfurt, Frankfurt, Germany
| | - Nenad Polomac
- Institute of Neuroradiology, Goethe-University Frankfurt, Frankfurt, Germany
| | - Eric C Porges
- Center for Cognitive Aging and Memory, McKnight Brain Institute, Department of Clinical and Health Psychology, College of Public Health and Health Professions. Department of Neuroscience, College of Medicine, University of Florida, Gainesville, USA
| | - Subechhya Pradhan
- Developing Brain Institute, Diagnostic Imaging and Radiology, Children's National Hospital, Washington, DC USA
| | - James Joseph Prisciandaro
- Department of Psychiatry and Behavioral Sciences, Medical University of South Carolina, Charleston, SC USA
| | - Nicolaas A Puts
- Department of Forensic & Neurodevelopmental Sciences, Sackler Institute for Translational Neurodevelopment, King's College London, London, UK
| | - Caroline D Rae
- NeuRA Imaging, Neuroscience Research Australia, Randwick, Australia
| | - Francisco Reyes-Madrigal
- Laboratory of Experimental Psychiatry & Neuropsychiatry Department, Instituto Nacional de Neurología y Neurocirugía, Mexico City, Mexico
| | - Timothy P L Roberts
- Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA USA
| | - Caroline E Robertson
- Department of Psychological and Brain Sciences, Dartmouth College, Hanover, NH USA
| | - Jens T Rosenberg
- McKnight Brain Institute, AMRIS, University of Florida, Gainesville, FL USA
| | - Diana-Georgiana Rotaru
- Department of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Ruth L O'Gorman Tuura
- Center for MR Research, University Children's Hospital, Zurich, University of Zurich, Switzerland
| | - Muhammad G Saleh
- Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, Baltimore, USA
| | - Kristian Sandberg
- Center of Functionally Integrative Neuroscience, Aarhus University, Aarhus, Denmark
| | - Ryan Sangill
- Center of Functionally Integrative Neuroscience, Aarhus University, Aarhus, Denmark
| | | | - Anouk Schrantee
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Center, University of Amsterdam, Amsterdam, The Netherlands
| | - Natalia A Semenova
- Department of Radiology, Clinical and Research Institute of Emergency Pediatric Surgery and Trauma, Moscow, Russia; Emanuel Institute of Biochemical Physics of the Russian Academy of Sciences, Moscow, Russia
| | - Debra Singel
- Department of Psychiatry, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Rouslan Sitnikov
- Clinical Neuroscience, MRI Centre, Karolinska Institute, Stockholm, Sweden
| | - Jolinda Smith
- Lewis Center for Neuroimaging, University of Oregon, Eugene, OR USA
| | - Yulu Song
- Department of Imaging and Nuclear Medicine, Shandong Medical Imaging Research Institute, Shandong University, Jinan, China
| | - Craig Stark
- Department of Neurobiology and Behavior, Facility for Imaging and Brain Research (FIBRE) & Campus Center for Neuroimaging (CCNI), School of Biological Sciences, University of California, Irvine, Irvine, CA USA
| | - Diederick Stoffers
- Spinoza Centre for Neuroimaging, Royal Netherlands Academy of Arts and Sciences, Amsterdam, The Netherlands
| | | | - Rongwen Tain
- Department of Neurobiology and Behavior, Facility for Imaging and Brain Research (FIBRE) & Campus Center for Neuroimaging (CCNI), School of Biological Sciences, University of California, Irvine, Irvine, CA USA
| | - Costin Tanase
- Department of Psychiatry and Behavioral Sciences, University of California Davis, Imaging Research Center, Davis, CA USA
| | - Sofie Tapper
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA; F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Martin Tegenthoff
- Department of Neurology, BG University Hospital Bergmannsheil, Bochum, Germany
| | - Thomas Thiel
- Institute of Clinical Neuroscience and Medical Psychology, University Dusseldorf, Medical Faculty, Düsseldorf, Germany
| | - Marc Thioux
- Department of Otorhinolaryngology, Head and Neck Surgery, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Peter Truong
- Brain Health Imaging Centre, Centre for Addiction and Mental Health, Toronto, Canada
| | - Pim van Dijk
- Department of Otorhinolaryngology, Head and Neck Surgery, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Nolan Vella
- Medical Physics, Mater Dei Hospital, Imsida, Malta
| | - Rishma Vidyasagar
- Melbourne Dementia Research Centre, Florey Institute of Neurosciences and Mental Health, Melbourne, Australia
| | - Andrej Vovk
- Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
| | - Guangbin Wang
- Department of Imaging and Nuclear Medicine, Shandong Medical Imaging Research Institute, Shandong University, Jinan, China
| | - Lars T Westlye
- NORMENT, Division of Mental Health and Addiction and Department of Diagnostic Physics, Division of Radiology and Nuclear Medicine, Oslo University Hospital / Department of Psychology, University of Oslo, Oslo, Norway
| | - Timothy K Wilbur
- Department of Radiology, University of Washington, Seattle, WA USA
| | - William R Willoughby
- Department of Radiology, University of Alabama at Birmingham, Birmingham, AL USA
| | - Martin Wilson
- Centre for Human Brain Health and School of Psychology, University of Birmingham, Birmingham, UK
| | - Hans-Jörg Wittsack
- Department of Diagnostic and Interventional Radiology, University Düsseldorf, Medical Faculty, Düsseldorf, Germany
| | - Adam J Woods
- Center for Cognitive Aging and Memory, McKnight Brain Institute, Department of Clinical and Health Psychology, College of Public Health and Health Professions. Department of Neuroscience, College of Medicine, University of Florida, Gainesville, USA
| | - Yen-Chien Wu
- Department of Radiology, TMU-Shuang Ho Hospital, New Taipei City, Taiwan
| | - Junqian Xu
- Department of Radiology and Psychiatry, Baylor College of Medicine, Houston, USA
| | | | - David K W Yeung
- Department of Imaging and Interventional Radiology, The Chinese University of Hong Kong, Hong Kong, China
| | - Qun Zhao
- Bioimaging Research Center, Department of Physics and Astronomy, University of Georgia, Athens, GA USA
| | - Xiaopeng Zhou
- School of Health Sciences, Purdue University, West Lafayette, IN USA
| | - Gasper Zupan
- Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
| | - Richard A E Edden
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA; F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA.
| |
Collapse
|
11
|
Prinz C, Starke L, Millward JM, Fillmer A, Delgado PR, Waiczies H, Pohlmann A, Rothe M, Nazaré M, Paul F, Niendorf T, Waiczies S. In vivo detection of teriflunomide-derived fluorine signal during neuroinflammation using fluorine MR spectroscopy. Theranostics 2021; 11:2490-2504. [PMID: 33456555 PMCID: PMC7806491 DOI: 10.7150/thno.47130] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2020] [Accepted: 11/17/2020] [Indexed: 12/12/2022] Open
Abstract
Background: Magnetic resonance imaging (MRI) is indispensable for diagnosing neurological conditions such as multiple sclerosis (MS). MRI also supports decisions regarding the choice of disease-modifying drugs (DMDs). Determining in vivo tissue concentrations of DMDs has the potential to become an essential clinical tool for therapeutic drug monitoring (TDM). The aim here was to examine the feasibility of fluorine-19 (19F) MR methods to detect the fluorinated DMD teriflunomide (TF) during normal and pathological conditions. Methods: We used 19F MR spectroscopy to detect TF in the experimental autoimmune encephalomyelitis (EAE) mouse model of multiple sclerosis (MS) in vivo. Prior to the in vivo investigations we characterized the MR properties of TF in vitro. We studied the impact of pH and protein binding as well as MR contrast agents. Results: We could detect TF in vivo and could follow the 19F MR signal over different time points of disease. We quantified TF concentrations in different tissues using HPLC/MS and showed a significant correlation between ex vivo TF levels in serum and the ex vivo19F MR signal. Conclusion: This study demonstrates the feasibility of 19F MR methods to detect TF during neuroinflammation in vivo. It also highlights the need for further technological developments in this field. The ultimate goal is to add 19F MR protocols to conventional 1H MRI protocols in clinical practice to guide therapy decisions.
Collapse
|
12
|
Xavier A, Arteaga de Castro C, Andia ME, Luijten PR, Klomp DW, Fillmer A, Prompers JJ. Metabolite cycled liver 1 H MRS on a 7 T parallel transmit system. NMR Biomed 2020; 33:e4343. [PMID: 32515151 PMCID: PMC7379278 DOI: 10.1002/nbm.4343] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/11/2019] [Revised: 05/08/2020] [Accepted: 05/12/2020] [Indexed: 05/03/2023]
Abstract
INTRODUCTION Single-voxel 1 H MRS in body applications often suffers from respiratory and other motion induced phase and frequency shifts, which lead to incoherent averaging and hence to suboptimal results. METHODS Here we show the application of metabolite cycling (MC) for liver STEAM-localized 1 H MRS on a 7 T parallel transmit system, using eight transmit-receive fractionated dipole antennas with 16 additional, integrated receive loops. MC-STEAM measurements were made in six healthy, lean subjects and compared with STEAM measurements using VAPOR water suppression. Measurements were performed during free breathing and during synchronized breathing, for which the subjects did breathe in between the MRS acquisitions. Both intra-session repeatability and inter-session reproducibility of liver lipid quantification with MC-STEAM and VAPOR-STEAM were determined. RESULTS The preserved water signal in MC-STEAM allowed for robust phase and frequency correction of individual acquisitions before averaging, which resulted in in vivo liver spectra that were of equal quality when measurements were made with free breathing or synchronized breathing. Intra-session repeatability and inter-session reproducibility of liver lipid quantification were better for MC-STEAM than for VAPOR-STEAM. This may also be explained by the more robust phase and frequency correction of the individual MC-STEAM acquisitions as compared with the VAPOR-STEAM acquisitions, for which the low-signal-to-noise ratio lipid signals had to be used for the corrections. CONCLUSION Non-water-suppressed MC-STEAM on a 7 T system with parallel transmit is a promising approach for 1 H MRS applications in the body that are affected by motion, such as in the liver, and yields better repeatability and reproducibility compared with water-suppressed measurements.
Collapse
Affiliation(s)
- Aline Xavier
- Department of Radiology, Imaging DivisionUniversity Medical Center UtrechtUtrechtThe Netherlands
- Biomedical Imaging Center, Pontificia Universidad Católica de ChileSantiagoChile
- Millennium Nucleus for Cardiovascular Magnetic ResonanceSantiagoChile
| | | | - Marcelo E. Andia
- Biomedical Imaging Center, Pontificia Universidad Católica de ChileSantiagoChile
- Millennium Nucleus for Cardiovascular Magnetic ResonanceSantiagoChile
| | - Peter R. Luijten
- Department of Radiology, Imaging DivisionUniversity Medical Center UtrechtUtrechtThe Netherlands
| | - Dennis W. Klomp
- Department of Radiology, Imaging DivisionUniversity Medical Center UtrechtUtrechtThe Netherlands
| | - Ariane Fillmer
- Department of Radiology, Imaging DivisionUniversity Medical Center UtrechtUtrechtThe Netherlands
- Physikalisch‐Technische Bundesanstalt (PTB)BerlinGermany
| | - Jeanine J. Prompers
- Department of Radiology, Imaging DivisionUniversity Medical Center UtrechtUtrechtThe Netherlands
| |
Collapse
|
13
|
Düzel E, Acosta-Cabronero J, Berron D, Biessels GJ, Björkman-Burtscher I, Bottlaender M, Bowtell R, Buchem MV, Cardenas-Blanco A, Boumezbeur F, Chan D, Clare S, Costagli M, de Rochefort L, Fillmer A, Gowland P, Hansson O, Hendrikse J, Kraff O, Ladd ME, Ronen I, Petersen E, Rowe JB, Siebner H, Stoecker T, Straub S, Tosetti M, Uludag K, Vignaud A, Zwanenburg J, Speck O. European Ultrahigh-Field Imaging Network for Neurodegenerative Diseases (EUFIND). Alzheimers Dement (Amst) 2019; 11:538-549. [PMID: 31388558 PMCID: PMC6675944 DOI: 10.1016/j.dadm.2019.04.010] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Introduction The goal of European Ultrahigh-Field Imaging Network in Neurodegenerative Diseases (EUFIND) is to identify opportunities and challenges of 7 Tesla (7T) MRI for clinical and research applications in neurodegeneration. EUFIND comprises 22 European and one US site, including over 50 MRI and dementia experts as well as neuroscientists. Methods EUFIND combined consensus workshops and data sharing for multisite analysis, focusing on 7 core topics: clinical applications/clinical research, highest resolution anatomy, functional imaging, vascular systems/vascular pathology, iron mapping and neuropathology detection, spectroscopy, and quality assurance. Across these topics, EUFIND considered standard operating procedures, safety, and multivendor harmonization. Results The clinical and research opportunities and challenges of 7T MRI in each subtopic are set out as a roadmap. Specific MRI sequences for each subtopic were implemented in a pilot study presented in this report. Results show that a large multisite 7T imaging network with highly advanced and harmonized imaging sequences is feasible and may enable future multicentre ultrahigh-field MRI studies and clinical trials. Discussion The EUFIND network can be a major driver for advancing clinical neuroimaging research using 7T and for identifying use-cases for clinical applications in neurodegeneration.
Collapse
Affiliation(s)
- Emrah Düzel
- Institute of Cognitive Neurology and Dementia Research, Otto-von-Guericke University Magdeburg, Magdeburg, Germany.,German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Magdeburg, Germany.,Institute of Cognitive Neuroscience, University College London, London, UK.,Center for Behavioral Brain Science, Magdeburg, Germany
| | - Julio Acosta-Cabronero
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Magdeburg, Germany.,Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - David Berron
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Magdeburg, Germany.,7Lund University BioImaging Center, Lund University, Lund, Sweden
| | - Geert Jan Biessels
- Department of Neurology, UMC Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Isabella Björkman-Burtscher
- 7Lund University BioImaging Center, Lund University, Lund, Sweden.,Departement of Radiology, Sahlgrenska Akademy, University of Gothenburg, Gothenburg, Sweden
| | | | - Richard Bowtell
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, Nottingham, UK
| | - Mark V Buchem
- Department of Radiology, University Medical Center Leiden, Leiden, The Netherlands
| | - Arturo Cardenas-Blanco
- Institute of Cognitive Neurology and Dementia Research, Otto-von-Guericke University Magdeburg, Magdeburg, Germany.,German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Magdeburg, Germany
| | - Fawzi Boumezbeur
- NeuroSpin, CEA & Université Paris-Saclay, Gif-Sur-Yvette, France
| | - Dennis Chan
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | - Stuart Clare
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK
| | - Mauro Costagli
- Imago 7 Research Foundation, Pisa, Italy.,Laboratory of Medical Physics and Magnetic Resonance, IRCCS Stella Maris, Pisa, Italy
| | - Ludovic de Rochefort
- Center for Magnetic Resonance in Biology and Medicine (UMR 7339), CRMBM, CNRS - Aix Marseille Université, Marseille, France
| | - Ariane Fillmer
- Physikalisch-Technische Bundesanstalt (PTB), Berlin, Germany
| | - Penny Gowland
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, Nottingham, UK
| | - Oskar Hansson
- 7Lund University BioImaging Center, Lund University, Lund, Sweden.,Memory Clinic, Skåne University Hospital, Malmö, Sweden
| | - Jeroen Hendrikse
- Department of Neurology, UMC Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Oliver Kraff
- Erwin L. Hahn Institute for Magnetic Resonance Imaging, University of Duisburg-Essen, Essen, Germany
| | - Mark E Ladd
- Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany.,Faculty of Physics and Astronomy and Faculty of Medicine, University of Heidelberg, Heidelberg, Germany
| | - Itamar Ronen
- Department of Radiology, University Medical Center Leiden, Leiden, The Netherlands
| | - Esben Petersen
- Danish Center for Magnetic Resonance, Copenhagen University Hospital Hvidovre, Hvidovre, Denmark
| | - James B Rowe
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | - Hartwig Siebner
- Danish Center for Magnetic Resonance, Copenhagen University Hospital Hvidovre, Hvidovre, Denmark.,Department of Neurology, Copenhagen University Hospital Bispebjerg, Copenhagen, Denmark
| | - Tony Stoecker
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
| | - Sina Straub
- Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Michela Tosetti
- Imago 7 Research Foundation, Pisa, Italy.,Laboratory of Medical Physics and Magnetic Resonance, IRCCS Stella Maris, Pisa, Italy
| | - Kamil Uludag
- Center for Neuroscience Imaging Research, Institute for Basic Science and Department of Biomedical Engineering, Sungkyunkwan University, Suwon, Republic of Korea.,Techna Institute & Koerner Scientist in MR Imaging, University Health Network, Toronto, Ontario, Canada
| | | | - Jaco Zwanenburg
- Department of Neurology, UMC Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Oliver Speck
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Magdeburg, Germany.,Center for Behavioral Brain Science, Magdeburg, Germany.,Biomedical Magnetic Resonance, Otto-von-Guericke University, Magdeburg, Germany.,Leibniz-Institute for Neurobiology (LIN), Magdeburg, Germany
| |
Collapse
|
14
|
Göschel L, Köbe T, Wang H, Aydin S, Ittermann B, Fillmer A, Flöel A. P3-400: MYOINOSITOL CONCENTRATION AND VOLUME OF THE POSTERIOR CINGULATE CORTEX ACROSS THE AD CONTINUUM MEASURED BY 7T MRI/MRS. Alzheimers Dement 2019. [DOI: 10.1016/j.jalz.2019.06.3433] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Affiliation(s)
- Laura Göschel
- Charité - Universitätsmedizin Berlin; Corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin; Berlin Germany
- Berlin Institute of Health; NeuroCure Clinical Research Center, Department of Neurology; Berlin Germany
| | - Theresa Köbe
- Charité - Universitätsmedizin Berlin; Corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin; Berlin Germany
- Centre for Studies on Prevention of Alzheimer's disease (StoP-AD Centre); Douglas Mental Health Institute; Montreal QC Canada
- McGill University; Montreal QC Canada
| | - Hui Wang
- Charité - Universitätsmedizin Berlin; Corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin; Berlin Germany
| | - Semiha Aydin
- Physikalisch-Technische Bundesanstalt; Berlin Germany
| | | | | | - Agnes Flöel
- University Medicine Greifswald; Greifswald Germany
| |
Collapse
|
15
|
Quaglia M, Cano S, Delatour V, Divieto C, Fillmer A, Goeschel L, Lehmann S, Melin J, Pang S, Verona G. Innovative measurements for improved diagnosis and management of neurodegenerative diseases. Clin Chim Acta 2019. [DOI: 10.1016/j.cca.2019.03.1267] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
|
16
|
Göschel L, Köbe T, Wang H, Fillmer A, Aydin S, Bernd I, Flöel A. P79. The effect of cognitive reserve in a subcohort of the EMPIR project NeuroMet ‘Innovative measurements for improved diagnosis and management of neurodegenerative diseases’. Clin Neurophysiol 2018. [DOI: 10.1016/j.clinph.2018.04.711] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
|
17
|
Köbe T, Wang H, Göschel L, Aydin S, Ittermann B, Flöel A, Fillmer A. P3‐442: CEREBRAL GABA, RESTING‐STATE FUNCTIONAL CONNECTIVITY AND MEMORY FUNCTION IN ALZHEIMER'S DISEASE. Alzheimers Dement 2018. [DOI: 10.1016/j.jalz.2018.06.1805] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
- Theresa Köbe
- Charité–Universitätsmedizin Berlin (corporate member of Freie Universität Berlin, Humboldt‐Universität zu Berlin, and Berlin Institute of Health)NeuroCure Clinical Research Center, Department of NeurologyBerlinGermany
| | - Hui Wang
- Charité–Universitätsmedizin Berlin (corporate member of Freie Universität Berlin, Humboldt‐Universität zu Berlin, and Berlin Institute of Health)NeuroCure Clinical Research Center, Department of NeurologyBerlinGermany
| | - Laura Göschel
- Charité–Universitätsmedizin Berlin (corporate member of Freie Universität Berlin, Humboldt‐Universität zu Berlin, and Berlin Institute of Health)NeuroCure Clinical Research Center, Department of NeurologyBerlinGermany
| | - Semiha Aydin
- Physikalisch-Technische BundesanstaltBerlinGermany
| | | | - Agnes Flöel
- Universitätsmedizin Greifswald-Department of NeurologyGreifswaldGermany
| | | |
Collapse
|
18
|
Quaglia M, Bellotti V, Cano S, Cryar A, Deane K, Divieto C, Fillmer A, Giangrande C, Köbe T, Lehmann S, Melin J, Pang S, Parkes H, Pendrill L. P2‐233: BETTER MEASUREMENT FOR IMPROVED DIAGNOSIS AND MANAGEMENT OF ALZHEIMER'S DISEASE: UPDATE ON THE EMPIR NEUROMET PROJECT. Alzheimers Dement 2018. [DOI: 10.1016/j.jalz.2018.06.920] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Affiliation(s)
| | | | - Stefan Cano
- Modus OutcomesLetchworth Garden CityUnited Kingdom
| | | | | | - Carla Divieto
- Istituto Nazionale di Ricerca MetrologicaTorinoItaly
| | | | | | - Theresa Köbe
- Charité – Universitätsmedizin Berlin
- Humboldt‐UniversitätBerlin
- Berlin Institute of HealthNeuroCure Clinical Research Center, Department of NeurologyBerlinGermany
| | | | | | | | | | | |
Collapse
|
19
|
Fillmer A, Hock A, Cameron D, Henning A. Non-Water-Suppressed 1H MR Spectroscopy with Orientational Prior Knowledge Shows Potential for Separating Intra- and Extramyocellular Lipid Signals in Human Myocardium. Sci Rep 2017; 7:16898. [PMID: 29203776 PMCID: PMC5714998 DOI: 10.1038/s41598-017-16318-0] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2017] [Accepted: 11/09/2017] [Indexed: 11/09/2022] Open
Abstract
Conditions such as type II diabetes are linked with elevated lipid levels in the heart, and significantly increased risk of heart failure; however, metabolic processes underlying the development of cardiac disease in type II diabetes are not fully understood. Here we present a non-invasive method for in vivo investigation of cardiac lipid metabolism: namely, IVS-McPRESS. This technique uses metabolite-cycled, non-water suppressed 1H cardiac magnetic resonance spectroscopy with prospective and retrospective motion correction. High-quality IVS-McPRESS data acquired from healthy volunteers allowed us to investigate the frequency shift of extramyocellular lipid signals, which depends on the myocardial fibre orientation. Assuming consistent voxel positioning relative to myofibres, the myofibre angle with the magnetic field was derived from the voxel orientation. For separation and individual analysis of intra- and extramyocellular lipid signals, the angle myocardial fibres in the spectroscopy voxel take with the magnetic field should be within ±24.5°. Metabolite and lipid concentrations were analysed with respect to BMI. Significant correlations between BMI and unsaturated fatty acids in intramyocellular lipids, and methylene groups in extramyocellular lipids were found. The proposed IVS-McPRESS technique enables non-invasive investigation of cardiac lipid metabolism and may thus be a useful tool to study healthy and pathological conditions.
Collapse
Affiliation(s)
- Ariane Fillmer
- Institute for Biomedical Engineering, University and ETH Zurich, Gloriastr. 35, 8092, Zurich, Switzerland.
- Physikalisch-Technische Bundesanstalt (PTB), Abbestr. 2-12, 10587, Berlin, Germany.
| | - Andreas Hock
- Institute for Biomedical Engineering, University and ETH Zurich, Gloriastr. 35, 8092, Zurich, Switzerland
- Department of Psychiatry, Psychotherapy and Psychosomatics, Hospital of Psychiatry, University of Zurich, Lenggstr. 31, 8032, Zurich, Switzerland
| | - Donnie Cameron
- Norwich Medical School, University of East Anglia, Norwich, NR4 7UQ, UK
- National Institute on Aging, National Institutes of Health, MedStar Harbor Hospital, 3001 South Hanover Street, Baltimore, MD21225, Maryland, USA
| | - Anke Henning
- Institute for Biomedical Engineering, University and ETH Zurich, Gloriastr. 35, 8092, Zurich, Switzerland
- Max Planck Institute for Biological Cybernetics, Max Planck Ring 11, 72076, Tuebingen, Germany
| |
Collapse
|
20
|
Nassirpour S, Chang P, Fillmer A, Henning A. A comparison of optimization algorithms for localized in vivo B 0 shimming. Magn Reson Med 2017; 79:1145-1156. [PMID: 28543722 DOI: 10.1002/mrm.26758] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2016] [Revised: 04/05/2017] [Accepted: 04/29/2017] [Indexed: 01/06/2023]
Abstract
PURPOSE To compare several different optimization algorithms currently used for localized in vivo B0 shimming, and to introduce a novel, fast, and robust constrained regularized algorithm (ConsTru) for this purpose. METHODS Ten different optimization algorithms (including samples from both generic and dedicated least-squares solvers, and a novel constrained regularized inversion method) were implemented and compared for shimming in five different shimming volumes on 66 in vivo data sets from both 7 T and 9.4 T. The best algorithm was chosen to perform single-voxel spectroscopy at 9.4 T in the frontal cortex of the brain on 10 volunteers. RESULTS The results of the performance tests proved that the shimming algorithm is prone to unstable solutions if it depends on the value of a starting point, and is not regularized to handle ill-conditioned problems. The ConsTru algorithm proved to be the most robust, fast, and efficient algorithm among all of the chosen algorithms. It enabled acquisition of spectra of reproducible high quality in the frontal cortex at 9.4 T. CONCLUSIONS For localized in vivo B0 shimming, the use of a dedicated linear least-squares solver instead of a generic nonlinear one is highly recommended. Among all of the linear solvers, the constrained regularized method (ConsTru) was found to be both fast and most robust. Magn Reson Med 79:1145-1156, 2018. © 2017 International Society for Magnetic Resonance in Medicine.
Collapse
Affiliation(s)
- Sahar Nassirpour
- Max Planck Institute for Biological Cybernetics, Tuebingen, Germany.,IMPRS for Cognitive and Systems Neuroscience, Eberhard-Karls University of Tuebingen, Germany
| | - Paul Chang
- Max Planck Institute for Biological Cybernetics, Tuebingen, Germany.,IMPRS for Cognitive and Systems Neuroscience, Eberhard-Karls University of Tuebingen, Germany
| | | | - Anke Henning
- Max Planck Institute for Biological Cybernetics, Tuebingen, Germany.,Institute for Biomedical Engineering, UZH and ETH Zürich, Zürich, Switzerland
| |
Collapse
|
21
|
Kirchner T, Fillmer A, Henning A. Mechanisms of SNR and line shape improvement by B 0 correction in overdiscrete MRSI reconstruction. Magn Reson Med 2016; 77:44-56. [PMID: 26860614 DOI: 10.1002/mrm.26118] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2015] [Revised: 11/19/2015] [Accepted: 12/15/2015] [Indexed: 11/09/2022]
Abstract
PURPOSE Inhomogeneities of the main magnetic field cause line broadening and location-dependent frequency shifts in brain MRSI. These are often visible despite advanced B0 shimming. The purpose of this work is to propose an advanced B0 correction method that can easily be applied during postprocessing. METHODS A target-driven overdiscrete reconstruction method previously introduced for MRSI is modified by dividing it into two steps. In a first step, an intermediate spectroscopic image with arbitrarily high resolution is generated, on which B0 correction is performed as an additional processing step based on an additionally acquired B0 map. This frequency-aligns metabolite peaks and destroys noise correlations between neighboring subvoxels. Second, the voxel is shaped by application of the spatial response target. The method was tested with simulated spectroscopic imaging data as well as in a series of MRSI data sets obtained from four healthy volunteers at 7T. RESULTS A systematic gain in spectral signal-to-noise ratio is achieved, due to spatial averaging now occurring over peak aligned and noise decorrelated subvoxel spectra. At the same time, metabolite peak line widths are reduced. CONCLUSION In the presence of B0 inhomogeneities across the field of view, the proposed method offers the potential to improve spectral quality with only a minimal additional effort during acquisition. Magn Reson Med 77:44-56, 2017. © 2015 Wiley Periodicals, Inc.
Collapse
Affiliation(s)
- Thomas Kirchner
- Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland
| | - Ariane Fillmer
- Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland
| | - Anke Henning
- Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland.,Max Planck Institute for Biological Cybernetics, Tuebingen, Germany
| |
Collapse
|
22
|
Fillmer A, Vannesjo SJ, Pavan M, Scheidegger M, Pruessmann KP, Henning A. Fast iterative pre-emphasis calibration method enabling third-order dynamic shim updated fMRI. Magn Reson Med 2015; 75:1119-31. [PMID: 25950147 DOI: 10.1002/mrm.25695] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2014] [Revised: 01/27/2015] [Accepted: 02/24/2015] [Indexed: 11/06/2022]
Abstract
PURPOSE To calibrate a pre-emphasis to sufficiently compensate eddy currents for application of dynamic shim updating to fMRI without extension of scan times. METHODS Eddy current effects induced into all shim terms up to third-order were characterized by spatiotemporal field monitoring, using a third-order field camera. Pre-emphasis settings were derived from the measurements and iteratively evaluated and refined. The calibrated pre-emphasis was applied to slice-wise dynamic shim updating in combination with a dynamic excitation frequency (F0) determination and a slice-wise B0 optimization routine for in vivo echo planar imaging and resting-state functional MRI. RESULTS The described method for pre-emphasis calibration led to settling times of remaining eddy current effects below 2 ms, allowing for the application of dynamic shim updating to fMRI without extension of scan times or induction of eddy current related artifacts. A dynamic F0 determination compensates frequency shifts induced by the superposition of different shim fields, and therefore, prevents an image shift within the field of view. Hardware limitations necessitate the reduction of the maximum applicable B0 shim field amplitudes and restrict the shim performance. CONCLUSION The proposed method enables accurate pre-emphasis calibration, and therefore, the application of dynamic shim updating to fMRI.
Collapse
Affiliation(s)
- Ariane Fillmer
- Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland
| | | | - Matteo Pavan
- Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland
| | - Milan Scheidegger
- Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland.,Clinic of Affective Disorders and General Psychiatry, University Hospital of Psychiatry Zurich, Zurich, Switzerland
| | - Klaas Paul Pruessmann
- Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland
| | - Anke Henning
- Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland.,Max Planck Institute for Biological Cybernetics, Tuebingen, Germany
| |
Collapse
|
23
|
Fillmer A, Kirchner T, Cameron D, Henning A. Constrained image-based B0 shimming accounting for "local minimum traps" in the optimization and field inhomogeneities outside the region of interest. Magn Reson Med 2014; 73:1370-80. [PMID: 24715495 DOI: 10.1002/mrm.25248] [Citation(s) in RCA: 37] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2013] [Revised: 03/17/2014] [Accepted: 03/19/2014] [Indexed: 01/09/2023]
Abstract
PURPOSE To improve B0 shimming for applications in high- and ultrahigh-field magnetic resonance imaging and magnetic resonance spectroscopy. METHODS An existing image-based constrained B0 shimming algorithm was enhanced using two techniques: (1) A region of less interest was introduced to control B0 field inhomogeneities in the vicinity of the region of interest; (2) multiple sets of starting values were used for the fitting routine, to avoid "getting trapped" in a local minimum of the optimization function. The influence of constraints during the fitting procedure, due to hardware limitations, on the B0 shim result was investigated. The performance of this algorithm was compared to other B0 shim algorithms for typical shim problems in head and body applications at 3T and 7T. RESULTS Utilization of a weighted region of less interest lead to a significant gain in B0 homogeneity adjacent to the region of interest. The loss of B0 quality due to the enlarged total shim volume within the region of interest remained minimal, allowing for improved artifact reduction in magnetic resonance spectroscopic imaging. Multiple sets of starting values and consideration of shim field constraints led to an additional gain in B0 shim quality. CONCLUSION The proposed algorithm allows for more flexible control of B0 inhomogeneities and, hence, enables gains in image and spectral quality for MR applications. RO1AR050597
Collapse
Affiliation(s)
- Ariane Fillmer
- Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland
| | | | | | | |
Collapse
|
24
|
Kirchner T, Fillmer A, Tsao J, Pruessmann KP, Henning A. Reduction of voxel bleeding in highly accelerated parallel (1) H MRSI by direct control of the spatial response function. Magn Reson Med 2014; 73:469-80. [PMID: 24585512 DOI: 10.1002/mrm.25185] [Citation(s) in RCA: 29] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2013] [Revised: 01/24/2014] [Accepted: 01/27/2014] [Indexed: 11/08/2022]
Abstract
PURPOSE To substantially improve spatial localization in magnetic resonance spectroscopic imaging (MRSI) accelerated by parallel imaging. This is important in order to make MRSI more reliable as a tool for clinical applications. METHODS The sensitivity encoding acceleration technique with spatial overdiscretization is applied for the reconstruction of parallel MRSI. In addition, the spatial response function is optimized by minimizing its deviation from a previously chosen target function. This modified minimum-norm sensitivity encoding-MRSI reconstruction approach is applied in this article for in vivo pulse-acquire MRSI of human brain at 7T with simulated acceleration factors of 2, 4, and 9 as well as actual 4-fold accelerated MRSI. RESULTS The sidelobes of the spatial response function are significantly suppressed, which reduces far-reaching voxel bleeding. At the same time, the major enlargement of the effective voxel size, which would be introduced by conventional k-space apodization methods, is largely avoided. Regularization allows for a practical trade-off between noise minimization, effective voxel size, and unaliasing. Although not aiming at increasing the nominal spatial resolution, a better spatial specificity is achieved. CONCLUSION Simultaneous suppression of short- and far-reaching voxel bleeding in MRSI is analyzed and reconstruction of highly accelerated parallel in vivo MRSI is demonstrated.
Collapse
Affiliation(s)
- Thomas Kirchner
- Institute for Biomedical Engineering, University and ETH Zurich, Zurich, Switzerland
| | | | | | | | | |
Collapse
|
25
|
Gainaru C, Fillmer A, Böhmer R. Dielectric Response of Deeply Supercooled Hydration Water in the Connective Tissue Proteins Collagen and Elastin. J Phys Chem B 2009; 113:12628-31. [DOI: 10.1021/jp9065899] [Citation(s) in RCA: 58] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Affiliation(s)
- Catalin Gainaru
- Fakultät für Physik, Technische Universität Dortmund, 44221 Dortmund, Germany
| | - Ariane Fillmer
- Fakultät für Physik, Technische Universität Dortmund, 44221 Dortmund, Germany
| | - Roland Böhmer
- Fakultät für Physik, Technische Universität Dortmund, 44221 Dortmund, Germany
| |
Collapse
|