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Schipper MR, Vlegels N, van Harten TW, Rasing I, Koemans EA, Voigt S, de Luca A, Kaushik K, van Etten ES, van Zwet EW, Terwindt GM, Biessels GJ, van Osch MJP, van Walderveen MAA, Wermer MJH. Microstructural white matter integrity in relation to vascular reactivity in Dutch-type hereditary cerebral amyloid angiopathy. J Cereb Blood Flow Metab 2023; 43:2144-2155. [PMID: 37708241 PMCID: PMC10925868 DOI: 10.1177/0271678x231200425] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/04/2023] [Revised: 08/04/2023] [Accepted: 08/07/2023] [Indexed: 09/16/2023]
Abstract
Cerebral Amyloid Angiopathy (CAA) is characterized by cerebrovascular amyloid-β accumulation leading to hallmark cortical MRI markers, such as vascular reactivity, but white matter is also affected. By studying the relationship in different disease stages of Dutch-type CAA (D-CAA), we tested the relation between vascular reactivity and microstructural white matter integrity loss. In a cross-sectional study in D-CAA, 3 T MRI was performed with Blood-Oxygen-Level-Dependent (BOLD) fMRI upon visual activation to assess vascular reactivity and diffusion tensor imaging to assess microstructural white matter integrity through Peak Width of Skeletonized Mean Diffusivity (PSMD). We assessed the relationship between BOLD parameters - amplitude, time-to-peak (TTP), and time-to-baseline (TTB) - and PSMD, with linear and quadratic regression modeling. In total, 25 participants were included (15/10 pre-symptomatic/symptomatic; mean age 36/59 y). A lowered BOLD amplitude (unstandardized β = 0.64, 95%CI [0.10, 1.18], p = 0.02, Adjusted R2 = 0.48), was quadratically associated with increased PSMD levels. A delayed BOLD response, with prolonged TTP (β = 8.34 × 10-6, 95%CI [1.84 × 10-6, 1.48 × 10-5], p = 0.02, Adj. R2 = 0.25) and TTB (β = 6.57 × 10-6, 95%CI [1.92 × 10-6, 1.12 × 10-5], p = 0.008, Adj. R2 = 0.29), was linearly associated with increased PSMD. In D-CAA subjects, predominantly in the symptomatic stage, impaired cerebrovascular reactivity is related to microstructural white matter integrity loss. Future longitudinal studies are needed to investigate whether this relation is causal.
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Affiliation(s)
- Manon R Schipper
- Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Naomi Vlegels
- Department of Neurology and Neurosurgery, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht, The Netherlands
- Institute for Stroke and Dementia Research, University Hospital, LMU Munich, Munich, Germany
| | - Thijs W van Harten
- Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Ingeborg Rasing
- Department of Neurology, Leiden University Medical Center, Leiden, The Netherlands
| | - Emma A Koemans
- Department of Neurology, Leiden University Medical Center, Leiden, The Netherlands
| | - Sabine Voigt
- Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands
- Department of Neurology, Leiden University Medical Center, Leiden, The Netherlands
| | - Alberto de Luca
- Department of Neurology and Neurosurgery, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht, The Netherlands
- Image Sciences Institute, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Kanishk Kaushik
- Department of Neurology, Leiden University Medical Center, Leiden, The Netherlands
| | - Ellis S van Etten
- Department of Neurology, Leiden University Medical Center, Leiden, The Netherlands
| | - Erik W van Zwet
- Department of Biostatistics, Leiden University Medical Center, Leiden, The Netherlands
| | - Gisela M Terwindt
- Department of Neurology, Leiden University Medical Center, Leiden, The Netherlands
| | - Geert Jan Biessels
- Department of Neurology and Neurosurgery, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Matthias JP van Osch
- Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands
| | | | - Marieke JH Wermer
- Department of Neurology, Leiden University Medical Center, Leiden, The Netherlands
- Department of Neurology, University Medical Center Groningen, Groningen, The Netherlands
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de Brito Robalo BM, de Luca A, Chen C, Dewenter A, Duering M, Hilal S, Koek HL, Kopczak A, Lam BYK, Leemans A, Mok V, Onkenhout LP, van den Brink H, Biessels GJ. Improved sensitivity and precision in multicentre diffusion MRI network analysis using thresholding and harmonization. Neuroimage Clin 2022; 36:103217. [PMID: 36240537 PMCID: PMC9668636 DOI: 10.1016/j.nicl.2022.103217] [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] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2022] [Revised: 08/22/2022] [Accepted: 10/01/2022] [Indexed: 11/06/2022]
Abstract
PURPOSE To investigate if network thresholding and raw data harmonization improve consistency of diffusion MRI (dMRI)-based brain networks while also increasing precision and sensitivity to detect disease effects in multicentre datasets. METHODS Brain networks were reconstructed from dMRI of five samples with cerebral small vessel disease (SVD; 629 patients, 166 controls), as a clinically relevant exemplar condition for studies on network integrity. We evaluated consistency of network architecture in age-matched controls, by calculating cross-site differences in connection probability and fractional anisotropy (FA). Subsequently we evaluated precision and sensitivity to disease effects by identifying connections with low FA in sporadic SVD patients relative to controls, using more severely affected patients with a pure form of genetically defined SVD as reference. RESULTS In controls, thresholding and harmonization improved consistency of network architecture, minimizing cross-site differences in connection probability and FA. In patients relative to controls, thresholding improved precision to detect disrupted connections by removing false positive connections (precision, before: 0.09-0.19; after: 0.38-0.70). Before harmonization, sensitivity was low within individual sites, with few connections surviving multiple testing correction (k = 0-25 connections). Harmonization and pooling improved sensitivity (k = 38), while also achieving higher precision when combined with thresholding (0.97). CONCLUSION We demonstrated that network consistency, precision and sensitivity to detect disease effects in SVD are improved by thresholding and harmonization. We recommend introducing these techniques to leverage large existing multicentre datasets to better understand the impact of disease on brain networks.
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Affiliation(s)
- Bruno M. de Brito Robalo
- Department of Neurology and Neurosurgery, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht, the Netherlands,Image Sciences Institute, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands
| | - Alberto de Luca
- Department of Neurology and Neurosurgery, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht, the Netherlands,Image Sciences Institute, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands
| | - Christopher Chen
- Memory, Aging and Cognition Center, Department of Pharmacology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Anna Dewenter
- Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, Germany
| | - Marco Duering
- Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, Germany,Medical Image Analysis Center (MIAC AG) and Department of Biomedical Engineering, University of Basel, Basel, Switzerland
| | - Saima Hilal
- Memory, Aging and Cognition Center, Department of Pharmacology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore,Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore
| | - Huiberdina L. Koek
- Department of Geriatric Medicine, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Anna Kopczak
- Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, Germany
| | - Bonnie Yin Ka Lam
- Division of Neurology, Department of Medicine and Therapeutics, Gerald Choa Neuroscience Centre, Faculty of Medicine, Prince of Wales Hospital, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region
| | - Alexander Leemans
- Image Sciences Institute, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands
| | - Vincent Mok
- Division of Neurology, Department of Medicine and Therapeutics, Gerald Choa Neuroscience Centre, Faculty of Medicine, Prince of Wales Hospital, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region
| | - Laurien P. Onkenhout
- Department of Neurology and Neurosurgery, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Hilde van den Brink
- Department of Neurology and Neurosurgery, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Geert Jan Biessels
- Department of Neurology and Neurosurgery, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht, the Netherlands,Corresponding author at: Department of Neurology and Neurosurgery, UMC Utrecht Brain Center, University Medical Center Utrecht, P.O. Box 85500, 3508 GA Utrecht, the Netherlands.
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de Luca A, Biessels GJ. Towards multicentre diffusion MRI studies in cerebral small vessel disease. J Neurol Neurosurg Psychiatry 2022; 93:5. [PMID: 34663625 DOI: 10.1136/jnnp-2021-326993] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/12/2021] [Accepted: 10/04/2021] [Indexed: 11/03/2022]
Affiliation(s)
- Alberto de Luca
- Department of Neurology, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht, The Netherlands.,Department of Radiology, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Geert Jan Biessels
- Department of Neurology, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht, The Netherlands
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de Brito Robalo BM, Biessels GJ, Chen C, Dewenter A, Duering M, Hilal S, Koek HL, Kopczak A, Yin Ka Lam B, Leemans A, Mok V, Onkenhout LP, van den Brink H, de Luca A. Diffusion MRI harmonization enables joint-analysis of multicentre data of patients with cerebral small vessel disease. Neuroimage Clin 2021; 32:102886. [PMID: 34911192 PMCID: PMC8609094 DOI: 10.1016/j.nicl.2021.102886] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2021] [Accepted: 11/16/2021] [Indexed: 01/10/2023]
Abstract
OBJECTIVES Acquisition-related differences in diffusion magnetic resonance imaging (dMRI) hamper pooling of multicentre data to achieve large sample sizes. A promising solution is to harmonize the raw diffusion signal using rotation invariant spherical harmonic (RISH) features, but this has not been tested in elderly subjects. Here we aimed to establish if RISH harmonization effectively removes acquisition-related differences in multicentre dMRI of elderly subjects with cerebral small vessel disease (SVD), while preserving sensitivity to disease effects. METHODS Five cohorts of patients with SVD (N = 397) and elderly controls (N = 175) with 3 Tesla MRI on different systems were included. First, to establish effectiveness of harmonization, the RISH method was trained with data of 13 to 15 age and sex-matched controls from each site. Fractional anisotropy (FA) and mean diffusivity (MD) were compared in matched controls between sites using tract-based spatial statistics (TBSS) and voxel-wise analysis, before and after harmonization. Second, to assess sensitivity to disease effects, we examined whether the contrast (effect sizes of FA, MD and peak width of skeletonized MD - PSMD) between patients and controls within each site remained unaffected by harmonization. Finally, we evaluated the association between white matter hyperintensity (WMH) burden, FA, MD and PSMD using linear regression analyses both within individual cohorts as well as with pooled scans from multiple sites, before and after harmonization. RESULTS Before harmonization, significant differences in FA and MD were observed between matched controls of different sites (p < 0.05). After harmonization these site-differences were removed. Within each site, RISH harmonization did not alter the effect sizes of FA, MD and PSMD between patients and controls (relative change in Cohen's d = 4 %) nor the strength of association with WMH volume (relative change in R2 = 2.8 %). After harmonization, patient data of all sites could be aggregated in a single analysis to infer the association between WMH volume and FA (R2 = 0.62), MD (R2 = 0.64), and PSMD (R2 = 0.60). CONCLUSIONS We showed that RISH harmonization effectively removes acquisition-related differences in dMRI of elderly subjects while preserving sensitivity to SVD-related effects. This study provides proof of concept for future multicentre SVD studies with pooled datasets.
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Affiliation(s)
- Bruno M de Brito Robalo
- Department of Neurology and Neurosurgery, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht, The Netherlands; Image Sciences Institute, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands.
| | - Geert Jan Biessels
- Department of Neurology and Neurosurgery, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht, The Netherlands.
| | - Christopher Chen
- Memory, Aging and Cognition Center, Department of Pharmacology, National University of Singapore, Singapore.
| | - Anna Dewenter
- Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, Germany.
| | - Marco Duering
- Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, Germany; Medical Image Analysis Center (MIAC AG) and qbig, Department of Biomedical Engineering, University of Basel, Basel, Switzerland.
| | - Saima Hilal
- Memory, Aging and Cognition Center, Department of Pharmacology, National University of Singapore, Singapore.
| | - Huiberdina L Koek
- Department of Geriatric Medicine, University Medical Center Utrecht, Utrecht, The Netherlands.
| | - Anna Kopczak
- Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, Germany.
| | - Bonnie Yin Ka Lam
- Division of Neurology, Department of Medicine and Therapeutics, Gerald Choa Neuroscience Centre, Faculty of Medicine, Prince of Wales Hospital, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region.
| | - Alexander Leemans
- Image Sciences Institute, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands.
| | - Vincent Mok
- Division of Neurology, Department of Medicine and Therapeutics, Gerald Choa Neuroscience Centre, Faculty of Medicine, Prince of Wales Hospital, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region.
| | - Laurien P Onkenhout
- Department of Neurology and Neurosurgery, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht, The Netherlands.
| | - Hilde van den Brink
- Department of Neurology and Neurosurgery, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht, The Netherlands.
| | - Alberto de Luca
- Department of Neurology and Neurosurgery, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht, The Netherlands; Image Sciences Institute, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands.
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van Rosmalen MHJ, Goedee HS, Derks R, Asselman F, Verhamme C, de Luca A, Hendrikse J, van der Pol WL, Froeling M. Quantitative magnetic resonance imaging of the brachial plexus shows specific changes in nerve architecture in chronic inflammatory demyelinating polyneuropathy, multifocal motor neuropathy and motor neuron disease. Eur J Neurol 2021; 28:2716-2726. [PMID: 33934438 PMCID: PMC8362016 DOI: 10.1111/ene.14896] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [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: 02/02/2021] [Revised: 04/12/2021] [Accepted: 04/28/2021] [Indexed: 02/06/2023]
Abstract
BACKGROUND The immunological pathophysiologies of chronic inflammatory demyelinating polyneuropathy (CIDP) and multifocal motor neuropathy (MMN) differ considerably, but neither has been elucidated completely. Quantitative magnetic resonance imaging (MRI) techniques such as diffusion tensor imaging, T2 mapping, and fat fraction analysis may indicate in vivo pathophysiological changes in nerve architecture. Our study aimed to systematically study nerve architecture of the brachial plexus in patients with CIDP, MMN, motor neuron disease (MND) and healthy controls using these quantitative MRI techniques. METHODS We enrolled patients with CIDP (n = 47), MMN (n = 29), MND (n = 40) and healthy controls (n = 10). All patients underwent MRI of the brachial plexus and we obtained diffusion parameters, T2 relaxation times and fat fraction using an automated processing pipeline. We compared these parameters between groups using a univariate general linear model. RESULTS Fractional anisotropy was lower in patients with CIDP compared to healthy controls (p < 0.001), patients with MND (p = 0.010) and MMN (p < 0.001). Radial diffusivity was higher in patients with CIDP compared to healthy controls (p = 0.015) and patients with MND (p = 0.001) and MMN (p < 0.001). T2 relaxation time was elevated in patients with CIDP compared to patients with MND (p = 0.023). Fat fraction was lower in patients with CIDP and MMN compared to patients with MND (both p < 0.001). CONCLUSION Our results show that quantitative MRI parameters differ between CIDP, MMN and MND, which may reflect differences in underlying pathophysiological mechanisms.
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Affiliation(s)
- Marieke H. J. van Rosmalen
- Department of Neurology and NeurosurgeryBrain Center Rudolf MagnusUniversity Medical Center UtrechtUtrechtThe Netherlands
- Department of RadiologyUniversity Medical Center UtrechtUtrechtThe Netherlands
| | - H. Stephan Goedee
- Department of Neurology and NeurosurgeryBrain Center Rudolf MagnusUniversity Medical Center UtrechtUtrechtThe Netherlands
| | - Rosina Derks
- Department of RadiologyUniversity Medical Center UtrechtUtrechtThe Netherlands
| | - Fay‐Lynn Asselman
- Department of Neurology and NeurosurgeryBrain Center Rudolf MagnusUniversity Medical Center UtrechtUtrechtThe Netherlands
| | - Camiel Verhamme
- Department of NeurologyAmsterdam NeuroscienceAmsterdam University Medical CentersUniversity of AmsterdamAmsterdamThe Netherlands
| | - Alberto de Luca
- Department of RadiologyUniversity Medical Center UtrechtUtrechtThe Netherlands
| | - J. Hendrikse
- Department of RadiologyUniversity Medical Center UtrechtUtrechtThe Netherlands
| | - W. Ludo van der Pol
- Department of Neurology and NeurosurgeryBrain Center Rudolf MagnusUniversity Medical Center UtrechtUtrechtThe Netherlands
| | - Martijn Froeling
- Department of RadiologyUniversity Medical Center UtrechtUtrechtThe Netherlands
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van den Brink H, Kopczak A, Arts T, Onkenhout L, Siero JC, Zwanenburg JJ, Duering M, Blair GW, Doubal FN, Stringer MS, Thrippleton MJ, Kuijf HJ, de Luca A, Hendrikse J, Wardlaw JM, Dichgans M, Biessels GJ. Zooming in on cerebral small vessel function in small vessel diseases with 7T MRI: Rationale and design of the "ZOOM@SVDs" study. Cereb Circ Cogn Behav 2021; 2:100013. [PMID: 36324717 PMCID: PMC9616370 DOI: 10.1016/j.cccb.2021.100013] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/18/2021] [Revised: 04/14/2021] [Accepted: 04/15/2021] [Indexed: 06/01/2023]
Abstract
Background Cerebral small vessel diseases (SVDs) are a major cause of stroke and dementia. Yet, specific treatment strategies are lacking in part because of a limited understanding of the underlying disease processes. There is therefore an urgent need to study SVDs at their core, the small vessels themselves. Objective This paper presents the rationale and design of the ZOOM@SVDs study, which aims to establish measures of cerebral small vessel dysfunction on 7T MRI as novel disease markers of SVDs. Methods ZOOM@SVDs is a prospective observational cohort study with two years follow-up. ZOOM@SVDs recruits participants with Cerebral Autosomal Dominant Arteriopathy with Subcortical Infarcts and Leukoencephalopathy (CADASIL, N = 20), sporadic SVDs (N = 60), and healthy controls (N = 40). Participants undergo 7T brain MRI to assess different aspects of small vessel function including small vessel reactivity, cerebral perforating artery flow, and pulsatility. Extensive work-up at baseline and follow-up further includes clinical and neuropsychological assessment as well as 3T brain MRI to assess conventional SVD imaging markers. Measures of small vessel dysfunction are compared between patients and controls, and related to the severity of clinical and conventional MRI manifestations of SVDs. Discussion ZOOM@SVDs will deliver novel markers of cerebral small vessel function in patients with monogenic and sporadic forms of SVDs, and establish their relation with disease burden and progression. These small vessel markers can support etiological studies in SVDs and may serve as surrogate outcome measures in future clinical trials to show target engagement of drugs directed at the small vessels.
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Key Words
- ASL, Arterial Spin Labeling
- BOLD, Blood Oxygenation Level-Dependent
- CADASIL
- CADASIL, Cerebral Autosomal Dominant Arteriopathy with Leukoencephalopathy and Subcortical Infarcts
- CDR, Clinical Dementia Rating scale
- CERAD+, Consortium to Establish a Disease Registry for Alzheimer's Disease Plus battery
- CES-D, Center for Epidemiologic Studies Depression Scale
- CO2, Carbon Dioxide
- CSF, Cerebrospinal Fluid
- Cerebral small vessel disease
- DTI, Diffusion Tensor Imaging
- EPIC, European Prospective Investigation into Cancer and Nutrition
- EtCO2, End-tidal Carbon Dioxide
- FLAIR, Fluid Attenuated Inversion Recovery
- FOV, Field Of View
- FWHM, Full-Width-at-Half-Maximum
- GE, Gradient Echo
- GM, Grey Matter
- GPRS, General Packet Radio Service
- HRF, Hemodynamic Response Function
- High field strength MRI
- LMU, Ludwig-Maximilians-Universität
- MMSE, Mini-Mental State Examination
- NAWM, Normal Appearing White Matter
- NIHSS, National Institute for Health Stroke Scale
- PI, Pulsatility Index
- ROI, Region Of Interest
- SPPB, Short Physical Performance Battery
- SVDs, Small Vessel Diseases
- SWI, Susceptibility Weighted Imaging
- Small vessel function
- Sporadic SVD
- Stroke
- TE, Echo Time
- TI, Inversion Time
- TR, Repetition Time
- TSE, Turbo Spin Echo
- UMCU, University Medical Center Utrecht
- Vmax, Maximum velocity
- Vmean, Mean velocity
- Vmin, Minimum velocity
- WM, White Matter
- WMH, White Matter Hyperintensity
- fMRI, Functional Magnetic Resonance Imaging
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Affiliation(s)
- Hilde van den Brink
- Department of Neurology and Neurosurgery, UMC Utrecht Brain Center, University Medical Center Utrecht, Heidelberglaan 100, Utrecht, 3508 GA, the Netherlands
| | - Anna Kopczak
- Institute for Stroke and Dementia Research, University Hospital, Ludwig-Maximilians-Universität, Munich, Germany
| | - Tine Arts
- Department of Radiology, Center for Image Sciences, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Laurien Onkenhout
- Department of Neurology and Neurosurgery, UMC Utrecht Brain Center, University Medical Center Utrecht, Heidelberglaan 100, Utrecht, 3508 GA, the Netherlands
| | - Jeroen C.W. Siero
- Department of Radiology, Center for Image Sciences, University Medical Center Utrecht, Utrecht, the Netherlands
- Spinoza Centre for Neuroimaging Amsterdam, Amsterdam, the Netherlands
| | - Jaco J.M. Zwanenburg
- Department of Radiology, Center for Image Sciences, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Marco Duering
- Institute for Stroke and Dementia Research, University Hospital, Ludwig-Maximilians-Universität, Munich, Germany
- Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
- German Center for Neurodegenerative Disease (DZNE), Munich, Germany
| | - Gordon W. Blair
- Brain Research Imaging Centre, Centre for Clinical Brain Sciences, UK Dementia Research Institute Centre at the University of Edinburgh, Edinburgh, United Kingdom
| | - Fergus N. Doubal
- Brain Research Imaging Centre, Centre for Clinical Brain Sciences, UK Dementia Research Institute Centre at the University of Edinburgh, Edinburgh, United Kingdom
| | - Michael S. Stringer
- Brain Research Imaging Centre, Centre for Clinical Brain Sciences, UK Dementia Research Institute Centre at the University of Edinburgh, Edinburgh, United Kingdom
| | - Michael J. Thrippleton
- Brain Research Imaging Centre, Centre for Clinical Brain Sciences, UK Dementia Research Institute Centre at the University of Edinburgh, Edinburgh, United Kingdom
| | - Hugo J. Kuijf
- Image Sciences Institute, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Alberto de Luca
- Department of Neurology and Neurosurgery, UMC Utrecht Brain Center, University Medical Center Utrecht, Heidelberglaan 100, Utrecht, 3508 GA, the Netherlands
- Brain Research Imaging Centre, Centre for Clinical Brain Sciences, UK Dementia Research Institute Centre at the University of Edinburgh, Edinburgh, United Kingdom
| | - Jeroen Hendrikse
- Department of Radiology, Center for Image Sciences, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Joanna M. Wardlaw
- Brain Research Imaging Centre, Centre for Clinical Brain Sciences, UK Dementia Research Institute Centre at the University of Edinburgh, Edinburgh, United Kingdom
| | - Martin Dichgans
- Institute for Stroke and Dementia Research, University Hospital, Ludwig-Maximilians-Universität, Munich, Germany
- Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
- German Center for Neurodegenerative Disease (DZNE), Munich, Germany
| | - Geert Jan Biessels
- Department of Neurology and Neurosurgery, UMC Utrecht Brain Center, University Medical Center Utrecht, Heidelberglaan 100, Utrecht, 3508 GA, the Netherlands
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Sloots JJ, Biessels GJ, de Luca A, Zwanenburg JJM. Strain Tensor Imaging: Cardiac-induced brain tissue deformation in humans quantified with high-field MRI. Neuroimage 2021; 236:118078. [PMID: 33878376 DOI: 10.1016/j.neuroimage.2021.118078] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [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: 12/08/2020] [Revised: 02/02/2021] [Accepted: 04/07/2021] [Indexed: 11/15/2022] Open
Abstract
The cardiac cycle induces blood volume pulsations in the cerebral microvasculature that cause subtle deformation of the surrounding tissue. These tissue deformations are highly relevant as a potential source of information on the brain's microvasculature as well as of tissue condition. Besides, cyclic brain tissue deformations may be a driving force in clearance of brain waste products. We have developed a high-field magnetic resonance imaging (MRI) technique to capture these tissue deformations with full brain coverage and sufficient signal-to-noise to derive the cardiac-induced strain tensor on a voxel by voxel basis, that could not be assessed non-invasively before. We acquired the strain tensor with 3 mm isotropic resolution in 9 subjects with repeated measurements for 8 subjects. The strain tensor yielded both positive and negative eigenvalues (principle strains), reflecting the Poison effect in tissue. The principle strain associated with expansion followed the known funnel shaped brain motion pattern pointing towards the foramen magnum. Furthermore, we evaluate two scalar quantities from the strain tensor: the volumetric strain and octahedral shear strain. These quantities showed consistent patterns between subjects, and yielded repeatable results: the peak systolic volumetric strain (relative to end-diastolic strain) was 4.19⋅10-4 ± 0.78⋅10-4 and 3.98⋅10-4 ± 0.44⋅10-4 (mean ± standard deviation for first and second measurement, respectively), and the peak octahedral shear strain was 2.16⋅10-3 ± 0.31⋅10-3 and 2.31⋅10-3 ± 0.38⋅10-3, for the first and second measurement, respectively. The volumetric strain was typically highest in the cortex and lowest in the periventricular white matter, while anisotropy was highest in the subcortical white matter and basal ganglia. This technique thus reveals new, regional information on the brain's cardiac-induced deformation characteristics, and has the potential to advance our understanding of the role of microvascular pulsations in health and disease.
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Affiliation(s)
| | - Geert Jan Biessels
- Neurology, UMC Utrecht Brain Center, University Medical Center Utrecht, the Netherlands
| | - Alberto de Luca
- Neurology, UMC Utrecht Brain Center, University Medical Center Utrecht, the Netherlands
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Guo F, de Luca A, Parker G, Jones DK, Viergever MA, Leemans A, Tax CMW. The effect of gradient nonlinearities on fiber orientation estimates from spherical deconvolution of diffusion magnetic resonance imaging data. Hum Brain Mapp 2021; 42:367-383. [PMID: 33035372 PMCID: PMC7776002 DOI: 10.1002/hbm.25228] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [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: 03/04/2020] [Revised: 09/22/2020] [Accepted: 09/24/2020] [Indexed: 12/12/2022] Open
Abstract
Gradient nonlinearities in magnetic resonance imaging (MRI) cause spatially varying mismatches between the imposed and the effective gradients and can cause significant biases in rotationally invariant diffusion MRI measures derived from, for example, diffusion tensor imaging. The estimation of the orientational organization of fibrous tissue, which is nowadays frequently performed with spherical deconvolution techniques ideally using higher diffusion weightings, can likewise be biased by gradient nonlinearities. We explore the sensitivity of two established spherical deconvolution approaches to gradient nonlinearities, namely constrained spherical deconvolution (CSD) and damped Richardson-Lucy (dRL). Additionally, we propose an extension of dRL to take into account gradient imperfections, without the need of data interpolation. Simulations show that using the effective b-matrix can improve dRL fiber orientation estimation and reduces angular deviations, while CSD can be more robust to gradient nonlinearity depending on the implementation. Angular errors depend on a complex interplay of many factors, including the direction and magnitude of gradient deviations, underlying microstructure, SNR, anisotropy of the effective response function, and diffusion weighting. Notably, angular deviations can also be observed at lower b-values in contrast to the perhaps common assumption that only high b-value data are affected. In in vivo Human Connectome Project data and acquisitions from an ultrastrong gradient (300 mT/m) scanner, angular differences are observed between applying and not applying the effective gradients in dRL estimation. As even small angular differences can lead to error propagation during tractography and as such impact connectivity analyses, incorporating gradient deviations into the estimation of fiber orientations should make such analyses more reliable.
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Affiliation(s)
- Fenghua Guo
- Image Sciences InstituteUniversity Medical Center Utrecht, Utrecht UniversityUtrechtThe Netherlands
| | - Alberto de Luca
- Image Sciences InstituteUniversity Medical Center Utrecht, Utrecht UniversityUtrechtThe Netherlands
| | - Greg Parker
- Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff UniversityCardiffUK
| | - Derek K. Jones
- Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff UniversityCardiffUK
| | - Max A. Viergever
- Image Sciences InstituteUniversity Medical Center Utrecht, Utrecht UniversityUtrechtThe Netherlands
| | - Alexander Leemans
- Image Sciences InstituteUniversity Medical Center Utrecht, Utrecht UniversityUtrechtThe Netherlands
| | - Chantal M. W. Tax
- Image Sciences InstituteUniversity Medical Center Utrecht, Utrecht UniversityUtrechtThe Netherlands
- Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff UniversityCardiffUK
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9
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Schlaffke L, Rehmann R, Rohm M, Otto LAM, de Luca A, Burakiewicz J, Baligand C, Monte J, den Harder C, Hooijmans MT, Nederveen A, Schlaeger S, Weidlich D, Karampinos DC, Stouge A, Vaeggemose M, D'Angelo MG, Arrigoni F, Kan HE, Froeling M. Multi-center evaluation of stability and reproducibility of quantitative MRI measures in healthy calf muscles. NMR Biomed 2019; 32:e4119. [PMID: 31313867 DOI: 10.1002/nbm.4119] [Citation(s) in RCA: 25] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/19/2019] [Revised: 04/17/2019] [Accepted: 04/23/2019] [Indexed: 05/18/2023]
Abstract
The purpose of this study was to evaluate temporal stability, multi-center reproducibility and the influence of covariates on a multimodal MR protocol for quantitative muscle imaging and to facilitate its use as a standardized protocol for evaluation of pathology in skeletal muscle. Quantitative T2, quantitative diffusion and four-point Dixon acquisitions of the calf muscles of both legs were repeated within one hour. Sixty-five healthy volunteers (31 females) were included in one of eight 3-T MR systems. Five traveling subjects were examined in six MR scanners. Average values over all slices of water-T2 relaxation time, proton density fat fraction (PDFF) and diffusion metrics were determined for seven muscles. Temporal stability was tested with repeated measured ANOVA and two-way random intraclass correlation coefficient (ICC). Multi-center reproducibility of traveling volunteers was assessed by a two-way mixed ICC. The factors age, body mass index, gender and muscle were tested for covariance. ICCs of temporal stability were between 0.963 and 0.999 for all parameters. Water-T2 relaxation decreased significantly (P < 10-3 ) within one hour by ~ 1 ms. Multi-center reproducibility showed ICCs within 0.879-0.917 with the lowest ICC for mean diffusivity. Different muscles showed the highest covariance, explaining 20-40% of variance for observed parameters. Standardized acquisition and processing of quantitative muscle MRI data resulted in high comparability among centers. The imaging protocol exhibited high temporal stability over one hour except for water T2 relaxation times. These results show that data pooling is feasible and enables assembling data from patients with neuromuscular diseases, paving the way towards larger studies of rare muscle disorders.
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Affiliation(s)
- Lara Schlaffke
- Department of Radiology, University Medical Centre Utrecht, Utrecht, The Netherlands
- Department of Neurology, BG-University Hospital Bergmannsheil, Ruhr-University Bochum, Bochum, Germany
- C.J., Gorter Center for High Field MRI, Department of Radiology, Leiden University Medical Centre, Leiden, The Netherlands
| | - Robert Rehmann
- Department of Neurology, BG-University Hospital Bergmannsheil, Ruhr-University Bochum, Bochum, Germany
| | - Marlena Rohm
- Department of Neurology, BG-University Hospital Bergmannsheil, Ruhr-University Bochum, Bochum, Germany
| | - Louise A M Otto
- Brain Centre Rudolf Magnus, Department of Neurology, University Medical Centre Utrecht, Utrecht, The Netherlands
| | - Alberto de Luca
- Department of Radiology, University Medical Centre Utrecht, Utrecht, The Netherlands
| | - Jedrzej Burakiewicz
- C.J., Gorter Center for High Field MRI, Department of Radiology, Leiden University Medical Centre, Leiden, The Netherlands
| | - Celine Baligand
- C.J., Gorter Center for High Field MRI, Department of Radiology, Leiden University Medical Centre, Leiden, The Netherlands
| | - Jithsa Monte
- Department of Radiology, Academic Medical Center, Amsterdam, The Netherlands
| | - Chiel den Harder
- Department of Radiology, Academic Medical Center, Amsterdam, The Netherlands
| | - Melissa T Hooijmans
- Department of Radiology, Academic Medical Center, Amsterdam, The Netherlands
| | - Aart Nederveen
- Department of Radiology, Academic Medical Center, Amsterdam, The Netherlands
| | - Sarah Schlaeger
- Department of Diagnostic and Interventional Radiology, Technical University of Munich, Munich, Germany
| | - Dominik Weidlich
- Department of Diagnostic and Interventional Radiology, Technical University of Munich, Munich, Germany
| | - Dimitrios C Karampinos
- Department of Diagnostic and Interventional Radiology, Technical University of Munich, Munich, Germany
| | - Anders Stouge
- Department of Neurology, Aarhus University Hospital, Aarhus, Denmark
| | | | | | - Filippo Arrigoni
- Neuroimaging Lab, Scientific Institute, IRCCS E. Medea, Bosisio Parini, Italy
| | - Hermien E Kan
- C.J., Gorter Center for High Field MRI, Department of Radiology, Leiden University Medical Centre, Leiden, The Netherlands
| | - Martijn Froeling
- Department of Radiology, University Medical Centre Utrecht, Utrecht, The Netherlands
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10
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Cinti C, Claudio PP, Luca AD, Cuccurese M, Howard CM, D'Esposito M, Paggi MG, Sala DL, Azzoni L, Halazonetis TD, Giordano A, Maraldi NM. A serine 37 mutation associated with two missense mutations at highly conserved regions of p53 affect pro-apoptotic genes expression in a T-lymphoblastoid drug resistant cell line. Oncogene 2000; 19:5098-105. [PMID: 11042698 DOI: 10.1038/sj.onc.1203848] [Citation(s) in RCA: 12] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2023]
Abstract
The p53 protein accumulates rapidly through post-transcriptional mechanisms following cellular exposure to DNA damaging agents and is also activated as a transcription factor leading to growth arrest or apoptosis. Phosphorylation of p53 occurs after DNA damage thereby modulating its activity and impeding the interaction of p53 with its negative regulator oncogene Mdm2. The serines 15 and 37 present in the amino terminal region of p53 are phosphorylated by the DNA-dependent protein kinase (DNA-PK) in response to DNA damage. In order to verify if specific p53 mutations occur in the multi-drug resistance phenotype, we analysed the p53 gene in two T-lymphoblastoid cell lines, CCRF-CEM and its multi-drug-resistant clone CCRF-CEM VLB100, selected for resistance to vinblastine sulfate and cross-resistant to other cytotoxic drugs. Both cell lines showed two heterozygous mutations in the DNA binding domain at codons 175 and 248. The multi-drug resistant cell line, CCRF-CEM VLB100, showed an additional mutation that involves the serine 37 whose phosphorylation is important to modulate the protein activity in response to DNA damage. The effects of these mutations on p53 transactivation capacity were evaluated. The activity of p53 on pro-apoptotic genes expression in response to DNA damage induced by (-irradiation, was affected in the vinblastine (VLB) resistant cell line but not in CCRF-CEM sensitive cell line resulting in a much reduced apoptotic cell death of the multi-drug resistant cells.
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MESH Headings
- Amino Acid Substitution
- Antibiotics, Antineoplastic/pharmacology
- Antineoplastic Agents, Phytogenic/pharmacology
- Apoptosis/genetics
- Base Sequence
- Cell Survival/radiation effects
- Conserved Sequence
- DNA, Neoplasm/genetics
- DNA, Neoplasm/metabolism
- DNA, Neoplasm/radiation effects
- Dactinomycin/pharmacology
- Doxorubicin/pharmacology
- Drug Resistance, Multiple/genetics
- Drug Resistance, Neoplasm/genetics
- Exons
- Gene Expression Regulation, Leukemic/genetics
- Genes, p53/genetics
- Humans
- Leukemia, T-Cell/genetics
- Leukemia, T-Cell/metabolism
- Leukemia, T-Cell/pathology
- Mutation, Missense
- Polymorphism, Single-Stranded Conformational
- Radiation Tolerance/genetics
- Serine/genetics
- Tumor Cells, Cultured/drug effects
- Tumor Cells, Cultured/radiation effects
- Tumor Suppressor Protein p53/genetics
- Tumor Suppressor Protein p53/metabolism
- Tumor Suppressor Protein p53/physiology
- Vinblastine/pharmacology
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Affiliation(s)
- C Cinti
- Institute of Normal and Pathologic Cytomorphology, CNR, c/o IOR, 40136 Bologna, Italy
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Favaloro B, Tamburro A, Angelucci S, Luca AD, Melino S, di Ilio C, Rotilio D. Molecular cloning, expression and site-directed mutagenesis of glutathione S-transferase from Ochrobactrum anthropi. Biochem J 1998; 335 ( Pt 3):573-9. [PMID: 9794797 PMCID: PMC1219818 DOI: 10.1042/bj3350573] [Citation(s) in RCA: 28] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
The gene coding for a novel glutathione S-transferase (GST) has been isolated from the bacterium Ochrobactrum anthropi. A PCR fragment of 230 bp was obtained using oligonucleotide primers deduced from N-terminal and 'internal' sequences of the purified enzyme. The gene was obtained by screening of a genomic DNA partial library from O. anthropi constructed in pBluescript with a PCR fragment probe. The gene encodes a protein (OaGST) of 201 amino acids with a calculated molecular mass of 21738 Da. The product of the gene was expressed and characterized; it showed GST activity with substrates 1-chloro-2, 4-dinitrobenzene (CDNB), p-nitrobenzyl chloride and 4-nitroquinoline 1-oxide, and glutathione-dependent peroxidase activity towards cumene hydroperoxide. The overexpressed product of the gene was also confirmed to have in vivo GST activity towards CDNB. The interaction of the recombinant GST with several antibiotics indicated that the enzyme is involved in the binding of rifamycin and tetracycline. The OaGST amino acid sequence showed the greatest identity (45%) with a GST from Pseudomonas sp. strain LB400. A serine residue in the N-terminal region is conserved in almost all known bacterial GSTs, and it appears to be the counterpart of the catalytic serine residue present in Theta-class GSTs. Substitution of the Ser-11 residue resulted in a mutant OaGST protein lacking CDNB-conjugating activity; moreover the mutant enzyme was not able to bind Sepharose-GSH affinity matrices.
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Affiliation(s)
- B Favaloro
- Istituto di Ricerche Farmacologiche Mario Negri, Consorzio Mario Negri Sud, 'G. Paone' Environmental Health Center, Department of Environmental Sciences, 66030 Santa Maria Imbaro, Italy.
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