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Paschoal AM, Woods JG, Pinto J, Bron EE, Petr J, Kennedy McConnell FA, Bell L, Dounavi ME, van Praag CG, Mutsaerts HJMM, Taylor AO, Zhao MY, Brumer I, Chan WSM, Toner J, Hu J, Zhang LX, Domingos C, Monteiro SP, Figueiredo P, Harms AGJ, Padrela BE, Tham C, Abdalle A, Croal PL, Anazodo U. Reproducibility of arterial spin labeling cerebral blood flow image processing: A report of the ISMRM open science initiative for perfusion imaging (OSIPI) and the ASL MRI challenge. Magn Reson Med 2024; 92:836-852. [PMID: 38502108 DOI: 10.1002/mrm.30081] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2023] [Revised: 02/20/2024] [Accepted: 02/21/2024] [Indexed: 03/20/2024]
Abstract
PURPOSE Arterial spin labeling (ASL) is a widely used contrast-free MRI method for assessing cerebral blood flow (CBF). Despite the generally adopted ASL acquisition guidelines, there is still wide variability in ASL analysis. We explored this variability through the ISMRM-OSIPI ASL-MRI Challenge, aiming to establish best practices for more reproducible ASL analysis. METHODS Eight teams analyzed the challenge data, which included a high-resolution T1-weighted anatomical image and 10 pseudo-continuous ASL datasets simulated using a digital reference object to generate ground-truth CBF values in normal and pathological states. We compared the accuracy of CBF quantification from each team's analysis to the ground truth across all voxels and within predefined brain regions. Reproducibility of CBF across analysis pipelines was assessed using the intra-class correlation coefficient (ICC), limits of agreement (LOA), and replicability of generating similar CBF estimates from different processing approaches. RESULTS Absolute errors in CBF estimates compared to ground-truth synthetic data ranged from 18.36 to 48.12 mL/100 g/min. Realistic motion incorporated into three datasets produced the largest absolute error and variability between teams, with the least agreement (ICC and LOA) with ground-truth results. Fifty percent of the submissions were replicated, and one produced three times larger CBF errors (46.59 mL/100 g/min) compared to submitted results. CONCLUSIONS Variability in CBF measurements, influenced by differences in image processing, especially to compensate for motion, highlights the significance of standardizing ASL analysis workflows. We provide a recommendation for ASL processing based on top-performing approaches as a step toward ASL standardization.
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Affiliation(s)
- Andre M Paschoal
- Institute of Physics, University of Campinas, Campinas, Brazil
- LIM44, Institute of Radiology, Department of Radiology and Oncology of Clinical Hospital, University of Sao Paulo, Sao Paulo, Brazil
| | - Joseph G Woods
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK
- Department of Radiology, Center for Functional Magnetic Resonance Imaging, University of California, San Diego, La Jolla, California, USA
| | - Joana Pinto
- Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford, UK
| | - Esther E Bron
- Department of Radiology & Nuclear Medicine, Erasmus MC-University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Jan Petr
- Helmholtz-Zentrum Dresden-Rossendorf, Institute of Radiopharmaceutical Cancer Research, Dresden, Germany
| | - Flora A Kennedy McConnell
- Radiological Sciences, Division of Clinical Neuroscience, School of Medicine, University of Nottingham, Nottingham, UK
- Sir Peter Mansfield Imaging Centre, School of Medicine, University of Nottingham, Nottingham, UK
- Nottingham Biomedical Research Centre, Queens Medical Centre, Nottingham, UK
| | - Laura Bell
- Clinical Imaging Group, Genentech, Inc., South San Francisco, California, USA
| | | | - Cassandra Gould van Praag
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK
- Department of Psychiatry, University of Oxford, Oxford, UK
| | - Henk J M M Mutsaerts
- Department of Radiology and Nuclear Medicine, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, Amsterdam, the Netherlands
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, the Netherlands
| | | | - Moss Y Zhao
- Department of Radiology, Stanford University, Stanford, California, USA
| | - Irène Brumer
- Computer Assisted Clinical Medicine, Mannheim Institute for Intelligent Systems in Medicine, Medical Faculty Mannheim, Heidelberg University, Heidelberg, Germany
| | - Wei Siang Marcus Chan
- Computer Assisted Clinical Medicine, Mannheim Institute for Intelligent Systems in Medicine, Medical Faculty Mannheim, Heidelberg University, Heidelberg, Germany
| | - Jack Toner
- Sir Peter Mansfield Imaging Centre, School of Medicine, University of Nottingham, Nottingham, UK
- Mental Health & Clinical Neurosciences, School of Medicine, University of Nottingham, Nottingham, UK
| | - Jian Hu
- Sir Peter Mansfield Imaging Centre, School of Medicine, University of Nottingham, Nottingham, UK
- Mental Health & Clinical Neurosciences, School of Medicine, University of Nottingham, Nottingham, UK
| | - Logan X Zhang
- Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford, UK
| | - Catarina Domingos
- Institute for Systems and Robotics-Lisboa and Department of Bioengineering, Instituto Superior Técnico-Universidade de Lisboa, Lisbon, Portugal
| | - Sara P Monteiro
- Institute for Systems and Robotics-Lisboa and Department of Bioengineering, Instituto Superior Técnico-Universidade de Lisboa, Lisbon, Portugal
| | - Patrícia Figueiredo
- Institute for Systems and Robotics-Lisboa and Department of Bioengineering, Instituto Superior Técnico-Universidade de Lisboa, Lisbon, Portugal
| | - Alexander G J Harms
- Department of Radiology & Nuclear Medicine, Erasmus MC-University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Beatriz E Padrela
- Department of Radiology and Nuclear Medicine, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, Amsterdam, the Netherlands
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, the Netherlands
| | - Channelle Tham
- Department of Cognitive Neuroscience, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Ahmed Abdalle
- Schulich School of Medicine and Dentistry, Western University, London, Ontario, Canada
| | - Paula L Croal
- Radiological Sciences, Division of Clinical Neuroscience, School of Medicine, University of Nottingham, Nottingham, UK
- Sir Peter Mansfield Imaging Centre, School of Medicine, University of Nottingham, Nottingham, UK
| | - Udunna Anazodo
- Department of Neurology and Neurosurgery, Montreal Neurological Institute, McGill University, Montreal, Québec, Canada
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Jellema PEJ, Mannsdörfer LM, Visser F, De Luca A, Smit CLE, Hoving EW, van Baarsen KM, Lindner T, Mutsaerts HJMM, Dankbaar JW, Lequin MH, Wijnen JP. Improving advanced intraoperative MRI methods during pediatric neurosurgery. NMR IN BIOMEDICINE 2024; 37:e5124. [PMID: 38403798 DOI: 10.1002/nbm.5124] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/27/2023] [Revised: 01/24/2024] [Accepted: 01/25/2024] [Indexed: 02/27/2024]
Abstract
Advanced intraoperative MR images (ioMRI) acquired during the resection of pediatric brain tumors could offer additional physiological information to preserve healthy tissue. With this work, we aimed to develop a protocol for ioMRI with increased sensitivity for arterial spin labeling (ASL) and diffusion MRI (dMRI), optimized for patient positioning regularly used in the pediatric neurosurgery setting. For ethical reasons, ASL images were acquired in healthy adult subjects that were imaged in the prone and supine position. After this, the ASL cerebral blood flow (CBF) was quantified and compared between both positions. To evaluate the impact of the RF coils setups on image quality, we compared different setups (two vs. four RF coils) by looking at T1-weighted (T1w) signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR), as well as undertaking a qualitative evaluation of T1w, T2w, ASL, and dMR images. Mean ASL CBF did not differ between the surgical prone and supine positions in any of the investigated regions of interest or the whole brain. T1w SNR (gray matter: p = 0.016, 34% increase; white matter: p = 0.016, 32% increase) and CNR were higher (p = 0.016) in the four versus two RF coils setups (18.0 ± 1.8 vs. 13.9 ± 1.8). Qualitative evaluation of T1w, T2w, ASL, and dMR images resulted in acceptable to good image quality and did not differ statistically significantly between setups. Only the nonweighted diffusion image maps and corticospinal tract reconstructions yielded higher image quality and reduced susceptibility artifacts with four RF coils. Advanced ioMRI metrics were more precise with four RF coils as the standard deviation decreased. Taken together, we have investigated the practical use of advanced ioMRI during pediatric neurosurgery. We conclude that ASL CBF quantification in the surgical prone position is valid and that ASL and dMRI acquisition with two RF coils can be performed adequately for clinical use. With four versus two RF coils, the SNR of the images increases, and the sensitivity to artifacts reduces.
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Affiliation(s)
- Pien E J Jellema
- Department of Pediatric Neuro-Oncology, Princess Máxima Centre for Pediatric Oncology, Utrecht, The Netherlands
- Centre for Image Sciences, University Medical Centre Utrecht, Utrecht, The Netherlands
| | - Lilli M Mannsdörfer
- Department of Pediatric Neuro-Oncology, Princess Máxima Centre for Pediatric Oncology, Utrecht, The Netherlands
| | - Fredy Visser
- Centre for Image Sciences, University Medical Centre Utrecht, Utrecht, The Netherlands
- Philips HealthCare, Best, The Netherlands
| | - Alberto De Luca
- Centre for Image Sciences, University Medical Centre Utrecht, Utrecht, The Netherlands
- Department of Neurology, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Cynthia L E Smit
- Department of Pediatric Neuro-Oncology, Princess Máxima Centre for Pediatric Oncology, Utrecht, The Netherlands
| | - Eelco W Hoving
- Department of Pediatric Neuro-Oncology, Princess Máxima Centre for Pediatric Oncology, Utrecht, The Netherlands
- Department of Neurosurgery, University Medical Centre Utrecht, Utrecht, The Netherlands
| | - Kirsten M van Baarsen
- Department of Pediatric Neuro-Oncology, Princess Máxima Centre for Pediatric Oncology, Utrecht, The Netherlands
- Department of Neurosurgery, University Medical Centre Utrecht, Utrecht, The Netherlands
| | - Thomas Lindner
- Department of Diagnostic and Interventional Neuroradiology, University Hospital Hamburg-Eppendorf, Hamburg, Germany
| | - Henk-Jan M M Mutsaerts
- Department of Radiology and Nuclear Medicine, Amsterdam UMC Location Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, The Netherlands
| | - Jan Willem Dankbaar
- Department of Radiology, University Medical Centre Utrecht, Utrecht, The Netherlands
| | - Maarten H Lequin
- Department of Pediatric Neuro-Oncology, Princess Máxima Centre for Pediatric Oncology, Utrecht, The Netherlands
- Department of Radiology, University Medical Centre Utrecht, Utrecht, The Netherlands
| | - Jannie P Wijnen
- Centre for Image Sciences, University Medical Centre Utrecht, Utrecht, The Netherlands
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Pasternak M, Mirza SS, Luciw N, Mutsaerts HJMM, Petr J, Thomas D, Cash D, Bocchetta M, Tartaglia MC, Mitchell SB, Black SE, Freedman M, Tang‐Wai D, Rogaeva E, Russell LL, Bouzigues A, van Swieten JC, Jiskoot LC, Seelaar H, Laforce R, Tiraboschi P, Borroni B, Galimberti D, Rowe JB, Graff C, Finger E, Sorbi S, de Mendonça A, Butler C, Gerhard A, Sanchez‐Valle R, Moreno F, Synofzik M, Vandenberghe R, Ducharme S, Levin J, Otto M, Santana I, Strafella AP, MacIntosh BJ, Rohrer JD, Masellis M. Longitudinal cerebral perfusion in presymptomatic genetic frontotemporal dementia: GENFI results. Alzheimers Dement 2024; 20:3525-3542. [PMID: 38623902 PMCID: PMC11095434 DOI: 10.1002/alz.13750] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2023] [Revised: 01/16/2024] [Accepted: 01/21/2024] [Indexed: 04/17/2024]
Abstract
INTRODUCTION Effective longitudinal biomarkers that track disease progression are needed to characterize the presymptomatic phase of genetic frontotemporal dementia (FTD). We investigate the utility of cerebral perfusion as one such biomarker in presymptomatic FTD mutation carriers. METHODS We investigated longitudinal profiles of cerebral perfusion using arterial spin labeling magnetic resonance imaging in 42 C9orf72, 70 GRN, and 31 MAPT presymptomatic carriers and 158 non-carrier controls. Linear mixed effects models assessed perfusion up to 5 years after baseline assessment. RESULTS Perfusion decline was evident in all three presymptomatic groups in global gray matter. Each group also featured its own regional pattern of hypoperfusion over time, with the left thalamus common to all groups. Frontal lobe regions featured lower perfusion in those who symptomatically converted versus asymptomatic carriers past their expected age of disease onset. DISCUSSION Cerebral perfusion is a potential biomarker for assessing genetic FTD and its genetic subgroups prior to symptom onset. HIGHLIGHTS Gray matter perfusion declines in at-risk genetic frontotemporal dementia (FTD). Regional perfusion decline differs between at-risk genetic FTD subgroups . Hypoperfusion in the left thalamus is common across all presymptomatic groups. Converters exhibit greater right frontal hypoperfusion than non-converters past their expected conversion date. Cerebral hypoperfusion is a potential early biomarker of genetic FTD.
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Liu X, Tyler LK, Rowe JB, Tsvetanov KA. Multimodal fusion analysis of functional, cerebrovascular and structural neuroimaging in healthy aging subjects. Hum Brain Mapp 2022; 43:5490-5508. [PMID: 35855641 PMCID: PMC9704789 DOI: 10.1002/hbm.26025] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2022] [Revised: 06/24/2022] [Accepted: 07/07/2022] [Indexed: 01/15/2023] Open
Abstract
Brain aging is a complex process that requires a multimodal approach. Neuroimaging can provide insights into brain morphology, functional organization, and vascular dynamics. However, most neuroimaging studies of aging have focused on each imaging modality separately, limiting the understanding of interrelations between processes identified by different modalities and their relevance to cognitive decline in aging. Here, we used a data-driven multimodal approach, linked independent component analysis (ICA), to jointly analyze magnetic resonance imaging (MRI) of grey matter volume, cerebrovascular, and functional network topographies in relation to measures of fluid intelligence. Neuroimaging and cognitive data from the Cambridge Centre for Ageing and Neuroscience study were used, with healthy participants aged 18-88 years (main dataset n = 215 and secondary dataset n = 433). Using linked ICA, functional network activities were characterized in independent components but not captured in the same component as structural and cerebrovascular patterns. Split-sample (n = 108/107) and out-of-sample (n = 433) validation analyses using linked ICA were also performed. Global grey matter volume with regional cerebrovascular changes and the right frontoparietal network activity were correlated with age-related and individual differences in fluid intelligence. This study presents the insights from linked ICA to bring together measurements from multiple imaging modalities, with independent and additive information. We propose that integrating multiple neuroimaging modalities allows better characterization of brain pattern variability and changes associated with healthy aging.
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Affiliation(s)
- Xulin Liu
- Department of Clinical NeurosciencesUniversity of CambridgeCambridgeUK
| | - Lorraine K. Tyler
- The Centre for Speech, Language and the Brain, Department of PsychologyUniversity of CambridgeCambridgeUK
| | - Cam‐CAN
- Cambridge Centre for Ageing and Neuroscience (Cam‐CAN), MRC Cognition and Brain Sciences UnitUniversity of CambridgeCambridgeUK
| | - James B. Rowe
- Department of Clinical NeurosciencesUniversity of CambridgeCambridgeUK
- MRC Cognition and Brain Sciences UnitUniversity of CambridgeCambridgeUK
| | - Kamen A. Tsvetanov
- Department of Clinical NeurosciencesUniversity of CambridgeCambridgeUK
- The Centre for Speech, Language and the Brain, Department of PsychologyUniversity of CambridgeCambridgeUK
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5
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Wu S, Tyler LK, Henson RN, Rowe JB, Cam-CAN, Tsvetanov KA. Cerebral blood flow predicts multiple demand network activity and fluid intelligence across the adult lifespan. Neurobiol Aging 2022; 121:1-14. [PMID: 36306687 PMCID: PMC7613814 DOI: 10.1016/j.neurobiolaging.2022.09.006] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2021] [Revised: 09/13/2022] [Accepted: 09/14/2022] [Indexed: 10/14/2022]
Abstract
The preservation of cognitive function in old age is a public health priority. Cerebral hypoperfusion is a hallmark of dementia but its impact on maintaining cognitive ability across the lifespan is less clear. We investigated the relationship between baseline cerebral blood flow (CBF) and blood oxygenation level-dependent (BOLD) response during a fluid reasoning task in a population-based adult lifespan cohort. As age differences in CBF could lead to non-neuronal contributions to the BOLD signal, we introduced commonality analysis to neuroimaging to dissociate performance-related CBF effects from the physiological confounding effects of CBF on the BOLD response. Accounting for CBF, we confirmed that performance- and age-related differences in BOLD responses in the multiple-demand network were implicated in fluid reasoning. Age differences in CBF explained not only performance-related BOLD responses but also performance-independent BOLD responses. Our results suggest that CBF is important for maintaining cognitive function, while its non-neuronal contributions to BOLD signals reflect an age-related confound. Maintaining perfusion into old age may serve to support brain function and preserve cognitive performance.
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Affiliation(s)
- Shuyi Wu
- Centre for Speech, Language and the Brain, Department of Psychology, University of Cambridge, Cambridge, UK,Department of Management, School of Business, Hong Kong Baptist University, Hong Kong, China
| | - Lorraine K. Tyler
- Centre for Speech, Language and the Brain, Department of Psychology, University of Cambridge, Cambridge, UK
| | - Richard N.A. Henson
- Medical Research Council Cognition and Brain Sciences Unit, Department of Psychiatry, Cambridge, UK
| | - James B. Rowe
- Medical Research Council Cognition and Brain Sciences Unit, Department of Psychiatry, Cambridge, UK,Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | - Cam-CAN
- Centre for Speech, Language and the Brain, Department of Psychology, University of Cambridge, Cambridge, UK,Medical Research Council Cognition and Brain Sciences Unit, Department of Psychiatry, Cambridge, UK
| | - Kamen A. Tsvetanov
- Centre for Speech, Language and the Brain, Department of Psychology, University of Cambridge, Cambridge, UK,Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK,Corresponding author (, +44 1223 766 556)
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Hafdi M, Mutsaerts HJMM, Petr J, Richard E, van Dalen JW. Atherosclerotic risk is associated with cerebral perfusion - A cross-sectional study using arterial spin labeling MRI. Neuroimage Clin 2022; 36:103142. [PMID: 35970112 PMCID: PMC9400119 DOI: 10.1016/j.nicl.2022.103142] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2022] [Revised: 07/11/2022] [Accepted: 08/01/2022] [Indexed: 12/14/2022]
Abstract
BACKGROUND Arterial spin labeling (ASL) magnetic resonance imaging (MRI) may be a promising technique to evaluate the presence of cerebral atherosclerosis. We tested whether the new and easily calculated ASL MRI parameter for vascular and tissue signal distribution - 'spatial coefficient of variation' (ASL-sCoV) - is a better radiological marker for atherosclerotic risk than the more conventional markers of white matter hyperintensity (WMH) volume and cerebral blood flow (ASL-CBF). METHODS Participants of the preDIVA trial (n = 195), aged 72-80 years with systolic hypertension (>140 mmHg) underwent two MRI scans two to three years apart. WMH volume was derived from 3D FLAIR-MRI; gray matter ASL-CBF and ASL-sCoV from ASL-MRI. Atherosclerotic risk was operationalized as 10-year cardiovascular risk by the Systematic COronary Risk Evaluation Older Persons (SCORE O.P) and calculated at baseline and follow-up. Data were analyzed using linear regression. RESULTS ASL-CBF was associated with atherosclerotic risk scores at baseline (standardized-beta = -0.26, 95 %CI = -0.40 to -0.13, p < 0.001) but not at follow-up (standardized-beta = -0.14, 95 %CI = -0.33 to 0.04, p = 0.12). ASL-sCoV was associated with atherosclerotic risk scores at both time points (baseline standardized-beta = 0.23, 95 %CI = 0.10 to 0.36, p < 0.0001, follow-up standardized beta = 0.20, 95 %CI = 0.03 to 0.36, p = 0.02). WMH volume was not associated with atherosclerotic risk scores at either time-point. There were no longitudinal associations between changes in MRI parameters and baseline atherosclerotic risk scores. CONCLUSIONS Our findings suggest that ASL-sCoV correlates better with atherosclerotic risk than the more conventional markers ASL-CBF and WMH volume. Our data reaffirm that non-invasive imaging with MRI is highly informative and could provide additional information about cerebrovascular damage.
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Affiliation(s)
- Melanie Hafdi
- Department of Neurology, Amsterdam University Medical Center, Amsterdam, The Netherlands,Corresponding author at: Amsterdam University Medical Centre, Department of Neurology Location AMC, Meibergdreef 9, 1105 AZ Amsterdam, The Netherlands.
| | - Henk JMM Mutsaerts
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Center, Amsterdam, The Netherlands
| | - Jan Petr
- Helmholtz-Zentrum Dresden-Rossendorf, Institute of Radiopharmaceutical Cancer Research, Dresden, Germany
| | - Edo Richard
- Department of Public and Occupational Health, Amsterdam University Medical Center, Amsterdam, The Netherlands,Department of Neurology, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Jan Willem van Dalen
- Department of Neurology, Amsterdam University Medical Center, Amsterdam, The Netherlands,Department of Neurology, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, The Netherlands
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7
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Morgan CA, Roberts RP, Chaffey T, Tahara-Eckl L, van der Meer M, Günther M, Anderson TJ, Cutfield NJ, Dalrymple-Alford JC, Kirk IJ, Rose Addis D, Tippett LJ, Melzer TR. Reproducibility and repeatability of magnetic resonance imaging in dementia. Phys Med 2022; 101:8-17. [PMID: 35849909 DOI: 10.1016/j.ejmp.2022.06.012] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/15/2022] [Revised: 06/09/2022] [Accepted: 06/27/2022] [Indexed: 01/01/2023] Open
Abstract
PURPOSE Individualised predictive models of cognitive decline require disease-monitoring markers that are repeatable. For wide-spread adoption, such markers also need to be reproducible at different locations. This study assessed the repeatability and reproducibility of MRI markers derived from a dementia protocol. METHODS Six participants were scanned at three different sites with a 3T MRI scanner. The protocol employed: T1-weighted (T1w) imaging, resting state functional MRI (rsfMRI), arterial spin labelling (ASL), diffusion-weighted imaging (DWI), T2-weighted fluid attenuation inversion recovery (FLAIR), T2-weighted (T2w) imaging, and susceptibility weighted imaging (SWI). Participants were scanned repeatedly, up to six times over a maximum period of five years. One participant was also scanned a further three times on sequential days on one scanner. Fifteen derived metrics were computed from the seven different modalities. RESULTS Reproducibility (coefficient of variation; CoV, across sites) was best for T1w derived grey matter, white matter and hippocampal volume (CoV < 1.5%), compared to rsfMRI and SWI derived metrics (CoV, 19% and 21%). For a given metric, long-term repeatability (CoV across time) was comparable to reproducibility, with short-term repeatability considerably better. CONCLUSIONS Reproducibility and repeatability were assessed for a suite of markers calculated from a dementia MRI protocol. In general, structural markers were less variable than functional MRI markers. Variability over time on the same scanner was comparable to variability measured across different scanners. Overall, the results support the viability of multi-site longitudinal studies for monitoring cognitive decline.
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Affiliation(s)
- Catherine A Morgan
- School of Psychology and Centre for Brain Research, The University of Auckland, Auckland, New Zealand; Brain Research New Zealand - Rangahau Roro Aotearoa, Centre of Research Excellence, New Zealand; Centre for Advanced MRI, Auckland UniServices Limited, Auckland, New Zealand.
| | - Reece P Roberts
- School of Psychology and Centre for Brain Research, The University of Auckland, Auckland, New Zealand; Brain Research New Zealand - Rangahau Roro Aotearoa, Centre of Research Excellence, New Zealand
| | - Tessa Chaffey
- School of Psychology and Centre for Brain Research, The University of Auckland, Auckland, New Zealand
| | - Lenore Tahara-Eckl
- School of Psychology and Centre for Brain Research, The University of Auckland, Auckland, New Zealand
| | - Meghan van der Meer
- School of Psychology and Centre for Brain Research, The University of Auckland, Auckland, New Zealand
| | - Matthias Günther
- Fraunhofer Institute for Digital Medicine and University of Bremen, Bremen, Germany
| | - Timothy J Anderson
- Brain Research New Zealand - Rangahau Roro Aotearoa, Centre of Research Excellence, New Zealand; Department of Medicine, University of Otago, Christchurch, New Zealand; NZ Brain Research Institute, Christchurch, New Zealand
| | - Nicholas J Cutfield
- Brain Research New Zealand - Rangahau Roro Aotearoa, Centre of Research Excellence, New Zealand; Department of Medicine, University of Otago, Dunedin, New Zealand
| | - John C Dalrymple-Alford
- Brain Research New Zealand - Rangahau Roro Aotearoa, Centre of Research Excellence, New Zealand; Department of Medicine, University of Otago, Christchurch, New Zealand; NZ Brain Research Institute, Christchurch, New Zealand; School of Psychology, Speech and Hearing, University of Canterbury, Christchurch, New Zealand
| | - Ian J Kirk
- School of Psychology and Centre for Brain Research, The University of Auckland, Auckland, New Zealand; Brain Research New Zealand - Rangahau Roro Aotearoa, Centre of Research Excellence, New Zealand
| | - Donna Rose Addis
- School of Psychology and Centre for Brain Research, The University of Auckland, Auckland, New Zealand; Brain Research New Zealand - Rangahau Roro Aotearoa, Centre of Research Excellence, New Zealand; Rotman Research Institute, Baycrest Health Sciences, Toronto, Canada; Department of Psychology, University of Toronto, Toronto, Canada
| | - Lynette J Tippett
- School of Psychology and Centre for Brain Research, The University of Auckland, Auckland, New Zealand; Brain Research New Zealand - Rangahau Roro Aotearoa, Centre of Research Excellence, New Zealand
| | - Tracy R Melzer
- Brain Research New Zealand - Rangahau Roro Aotearoa, Centre of Research Excellence, New Zealand; Department of Medicine, University of Otago, Christchurch, New Zealand; NZ Brain Research Institute, Christchurch, New Zealand; School of Psychology, Speech and Hearing, University of Canterbury, Christchurch, New Zealand
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8
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Leijenaar JF, Ingala S, Sudre CH, Mutsaerts HJMM, Leeuwis AE, van der Flier WM, Scheltens P, Weinstein HC, Barkhof F, van Gerven J, Groeneveld GJ, Prins ND. Decreased integrity of the monoaminergic tract is associated with a positive response to MPH in patients with vascular cognitive impairment - proof of principle study STREAM-VCI. CEREBRAL CIRCULATION - COGNITION AND BEHAVIOR 2022; 3:100128. [PMID: 36324417 PMCID: PMC9616323 DOI: 10.1016/j.cccb.2022.100128] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/08/2021] [Revised: 01/30/2022] [Accepted: 02/21/2022] [Indexed: 11/22/2022]
Abstract
Background Patients with vascular cognitive impairment (VCI) are very heterogeneous in both symptoms and type of cerebrovascular pathology. This might be an important reason why there is no symptomatic treatment available for VCI patients. In this study, we investigated in patients with VCI, whether there was an association between a positive response to methylphenidate and galantamine and the type of cerebrovascular disease, structural damage to specific neurotransmitter systems, cerebral perfusion, and presence of co-morbid Alzheimer (AD) pathology. Methods We included 27 VCI patients (mean age 67 years ± 8,30% female) from the STREAM-VCI trial who received placebo, methylphenidate(10 mg), and galantamine(16 mg) in a single challenge, cross-over design. In this study, we classified patients improving on a task for executive functioning after methylphenidate compared to placebo as methylphenidate responders (MPH+; resp. non-responders, MPH-) and patients improving on a task for memory after galantamine compared to placebo as galantamine responders (GAL+; resp. non-responders, GAL-). On baseline MRI, we visually assessed measures of cerebrovascular disease, automatically segmented white matter hyperintensities, used diffusion tensor imaging to visualize the integrity of monoaminergic and cholinergic neurotransmitter systems with mean diffusivity (MD) and fractional anisotropy (FA). Comorbid AD pathology was assessed using CSF or amyloid-PET. We tested differences between responders and non-responders using ANOVA, adjusting for age and sex. Results Nine patients were MPH+ vs 18 MPH-. MPH+ had higher MD (1.22 ± 0.07 vs 0.94 ± 0.05); p = .001) and lower FA (0.38 ± .01 vs 0.43 ± .01); p = .04) in the monoaminergic tract compared to MPH-. Eight patients were GAL+ and 18 GAL-. We found no differences between GAL+ and GAL- in any of the MRI measures. Information on co-morbid AD pathology was present in 17 patients. AD pathology tended to be more frequent in GAL+ vs GAL- (5(71%) vs 2(20%); p = .06). Conclusions In patients with VCI, we found that decreased integrity of the monoaminergic tract is associated with a positive response to MPH. Responsiveness to galantamine may be related to co-morbid AD pathology.
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Affiliation(s)
- Jolene F Leijenaar
- Alzheimer Center & Department of Neurology, Amsterdam Neuroscience, VU University Medical Center, Amsterdam UMC Locatie VUmc, Amsterdam, the Netherland
| | - Silvia Ingala
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, VU University Medical Center, Amsterdam UMC, Amsterdam, the Netherland
| | - Carole H Sudre
- School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
- Dementia Research Centre, Institute of Neurology, University College London, London, United Kingdom
| | - Henk-Jan MM Mutsaerts
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, VU University Medical Center, Amsterdam UMC, Amsterdam, the Netherland
- Department of Radiology and Nuclear Medicine, University Hospital Ghent, Ghent, Belgium
| | - Anna E. Leeuwis
- Alzheimer Center & Department of Neurology, Amsterdam Neuroscience, VU University Medical Center, Amsterdam UMC Locatie VUmc, Amsterdam, the Netherland
| | - Wiesje M van der Flier
- Alzheimer Center & Department of Neurology, Amsterdam Neuroscience, VU University Medical Center, Amsterdam UMC Locatie VUmc, Amsterdam, the Netherland
- Department of Epidemiology, Amsterdam Neuroscience, VU University Medical Center, Amsterdam UMC, Amsterdam, the Netherland
| | - Philip Scheltens
- Alzheimer Center & Department of Neurology, Amsterdam Neuroscience, VU University Medical Center, Amsterdam UMC Locatie VUmc, Amsterdam, the Netherland
| | - Henry C Weinstein
- Department of Neurology, Onze Lieve Vrouwe Gasthuis West, Amsterdam, the Netherland
| | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, VU University Medical Center, Amsterdam UMC, Amsterdam, the Netherland
- Institutes of Neurology and Healthcare Engineering, UCL, London, United Kingdom
| | | | - Geert Jan Groeneveld
- Centre for Human Drug Research, Leiden, the Netherland
- Department of Anesthesiology, Leiden University Medical Center, Leiden, the Netherland
| | - Niels D Prins
- Alzheimer Center & Department of Neurology, Amsterdam Neuroscience, VU University Medical Center, Amsterdam UMC Locatie VUmc, Amsterdam, the Netherland
- Brain Research Center, Amsterdam, the Netherland
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9
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Cerebral Blood Flow of the Frontal Lobe in Untreated Children with Trigonocephaly versus Healthy Controls: An Arterial Spin Labeling Study. Plast Reconstr Surg 2022; 149:931-937. [PMID: 35171857 DOI: 10.1097/prs.0000000000008931] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
BACKGROUND Craniofacial surgery is the standard treatment for children with moderate to severe trigonocephaly. The added value of surgery to release restriction of the frontal lobes is unproven, however. In this study, the authors aim to address the hypothesis that the frontal lobe perfusion is not restricted in trigonocephaly patients by investigating cerebral blood flow. METHODS Between 2018 and 2020, trigonocephaly patients for whom a surgical correction was considered underwent magnetic resonance imaging brain studies with arterial spin labeling to measure cerebral perfusion. The mean value of cerebral blood flow in the frontal lobe was calculated for each subject and compared to that of healthy controls. RESULTS Magnetic resonance imaging scans of 36 trigonocephaly patients (median age, 0.5 years; interquartile range, 0.3; 11 female patients) were included and compared to those of 16 controls (median age, 0.83 years; interquartile range, 0.56; 10 female patients). The mean cerebral blood flow values in the frontal lobe of the trigonocephaly patients (73.0 ml/100 g/min; SE, 2.97 ml/100 g/min) were not significantly different in comparison to control values (70.5 ml/100 g/min; SE, 4.45 ml/100 g/min; p = 0.65). The superior, middle, and inferior gyri of the frontal lobe showed no significant differences either. CONCLUSIONS The authors' findings suggest that the frontal lobes of trigonocephaly patients aged less than 18 months have a normal cerebral blood flow before surgery. In addition to the very low prevalence of papilledema or impaired skull growth previously reported, this finding further supports the authors' hypothesis that craniofacial surgery for trigonocephaly is rarely indicated for signs of raised intracranial pressure or restricted perfusion for patients younger than 18 months. CLINICAL QUESTION/LEVEL OF EVIDENCE Risk, II.
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10
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Cerebral perfusion and the risk of cognitive decline and dementia in community dwelling older people. CEREBRAL CIRCULATION - COGNITION AND BEHAVIOR 2022; 3:100125. [PMID: 36324415 PMCID: PMC9616444 DOI: 10.1016/j.cccb.2022.100125] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/19/2021] [Revised: 01/18/2022] [Accepted: 02/19/2022] [Indexed: 11/23/2022]
Abstract
Cerebral blood flow (CBF) and spatial coefficient of variation of the arterial transit time (ATT) are less sensitive markers of cognitive impairment and clinical dementia. Greater white matter hyperintensity volume (WMHV) was consistently associated with cognitive impairment and dementia, rendering it as a more sensitive longitudinal marker.
Background The arterial spin labeling-spatial coefficient of variation (sCoV) is a new vascular magnetic resonance imaging (MRI) parameter that could be a more sensitive marker for dementia-associated cerebral microvascular disease than the commonly used MRI markers cerebral blood flow (CBF) and white matter hyperintensity volume (WMHV). Methods 195 community-dwelling older people with hypertension were invited to undergo MRI twice, with a three-year interval. Cognition was evaluated every two years for 6-8 years using the mini-mental state examination (MMSE). We assessed relations of sCoV, CBF and WMHV with cognitive decline during follow-up. We also registered dementia diagnoses, up to 9 years after the first scan. In an additional analysis, we compared these MRI parameters between participants that did and did not develop dementia. Results 136/195 completed the second scan. sCoV and CBF were not associated with MMSE changes during 6-8 years of follow-up. Higher WMHV was associated with declining MMSE scores (-0.02 points/year/ml, 95%CI=-0.03 to -0.00). ScOv and CBF did not differ between participants who did (n=15) and did not (n=180) develop dementia, whereas higher WMHV was reported in participants who developed dementia after the first MRI (13.3 vs 6.1mL, p<0.001). There were no associations between longitudinal change in any of the MRI parameters and cognitive decline or subsequent dementia. Conclusion Global sCoV and CBF were less sensitive longitudinal markers of cognitive decline and dementia compared to WMHV in community-dwelling older people with hypertension. Larger longitudinal MRI perfusion studies are needed to identify possible (regional) patterns of cerebral perfusion preceding cognitive decline and dementia diagnosis.
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11
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Ssali T, Anazodo UC, Narciso L, Liu L, Jesso S, Richardson L, Günther M, Konstandin S, Eickel K, Prato F, Finger E, St Lawrence K. Sensitivity of arterial Spin labeling for characterization of longitudinal perfusion changes in Frontotemporal dementia and related disorders. NEUROIMAGE-CLINICAL 2021; 35:102853. [PMID: 34697009 PMCID: PMC9421452 DOI: 10.1016/j.nicl.2021.102853] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/19/2021] [Revised: 09/24/2021] [Accepted: 10/04/2021] [Indexed: 11/28/2022]
Abstract
This study demonstrates the value of ASL for longitudinal monitoring of perfusion in FTD patients. Good agreement was found in repeat measures of CBF in patients and controls. Transit times were not a significant source of error for the selected post labeling delay (2 s).
Background Advances in the understanding of the pathophysiology of frontotemporal dementia (FTD) and related disorders, along with the development of novel candidate disease modifying treatments, have stimulated the need for tools to assess the efficacy of new therapies. While perfusion imaging by arterial spin labeling (ASL) is an attractive approach for longitudinal imaging biomarkers of neurodegeneration, sources of variability between sessions including arterial transit times (ATT) and fluctuations in resting perfusion can reduce its sensitivity. Establishing the magnitude of perfusion changes that can be reliably detected is necessary to delineate longitudinal perfusion changes related to disease processes from the effects of these sources of error. Purpose To assess the feasibility of ASL for longitudinal monitoring of patients with FTD by quantifying between-session variability of perfusion on a voxel-by-voxel basis. Methods and materials ASL data were collected in 13 healthy controls and 8 patients with FTD or progressive supra-nuclear palsy. Variability in cerebral blood flow (CBF) by single delay pseudo-continuous ASL (SD-pCASL) acquired one month apart were quantified by the coefficient of variation (CV) and intraclass correlation coefficient (ICC). Additionally, CBF by SD-pCASL and ATT by low-resolution multiple inversion time ASL (LowRes-pCASL) were compared to Hadamard encoded sequences which are able to simultaneously measure CBF and ATT with improved time-efficiency. Results Agreement of grey-matter perfusion between sessions was found for both patients and controls (CV = 10.8% and 8.3% respectively) with good reliability for both groups (ICC > 0.6). Intensity normalization to remove day-to-day fluctuations in resting perfusion reduced the CV by 28%. Less than 5% of voxels had ATTs above the chosen post labelling delay (2 s), indicating that the ATT was not a significant source of error. Hadamard-encoded perfusion imaging yielded systematically higher CBF compared to SD-pCASL, but produced similar transit-time measurements. Power analysis revealed that SD-pCASL has the sensitivity to detect longitudinal changes as low as 10% with as few as 10 patient participants. Conclusion With the appropriate labeling parameters, SD-pCASL is a promising approach for assessing longitudinal changes in CBF associated with FTD.
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Affiliation(s)
- Tracy Ssali
- Lawson Health Research Institute, London, Canada; Department of Medical Biophysics, Western University, London, Canada.
| | - Udunna C Anazodo
- Lawson Health Research Institute, London, Canada; Department of Medical Biophysics, Western University, London, Canada
| | - Lucas Narciso
- Lawson Health Research Institute, London, Canada; Department of Medical Biophysics, Western University, London, Canada
| | - Linshan Liu
- Lawson Health Research Institute, London, Canada; Department of Medical Biophysics, Western University, London, Canada
| | - Sarah Jesso
- Lawson Health Research Institute, London, Canada; St. Joseph's Health Care, London, Canada
| | - Lauryn Richardson
- Lawson Health Research Institute, London, Canada; St. Joseph's Health Care, London, Canada
| | - Matthias Günther
- Fraunhofer Institute for Medical Image Computing MEVIS, Bremen, Germany; University Bremen, Bremen, Germany
| | - Simon Konstandin
- Fraunhofer Institute for Medical Image Computing MEVIS, Bremen, Germany; Mediri GmbH, Heidelberg, Germany
| | | | - Frank Prato
- Lawson Health Research Institute, London, Canada; Department of Medical Biophysics, Western University, London, Canada
| | - Elizabeth Finger
- Lawson Health Research Institute, London, Canada; Department of Medical Biophysics, Western University, London, Canada; Department of Clinical Neurological Sciences, Western University, London, Canada
| | - Keith St Lawrence
- Lawson Health Research Institute, London, Canada; Department of Medical Biophysics, Western University, London, Canada
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12
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de Planque CA, Mutsaerts HJMM, Keil VC, Erler NS, Dremmen MHG, Mathijssen IMJ, Petr J. Using Perfusion Contrast for Spatial Normalization of ASL MRI Images in a Pediatric Craniosynostosis Population. Front Neurosci 2021; 15:698007. [PMID: 34349619 PMCID: PMC8326566 DOI: 10.3389/fnins.2021.698007] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2021] [Accepted: 06/04/2021] [Indexed: 11/13/2022] Open
Abstract
Spatial normalization is an important step for group image processing and evaluation of mean brain perfusion in anatomical regions using arterial spin labeling (ASL) MRI and is typically performed via high-resolution structural brain scans. However, structural segmentation and/or spatial normalization to standard space is complicated when gray-white matter contrast in structural images is low due to ongoing myelination in newborns and infants. This problem is of particularly clinical relevance for imaging infants with inborn or acquired disorders that impair normal brain development. We investigated whether the ASL MRI perfusion contrast is a viable alternative for spatial normalization, using a pseudo-continuous ASL acquired using a 1.5 T MRI unit (GE Healthcare). Four approaches have been compared: (1) using the structural image contrast, or perfusion contrast with (2) rigid, (3) affine, and (4) nonlinear transformations - in 16 healthy controls [median age 0.83 years, inter-quartile range (IQR) ± 0.56] and 36 trigonocephaly patients (median age 0.50 years, IQR ± 0.30) - a non-syndromic type of craniosynostosis. Performance was compared quantitatively using the real-valued Tanimoto coefficient (TC), visually by three blinded readers, and eventually by the impact on regional cerebral blood flow (CBF) values. For both patients and controls, nonlinear registration using perfusion contrast showed the highest TC, at 17.51 (CI 6.66-49.38) times more likely to have a higher rating and 17.45-18.88 ml/100 g/min higher CBF compared with the standard normalization. Using perfusion-based contrast improved spatial normalization compared with the use of structural images, significantly affected the regional CBF, and may open up new possibilities for future large pediatric ASL brain studies.
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Affiliation(s)
- Catherine A. de Planque
- Department of Plastic and Reconstructive Surgery and Hand Surgery, University Medical Center Rotterdam, Rotterdam, Netherlands
| | - Henk J. M. M. Mutsaerts
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Amsterdam University Medical Center, Amsterdam, Netherlands
| | - Vera C. Keil
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Amsterdam University Medical Center, Amsterdam, Netherlands
| | - Nicole S. Erler
- Department of Biostatistics, University Medical Center Rotterdam, Rotterdam, Netherlands
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, Netherlands
| | - Marjolein H. G. Dremmen
- Department of Radiology and Nuclear Medicine, University Medical Center Rotterdam, Rotterdam, Netherlands
| | - Irene M. J. Mathijssen
- Department of Plastic and Reconstructive Surgery and Hand Surgery, University Medical Center Rotterdam, Rotterdam, Netherlands
| | - Jan Petr
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Amsterdam University Medical Center, Amsterdam, Netherlands
- Helmholtz-Zentrum Dresden-Rossendorf, Institute of Radiopharmaceutical Cancer Research, Dresden, Germany
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13
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Tsvetanov KA, Henson RNA, Jones PS, Mutsaerts H, Fuhrmann D, Tyler LK, Rowe JB. The effects of age on resting-state BOLD signal variability is explained by cardiovascular and cerebrovascular factors. Psychophysiology 2021; 58:e13714. [PMID: 33210312 PMCID: PMC8244027 DOI: 10.1111/psyp.13714] [Citation(s) in RCA: 37] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2019] [Revised: 07/27/2020] [Accepted: 09/28/2020] [Indexed: 12/18/2022]
Abstract
Accurate identification of brain function is necessary to understand neurocognitive aging, and thereby promote health and well-being. Many studies of neurocognitive aging have investigated brain function with the blood-oxygen level-dependent (BOLD) signal measured by functional magnetic resonance imaging. However, the BOLD signal is a composite of neural and vascular signals, which are differentially affected by aging. It is, therefore, essential to distinguish the age effects on vascular versus neural function. The BOLD signal variability at rest (known as resting state fluctuation amplitude, RSFA), is a safe, scalable, and robust means to calibrate vascular responsivity, as an alternative to breath-holding and hypercapnia. However, the use of RSFA for normalization of BOLD imaging assumes that age differences in RSFA reflecting only vascular factors, rather than age-related differences in neural function (activity) or neuronal loss (atrophy). Previous studies indicate that two vascular factors, cardiovascular health (CVH) and cerebrovascular function, are insufficient when used alone to fully explain age-related differences in RSFA. It remains possible that their joint consideration is required to fully capture age differences in RSFA. We tested the hypothesis that RSFA no longer varies with age after adjusting for a combination of cardiovascular and cerebrovascular measures. We also tested the hypothesis that RSFA variation with age is not associated with atrophy. We used data from the population-based, lifespan Cam-CAN cohort. After controlling for cardiovascular and cerebrovascular estimates alone, the residual variance in RSFA across individuals was significantly associated with age. However, when controlling for both cardiovascular and cerebrovascular estimates, the variance in RSFA was no longer associated with age. Grey matter volumes did not explain age differences in RSFA, after controlling for CVH. The results were consistent between voxel-level analysis and independent component analysis. Our findings indicate that cardiovascular and cerebrovascular signals are together sufficient predictors of age differences in RSFA. We suggest that RSFA can be used to separate vascular from neuronal factors, to characterize neurocognitive aging. We discuss the implications and make recommendations for the use of RSFA in the research of aging.
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Affiliation(s)
- Kamen A. Tsvetanov
- Department of Clinical NeurosciencesUniversity of CambridgeCambridgeUK
- Department of PsychologyCentre for Speech, Language and the BrainUniversity of CambridgeCambridgeUK
| | - Richard N. A. Henson
- Medical Research Council Cognition and Brain Sciences UnitCambridgeUK
- Department of PsychiatryUniversity of CambridgeCambridgeUK
| | - P. Simon Jones
- Department of PsychologyCentre for Speech, Language and the BrainUniversity of CambridgeCambridgeUK
| | - Henk Mutsaerts
- Department of Radiology and Nuclear MedicineAmsterdam University Medical CenterAmsterdamthe Netherlands
| | - Delia Fuhrmann
- Medical Research Council Cognition and Brain Sciences UnitCambridgeUK
| | - Lorraine K. Tyler
- Department of PsychologyCentre for Speech, Language and the BrainUniversity of CambridgeCambridgeUK
| | - Cam‐CAN
- Department of Clinical NeurosciencesUniversity of CambridgeCambridgeUK
- Department of PsychologyCentre for Speech, Language and the BrainUniversity of CambridgeCambridgeUK
| | - James B. Rowe
- Department of Clinical NeurosciencesUniversity of CambridgeCambridgeUK
- Medical Research Council Cognition and Brain Sciences UnitCambridgeUK
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14
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van Dalen JW, Mutsaerts HJ, Petr J, Caan MW, van Charante EPM, MacIntosh BJ, van Gool WA, Nederveen AJ, Richard E. Longitudinal relation between blood pressure, antihypertensive use and cerebral blood flow, using arterial spin labelling MRI. J Cereb Blood Flow Metab 2021; 41:1756-1766. [PMID: 33325767 PMCID: PMC8217888 DOI: 10.1177/0271678x20966975] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Consistent cerebral blood flow (CBF) is fundamental to brain function. Cerebral autoregulation ensures CBF stability. Chronic hypertension can lead to disrupted cerebral autoregulation in older people, potentially leading to blood pressure levels interfering with CBF. This study tested whether low BP and AHD use are associated with contemporaneous low CBF, and whether longitudinal change in BP is associated with change in CBF, using arterial spin labelling (ASL) MRI, in a prospective longitudinal cohort of 186 community-dwelling older individuals with hypertension (77 ± 3 years, 53% female), 125 (67%) of whom with 3-year follow-up. Diastolic blood pressure, systolic blood pressure, mean arterial pressure, and pulse pressure were assessed as blood pressure parameters. As additional cerebrovascular marker, we evaluated the ASL signal spatial coefficient of variation (ASL SCoV), a measure of ASL signal heterogeneity that may reflect cerebrovascular health. We found no associations between any of the blood pressure measures and concurrent CBF nor between changes in blood pressure measures and CBF over three-year follow-up. Antihypertensive use was associated with lower grey matter CBF (-5.49 ml/100 g/min, 95%CI = -10.7|-0.27, p = 0.04) and higher ASL SCoV (0.32 SD, 95%CI = 0.12|0.52, p = 0.002). These results warrant future research on the potential relations between antihypertensive use and cerebral perfusion.
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Affiliation(s)
- Jan Willem van Dalen
- Department of Neurology, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands.,Department of Neurology, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Henri Jmm Mutsaerts
- Department of Radiology, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
| | - Jan Petr
- Institute of Radiopharmaceutical Cancer Research, Helmholtz-Zentrum Dresden-Rossendorf, Dresden, Germany
| | - Matthan Wa Caan
- Department of Biomedical Engineering and Physics, Amsterdam UMC, University of Amsterdam, Amsterdam, Netherlands
| | - Eric P Moll van Charante
- Department of General Practice, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
| | - Bradley J MacIntosh
- Department of Medical Biophysics, University of Toronto, Sunnybrook Research Institute, Toronto, ON, Canada
| | - Willem A van Gool
- Department of Neurology, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
| | - Aart J Nederveen
- Department of Radiology, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
| | - Edo Richard
- Department of Neurology, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands.,Department of Neurology, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, the Netherlands
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15
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Friedman LG, McKeehan N, Hara Y, Cummings JL, Matthews DC, Zhu J, Mohs RC, Wang D, Hendrix SB, Quintana M, Schneider LS, Grundman M, Dickson SP, Feldman HH, Jaeger J, Finger EC, Ryan JM, Niehoff D, Dickinson SLJ, Markowitz JT, Owen M, Travaglia A, Fillit HM. Value-Generating Exploratory Trials in Neurodegenerative Dementias. Neurology 2021; 96:944-954. [PMID: 33674360 PMCID: PMC8205472 DOI: 10.1212/wnl.0000000000011774] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2020] [Accepted: 02/12/2021] [Indexed: 11/25/2022] Open
Abstract
Drug development for Alzheimer disease and other neurodegenerative dementias, including frontotemporal dementia, has experienced a long history of phase 2 and phase 3 clinical trials that failed to show efficacy of investigational drugs. Despite differences in clinical and behavioral characteristics, these disorders have shared pathologies and face common challenges in designing early-phase trials that are predictive of late-stage success. Here, we discuss exploratory clinical trials in neurodegenerative dementias. These are generally phase 1b or phase 2a trials that are designed to assess pharmacologic effects and rely on biomarker outcomes, with shorter treatment durations and fewer patients than traditional phase 2 studies. Exploratory trials can establish go/no-go decision points, support proof of concept and dose selection, and terminate drugs that fail to show target engagement with suitable exposure and acceptable safety profiles. Early failure saves valuable resources including opportunity costs. This is especially important for programs in academia and small biotechnology companies but may be applied to high-risk projects in large pharmaceutical companies to achieve proof of concept more rapidly at lower costs than traditional approaches. Exploratory studies in a staged clinical development program may provide promising data to warrant the substantial resources needed to advance compounds through late-stage development. To optimize the design and application of exploratory trials, the Alzheimer's Drug Discovery Foundation and the Association for Frontotemporal Degeneration convened an advisory panel to provide recommendations on outcome measures and statistical considerations for these types of studies and study designs that can improve efficiency in clinical development.
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Affiliation(s)
- Lauren G Friedman
- From the Alzheimer's Drug Discovery Foundation (L.G.F., N.M., Y.H., M.O., A.T., H.M.F.), New York; Chambers-Grundy Center for Transformative Neuroscience (J.L.C.), Department of Brain Health, School of Integrated Health Sciences, University of Nevada Las Vegas; ADM Diagnostics (D.C.M.), Inc. Northbrook, IL; Servier Pharmaceuticals (J.Z.), Boston, MA; Global Alzheimer's Platform Foundation (R.C.M.), Washington, DC; AgeneBio (R.C.M.), Inc. Baltimore, MD; AbbVie Inc. (D.W.), North Chicago, IL; Pentara Corporation (S.B.H., S.P.D.), Salt Lake City, UT; Berry Consultants (M.Q.), Austin TX; Keck School of Medicine of the University of Southern California (L.S.S.), Los Angeles; Global R&D Partners (M.G.), LLC, University of California, San Diego, La Jolla; Department of Neurosciences (H.H.F.), University of California, San Diego, La Jolla; Albert Einstein College of Medicine (J.J.), Bronx, NY; CognitionMetrics (J.J.), LLC; Department of Clinical Neurological Sciences and Robarts Research Institute (E.C.F.), Schulich School of Medicine and Dentistry, University of Western Ontario; Parkwood Institute (E.C.F.), Lawson Health Research Institute, St. Josephs Health Care, London, Ontario, Canada; Rodin Therapeutics (J.M.R.), Boston, MA; Association for Frontotemporal Degeneration (D.N., S.L.-J.D.), Radnor, PA; and Modus Outcomes LLP (J.T.M.), Cambridge, MA
| | - Nicholas McKeehan
- From the Alzheimer's Drug Discovery Foundation (L.G.F., N.M., Y.H., M.O., A.T., H.M.F.), New York; Chambers-Grundy Center for Transformative Neuroscience (J.L.C.), Department of Brain Health, School of Integrated Health Sciences, University of Nevada Las Vegas; ADM Diagnostics (D.C.M.), Inc. Northbrook, IL; Servier Pharmaceuticals (J.Z.), Boston, MA; Global Alzheimer's Platform Foundation (R.C.M.), Washington, DC; AgeneBio (R.C.M.), Inc. Baltimore, MD; AbbVie Inc. (D.W.), North Chicago, IL; Pentara Corporation (S.B.H., S.P.D.), Salt Lake City, UT; Berry Consultants (M.Q.), Austin TX; Keck School of Medicine of the University of Southern California (L.S.S.), Los Angeles; Global R&D Partners (M.G.), LLC, University of California, San Diego, La Jolla; Department of Neurosciences (H.H.F.), University of California, San Diego, La Jolla; Albert Einstein College of Medicine (J.J.), Bronx, NY; CognitionMetrics (J.J.), LLC; Department of Clinical Neurological Sciences and Robarts Research Institute (E.C.F.), Schulich School of Medicine and Dentistry, University of Western Ontario; Parkwood Institute (E.C.F.), Lawson Health Research Institute, St. Josephs Health Care, London, Ontario, Canada; Rodin Therapeutics (J.M.R.), Boston, MA; Association for Frontotemporal Degeneration (D.N., S.L.-J.D.), Radnor, PA; and Modus Outcomes LLP (J.T.M.), Cambridge, MA
| | - Yuko Hara
- From the Alzheimer's Drug Discovery Foundation (L.G.F., N.M., Y.H., M.O., A.T., H.M.F.), New York; Chambers-Grundy Center for Transformative Neuroscience (J.L.C.), Department of Brain Health, School of Integrated Health Sciences, University of Nevada Las Vegas; ADM Diagnostics (D.C.M.), Inc. Northbrook, IL; Servier Pharmaceuticals (J.Z.), Boston, MA; Global Alzheimer's Platform Foundation (R.C.M.), Washington, DC; AgeneBio (R.C.M.), Inc. Baltimore, MD; AbbVie Inc. (D.W.), North Chicago, IL; Pentara Corporation (S.B.H., S.P.D.), Salt Lake City, UT; Berry Consultants (M.Q.), Austin TX; Keck School of Medicine of the University of Southern California (L.S.S.), Los Angeles; Global R&D Partners (M.G.), LLC, University of California, San Diego, La Jolla; Department of Neurosciences (H.H.F.), University of California, San Diego, La Jolla; Albert Einstein College of Medicine (J.J.), Bronx, NY; CognitionMetrics (J.J.), LLC; Department of Clinical Neurological Sciences and Robarts Research Institute (E.C.F.), Schulich School of Medicine and Dentistry, University of Western Ontario; Parkwood Institute (E.C.F.), Lawson Health Research Institute, St. Josephs Health Care, London, Ontario, Canada; Rodin Therapeutics (J.M.R.), Boston, MA; Association for Frontotemporal Degeneration (D.N., S.L.-J.D.), Radnor, PA; and Modus Outcomes LLP (J.T.M.), Cambridge, MA
| | - Jeffrey L Cummings
- From the Alzheimer's Drug Discovery Foundation (L.G.F., N.M., Y.H., M.O., A.T., H.M.F.), New York; Chambers-Grundy Center for Transformative Neuroscience (J.L.C.), Department of Brain Health, School of Integrated Health Sciences, University of Nevada Las Vegas; ADM Diagnostics (D.C.M.), Inc. Northbrook, IL; Servier Pharmaceuticals (J.Z.), Boston, MA; Global Alzheimer's Platform Foundation (R.C.M.), Washington, DC; AgeneBio (R.C.M.), Inc. Baltimore, MD; AbbVie Inc. (D.W.), North Chicago, IL; Pentara Corporation (S.B.H., S.P.D.), Salt Lake City, UT; Berry Consultants (M.Q.), Austin TX; Keck School of Medicine of the University of Southern California (L.S.S.), Los Angeles; Global R&D Partners (M.G.), LLC, University of California, San Diego, La Jolla; Department of Neurosciences (H.H.F.), University of California, San Diego, La Jolla; Albert Einstein College of Medicine (J.J.), Bronx, NY; CognitionMetrics (J.J.), LLC; Department of Clinical Neurological Sciences and Robarts Research Institute (E.C.F.), Schulich School of Medicine and Dentistry, University of Western Ontario; Parkwood Institute (E.C.F.), Lawson Health Research Institute, St. Josephs Health Care, London, Ontario, Canada; Rodin Therapeutics (J.M.R.), Boston, MA; Association for Frontotemporal Degeneration (D.N., S.L.-J.D.), Radnor, PA; and Modus Outcomes LLP (J.T.M.), Cambridge, MA
| | - Dawn C Matthews
- From the Alzheimer's Drug Discovery Foundation (L.G.F., N.M., Y.H., M.O., A.T., H.M.F.), New York; Chambers-Grundy Center for Transformative Neuroscience (J.L.C.), Department of Brain Health, School of Integrated Health Sciences, University of Nevada Las Vegas; ADM Diagnostics (D.C.M.), Inc. Northbrook, IL; Servier Pharmaceuticals (J.Z.), Boston, MA; Global Alzheimer's Platform Foundation (R.C.M.), Washington, DC; AgeneBio (R.C.M.), Inc. Baltimore, MD; AbbVie Inc. (D.W.), North Chicago, IL; Pentara Corporation (S.B.H., S.P.D.), Salt Lake City, UT; Berry Consultants (M.Q.), Austin TX; Keck School of Medicine of the University of Southern California (L.S.S.), Los Angeles; Global R&D Partners (M.G.), LLC, University of California, San Diego, La Jolla; Department of Neurosciences (H.H.F.), University of California, San Diego, La Jolla; Albert Einstein College of Medicine (J.J.), Bronx, NY; CognitionMetrics (J.J.), LLC; Department of Clinical Neurological Sciences and Robarts Research Institute (E.C.F.), Schulich School of Medicine and Dentistry, University of Western Ontario; Parkwood Institute (E.C.F.), Lawson Health Research Institute, St. Josephs Health Care, London, Ontario, Canada; Rodin Therapeutics (J.M.R.), Boston, MA; Association for Frontotemporal Degeneration (D.N., S.L.-J.D.), Radnor, PA; and Modus Outcomes LLP (J.T.M.), Cambridge, MA
| | - Jian Zhu
- From the Alzheimer's Drug Discovery Foundation (L.G.F., N.M., Y.H., M.O., A.T., H.M.F.), New York; Chambers-Grundy Center for Transformative Neuroscience (J.L.C.), Department of Brain Health, School of Integrated Health Sciences, University of Nevada Las Vegas; ADM Diagnostics (D.C.M.), Inc. Northbrook, IL; Servier Pharmaceuticals (J.Z.), Boston, MA; Global Alzheimer's Platform Foundation (R.C.M.), Washington, DC; AgeneBio (R.C.M.), Inc. Baltimore, MD; AbbVie Inc. (D.W.), North Chicago, IL; Pentara Corporation (S.B.H., S.P.D.), Salt Lake City, UT; Berry Consultants (M.Q.), Austin TX; Keck School of Medicine of the University of Southern California (L.S.S.), Los Angeles; Global R&D Partners (M.G.), LLC, University of California, San Diego, La Jolla; Department of Neurosciences (H.H.F.), University of California, San Diego, La Jolla; Albert Einstein College of Medicine (J.J.), Bronx, NY; CognitionMetrics (J.J.), LLC; Department of Clinical Neurological Sciences and Robarts Research Institute (E.C.F.), Schulich School of Medicine and Dentistry, University of Western Ontario; Parkwood Institute (E.C.F.), Lawson Health Research Institute, St. Josephs Health Care, London, Ontario, Canada; Rodin Therapeutics (J.M.R.), Boston, MA; Association for Frontotemporal Degeneration (D.N., S.L.-J.D.), Radnor, PA; and Modus Outcomes LLP (J.T.M.), Cambridge, MA
| | - Richard C Mohs
- From the Alzheimer's Drug Discovery Foundation (L.G.F., N.M., Y.H., M.O., A.T., H.M.F.), New York; Chambers-Grundy Center for Transformative Neuroscience (J.L.C.), Department of Brain Health, School of Integrated Health Sciences, University of Nevada Las Vegas; ADM Diagnostics (D.C.M.), Inc. Northbrook, IL; Servier Pharmaceuticals (J.Z.), Boston, MA; Global Alzheimer's Platform Foundation (R.C.M.), Washington, DC; AgeneBio (R.C.M.), Inc. Baltimore, MD; AbbVie Inc. (D.W.), North Chicago, IL; Pentara Corporation (S.B.H., S.P.D.), Salt Lake City, UT; Berry Consultants (M.Q.), Austin TX; Keck School of Medicine of the University of Southern California (L.S.S.), Los Angeles; Global R&D Partners (M.G.), LLC, University of California, San Diego, La Jolla; Department of Neurosciences (H.H.F.), University of California, San Diego, La Jolla; Albert Einstein College of Medicine (J.J.), Bronx, NY; CognitionMetrics (J.J.), LLC; Department of Clinical Neurological Sciences and Robarts Research Institute (E.C.F.), Schulich School of Medicine and Dentistry, University of Western Ontario; Parkwood Institute (E.C.F.), Lawson Health Research Institute, St. Josephs Health Care, London, Ontario, Canada; Rodin Therapeutics (J.M.R.), Boston, MA; Association for Frontotemporal Degeneration (D.N., S.L.-J.D.), Radnor, PA; and Modus Outcomes LLP (J.T.M.), Cambridge, MA
| | - Deli Wang
- From the Alzheimer's Drug Discovery Foundation (L.G.F., N.M., Y.H., M.O., A.T., H.M.F.), New York; Chambers-Grundy Center for Transformative Neuroscience (J.L.C.), Department of Brain Health, School of Integrated Health Sciences, University of Nevada Las Vegas; ADM Diagnostics (D.C.M.), Inc. Northbrook, IL; Servier Pharmaceuticals (J.Z.), Boston, MA; Global Alzheimer's Platform Foundation (R.C.M.), Washington, DC; AgeneBio (R.C.M.), Inc. Baltimore, MD; AbbVie Inc. (D.W.), North Chicago, IL; Pentara Corporation (S.B.H., S.P.D.), Salt Lake City, UT; Berry Consultants (M.Q.), Austin TX; Keck School of Medicine of the University of Southern California (L.S.S.), Los Angeles; Global R&D Partners (M.G.), LLC, University of California, San Diego, La Jolla; Department of Neurosciences (H.H.F.), University of California, San Diego, La Jolla; Albert Einstein College of Medicine (J.J.), Bronx, NY; CognitionMetrics (J.J.), LLC; Department of Clinical Neurological Sciences and Robarts Research Institute (E.C.F.), Schulich School of Medicine and Dentistry, University of Western Ontario; Parkwood Institute (E.C.F.), Lawson Health Research Institute, St. Josephs Health Care, London, Ontario, Canada; Rodin Therapeutics (J.M.R.), Boston, MA; Association for Frontotemporal Degeneration (D.N., S.L.-J.D.), Radnor, PA; and Modus Outcomes LLP (J.T.M.), Cambridge, MA
| | - Suzanne B Hendrix
- From the Alzheimer's Drug Discovery Foundation (L.G.F., N.M., Y.H., M.O., A.T., H.M.F.), New York; Chambers-Grundy Center for Transformative Neuroscience (J.L.C.), Department of Brain Health, School of Integrated Health Sciences, University of Nevada Las Vegas; ADM Diagnostics (D.C.M.), Inc. Northbrook, IL; Servier Pharmaceuticals (J.Z.), Boston, MA; Global Alzheimer's Platform Foundation (R.C.M.), Washington, DC; AgeneBio (R.C.M.), Inc. Baltimore, MD; AbbVie Inc. (D.W.), North Chicago, IL; Pentara Corporation (S.B.H., S.P.D.), Salt Lake City, UT; Berry Consultants (M.Q.), Austin TX; Keck School of Medicine of the University of Southern California (L.S.S.), Los Angeles; Global R&D Partners (M.G.), LLC, University of California, San Diego, La Jolla; Department of Neurosciences (H.H.F.), University of California, San Diego, La Jolla; Albert Einstein College of Medicine (J.J.), Bronx, NY; CognitionMetrics (J.J.), LLC; Department of Clinical Neurological Sciences and Robarts Research Institute (E.C.F.), Schulich School of Medicine and Dentistry, University of Western Ontario; Parkwood Institute (E.C.F.), Lawson Health Research Institute, St. Josephs Health Care, London, Ontario, Canada; Rodin Therapeutics (J.M.R.), Boston, MA; Association for Frontotemporal Degeneration (D.N., S.L.-J.D.), Radnor, PA; and Modus Outcomes LLP (J.T.M.), Cambridge, MA
| | - Melanie Quintana
- From the Alzheimer's Drug Discovery Foundation (L.G.F., N.M., Y.H., M.O., A.T., H.M.F.), New York; Chambers-Grundy Center for Transformative Neuroscience (J.L.C.), Department of Brain Health, School of Integrated Health Sciences, University of Nevada Las Vegas; ADM Diagnostics (D.C.M.), Inc. Northbrook, IL; Servier Pharmaceuticals (J.Z.), Boston, MA; Global Alzheimer's Platform Foundation (R.C.M.), Washington, DC; AgeneBio (R.C.M.), Inc. Baltimore, MD; AbbVie Inc. (D.W.), North Chicago, IL; Pentara Corporation (S.B.H., S.P.D.), Salt Lake City, UT; Berry Consultants (M.Q.), Austin TX; Keck School of Medicine of the University of Southern California (L.S.S.), Los Angeles; Global R&D Partners (M.G.), LLC, University of California, San Diego, La Jolla; Department of Neurosciences (H.H.F.), University of California, San Diego, La Jolla; Albert Einstein College of Medicine (J.J.), Bronx, NY; CognitionMetrics (J.J.), LLC; Department of Clinical Neurological Sciences and Robarts Research Institute (E.C.F.), Schulich School of Medicine and Dentistry, University of Western Ontario; Parkwood Institute (E.C.F.), Lawson Health Research Institute, St. Josephs Health Care, London, Ontario, Canada; Rodin Therapeutics (J.M.R.), Boston, MA; Association for Frontotemporal Degeneration (D.N., S.L.-J.D.), Radnor, PA; and Modus Outcomes LLP (J.T.M.), Cambridge, MA
| | - Lon S Schneider
- From the Alzheimer's Drug Discovery Foundation (L.G.F., N.M., Y.H., M.O., A.T., H.M.F.), New York; Chambers-Grundy Center for Transformative Neuroscience (J.L.C.), Department of Brain Health, School of Integrated Health Sciences, University of Nevada Las Vegas; ADM Diagnostics (D.C.M.), Inc. Northbrook, IL; Servier Pharmaceuticals (J.Z.), Boston, MA; Global Alzheimer's Platform Foundation (R.C.M.), Washington, DC; AgeneBio (R.C.M.), Inc. Baltimore, MD; AbbVie Inc. (D.W.), North Chicago, IL; Pentara Corporation (S.B.H., S.P.D.), Salt Lake City, UT; Berry Consultants (M.Q.), Austin TX; Keck School of Medicine of the University of Southern California (L.S.S.), Los Angeles; Global R&D Partners (M.G.), LLC, University of California, San Diego, La Jolla; Department of Neurosciences (H.H.F.), University of California, San Diego, La Jolla; Albert Einstein College of Medicine (J.J.), Bronx, NY; CognitionMetrics (J.J.), LLC; Department of Clinical Neurological Sciences and Robarts Research Institute (E.C.F.), Schulich School of Medicine and Dentistry, University of Western Ontario; Parkwood Institute (E.C.F.), Lawson Health Research Institute, St. Josephs Health Care, London, Ontario, Canada; Rodin Therapeutics (J.M.R.), Boston, MA; Association for Frontotemporal Degeneration (D.N., S.L.-J.D.), Radnor, PA; and Modus Outcomes LLP (J.T.M.), Cambridge, MA
| | - Michael Grundman
- From the Alzheimer's Drug Discovery Foundation (L.G.F., N.M., Y.H., M.O., A.T., H.M.F.), New York; Chambers-Grundy Center for Transformative Neuroscience (J.L.C.), Department of Brain Health, School of Integrated Health Sciences, University of Nevada Las Vegas; ADM Diagnostics (D.C.M.), Inc. Northbrook, IL; Servier Pharmaceuticals (J.Z.), Boston, MA; Global Alzheimer's Platform Foundation (R.C.M.), Washington, DC; AgeneBio (R.C.M.), Inc. Baltimore, MD; AbbVie Inc. (D.W.), North Chicago, IL; Pentara Corporation (S.B.H., S.P.D.), Salt Lake City, UT; Berry Consultants (M.Q.), Austin TX; Keck School of Medicine of the University of Southern California (L.S.S.), Los Angeles; Global R&D Partners (M.G.), LLC, University of California, San Diego, La Jolla; Department of Neurosciences (H.H.F.), University of California, San Diego, La Jolla; Albert Einstein College of Medicine (J.J.), Bronx, NY; CognitionMetrics (J.J.), LLC; Department of Clinical Neurological Sciences and Robarts Research Institute (E.C.F.), Schulich School of Medicine and Dentistry, University of Western Ontario; Parkwood Institute (E.C.F.), Lawson Health Research Institute, St. Josephs Health Care, London, Ontario, Canada; Rodin Therapeutics (J.M.R.), Boston, MA; Association for Frontotemporal Degeneration (D.N., S.L.-J.D.), Radnor, PA; and Modus Outcomes LLP (J.T.M.), Cambridge, MA
| | - Samuel P Dickson
- From the Alzheimer's Drug Discovery Foundation (L.G.F., N.M., Y.H., M.O., A.T., H.M.F.), New York; Chambers-Grundy Center for Transformative Neuroscience (J.L.C.), Department of Brain Health, School of Integrated Health Sciences, University of Nevada Las Vegas; ADM Diagnostics (D.C.M.), Inc. Northbrook, IL; Servier Pharmaceuticals (J.Z.), Boston, MA; Global Alzheimer's Platform Foundation (R.C.M.), Washington, DC; AgeneBio (R.C.M.), Inc. Baltimore, MD; AbbVie Inc. (D.W.), North Chicago, IL; Pentara Corporation (S.B.H., S.P.D.), Salt Lake City, UT; Berry Consultants (M.Q.), Austin TX; Keck School of Medicine of the University of Southern California (L.S.S.), Los Angeles; Global R&D Partners (M.G.), LLC, University of California, San Diego, La Jolla; Department of Neurosciences (H.H.F.), University of California, San Diego, La Jolla; Albert Einstein College of Medicine (J.J.), Bronx, NY; CognitionMetrics (J.J.), LLC; Department of Clinical Neurological Sciences and Robarts Research Institute (E.C.F.), Schulich School of Medicine and Dentistry, University of Western Ontario; Parkwood Institute (E.C.F.), Lawson Health Research Institute, St. Josephs Health Care, London, Ontario, Canada; Rodin Therapeutics (J.M.R.), Boston, MA; Association for Frontotemporal Degeneration (D.N., S.L.-J.D.), Radnor, PA; and Modus Outcomes LLP (J.T.M.), Cambridge, MA
| | - Howard H Feldman
- From the Alzheimer's Drug Discovery Foundation (L.G.F., N.M., Y.H., M.O., A.T., H.M.F.), New York; Chambers-Grundy Center for Transformative Neuroscience (J.L.C.), Department of Brain Health, School of Integrated Health Sciences, University of Nevada Las Vegas; ADM Diagnostics (D.C.M.), Inc. Northbrook, IL; Servier Pharmaceuticals (J.Z.), Boston, MA; Global Alzheimer's Platform Foundation (R.C.M.), Washington, DC; AgeneBio (R.C.M.), Inc. Baltimore, MD; AbbVie Inc. (D.W.), North Chicago, IL; Pentara Corporation (S.B.H., S.P.D.), Salt Lake City, UT; Berry Consultants (M.Q.), Austin TX; Keck School of Medicine of the University of Southern California (L.S.S.), Los Angeles; Global R&D Partners (M.G.), LLC, University of California, San Diego, La Jolla; Department of Neurosciences (H.H.F.), University of California, San Diego, La Jolla; Albert Einstein College of Medicine (J.J.), Bronx, NY; CognitionMetrics (J.J.), LLC; Department of Clinical Neurological Sciences and Robarts Research Institute (E.C.F.), Schulich School of Medicine and Dentistry, University of Western Ontario; Parkwood Institute (E.C.F.), Lawson Health Research Institute, St. Josephs Health Care, London, Ontario, Canada; Rodin Therapeutics (J.M.R.), Boston, MA; Association for Frontotemporal Degeneration (D.N., S.L.-J.D.), Radnor, PA; and Modus Outcomes LLP (J.T.M.), Cambridge, MA
| | - Judith Jaeger
- From the Alzheimer's Drug Discovery Foundation (L.G.F., N.M., Y.H., M.O., A.T., H.M.F.), New York; Chambers-Grundy Center for Transformative Neuroscience (J.L.C.), Department of Brain Health, School of Integrated Health Sciences, University of Nevada Las Vegas; ADM Diagnostics (D.C.M.), Inc. Northbrook, IL; Servier Pharmaceuticals (J.Z.), Boston, MA; Global Alzheimer's Platform Foundation (R.C.M.), Washington, DC; AgeneBio (R.C.M.), Inc. Baltimore, MD; AbbVie Inc. (D.W.), North Chicago, IL; Pentara Corporation (S.B.H., S.P.D.), Salt Lake City, UT; Berry Consultants (M.Q.), Austin TX; Keck School of Medicine of the University of Southern California (L.S.S.), Los Angeles; Global R&D Partners (M.G.), LLC, University of California, San Diego, La Jolla; Department of Neurosciences (H.H.F.), University of California, San Diego, La Jolla; Albert Einstein College of Medicine (J.J.), Bronx, NY; CognitionMetrics (J.J.), LLC; Department of Clinical Neurological Sciences and Robarts Research Institute (E.C.F.), Schulich School of Medicine and Dentistry, University of Western Ontario; Parkwood Institute (E.C.F.), Lawson Health Research Institute, St. Josephs Health Care, London, Ontario, Canada; Rodin Therapeutics (J.M.R.), Boston, MA; Association for Frontotemporal Degeneration (D.N., S.L.-J.D.), Radnor, PA; and Modus Outcomes LLP (J.T.M.), Cambridge, MA
| | - Elizabeth C Finger
- From the Alzheimer's Drug Discovery Foundation (L.G.F., N.M., Y.H., M.O., A.T., H.M.F.), New York; Chambers-Grundy Center for Transformative Neuroscience (J.L.C.), Department of Brain Health, School of Integrated Health Sciences, University of Nevada Las Vegas; ADM Diagnostics (D.C.M.), Inc. Northbrook, IL; Servier Pharmaceuticals (J.Z.), Boston, MA; Global Alzheimer's Platform Foundation (R.C.M.), Washington, DC; AgeneBio (R.C.M.), Inc. Baltimore, MD; AbbVie Inc. (D.W.), North Chicago, IL; Pentara Corporation (S.B.H., S.P.D.), Salt Lake City, UT; Berry Consultants (M.Q.), Austin TX; Keck School of Medicine of the University of Southern California (L.S.S.), Los Angeles; Global R&D Partners (M.G.), LLC, University of California, San Diego, La Jolla; Department of Neurosciences (H.H.F.), University of California, San Diego, La Jolla; Albert Einstein College of Medicine (J.J.), Bronx, NY; CognitionMetrics (J.J.), LLC; Department of Clinical Neurological Sciences and Robarts Research Institute (E.C.F.), Schulich School of Medicine and Dentistry, University of Western Ontario; Parkwood Institute (E.C.F.), Lawson Health Research Institute, St. Josephs Health Care, London, Ontario, Canada; Rodin Therapeutics (J.M.R.), Boston, MA; Association for Frontotemporal Degeneration (D.N., S.L.-J.D.), Radnor, PA; and Modus Outcomes LLP (J.T.M.), Cambridge, MA
| | - J Michael Ryan
- From the Alzheimer's Drug Discovery Foundation (L.G.F., N.M., Y.H., M.O., A.T., H.M.F.), New York; Chambers-Grundy Center for Transformative Neuroscience (J.L.C.), Department of Brain Health, School of Integrated Health Sciences, University of Nevada Las Vegas; ADM Diagnostics (D.C.M.), Inc. Northbrook, IL; Servier Pharmaceuticals (J.Z.), Boston, MA; Global Alzheimer's Platform Foundation (R.C.M.), Washington, DC; AgeneBio (R.C.M.), Inc. Baltimore, MD; AbbVie Inc. (D.W.), North Chicago, IL; Pentara Corporation (S.B.H., S.P.D.), Salt Lake City, UT; Berry Consultants (M.Q.), Austin TX; Keck School of Medicine of the University of Southern California (L.S.S.), Los Angeles; Global R&D Partners (M.G.), LLC, University of California, San Diego, La Jolla; Department of Neurosciences (H.H.F.), University of California, San Diego, La Jolla; Albert Einstein College of Medicine (J.J.), Bronx, NY; CognitionMetrics (J.J.), LLC; Department of Clinical Neurological Sciences and Robarts Research Institute (E.C.F.), Schulich School of Medicine and Dentistry, University of Western Ontario; Parkwood Institute (E.C.F.), Lawson Health Research Institute, St. Josephs Health Care, London, Ontario, Canada; Rodin Therapeutics (J.M.R.), Boston, MA; Association for Frontotemporal Degeneration (D.N., S.L.-J.D.), Radnor, PA; and Modus Outcomes LLP (J.T.M.), Cambridge, MA
| | - Debra Niehoff
- From the Alzheimer's Drug Discovery Foundation (L.G.F., N.M., Y.H., M.O., A.T., H.M.F.), New York; Chambers-Grundy Center for Transformative Neuroscience (J.L.C.), Department of Brain Health, School of Integrated Health Sciences, University of Nevada Las Vegas; ADM Diagnostics (D.C.M.), Inc. Northbrook, IL; Servier Pharmaceuticals (J.Z.), Boston, MA; Global Alzheimer's Platform Foundation (R.C.M.), Washington, DC; AgeneBio (R.C.M.), Inc. Baltimore, MD; AbbVie Inc. (D.W.), North Chicago, IL; Pentara Corporation (S.B.H., S.P.D.), Salt Lake City, UT; Berry Consultants (M.Q.), Austin TX; Keck School of Medicine of the University of Southern California (L.S.S.), Los Angeles; Global R&D Partners (M.G.), LLC, University of California, San Diego, La Jolla; Department of Neurosciences (H.H.F.), University of California, San Diego, La Jolla; Albert Einstein College of Medicine (J.J.), Bronx, NY; CognitionMetrics (J.J.), LLC; Department of Clinical Neurological Sciences and Robarts Research Institute (E.C.F.), Schulich School of Medicine and Dentistry, University of Western Ontario; Parkwood Institute (E.C.F.), Lawson Health Research Institute, St. Josephs Health Care, London, Ontario, Canada; Rodin Therapeutics (J.M.R.), Boston, MA; Association for Frontotemporal Degeneration (D.N., S.L.-J.D.), Radnor, PA; and Modus Outcomes LLP (J.T.M.), Cambridge, MA
| | - Susan L-J Dickinson
- From the Alzheimer's Drug Discovery Foundation (L.G.F., N.M., Y.H., M.O., A.T., H.M.F.), New York; Chambers-Grundy Center for Transformative Neuroscience (J.L.C.), Department of Brain Health, School of Integrated Health Sciences, University of Nevada Las Vegas; ADM Diagnostics (D.C.M.), Inc. Northbrook, IL; Servier Pharmaceuticals (J.Z.), Boston, MA; Global Alzheimer's Platform Foundation (R.C.M.), Washington, DC; AgeneBio (R.C.M.), Inc. Baltimore, MD; AbbVie Inc. (D.W.), North Chicago, IL; Pentara Corporation (S.B.H., S.P.D.), Salt Lake City, UT; Berry Consultants (M.Q.), Austin TX; Keck School of Medicine of the University of Southern California (L.S.S.), Los Angeles; Global R&D Partners (M.G.), LLC, University of California, San Diego, La Jolla; Department of Neurosciences (H.H.F.), University of California, San Diego, La Jolla; Albert Einstein College of Medicine (J.J.), Bronx, NY; CognitionMetrics (J.J.), LLC; Department of Clinical Neurological Sciences and Robarts Research Institute (E.C.F.), Schulich School of Medicine and Dentistry, University of Western Ontario; Parkwood Institute (E.C.F.), Lawson Health Research Institute, St. Josephs Health Care, London, Ontario, Canada; Rodin Therapeutics (J.M.R.), Boston, MA; Association for Frontotemporal Degeneration (D.N., S.L.-J.D.), Radnor, PA; and Modus Outcomes LLP (J.T.M.), Cambridge, MA
| | - Jessica T Markowitz
- From the Alzheimer's Drug Discovery Foundation (L.G.F., N.M., Y.H., M.O., A.T., H.M.F.), New York; Chambers-Grundy Center for Transformative Neuroscience (J.L.C.), Department of Brain Health, School of Integrated Health Sciences, University of Nevada Las Vegas; ADM Diagnostics (D.C.M.), Inc. Northbrook, IL; Servier Pharmaceuticals (J.Z.), Boston, MA; Global Alzheimer's Platform Foundation (R.C.M.), Washington, DC; AgeneBio (R.C.M.), Inc. Baltimore, MD; AbbVie Inc. (D.W.), North Chicago, IL; Pentara Corporation (S.B.H., S.P.D.), Salt Lake City, UT; Berry Consultants (M.Q.), Austin TX; Keck School of Medicine of the University of Southern California (L.S.S.), Los Angeles; Global R&D Partners (M.G.), LLC, University of California, San Diego, La Jolla; Department of Neurosciences (H.H.F.), University of California, San Diego, La Jolla; Albert Einstein College of Medicine (J.J.), Bronx, NY; CognitionMetrics (J.J.), LLC; Department of Clinical Neurological Sciences and Robarts Research Institute (E.C.F.), Schulich School of Medicine and Dentistry, University of Western Ontario; Parkwood Institute (E.C.F.), Lawson Health Research Institute, St. Josephs Health Care, London, Ontario, Canada; Rodin Therapeutics (J.M.R.), Boston, MA; Association for Frontotemporal Degeneration (D.N., S.L.-J.D.), Radnor, PA; and Modus Outcomes LLP (J.T.M.), Cambridge, MA
| | - Meriel Owen
- From the Alzheimer's Drug Discovery Foundation (L.G.F., N.M., Y.H., M.O., A.T., H.M.F.), New York; Chambers-Grundy Center for Transformative Neuroscience (J.L.C.), Department of Brain Health, School of Integrated Health Sciences, University of Nevada Las Vegas; ADM Diagnostics (D.C.M.), Inc. Northbrook, IL; Servier Pharmaceuticals (J.Z.), Boston, MA; Global Alzheimer's Platform Foundation (R.C.M.), Washington, DC; AgeneBio (R.C.M.), Inc. Baltimore, MD; AbbVie Inc. (D.W.), North Chicago, IL; Pentara Corporation (S.B.H., S.P.D.), Salt Lake City, UT; Berry Consultants (M.Q.), Austin TX; Keck School of Medicine of the University of Southern California (L.S.S.), Los Angeles; Global R&D Partners (M.G.), LLC, University of California, San Diego, La Jolla; Department of Neurosciences (H.H.F.), University of California, San Diego, La Jolla; Albert Einstein College of Medicine (J.J.), Bronx, NY; CognitionMetrics (J.J.), LLC; Department of Clinical Neurological Sciences and Robarts Research Institute (E.C.F.), Schulich School of Medicine and Dentistry, University of Western Ontario; Parkwood Institute (E.C.F.), Lawson Health Research Institute, St. Josephs Health Care, London, Ontario, Canada; Rodin Therapeutics (J.M.R.), Boston, MA; Association for Frontotemporal Degeneration (D.N., S.L.-J.D.), Radnor, PA; and Modus Outcomes LLP (J.T.M.), Cambridge, MA
| | - Alessio Travaglia
- From the Alzheimer's Drug Discovery Foundation (L.G.F., N.M., Y.H., M.O., A.T., H.M.F.), New York; Chambers-Grundy Center for Transformative Neuroscience (J.L.C.), Department of Brain Health, School of Integrated Health Sciences, University of Nevada Las Vegas; ADM Diagnostics (D.C.M.), Inc. Northbrook, IL; Servier Pharmaceuticals (J.Z.), Boston, MA; Global Alzheimer's Platform Foundation (R.C.M.), Washington, DC; AgeneBio (R.C.M.), Inc. Baltimore, MD; AbbVie Inc. (D.W.), North Chicago, IL; Pentara Corporation (S.B.H., S.P.D.), Salt Lake City, UT; Berry Consultants (M.Q.), Austin TX; Keck School of Medicine of the University of Southern California (L.S.S.), Los Angeles; Global R&D Partners (M.G.), LLC, University of California, San Diego, La Jolla; Department of Neurosciences (H.H.F.), University of California, San Diego, La Jolla; Albert Einstein College of Medicine (J.J.), Bronx, NY; CognitionMetrics (J.J.), LLC; Department of Clinical Neurological Sciences and Robarts Research Institute (E.C.F.), Schulich School of Medicine and Dentistry, University of Western Ontario; Parkwood Institute (E.C.F.), Lawson Health Research Institute, St. Josephs Health Care, London, Ontario, Canada; Rodin Therapeutics (J.M.R.), Boston, MA; Association for Frontotemporal Degeneration (D.N., S.L.-J.D.), Radnor, PA; and Modus Outcomes LLP (J.T.M.), Cambridge, MA
| | - Howard M Fillit
- From the Alzheimer's Drug Discovery Foundation (L.G.F., N.M., Y.H., M.O., A.T., H.M.F.), New York; Chambers-Grundy Center for Transformative Neuroscience (J.L.C.), Department of Brain Health, School of Integrated Health Sciences, University of Nevada Las Vegas; ADM Diagnostics (D.C.M.), Inc. Northbrook, IL; Servier Pharmaceuticals (J.Z.), Boston, MA; Global Alzheimer's Platform Foundation (R.C.M.), Washington, DC; AgeneBio (R.C.M.), Inc. Baltimore, MD; AbbVie Inc. (D.W.), North Chicago, IL; Pentara Corporation (S.B.H., S.P.D.), Salt Lake City, UT; Berry Consultants (M.Q.), Austin TX; Keck School of Medicine of the University of Southern California (L.S.S.), Los Angeles; Global R&D Partners (M.G.), LLC, University of California, San Diego, La Jolla; Department of Neurosciences (H.H.F.), University of California, San Diego, La Jolla; Albert Einstein College of Medicine (J.J.), Bronx, NY; CognitionMetrics (J.J.), LLC; Department of Clinical Neurological Sciences and Robarts Research Institute (E.C.F.), Schulich School of Medicine and Dentistry, University of Western Ontario; Parkwood Institute (E.C.F.), Lawson Health Research Institute, St. Josephs Health Care, London, Ontario, Canada; Rodin Therapeutics (J.M.R.), Boston, MA; Association for Frontotemporal Degeneration (D.N., S.L.-J.D.), Radnor, PA; and Modus Outcomes LLP (J.T.M.), Cambridge, MA.
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Hilal S, Mutsaerts HJ, Ferro DA, Petr J, Kuijf HJ, Biessels GJ, Chen C. The Effects of Intracranial Stenosis on Cerebral Perfusion and Cognitive Performance. J Alzheimers Dis 2021; 79:1369-1380. [DOI: 10.3233/jad-201131] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Background: Intracranial stenosis (ICS) may contribute to cognitive dysfunction by decreased cerebral blood flow (CBF) which can be measured quantitatively by arterial spin labelling (ASL). Interpretation of CBF measurements with ASL, however, becomes difficult in patients with vascular disease due to prolonged arterial transit time (ATT). Recently, spatial coefficient of variation (sCoV) of ASL signal has been proposed that approximates ATT and utilized as a proxy marker for assessment of hemodynamic status of cerebral circulation. Objective: We investigate the association of ICS with CBF and sCoV parameters and its eventual effects on cognition in a memory clinic population. Methods: We included 381 patients (mean age = 72.3±7.9 years, women = 53.7%) who underwent 3T MRI and detailed neuropsychological assessment. ICS was defined as≥50% stenosis in any intracranial vessel on 3D Time-of-Flight MR Angiography. Gray matter sCoV and CBF were obtained from 2D EPI pseudo-continuous ASL images. Results: ICS was present in 58 (15.2%) patients. Patients with ICS had higher gray matter sCoV and lower CBF. The association with sCoV remained statistically significant after correction for cardiovascular risk factors. Moreover, ICS was associated with worse performance on visuoconstruction, which attenuated with higher sCoV. Mediation analysis showed that there was an indirect effect of ICS on visuoconstruction via sCoV. Conclusion: These findings suggest that compromised CBF as detected by higher sCoV is related to cognitive impairment among individuals diagnosed with ICS. We also showed that sCoV partially mediates the link between ICS and cognition. Therefore, sCoV may provide valuable hemodynamic information in patients with vascular disease.
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Affiliation(s)
- Saima Hilal
- Department of Pharmacology, National University of Singapore, Singapore
- Memory Aging and Cognition Center, National University Health System, Singapore
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore
| | - Henri J.M.M Mutsaerts
- Department of Radiology, VU University Medical Center, Amsterdam, the Netherlands
- Department of Radiology, Brain Center Rudolf Magnus, University Medical Center Utrecht, the Netherlands
| | - Doeschka A. Ferro
- Department of Neurology, Brain Center Rudolf Magnus, University Medical Center Utrecht, the Netherlands
| | - Jan Petr
- Helmholtz-Zentrum Dresden-Rossendorf, Institute of Radiopharmaceutical Cancer Research, Dresden, Germany
| | - Hugo J. Kuijf
- Image Sciences Institute, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Geert Jan Biessels
- Department of Neurology, Brain Center Rudolf Magnus, University Medical Center Utrecht, the Netherlands
| | - Christopher Chen
- Department of Pharmacology, National University of Singapore, Singapore
- Memory Aging and Cognition Center, National University Health System, Singapore
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17
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Kant IMJ, de Bresser J, van Montfort SJT, Mutsaerts HJMM, Witkamp TD, Buijsrogge M, Spies C, Hendrikse J, Slooter AJC. Preoperative brain MRI features and occurrence of postoperative delirium. J Psychosom Res 2021; 140:110301. [PMID: 33260072 DOI: 10.1016/j.jpsychores.2020.110301] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/19/2020] [Revised: 10/18/2020] [Accepted: 11/12/2020] [Indexed: 12/15/2022]
Abstract
OBJECTIVE Delirium is a frequent complication after surgery with important negative outcomes for affected patients and society. However, it is still largely unknown why some patients have a predisposition for delirium and others not. To increase our understanding of the neural substrate of postoperative delirium, we studied the association between preoperative brain MRI features and the occurrence of delirium after major surgery. METHODS A group of 413 patients without dementia (Mean 72 years, SD: 5) was included in a prospective observational two-center study design. The study was conducted at Charité Universitätsmedizin (Berlin, Germany) and the University Medical Center Utrecht (Utrecht, The Netherlands). We measured preoperative brain volumes (total brain, gray matter, white matter), white matter hyperintensity volume and shape, brain infarcts and cerebral perfusion, and used logistic regression analysis adjusted for age, sex, intracranial volume, study center and type of surgery. RESULTS Postoperative delirium was present in a total of 70 patients (17%). Preoperative cortical brain infarcts increased the risk of postoperative delirium, although this did not reach statistical significance (OR (95%CI): 1.63 (0.84-3.18). Furthermore, we found a trend for an association of a more complex shape of white matter hyperintensities with occurrence of postoperative delirium (OR (95%CI): 0.97 (0.95-1.00)). Preoperative brain volumes, white matter hyperintensity volume, and cerebral perfusion were not associated with occurrence of postoperative delirium. CONCLUSION Our study suggests that patients with preoperative cortical brain infarcts and those with a more complex white matter hyperintensity shape may have a predisposition for developing delirium after major surgery.
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Affiliation(s)
- Ilse M J Kant
- Department of Intensive Care Medicine and UMC Utrecht Brain Center, UMC Utrecht, Utrecht University, Heidelberglaan 100, Utrecht, the Netherlands; Department of Radiology and UMC Utrecht Brain Center, UMC Utrecht, Utrecht University, Heidelberglaan 100, Utrecht, the Netherlands.
| | - Jeroen de Bresser
- Department of Radiology, Leiden University Medical Center, Leiden, the Netherlands.
| | - Simone J T van Montfort
- Department of Intensive Care Medicine and UMC Utrecht Brain Center, UMC Utrecht, Utrecht University, Heidelberglaan 100, Utrecht, the Netherlands.
| | - Henri J M M Mutsaerts
- Department of Radiology and UMC Utrecht Brain Center, UMC Utrecht, Utrecht University, Heidelberglaan 100, Utrecht, the Netherlands.
| | - Theo D Witkamp
- Department of Radiology and UMC Utrecht Brain Center, UMC Utrecht, Utrecht University, Heidelberglaan 100, Utrecht, the Netherlands
| | - Marc Buijsrogge
- Department of Cardiothoracic Surgery, UMC Utrecht, Utrecht University, Heidelberglaan 100, Utrecht, the Netherlands
| | - Claudia Spies
- Department of Anesthesiology and Operative Intensive Care Medicine (CCM,CVK), Charité - Universitätsmedizin Berlin, Berlin, Germany.
| | - Jeroen Hendrikse
- Department of Radiology and UMC Utrecht Brain Center, UMC Utrecht, Utrecht University, Heidelberglaan 100, Utrecht, the Netherlands.
| | - Arjen J C Slooter
- Department of Intensive Care Medicine and UMC Utrecht Brain Center, UMC Utrecht, Utrecht University, Heidelberglaan 100, Utrecht, the Netherlands.
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18
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Rane S, Owen J, Hippe DS, Cholerton B, Zabetian CP, Montine T, Grabowski TJ. White Matter Lesions in Mild Cognitive Impairment and Idiopathic Parkinson's Disease: Multimodal Advanced MRI and Cognitive Associations. J Neuroimaging 2020; 30:843-850. [PMID: 32937003 DOI: 10.1111/jon.12778] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2020] [Accepted: 08/13/2020] [Indexed: 01/08/2023] Open
Abstract
Cerebrovascular disease is a common comorbidity in older adults, typically assessed in terms of white matter hyperintensities (WMHs) on MRI. While it is well known that WMHs exacerbate cognitive symptoms, the exact relation of WMHs with cognitive performance and other degenerative diseases is unknown. Furthermore, based on location, WMHs are often classified into periventricular and deep WMHs and are believed to have different pathological origins. Whether the two types of WMHs influence cognition differently is unclear. Using regression models, we assessed the independent association of these two types of WMHs with cognitive performance in two separate studies focused on distinct degenerative diseases, early Alzheimer's (mild cognitive impairment), and Parkinson's disease. We further tested if the two types of WMHs were differentially associated with reduced cortical cerebral blood flow (CBF) as measured by arterial spin labeling and increased mean diffusivity (MD, a marker of tissue injury) as measured by diffusion imaging. Our approach revealed that both deep and periventricular WMHs were associated with poor performance on tests of global cognition (Montreal cognitive Assessment, MoCA), task processing (Trail making test), and category fluency in the study of mild cognitive impairment. They were associated with poor performance in global cognition (MoCA) and category fluency in the Parkinson's disease study. Of note, more associations were detected between cognitive performance and deep WMHs than between cognitive performance and periventricular WMHs. Mechanistically, both deep and periventricular WMHs were associated with increased MD. Both deep and periventricular WMHs were also associated with reduced CBF in the gray matter.
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Affiliation(s)
- Swati Rane
- Department of Radiology, Integrated Brain Imaging Center, University of Washington Medical Center, Seattle, WA
| | - Julia Owen
- Department of Radiology, Integrated Brain Imaging Center, University of Washington Medical Center, Seattle, WA
| | - Daniel S Hippe
- Department of Radiology, Integrated Brain Imaging Center, University of Washington Medical Center, Seattle, WA
| | | | - Cyrus P Zabetian
- Veterans Affairs Puget Sound Health Care System, Seattle, WA.,Department of Neurology, University of Washington Medical Center, Seattle, WA
| | - Tom Montine
- Department of Pathology, Stanford University, Stanford, CA
| | - Thomas J Grabowski
- Department of Radiology, Integrated Brain Imaging Center, University of Washington Medical Center, Seattle, WA.,Department of Neurology, University of Washington Medical Center, Seattle, WA
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19
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Ferro DA, Mutsaerts HJ, Hilal S, Kuijf HJ, Petersen ET, Petr J, van Veluw SJ, Venketasubramanian N, Yeow TB, Biessels GJ, Chen C. Cortical microinfarcts in memory clinic patients are associated with reduced cerebral perfusion. J Cereb Blood Flow Metab 2020; 40:1869-1878. [PMID: 31558107 PMCID: PMC7430096 DOI: 10.1177/0271678x19877403] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
Cerebral cortical microinfarcts (CMIs) are small ischemic lesions associated with cognitive impairment and dementia. CMIs are frequently observed in cortical watershed areas suggesting that hypoperfusion contributes to their development. We investigated if presence of CMIs was related to a decrease in cerebral perfusion, globally or specifically in cortex surrounding CMIs. In 181 memory clinic patients (mean age 72 ± 9 years, 51% male), CMI presence was rated on 3-T magnetic resonance imaging (MRI). Cerebral perfusion was assessed from cortical gray matter of the anterior circulation using pseudo-continuous arterial spin labeling parameters cerebral blood flow (CBF) (perfusion in mL blood/100 g tissue/min) and spatial coefficient of variation (CoV) (reflecting arterial transit time (ATT)). Patients with CMIs had a 12% lower CBF (beta = -.20) and 22% higher spatial CoV (beta = .20) (both p < .05) without a specific regional pattern on voxel-based CBF analysis. CBF in a 2 cm region-of-interest around the CMIs did not differ from CBF in a reference zone in the contralateral hemisphere. These findings show that CMIs in memory clinic patients are primarily related to global reductions in cerebral perfusion, thus shedding new light on the etiology of vascular brain injury in dementia.
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Affiliation(s)
- Doeschka A Ferro
- Department of Neurology, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht, Netherlands
| | - Henri Jjm Mutsaerts
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Center, Amsterdam, Netherlands.,Department of Radiology, University Medical Center Utrecht, Utrecht, Netherlands
| | - Saima Hilal
- Department of Radiology and Nuclear Medicine & Department of Epidemiology, Erasmus Medical Center, Rotterdam, Netherlands.,Memory Aging and Cognition Centre, Department of Pharmacology, National University of Singapore, Singapore, Singapore
| | - Hugo J Kuijf
- Image Sciences Institute, University Medical Center Utrecht, Utrecht, Netherlands
| | - Esben T Petersen
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Hvidovre, Copenhagen, Denmark
| | - Jan Petr
- Institute of Radiopharmaceutical Cancer Research, Helmholtz-Zentrum Dresden-Rossendorf, Dresden, Germany
| | - Susanne J van Veluw
- Department of Neurology, J.P.K. Stroke Research Center, Massachusetts General Hospital, Boston, USA
| | | | | | - Geert Jan Biessels
- Department of Neurology, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht, Netherlands
| | - Christopher Chen
- Memory Aging and Cognition Centre, Department of Pharmacology, National University of Singapore, Singapore, Singapore
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20
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Rane S, Koh N, Oakley J, Caso C, Zabetian CP, Cholerton B, Montine TJ, Grabowski T. Arterial spin labeling detects perfusion patterns related to motor symptoms in Parkinson's disease. Parkinsonism Relat Disord 2020; 76:21-28. [PMID: 32559629 PMCID: PMC7554132 DOI: 10.1016/j.parkreldis.2020.05.014] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/08/2019] [Revised: 02/25/2020] [Accepted: 05/08/2020] [Indexed: 10/24/2022]
Abstract
INTRODUCTION Imaging neurovascular disturbances in Parkinson's disease (PD) is an excellent measure of disease severity. Indeed, a disease-specific regional pattern of abnormal metabolism has been identified using positron emission tomography. Only a handful of studies, however, have applied perfusion MRI to detect this disease pattern. Our goal was to replicate the evaluation of a PD-related perfusion pattern using scaled subprofile modeling/principal component analysis (SSM-PCA). METHODS We applied arterial spin labeling (ASL) MRI for this purpose. Uniquely, we assessed this pattern separately in PD individuals ON and OFF dopamine medications. We further compared the existence of these patterns and their strength in each individual with their Movement Disorder Society-Unified Parkinson's Disease Rating Scale motor (MDS-UPDRS) scores, cholinergic tone as indexed by short-term afferent inhibition (SAI), and other neuropsychiatric tests. RESULTS We observed a PD-related perfusion pattern that was similar to previous studies. The patterns were observed in both ON and OFF states but only the pattern in the OFF condition could significantly (AUC=0.72) differentiate between PD and healthy subjects. In the ON condition, PD subjects were similar to controls from a CBF standpoint (AUC=0.45). The OFF pattern prominently included the posterior cingulate, precentral region, precuneus, and the subcallosal cortex. Individual principal components from the ON and OFF states were strongly associated with MDS-UPDRS scores, SAI amplitude and latency. CONCLUSION Using ASL, our study identified patterns of abnormal perfusion in PD and were associated with disease symptoms.
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Affiliation(s)
- Swati Rane
- Integrated Brain Imaging Center, Radiology, University of Washington Medical Center, Seattle, WA, USA.
| | - Natalie Koh
- Integrated Brain Imaging Center, Radiology, University of Washington Medical Center, Seattle, WA, USA
| | - John Oakley
- Department of Neurology, University of Washington Medical Center, Seattle, WA, USA
| | - Christina Caso
- Integrated Brain Imaging Center, Radiology, University of Washington Medical Center, Seattle, WA, USA
| | - Cyrus P Zabetian
- Department of Neurology, University of Washington Medical Center, Seattle, WA, USA; Veterans Affairs Puget Sound Health Care System, Seattle, WA, USA
| | - Brenna Cholerton
- Department of Pathology, Stanford University, Stanford, CA, 94305, USA
| | - Thomas J Montine
- Department of Pathology, Stanford University, Stanford, CA, 94305, USA
| | - Thomas Grabowski
- Integrated Brain Imaging Center, Radiology, University of Washington Medical Center, Seattle, WA, USA
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21
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Mutsaerts HJMM, Petr J, Groot P, Vandemaele P, Ingala S, Robertson AD, Václavů L, Groote I, Kuijf H, Zelaya F, O'Daly O, Hilal S, Wink AM, Kant I, Caan MWA, Morgan C, de Bresser J, Lysvik E, Schrantee A, Bjørnebekk A, Clement P, Shirzadi Z, Kuijer JPA, Wottschel V, Anazodo UC, Pajkrt D, Richard E, Bokkers RPH, Reneman L, Masellis M, Günther M, MacIntosh BJ, Achten E, Chappell MA, van Osch MJP, Golay X, Thomas DL, De Vita E, Bjørnerud A, Nederveen A, Hendrikse J, Asllani I, Barkhof F. ExploreASL: An image processing pipeline for multi-center ASL perfusion MRI studies. Neuroimage 2020; 219:117031. [PMID: 32526385 DOI: 10.1016/j.neuroimage.2020.117031] [Citation(s) in RCA: 65] [Impact Index Per Article: 16.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2019] [Revised: 05/29/2020] [Accepted: 06/04/2020] [Indexed: 01/01/2023] Open
Abstract
Arterial spin labeling (ASL) has undergone significant development since its inception, with a focus on improving standardization and reproducibility of its acquisition and quantification. In a community-wide effort towards robust and reproducible clinical ASL image processing, we developed the software package ExploreASL, allowing standardized analyses across centers and scanners. The procedures used in ExploreASL capitalize on published image processing advancements and address the challenges of multi-center datasets with scanner-specific processing and artifact reduction to limit patient exclusion. ExploreASL is self-contained, written in MATLAB and based on Statistical Parameter Mapping (SPM) and runs on multiple operating systems. To facilitate collaboration and data-exchange, the toolbox follows several standards and recommendations for data structure, provenance, and best analysis practice. ExploreASL was iteratively refined and tested in the analysis of >10,000 ASL scans using different pulse-sequences in a variety of clinical populations, resulting in four processing modules: Import, Structural, ASL, and Population that perform tasks, respectively, for data curation, structural and ASL image processing and quality control, and finally preparing the results for statistical analyses on both single-subject and group level. We illustrate ExploreASL processing results from three cohorts: perinatally HIV-infected children, healthy adults, and elderly at risk for neurodegenerative disease. We show the reproducibility for each cohort when processed at different centers with different operating systems and MATLAB versions, and its effects on the quantification of gray matter cerebral blood flow. ExploreASL facilitates the standardization of image processing and quality control, allowing the pooling of cohorts which may increase statistical power and discover between-group perfusion differences. Ultimately, this workflow may advance ASL for wider adoption in clinical studies, trials, and practice.
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Affiliation(s)
- Henk J M M Mutsaerts
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Amsterdam University Medical Center, Location VUmc, Amsterdam, the Netherlands; Radiology and Nuclear Medicine, Amsterdam Neuroscience, Amsterdam University Medical Centers, Location Academic Medical Center, University of Amsterdam, Amsterdam, the Netherlands; Radiology, University Medical Center Utrecht, Utrecht, the Netherlands; Kate Gleason College of Engineering, Rochester Institute of Technology, NY, USA; Ghent Institute for Functional and Metabolic Imaging (GIfMI), Ghent University, Ghent, Belgium.
| | - Jan Petr
- Kate Gleason College of Engineering, Rochester Institute of Technology, NY, USA; Helmholtz-Zentrum Dresden-Rossendorf, Institute of Radiopharmaceutical Cancer Research, Dresden, Germany
| | - Paul Groot
- Radiology and Nuclear Medicine, Amsterdam Neuroscience, Amsterdam University Medical Centers, Location Academic Medical Center, University of Amsterdam, Amsterdam, the Netherlands
| | - Pieter Vandemaele
- Ghent Institute for Functional and Metabolic Imaging (GIfMI), Ghent University, Ghent, Belgium
| | - Silvia Ingala
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Amsterdam University Medical Center, Location VUmc, Amsterdam, the Netherlands
| | - Andrew D Robertson
- Schlegel-UW Research Institute for Aging, University of Waterloo, Waterloo, Ontario, Canada
| | - Lena Václavů
- C.J. Gorter Center for High Field MRI, Department of Radiology, Leiden University Medical Center, Leiden, the Netherlands
| | - Inge Groote
- Department of Diagnostic Physics, Oslo University Hospital, Oslo, Norway
| | - Hugo Kuijf
- Image Sciences Institute, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Fernando Zelaya
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Owen O'Daly
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Saima Hilal
- Department of Pharmacology, National University of Singapore, Singapore; Memory Aging and Cognition Center, National University Health System, Singapore; Saw Swee Hock School of Public Health, National University of Singapore, Singapore
| | - Alle Meije Wink
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Amsterdam University Medical Center, Location VUmc, Amsterdam, the Netherlands
| | - Ilse Kant
- Radiology, University Medical Center Utrecht, Utrecht, the Netherlands; Department of Intensive Care, University Medical Centre, Utrecht, the Netherlands
| | - Matthan W A Caan
- Department of Biomedical Engineering and Physics, Amsterdam University Medical Center, Location Academic Medical Center, Amsterdam, the Netherlands
| | - Catherine Morgan
- School of Psychology and Centre for Brain Research, University of Auckland, Auckland, New Zealand
| | - Jeroen de Bresser
- Department of Radiology, Leiden University Medical Center, Leiden, the Netherlands
| | - Elisabeth Lysvik
- Department of Diagnostic Physics, Oslo University Hospital, Oslo, Norway
| | - Anouk Schrantee
- Radiology and Nuclear Medicine, Amsterdam Neuroscience, Amsterdam University Medical Centers, Location Academic Medical Center, University of Amsterdam, Amsterdam, the Netherlands
| | - Astrid Bjørnebekk
- The Anabolic Androgenic Steroid Research Group, National Advisory Unit on Substance Use Disorder Treatment, Oslo University Hospital, Oslo, Norway
| | - Patricia Clement
- Ghent Institute for Functional and Metabolic Imaging (GIfMI), Ghent University, Ghent, Belgium
| | - Zahra Shirzadi
- Sunnybrook Research Institute, University of Toronto, Toronto, Canada
| | - Joost P A Kuijer
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Amsterdam University Medical Center, Location VUmc, Amsterdam, the Netherlands
| | - Viktor Wottschel
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Amsterdam University Medical Center, Location VUmc, Amsterdam, the Netherlands
| | - Udunna C Anazodo
- Department of Medical Biophysics, University of Western Ontario, London, Canada; Imaging Division, Lawson Health Research Institute, London, Canada
| | - Dasja Pajkrt
- Department of Pediatric Infectious Diseases, Emma Children's Hospital, Amsterdam University Medical Centre, Location Academic Medical Center, Amsterdam, the Netherlands
| | - Edo Richard
- Department of Neurology, Donders Institute for Brain, Behavior and Cognition, Radboud University Medical Centre, Nijmegen, the Netherlands; Neurology, Amsterdam University Medical Center, Location Academic Medical Center, University of Amsterdam, Amsterdam, the Netherlands
| | - Reinoud P H Bokkers
- Department of Radiology, Medical Imaging Center, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands
| | - Liesbeth Reneman
- Radiology and Nuclear Medicine, Amsterdam Neuroscience, Amsterdam University Medical Centers, Location Academic Medical Center, University of Amsterdam, Amsterdam, the Netherlands
| | - Mario Masellis
- Sunnybrook Research Institute, University of Toronto, Toronto, Canada
| | - Matthias Günther
- Fraunhofer MEVIS, Bremen, Germany; University of Bremen, Bremen, Germany; Mediri GmbH, Heidelberg, Germany
| | | | - Eric Achten
- Ghent Institute for Functional and Metabolic Imaging (GIfMI), Ghent University, Ghent, Belgium
| | - Michael A Chappell
- Institute of Biomedical Engineering, Department of Engineering Science & Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neuroscience, University of Oxford, Oxford, UK
| | - Matthias J P van Osch
- C.J. Gorter Center for High Field MRI, Department of Radiology, Leiden University Medical Center, Leiden, the Netherlands
| | - Xavier Golay
- UCL Queen Square Institute of Neurology, University College London, London, UK
| | - David L Thomas
- UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Enrico De Vita
- Department of Biomedical Engineering, School of Biomedical Engineering & Imaging Sciences, King's College London, King's Health Partners, St Thomas' Hospital, London, SE1 7EH, UK
| | - Atle Bjørnerud
- Department of Diagnostic Physics, Oslo University Hospital, Oslo, Norway; Department of Psychology, University of Oslo, Norway
| | - Aart Nederveen
- Radiology and Nuclear Medicine, Amsterdam Neuroscience, Amsterdam University Medical Centers, Location Academic Medical Center, University of Amsterdam, Amsterdam, the Netherlands
| | - Jeroen Hendrikse
- Radiology, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Iris Asllani
- Kate Gleason College of Engineering, Rochester Institute of Technology, NY, USA; Clinical Imaging Sciences Centre, Department of Neuroscience, Brighton and Sussex Medical School, Brighton, UK
| | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Amsterdam University Medical Center, Location VUmc, Amsterdam, the Netherlands; UCL Queen Square Institute of Neurology, University College London, London, UK; Centre for Medical Image Computing (CMIC), Faculty of Engineering Science, University College London, London, UK
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22
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Visser M, Petr J, Müller DMJ, Eijgelaar RS, Hendriks EJ, Witte M, Barkhof F, van Herk M, Mutsaerts HJMM, Vrenken H, de Munck JC, De Witt Hamer PC. Accurate MR Image Registration to Anatomical Reference Space for Diffuse Glioma. Front Neurosci 2020; 14:585. [PMID: 32581699 PMCID: PMC7290158 DOI: 10.3389/fnins.2020.00585] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2019] [Accepted: 05/12/2020] [Indexed: 12/26/2022] Open
Abstract
To summarize the distribution of glioma location within a patient population, registration of individual MR images to anatomical reference space is required. In this study, we quantified the accuracy of MR image registration to anatomical reference space with linear and non-linear transformations using estimated tumor targets of glioblastoma and lower-grade glioma, and anatomical landmarks at pre- and post-operative time-points using six commonly used registration packages (FSL, SPM5, DARTEL, ANTs, Elastix, and NiftyReg). Routine clinical pre- and post-operative, post-contrast T1-weighted images of 20 patients with glioblastoma and 20 with lower-grade glioma were collected. The 2009a Montreal Neurological Institute brain template was used as anatomical reference space. Tumors were manually segmented in the patient space and corresponding healthy tissue was delineated as a target volume in the anatomical reference space. Accuracy of the tumor alignment was quantified using the Dice score and the Hausdorff distance. To measure the accuracy of general brain alignment, anatomical landmarks were placed in patient and in anatomical reference space, and the landmark distance after registration was quantified. Lower-grade gliomas were registered more accurately than glioblastoma. Registration accuracy for pre- and post-operative MR images did not differ. SPM5 and DARTEL registered tumors most accurate, and FSL least accurate. Non-linear transformations resulted in more accurate general brain alignment than linear transformations, but tumor alignment was similar between linear and non-linear transformation. We conclude that linear transformation suffices to summarize glioma locations in anatomical reference space.
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Affiliation(s)
- Martin Visser
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Amsterdam, Netherlands
| | - Jan Petr
- Institute of Radiopharmaceutical Cancer Research, Helmholtz-Zentrum Dresden-Rossendorf, Dresden, Germany
| | - Domenique M J Müller
- Cancer Center Amsterdam, Brain Tumor Center, Department of Neurosurgery, Amsterdam UMC, Amsterdam, Netherlands
| | - Roelant S Eijgelaar
- Cancer Center Amsterdam, Brain Tumor Center, Department of Neurosurgery, Amsterdam UMC, Amsterdam, Netherlands
| | - Eef J Hendriks
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Amsterdam, Netherlands
| | - Marnix Witte
- Department of Radiotherapy, Netherlands Cancer Institute, Amsterdam, Netherlands
| | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Amsterdam, Netherlands.,UCL Queen Square Institute of Neurology, University College London, London, United Kingdom.,UCL Institute of Healthcare Engineering, University College London, London, United Kingdom
| | - Marcel van Herk
- Division of Cancer Sciences, Manchester Cancer Research Centre, School of Medical Sciences, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre, The University of Manchester, Manchester, United Kingdom
| | - Henk J M M Mutsaerts
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Amsterdam, Netherlands
| | - Hugo Vrenken
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Amsterdam, Netherlands
| | - Jan C de Munck
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Amsterdam, Netherlands
| | - Philip C De Witt Hamer
- Cancer Center Amsterdam, Brain Tumor Center, Department of Neurosurgery, Amsterdam UMC, Amsterdam, Netherlands
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23
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Mehranian A, McGinnity CJ, Neji R, Prieto C, Hammers A, De Vita E, Reader AJ. Motion‐corrected and high‐resolution anatomically assisted (MOCHA) reconstruction of arterial spin labeling MRI. Magn Reson Med 2020; 84:1306-1320. [PMID: 32125015 PMCID: PMC8614125 DOI: 10.1002/mrm.28205] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2019] [Revised: 01/12/2020] [Accepted: 01/18/2020] [Indexed: 11/30/2022]
Abstract
Purpose A model‐based reconstruction framework is proposed for motion‐corrected and high‐resolution anatomically assisted (MOCHA) reconstruction of arterial spin labeling (ASL) data. In this framework, all low‐resolution ASL control‐label pairs are used to reconstruct a single high‐resolution cerebral blood flow (CBF) map, corrected for rigid‐motion, point‐spread‐function blurring and partial volume effect. Methods Six volunteers were recruited for CBF imaging using pseudo‐continuous ASL labeling, two‐shot 3D gradient and spin‐echo sequences and high‐resolution T1‐weighted MRI. For 2 volunteers, high‐resolution scans with double and triple resolution in the partition direction were additionally collected. Simulations were designed for evaluations against a high‐resolution ground‐truth CBF map, including a simulated hyperperfused lesion and hyperperfusion/hypoperfusion abnormalities. The MOCHA technique was compared with standard reconstruction and a 3D linear regression partial‐volume effect correction method and was further evaluated for acquisitions with reduced control‐label pairs and k‐space undersampling. Results The MOCHA reconstructions of low‐resolution ASL data showed enhanced image quality, particularly in the partition direction. In simulations, both MOCHA and 3D linear regression provided more accurate CBF maps than the standard reconstruction; however, MOCHA resulted in the lowest errors and well delineated the abnormalities. The MOCHA reconstruction of standard‐resolution in vivo data showed good agreement with higher‐resolution scans requiring 4‐times and 9‐times longer acquisitions. The MOCHA reconstruction was found to be robust for 4‐times‐accelerated ASL acquisitions, achieved by reduced control‐label pairs or k‐space undersampling. Conclusion The MOCHA reconstruction reduces partial‐volume effect by direct reconstruction of CBF maps in the high‐resolution space of the corresponding anatomical image, incorporating motion correction and point spread function modeling. Following further evaluation, MOCHA should promote the clinical application of ASL.
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Affiliation(s)
- Abolfazl Mehranian
- Department of Biomedical Engineering School of Biomedical Engineering and Imaging Sciences King’s College London London United Kingdom
| | - Colm J. McGinnity
- School of Biomedical Engineering and Imaging Sciences, King’s College London and King’s College London & Guy’s and St. Thomas’ PET Centre, St. Thomas’ Hospital London United Kingdom
| | - Radhouene Neji
- Department of Biomedical Engineering School of Biomedical Engineering and Imaging Sciences King’s College London London United Kingdom
- MR Research Collaborations Siemens Healthcare Frimley United Kingdom
| | - Claudia Prieto
- Department of Biomedical Engineering School of Biomedical Engineering and Imaging Sciences King’s College London London United Kingdom
| | - Alexander Hammers
- School of Biomedical Engineering and Imaging Sciences, King’s College London and King’s College London & Guy’s and St. Thomas’ PET Centre, St. Thomas’ Hospital London United Kingdom
| | - Enrico De Vita
- Department of Biomedical Engineering School of Biomedical Engineering and Imaging Sciences King’s College London London United Kingdom
| | - Andrew J. Reader
- Department of Biomedical Engineering School of Biomedical Engineering and Imaging Sciences King’s College London London United Kingdom
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24
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Mutsaerts HJMM, Petr J, Bokkers RPH, Lazar RM, Marshall RS, Asllani I. Spatial coefficient of variation of arterial spin labeling MRI as a cerebrovascular correlate of carotid occlusive disease. PLoS One 2020; 15:e0229444. [PMID: 32101567 PMCID: PMC7043776 DOI: 10.1371/journal.pone.0229444] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2019] [Accepted: 02/06/2020] [Indexed: 12/13/2022] Open
Abstract
Clinical interpretation of arterial spin labeling (ASL) perfusion MRI in cerebrovascular disease remains challenging mainly because of the method's sensitivity to concomitant contributions from both intravascular and tissue compartments. While acquisition of multi-delay images can differentiate between the two contributions, the prolonged acquisition is prone to artifacts and not practical for clinical applications. Here, the utility of the spatial coefficient of variation (sCoV) of a single-delay ASL image as a marker of the intravascular contribution was evaluated by testing the hypothesis that sCoV can detect the effects of differences in label arrival times between ipsi- and contra-lateral hemispheres even in the absence of a hemispheric difference in CBF. Hemispheric lateralization values for sCoV and CBF were computed from ASL images acquired on 28 patients (age 73.9 ± 10.2 years, 8 women) with asymptomatic unilateral carotid occlusion. The results showed that sCoV lateralization predicted the occluded side with 96.4% sensitivity, missing only 1 patient. In contrast, the sensitivity of the CBF lateralization was 71.4%, with 8 patients showing no difference in CBF between hemispheres. The findings demonstrate the potential clinical utility of sCoV as a cerebrovascular correlate of large vessel disease. Using sCoV in tandem with CBF, vascular information can be obtained in image processing without the need for additional scan-time.
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Affiliation(s)
- Henri J. M. M. Mutsaerts
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Center, Location VUMC, Amsterdam, The Netherlands
- Department of Biomedical Engineering, Institute Hall, Rochester Institute of Technology (RIT), Rochester, New York, NY, United States of America
| | - Jan Petr
- Department of Biomedical Engineering, Institute Hall, Rochester Institute of Technology (RIT), Rochester, New York, NY, United States of America
- Helmholtz-Zentrum Dresden-Rossendorf, Institute of Radiopharmaceutical Cancer Research, Dresden, Germany
| | - Reinoud P. H. Bokkers
- Department of Radiology, Medical Imaging Center, University Medical Center Groningen, University of Groningen, Groningen, Netherlands
| | - Ronald M. Lazar
- Department of Neurology, UAB, McKnight Brain Institute, University of Alabama at Birmingham, Birmingham, AL, United States of America
- Department of Neurology, Columbia University Irving Medical Center, New York, NY, United States of America
| | - Randolph S. Marshall
- Department of Neurology, Columbia University Irving Medical Center, New York, NY, United States of America
| | - Iris Asllani
- Department of Biomedical Engineering, Institute Hall, Rochester Institute of Technology (RIT), Rochester, New York, NY, United States of America
- Clinical Imaging Sciences Centre, Neuroscience, University of Sussex, Brighton, United Kingdom
- * E-mail:
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25
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Boxer AL, Gold M, Feldman H, Boeve BF, Dickinson SLJ, Fillit H, Ho C, Paul R, Pearlman R, Sutherland M, Verma A, Arneric SP, Alexander BM, Dickerson BC, Dorsey ER, Grossman M, Huey ED, Irizarry MC, Marks WJ, Masellis M, McFarland F, Niehoff D, Onyike CU, Paganoni S, Panzara MA, Rockwood K, Rohrer JD, Rosen H, Schuck RN, Soares HD, Tatton N. New directions in clinical trials for frontotemporal lobar degeneration: Methods and outcome measures. Alzheimers Dement 2020; 16:131-143. [PMID: 31668596 PMCID: PMC6949386 DOI: 10.1016/j.jalz.2019.06.4956] [Citation(s) in RCA: 39] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
INTRODUCTION Frontotemporal lobar degeneration (FTLD) is the most common form of dementia for those under 60 years of age. Increasing numbers of therapeutics targeting FTLD syndromes are being developed. METHODS In March 2018, the Association for Frontotemporal Degeneration convened the Frontotemporal Degeneration Study Group meeting in Washington, DC, to discuss advances in the clinical science of FTLD. RESULTS Challenges exist for conducting clinical trials in FTLD. Two of the greatest challenges are (1) the heterogeneity of FTLD syndromes leading to difficulties in efficiently measuring treatment effects and (2) the rarity of FTLD disorders leading to recruitment challenges. DISCUSSION New personalized endpoints that are clinically meaningful to individuals and their families should be developed. Personalized approaches to analyzing MRI data, development of new fluid biomarkers and wearable technologies will help to improve the power to detect treatment effects in FTLD clinical trials and enable new, clinical trial designs, possibly leveraged from the experience of oncology trials. A computational visualization and analysis platform that can support novel analyses of combined clinical, genetic, imaging, biomarker data with other novel modalities will be critical to the success of these endeavors.
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Affiliation(s)
- Adam L. Boxer
- Memory and Aging Center, Department of Neurology, University of California San Francisco, San Francisco, CA
| | | | - Howard Feldman
- Department of Neurosciences, University of California San Diego, San Diego, CA
| | | | | | | | - Carole Ho
- Denali Therapeutics, San Francisco, CA
| | | | | | | | | | | | | | | | - Earl Ray Dorsey
- Center for Health and Technology, University of Rochester, Rochester, NY
| | - Murray Grossman
- Department of Neurology, University of Pennsylvania, Philadelphia, PA
| | - Edward D. Huey
- Departments of Psychiatry and Neurology, Columbia University, NY
| | | | - William J. Marks
- Clinical Neurology, Verily Life Sciences, South San Francisco, CA
| | - Mario Masellis
- Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, University of Toronto, ON, Canada; Department of Medicine (Neurology), Sunnybrook Health Sciences Centre, University of Toronto, ON, Canada
| | | | - Debra Niehoff
- Association for Frontotemporal Degeneration, Radnor, PA
| | - Chiadi U. Onyike
- Department Geriatric Psychiatry and Neuropsychiatry, Johns Hopkins University, Baltimore, MD
| | - Sabrina Paganoni
- Healey Center for ALS, Massachusetts General Hospital, Boston, MA
| | | | - Kenneth Rockwood
- Division of Geriatric Medicine, Dalhousie University, Halifax, NS
| | - Jonathan D. Rohrer
- Dementia Research Centre, UCL Institute of Neurology, Queen Square, London, UK
| | - Howard Rosen
- Memory and Aging Center, Department of Neurology, University of California San Francisco, San Francisco, CA
| | - Robert N. Schuck
- Office of Clinical Pharmacology, Center for Drug Evaluation and Research, FDA, Silver Spring, MD
| | | | - Nadine Tatton
- Association for Frontotemporal Degeneration, Radnor, PA
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26
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Nery F, Buchanan CE, Harteveld AA, Odudu A, Bane O, Cox EF, Derlin K, Gach HM, Golay X, Gutberlet M, Laustsen C, Ljimani A, Madhuranthakam AJ, Pedrosa I, Prasad PV, Robson PM, Sharma K, Sourbron S, Taso M, Thomas DL, Wang DJJ, Zhang JL, Alsop DC, Fain SB, Francis ST, Fernández-Seara MA. Consensus-based technical recommendations for clinical translation of renal ASL MRI. MAGMA (NEW YORK, N.Y.) 2019. [PMID: 31833014 DOI: 10.1007/s10334‐019‐00800‐z] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
OBJECTIVES This study aimed at developing technical recommendations for the acquisition, processing and analysis of renal ASL data in the human kidney at 1.5 T and 3 T field strengths that can promote standardization of renal perfusion measurements and facilitate the comparability of results across scanners and in multi-centre clinical studies. METHODS An international panel of 23 renal ASL experts followed a modified Delphi process, including on-line surveys and two in-person meetings, to formulate a series of consensus statements regarding patient preparation, hardware, acquisition protocol, analysis steps and data reporting. RESULTS Fifty-nine statements achieved consensus, while agreement could not be reached on two statements related to patient preparation. As a default protocol, the panel recommends pseudo-continuous (PCASL) or flow-sensitive alternating inversion recovery (FAIR) labelling with a single-slice spin-echo EPI readout with background suppression and a simple but robust quantification model. DISCUSSION This approach is considered robust and reproducible and can provide renal perfusion images of adequate quality and SNR for most applications. If extended kidney coverage is desirable, a 2D multislice readout is recommended. These recommendations are based on current available evidence and expert opinion. Nonetheless they are expected to be updated as more data become available, since the renal ASL literature is rapidly expanding.
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Affiliation(s)
- Fabio Nery
- Developmental Imaging and Biophysics Section, UCL Great Ormond Street Institute of Child Health, London, UK
| | - Charlotte E Buchanan
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, Nottingham, UK
| | - Anita A Harteveld
- Department of Radiology, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Aghogho Odudu
- Division of Cardiovascular Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK
| | - Octavia Bane
- Translational and Molecular Imaging Institute and Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Eleanor F Cox
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, Nottingham, UK
| | - Katja Derlin
- Department of Radiology, Hannover Medical School, Hannover, Germany
| | - H Michael Gach
- Departments of Radiation Oncology, Radiology, and Biomedical Engineering, Washington University in St. Louis, St. Louis, MO, USA
| | - Xavier Golay
- Department of Brain Repair and Rehabilitation, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Marcel Gutberlet
- Department of Radiology, Hannover Medical School, Hannover, Germany
| | - Christoffer Laustsen
- MR Research Centre, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Alexandra Ljimani
- Department of Diagnostic and Interventional Radiology, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Ananth J Madhuranthakam
- Department of Radiology and Advanced Imaging Research Center, UT Southwestern Medical Center, Dallas, TX, USA
| | - Ivan Pedrosa
- Department of Radiology and Advanced Imaging Research Center, UT Southwestern Medical Center, Dallas, TX, USA
| | - Pottumarthi V Prasad
- Department of Radiology, Center for Advanced Imaging, NorthShore University Health System, Evanston, IL, USA
| | - Philip M Robson
- Translational and Molecular Imaging Institute and Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Kanishka Sharma
- Imaging Biomarkers Group, Department of Biomedical Imaging Sciences, University of Leeds, Leeds, UK
| | - Steven Sourbron
- Imaging Biomarkers Group, Department of Biomedical Imaging Sciences, University of Leeds, Leeds, UK
| | - Manuel Taso
- Division of MRI Research, Department of Radiology, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA
| | - David L Thomas
- Department of Brain Repair and Rehabilitation, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Danny J J Wang
- Stevens Neuroimaging and Informatics Institute, University of Southern California, Los Angeles, CA, USA
| | - Jeff L Zhang
- A.A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, USA
| | - David C Alsop
- Division of MRI Research, Department of Radiology, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA
| | - Sean B Fain
- Departments of Medical Physics, Radiology, and Biomedical Engineering, University of Wisconsin, Madison, Madison, USA
| | - Susan T Francis
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, Nottingham, UK
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27
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Nery F, Buchanan CE, Harteveld AA, Odudu A, Bane O, Cox EF, Derlin K, Gach HM, Golay X, Gutberlet M, Laustsen C, Ljimani A, Madhuranthakam AJ, Pedrosa I, Prasad PV, Robson PM, Sharma K, Sourbron S, Taso M, Thomas DL, Wang DJJ, Zhang JL, Alsop DC, Fain SB, Francis ST, Fernández-Seara MA. Consensus-based technical recommendations for clinical translation of renal ASL MRI. MAGNETIC RESONANCE MATERIALS IN PHYSICS BIOLOGY AND MEDICINE 2019; 33:141-161. [PMID: 31833014 PMCID: PMC7021752 DOI: 10.1007/s10334-019-00800-z] [Citation(s) in RCA: 67] [Impact Index Per Article: 13.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/05/2019] [Revised: 11/08/2019] [Accepted: 11/11/2019] [Indexed: 12/14/2022]
Abstract
Objectives This study aimed at developing technical recommendations for the acquisition, processing and analysis of renal ASL data in the human kidney at 1.5 T and 3 T field strengths that can promote standardization of renal perfusion measurements and facilitate the comparability of results across scanners and in multi-centre clinical studies. Methods An international panel of 23 renal ASL experts followed a modified Delphi process, including on-line surveys and two in-person meetings, to formulate a series of consensus statements regarding patient preparation, hardware, acquisition protocol, analysis steps and data reporting. Results Fifty-nine statements achieved consensus, while agreement could not be reached on two statements related to patient preparation. As a default protocol, the panel recommends pseudo-continuous (PCASL) or flow-sensitive alternating inversion recovery (FAIR) labelling with a single-slice spin-echo EPI readout with background suppression and a simple but robust quantification model. Discussion This approach is considered robust and reproducible and can provide renal perfusion images of adequate quality and SNR for most applications. If extended kidney coverage is desirable, a 2D multislice readout is recommended. These recommendations are based on current available evidence and expert opinion. Nonetheless they are expected to be updated as more data become available, since the renal ASL literature is rapidly expanding. Electronic supplementary material The online version of this article (10.1007/s10334-019-00800-z) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Fabio Nery
- Developmental Imaging and Biophysics Section, UCL Great Ormond Street Institute of Child Health, London, UK
| | - Charlotte E Buchanan
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, Nottingham, UK
| | - Anita A Harteveld
- Department of Radiology, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Aghogho Odudu
- Division of Cardiovascular Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK
| | - Octavia Bane
- Translational and Molecular Imaging Institute and Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Eleanor F Cox
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, Nottingham, UK
| | - Katja Derlin
- Department of Radiology, Hannover Medical School, Hannover, Germany
| | - H Michael Gach
- Departments of Radiation Oncology, Radiology, and Biomedical Engineering, Washington University in St. Louis, St. Louis, MO, USA
| | - Xavier Golay
- Department of Brain Repair and Rehabilitation, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Marcel Gutberlet
- Department of Radiology, Hannover Medical School, Hannover, Germany
| | - Christoffer Laustsen
- MR Research Centre, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Alexandra Ljimani
- Department of Diagnostic and Interventional Radiology, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Ananth J Madhuranthakam
- Department of Radiology and Advanced Imaging Research Center, UT Southwestern Medical Center, Dallas, TX, USA
| | - Ivan Pedrosa
- Department of Radiology and Advanced Imaging Research Center, UT Southwestern Medical Center, Dallas, TX, USA
| | - Pottumarthi V Prasad
- Department of Radiology, Center for Advanced Imaging, NorthShore University Health System, Evanston, IL, USA
| | - Philip M Robson
- Translational and Molecular Imaging Institute and Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Kanishka Sharma
- Imaging Biomarkers Group, Department of Biomedical Imaging Sciences, University of Leeds, Leeds, UK
| | - Steven Sourbron
- Imaging Biomarkers Group, Department of Biomedical Imaging Sciences, University of Leeds, Leeds, UK
| | - Manuel Taso
- Division of MRI Research, Department of Radiology, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA
| | - David L Thomas
- Department of Brain Repair and Rehabilitation, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Danny J J Wang
- Stevens Neuroimaging and Informatics Institute, University of Southern California, Los Angeles, CA, USA
| | - Jeff L Zhang
- A.A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, USA
| | - David C Alsop
- Division of MRI Research, Department of Radiology, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA
| | - Sean B Fain
- Departments of Medical Physics, Radiology, and Biomedical Engineering, University of Wisconsin, Madison, Madison, USA
| | - Susan T Francis
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, Nottingham, UK
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28
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Mutsaerts HJMM, Mirza SS, Petr J, Thomas DL, Cash DM, Bocchetta M, de Vita E, Metcalfe AWS, Shirzadi Z, Robertson AD, Tartaglia MC, Mitchell SB, Black SE, Freedman M, Tang-Wai D, Keren R, Rogaeva E, van Swieten J, Laforce R, Tagliavini F, Borroni B, Galimberti D, Rowe JB, Graff C, Frisoni GB, Finger E, Sorbi S, de Mendonça A, Rohrer JD, MacIntosh BJ, Masellis M. Cerebral perfusion changes in presymptomatic genetic frontotemporal dementia: a GENFI study. Brain 2019; 142:1108-1120. [PMID: 30847466 PMCID: PMC6439322 DOI: 10.1093/brain/awz039] [Citation(s) in RCA: 29] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2018] [Revised: 12/14/2018] [Accepted: 01/04/2019] [Indexed: 11/12/2022] Open
Abstract
Genetic forms of frontotemporal dementia are most commonly due to mutations in three genes, C9orf72, GRN or MAPT, with presymptomatic carriers from families representing those at risk. While cerebral blood flow shows differences between frontotemporal dementia and other forms of dementia, there is limited evidence of its utility in presymptomatic stages of frontotemporal dementia. This study aimed to delineate the cerebral blood flow signature of presymptomatic, genetic frontotemporal dementia using a voxel-based approach. In the multicentre GENetic Frontotemporal dementia Initiative (GENFI) study, we investigated cross-sectional differences in arterial spin labelling MRI-based cerebral blood flow between presymptomatic C9orf72, GRN or MAPT mutation carriers (n = 107) and non-carriers (n = 113), using general linear mixed-effects models and voxel-based analyses. Cerebral blood flow within regions of interest derived from this model was then explored to identify differences between individual gene carrier groups and to estimate a timeframe for the expression of these differences. The voxel-based analysis revealed a significant inverse association between cerebral blood flow and the expected age of symptom onset in carriers, but not non-carriers. Regions included the bilateral insulae/orbitofrontal cortices, anterior cingulate/paracingulate gyri, and inferior parietal cortices, as well as the left middle temporal gyrus. For all bilateral regions, associations were greater on the right side. After correction for partial volume effects in a region of interest analysis, the results were found to be largely driven by the C9orf72 genetic subgroup. These cerebral blood flow differences first appeared approximately 12.5 years before the expected symptom onset determined on an individual basis. Cerebral blood flow was lower in presymptomatic mutation carriers closer to and beyond their expected age of symptom onset in key frontotemporal dementia signature regions. These results suggest that arterial spin labelling MRI may be a promising non-invasive imaging biomarker for the presymptomatic stages of genetic frontotemporal dementia.
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Affiliation(s)
- Henri J M M Mutsaerts
- Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, Canada
| | - Saira S Mirza
- Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, Canada
| | - Jan Petr
- PET Center, Institute of Radiopharmaceutical Cancer Research, Helmholtz-Zentrum Dresden-Rossendorf, Dresden, Germany
| | - David L Thomas
- Institute of Neurology, University College London, London, UK
| | - David M Cash
- Institute of Neurology, University College London, London, UK
| | | | - Enrico de Vita
- Institute of Neurology, University College London, London, UK
| | - Arron W S Metcalfe
- Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, Canada
| | - Zahra Shirzadi
- Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, Canada
| | - Andrew D Robertson
- Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, Canada
| | - Maria Carmela Tartaglia
- Tanz Centre for Research in Neurodegenerative Diseases, University of Toronto, Toronto, Canada.,Memory Clinic, University Health Network, Toronto, Canada.,Division of Neurology, Department of Medicine, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Canada
| | - Sara B Mitchell
- Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, Canada.,Division of Neurology, Department of Medicine, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Canada.,L.C. Campbell Cognitive Neurology Research Unit, Sunnybrook Health Sciences Centre, Toronto, Canada
| | - Sandra E Black
- Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, Canada.,Division of Neurology, Department of Medicine, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Canada.,L.C. Campbell Cognitive Neurology Research Unit, Sunnybrook Health Sciences Centre, Toronto, Canada
| | - Morris Freedman
- Division of Neurology, Department of Medicine, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Canada.,Baycrest Centre for Geriatric Care, Toronto, Canada
| | - David Tang-Wai
- Memory Clinic, University Health Network, Toronto, Canada.,Division of Neurology, Department of Medicine, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Canada
| | - Ron Keren
- Memory Clinic, University Health Network, Toronto, Canada
| | - Ekaterina Rogaeva
- Tanz Centre for Research in Neurodegenerative Diseases, University of Toronto, Toronto, Canada
| | - John van Swieten
- Department of Neurology, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Robert Laforce
- Clinique Interdisciplinaire de Mémoire (CIME), Département des Sciences Neurologiques, CHU de Québec, Faculté de médecine, Université Laval, Québec, Canada
| | - Fabrizio Tagliavini
- Fondazione Istituto di Ricovero e Cura a Carattere Scientifico, Milan, Italy
| | - Barbara Borroni
- Department of Medical and Experimental Sciences, University of Brescia, Brescia, Italy
| | - Daniela Galimberti
- Centro Dino Ferrari, Fondazione Ca' Granda IRCCS Ospedale Policlinico, University of Milan, Milan, Italy
| | - James B Rowe
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | - Caroline Graff
- Department of Geriatric Medicine, Karolinska Institutet, Stockholm, Sweden
| | | | - Elizabeth Finger
- Department of Clinical Neurological Sciences, University of Western Ontario, London, Canada
| | - Sandro Sorbi
- Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Florence, Italy
| | | | | | - Bradley J MacIntosh
- Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, Canada
| | - Mario Masellis
- Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, Canada.,Division of Neurology, Department of Medicine, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Canada.,L.C. Campbell Cognitive Neurology Research Unit, Sunnybrook Health Sciences Centre, Toronto, Canada.,Cognitive and Movement Disorders Clinic, Sunnybrook Health Sciences Centre, Toronto, Canada
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29
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Robust single-shot acquisition of high resolution whole brain ASL images by combining time-dependent 2D CAPIRINHA sampling with spatio-temporal TGV reconstruction. Neuroimage 2019; 206:116337. [PMID: 31707191 PMCID: PMC6980903 DOI: 10.1016/j.neuroimage.2019.116337] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2019] [Revised: 09/24/2019] [Accepted: 11/04/2019] [Indexed: 12/04/2022] Open
Abstract
For ASL perfusion imaging in clinical settings the current guidelines recommends pseudo-continuous arterial spin labeling with segmented 3D readout. This combination achieves the best signal to noise ratio with reasonable resolution but is prone to motion artifacts due to the segmented readout. Motion robust single-shot 3D acquisitions suffer from image blurring due to the T2 decay of the sampled signals during the long readout. To tackle this problem, we propose an accelerated 3D-GRASE sequence with a time-dependent 2D-CAIPIRINHA sampling pattern. This has several advantages: First, the single-shot echo trains are shortened by the acceleration factor; Second, the temporal incoherence between measurements is increased; And third, the coil sensitivity maps can be estimated directly from the averaged k-space data. To obtain improved perfusion images from the undersampled time series, we developed a variational image reconstruction approach employing spatio-temporal total-generalized-variation (TGV) regularization. The proposed ASL-TGV method reduced the total acquisition time, improved the motion robustness of 3D ASL data, and the image quality of the cerebral blood flow (CBF) maps compared to those by a standard segmented approach. An evaluation was performed on 5 healthy subjects including intentional movement for 2 subjects. Single-shot whole brain CBF-maps with high resolution3.1 × 3.1 × 3 mm and image quality can be acquired in 1min 46sec. Additionally high quality CBF- and arterial transit time (ATT) -maps from single-shot multi-post-labeling delay (PLD) data can be gained with the proposed method. This method may improve the robustness of 3D ASL in clinical settings, and may be applied for perfusion fMRI.
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30
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The association between frailty and MRI features of cerebral small vessel disease. Sci Rep 2019; 9:11343. [PMID: 31383903 PMCID: PMC6683288 DOI: 10.1038/s41598-019-47731-2] [Citation(s) in RCA: 33] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2019] [Accepted: 07/23/2019] [Indexed: 12/11/2022] Open
Abstract
Frailty is a common syndrome in older individuals that is associated with poor cognitive outcome. The underlying brain correlates of frailty are unclear. The aim of this study was to investigate the association between frailty and MRI features of cerebral small vessel disease in a group of non-demented older individuals. We included 170 participants who were classified as frail (n = 30), pre-frail (n = 85) or non-frail (n = 55). The association of frailty and white matter hyperintensity volume and shape features, lacunar infarcts and cerebral perfusion was investigated by regression analyses adjusted for age and sex. Frail and pre-frail participants were older, more often female and showed higher white matter hyperintensity volume (0.69 [95%-CI 0.08 to 1.31], p = 0.03 respectively 0.43 [95%-CI: 0.04 to 0.82], p = 0.03) compared to non-frail participants. Frail participants showed a non-significant trend, and pre-frail participants showed a more complex shape of white matter hyperintensities (concavity index: 0.04 [95%-CI: 0.03 to 0.08], p = 0.03; fractal dimensions: 0.07 [95%-CI: 0.00 to 0.15], p = 0.05) compared to non-frail participants. No between group differences were found in gray matter perfusion or in the presence of lacunar infarcts. In conclusion, increased white matter hyperintensity volume and a more complex white matter hyperintensity shape may be structural brain correlates of the frailty phenotype.
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31
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de Rooij SR, Mutsaerts HJMM, Petr J, Asllani I, Caan MWA, Groot P, Nederveen AJ, Schwab M, Roseboom TJ. Late-life brain perfusion after prenatal famine exposure. Neurobiol Aging 2019; 82:1-9. [PMID: 31376728 DOI: 10.1016/j.neurobiolaging.2019.06.012] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2019] [Revised: 05/29/2019] [Accepted: 06/30/2019] [Indexed: 01/10/2023]
Abstract
Early nutritional deprivation may cause irreversible damage to the brain and seems to affect cognitive function in older age. We investigated whether prenatal undernutrition was associated with brain perfusion differences in older age. We acquired Arterial spin labeling scans in 118 Dutch famine birth cohort members. Using linear regression analyses, cerebral blood flow was compared between exposed and unexposed groups in gray matter (GM) and white matter (WM), perfusion territories, the neurodegeneration-related regions anterior and posterior cingulate cortex and precuneus. Furthermore, we compared the GM/WM ratio and the spatial coefficient of variation as a proxy of overall cerebrovascular health. The WM arterial spin labeling signal and the GM/WM ratio were significantly lower and higher, respectively, among exposed participants (-2.5 mL/100 g/min [95% CI: -4.3 to -0.8; p = 0.01] and 0.48 [0.19 to 0.76; p = 0.002], respectively). Exposed men had lower cerebral blood flow in anterior and posterior cingulate cortices (-8.0 mL/100 g/min [-15.1 to -0.9; p = 0.03]; -11.4 mL/100 g/min [-19.6 to -3.2; p = 0.02]) and higher spatial coefficient of variation (0.05 [0.00 to 0.09; p = 0.05]). The latter seemed largely mediated by higher 2h-glucose levels at age 50. Our findings suggest that prenatal undernutrition affects brain perfusion parameters providing further evidence for life-long effects of undernutrition during early brain development.
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Affiliation(s)
- Susanne R de Rooij
- Department of Clinical Epidemiology, Biostatistics and Bioinformatics, Amsterdam UMC, the Netherlands.
| | | | - Jan Petr
- Helmholtz-Zentrum Dresden-Rossendorf, Institute of Radiopharmaceutical Cancer Research, Dresden, Germany; Department of Biomedical Engineering, Rochester Institute of Technology, College of Engineering, Rochester, NY, USA
| | - Iris Asllani
- Department of Biomedical Engineering, Rochester Institute of Technology, College of Engineering, Rochester, NY, USA
| | - Matthan W A Caan
- Department of Biomedical Engineering & Physics, Amsterdam UMC, the Netherlands
| | - Paul Groot
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, the Netherlands
| | - Aart J Nederveen
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, the Netherlands
| | - Matthias Schwab
- Hans Berger Department of Neurology, Jena University Hospital, Jena, Germany
| | - Tessa J Roseboom
- Department of Clinical Epidemiology, Biostatistics and Bioinformatics, Amsterdam UMC, the Netherlands; Department of Obstetrics and Gynaecology, Amsterdam UMC, the Netherlands
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32
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Schrantee A, Solleveld MM, Schwantje H, Bruin WB, Mutsaerts HJMM, Adriaanse SM, Lucassen P, Booij J, Reneman L. Dose-dependent effects of the selective serotonin reuptake inhibitor citalopram: A combined SPECT and phMRI study. J Psychopharmacol 2019; 33:660-669. [PMID: 30887865 PMCID: PMC6572584 DOI: 10.1177/0269881119836229] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
BACKGROUND Serotonin transporter blockers, like citalopram, dose-dependently bind to the serotonin transporter. Pharmacological magnetic resonance imaging (phMRI) can be used to non-invasively monitor effects of serotonergic medication. Although previous studies showed that phMRI can measure the effect of a single dose of serotoninergic medication, it is currently unclear whether it can also detect dose-dependent effects. AIMS To investigate the dose-dependent phMRI response to citalopram and compared this with serotonin transporter occupancy, measured with single photon emission computed tomography (SPECT). METHODS Forty-five healthy females were randomized to pre-treatment with placebo, a low (4 mg) or clinically standard (16 mg) oral citalopram dose. Prior to citalopram, and 3 h after, subjects underwent SPECT scanning. Subsequently, a phMRI scan with a citalopram challenge (7.5 mg intravenously) was conducted. Change in cerebral blood flow in response to the citalopram challenge was assessed in the thalamus and occipital cortex (control region). RESULTS Citalopram dose-dependently affected serotonin transporter occupancy, as measured with SPECT. In addition, citalopram dose-dependently affected the phMRI response to intravenous citalopram in the thalamus (but not occipital cortex), but phMRI was less sensitive in distinguishing between groups than SPECT. Serotonin transporter occupancy showed a trend-significant correlation to thalamic cerebral blood flow change. CONCLUSION These results suggest that phMRI likely suffers from higher variation than SPECT, but that these techniques probably also assess different functional aspects of the serotonergic synapse; therefore phMRI could complement positron emission tomography/SPECT for measuring effects of serotonergic medication.
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Affiliation(s)
- Anouk Schrantee
- Amsterdam University Medical Centers, Academic Medical Center, Department of Radiology and Nuclear Medicine, Amsterdam, The Netherlands,Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam, The Netherlands,A Schrantee, Amsterdam University Medical Centers, Academic Medical Center, Department of Radiology and Nuclear Medicine, Meibergdreef 9, Amsterdam, 1105 AZ, The Netherlands.
| | - Michelle M Solleveld
- Amsterdam University Medical Centers, Academic Medical Center, Department of Radiology and Nuclear Medicine, Amsterdam, The Netherlands,Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam, The Netherlands
| | - Hilde Schwantje
- Amsterdam University Medical Centers, Academic Medical Center, Department of Radiology and Nuclear Medicine, Amsterdam, The Netherlands
| | - Willem B Bruin
- Amsterdam University Medical Centers, Academic Medical Center, Department of Psychiatry, Amsterdam, The Netherlands
| | - Henk-Jan MM Mutsaerts
- Amsterdam University Medical Centers, Academic Medical Center, Department of Radiology and Nuclear Medicine, Amsterdam, The Netherlands
| | - Sofie M Adriaanse
- Amsterdam University Medical Centers, Academic Medical Center, Department of Radiology and Nuclear Medicine, Amsterdam, The Netherlands
| | - Paul Lucassen
- Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam, The Netherlands
| | - Jan Booij
- Amsterdam University Medical Centers, Academic Medical Center, Department of Radiology and Nuclear Medicine, Amsterdam, The Netherlands
| | - Liesbeth Reneman
- Amsterdam University Medical Centers, Academic Medical Center, Department of Radiology and Nuclear Medicine, Amsterdam, The Netherlands
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33
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Fallatah SM, Pizzini FB, Gomez-Anson B, Magerkurth J, De Vita E, Bisdas S, Jäger HR, Mutsaerts HJMM, Golay X. A visual quality control scale for clinical arterial spin labeling images. Eur Radiol Exp 2018; 2:45. [PMID: 30569375 PMCID: PMC6300452 DOI: 10.1186/s41747-018-0073-2] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2018] [Accepted: 10/17/2018] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Image-quality assessment is a fundamental step before clinical evaluation of magnetic resonance images. The aim of this study was to introduce a visual scoring system that provides a quality control standard for arterial spin labeling (ASL) and that can be applied to cerebral blood flow (CBF) maps, as well as to ancillary ASL images. METHODS The proposed image quality control (QC) system had two components: (1) contrast-based QC (cQC), describing the visual contrast between anatomical structures; and (2) artifact-based QC (aQC), evaluating image quality of the CBF map for the presence of common types of artifacts. Three raters evaluated cQC and aQC for 158 quantitative signal targeting with alternating radiofrequency labelling of arterial regions (QUASAR) ASL scans (CBF, T1 relaxation rate, arterial blood volume, and arterial transient time). Spearman correlation coefficient (r), intraclass correlation coefficients (ICC), and receiver operating characteristic analysis were used. RESULTS Intra/inter-rater agreement ranged from moderate to excellent; inter-rater ICC was 0.72 for cQC, 0.60 for aQC, and 0.74 for the combined QC (cQC + aQC). Intra-rater ICC was 0.90 for cQC; 0.80 for aQC, and 0.90 for the combined QC. Strong correlations were found between aQC and CBF maps quality (r = 0.75), and between aQC and cQC (r = 0.70). A QC score of 18 was optimal to discriminate between high and low quality clinical scans. CONCLUSIONS The proposed QC system provided high reproducibility and a reliable threshold for discarding low quality scans. Future research should compare this visual QC system with an automatic QC system.
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Affiliation(s)
- S M Fallatah
- Department of Brain Repair and Rehabilitation, UCL Institute of Neurology, London, UK.,The National Hospital for Neurology and Neurosurgery, London, UK.,Radiology Department, King Abdualaziz Medical City, Riyadh, Saudi Arabia
| | - F B Pizzini
- Neuroradiology, University Hospital of Verona, Piazzale Stefani 1, 37126, Verona, Italy.
| | - B Gomez-Anson
- Unitat Neuroradiologia, Hospital de la Santa Creu i Sant Pau, IIB-Sant Pau, Universitat Autonoma, Barcelona, Spain
| | - J Magerkurth
- Department of Brain Repair and Rehabilitation, UCL Institute of Neurology, London, UK
| | - E De Vita
- Department of Brain Repair and Rehabilitation, UCL Institute of Neurology, London, UK.,The National Hospital for Neurology and Neurosurgery, London, UK
| | - S Bisdas
- Department of Brain Repair and Rehabilitation, UCL Institute of Neurology, London, UK.,The National Hospital for Neurology and Neurosurgery, London, UK
| | - H R Jäger
- Department of Brain Repair and Rehabilitation, UCL Institute of Neurology, London, UK.,The National Hospital for Neurology and Neurosurgery, London, UK
| | - H J M M Mutsaerts
- Radiology Department, Academic Medical Center, Amsterdam, The Netherlands.,Radiology Department, Vrije Universiteit University Medical Center, Amsterdam, The Netherlands.,Radiology Department, University Medical Center Utrecht, Utrecht, The Netherlands
| | - X Golay
- Department of Brain Repair and Rehabilitation, UCL Institute of Neurology, London, UK.,The National Hospital for Neurology and Neurosurgery, London, UK
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34
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Elvsåshagen T, Mutsaerts HJ, Zak N, Norbom LB, Quraishi SH, Pedersen PØ, Malt UF, Westlye LT, van Someren EJ, Bjørnerud A, Groote IR. Cerebral blood flow changes after a day of wake, sleep, and sleep deprivation. Neuroimage 2018; 186:497-509. [PMID: 30471387 DOI: 10.1016/j.neuroimage.2018.11.032] [Citation(s) in RCA: 55] [Impact Index Per Article: 9.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2018] [Revised: 11/01/2018] [Accepted: 11/20/2018] [Indexed: 10/27/2022] Open
Abstract
Elucidating the neurobiological effects of sleep and wake is an important goal of the neurosciences. Whether and how human cerebral blood flow (CBF) changes during the sleep-wake cycle remain to be clarified. Based on the synaptic homeostasis hypothesis of sleep and wake, we hypothesized that a day of wake and a night of sleep deprivation would be associated with gray matter resting CBF (rCBF) increases and that sleep would be associated with rCBF decreases. Thirty-eight healthy adult males (age 22.1 ± 2.5 years) underwent arterial spin labeling perfusion magnetic resonance imaging at three time points: in the morning after a regular night's sleep, the evening of the same day, and the next morning, either after total sleep deprivation (n = 19) or a night of sleep (n = 19). All analyses were adjusted for hematocrit and head motion. rCBF increased from morning to evening and decreased after a night of sleep. These effects were most prominent in bilateral hippocampus, amygdala, thalamus, and in the occipital and sensorimotor cortices. Group × time interaction analyses for evening versus next morning revealed significant interaction in bilateral lateral and medial occipital cortices and in bilateral insula, driven by rCBF increases in the sleep deprived individuals and decreases in the sleepers, respectively. Furthermore, group × time interaction analyses for first morning versus next morning showed significant effects in medial and lateral occipital cortices, in anterior cingulate gyrus, and in the insula, in both hemispheres. These effects were mainly driven by CBF increases from TP1 to TP3 in the sleep deprived individuals. There were no associations between the rCBF changes and sleep characteristics, vigilant attention, or subjective sleepiness that remained significant after adjustments for multiple analyses. Altogether, these results encourage future studies to clarify mechanisms underlying sleep-related rCBF changes.
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Affiliation(s)
- Torbjørn Elvsåshagen
- Norwegian Centre for Mental Disorders Research (NORMENT), KG Jebsen Centre for Psychosis Research, Oslo University Hospital, Norway; Department of Neurology, Oslo University Hospital, Norway; Institute of Clinical Medicine, University of Oslo, Norway.
| | - Henri Jmm Mutsaerts
- Cognitive Neurology Research Unit, Sunnybrook Health Sciences Centre, Toronto, Canada; Department of Radiology, Amsterdam University Medical Center, the Netherlands
| | - Nathalia Zak
- Norwegian Centre for Mental Disorders Research (NORMENT), KG Jebsen Centre for Psychosis Research, Oslo University Hospital, Norway
| | - Linn B Norbom
- Norwegian Centre for Mental Disorders Research (NORMENT), KG Jebsen Centre for Psychosis Research, Oslo University Hospital, Norway
| | | | - Per Ø Pedersen
- Institute of Clinical Medicine, University of Oslo, Norway
| | - Ulrik F Malt
- Institute of Clinical Medicine, University of Oslo, Norway; Department of Research and Education, Oslo University Hospital, Norway
| | - Lars T Westlye
- Norwegian Centre for Mental Disorders Research (NORMENT), KG Jebsen Centre for Psychosis Research, Oslo University Hospital, Norway; Department of Psychology, University of Oslo, Norway
| | - Eus Jw van Someren
- Department of Sleep and Cognition, Netherlands Institute for Neuroscience, Amsterdam, the Netherlands; Department of Psychiatry, Amsterdam University Medical Center, the Netherlands; Department of Integrative Neurophysiology, Amsterdam University Medical Center, the Netherlands
| | - Atle Bjørnerud
- Department of Psychology, University of Oslo, Norway; Department of Physics, University of Oslo, Norway; The Intervention Center, Oslo University Hospital, Norway
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35
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Chai Y, Chen J, Galarza C, Sluman MA, Xu B, Vu CQ, Richard E, Mulder B, Tamrazi B, Lepore N, Mutsaerts HJMM, Wood JC. CEREBRAL BLOOD FLOW AND PREDICTORS OF WHITE MATTER LESIONS IN ADULTS WITH TETRALOGY OF FALLOT. PROCEEDINGS. IEEE INTERNATIONAL SYMPOSIUM ON BIOMEDICAL IMAGING 2018; 2018:1309-1312. [PMID: 30344894 DOI: 10.1109/isbi.2018.8363812] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Abstract
Long-term outcomes for Tetralogy of Fallot (TOF) have improved dramatically in recent years, but survivors are still afflicted by cerebral damage. In this paper, we characterized the prevalence and predictors of cerebral silent infarction (SCI) and their relationship to cerebral blood flow (CBF) in 46 adult TOF patients. We calculated both whole brain and regional CBF using 2D arterial spin labeling (ASL) images, and investigated the spatial overlap between voxel-wise CBF values and white matter hyperintensities (WMHs) identified from T2-FLAIR images. SCIs were found in 83% of subjects and were predicted by the year of the patient's first cardiac surgery and patient's age at scanning (combined r2 0.44). CBF was not different in brain regions prone to stroke compared with healthy white matter.
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Affiliation(s)
- Yaqiong Chai
- CIBORG laboratory, Department of Radiology, Children's Hospital Los Angeles, CA, USA.,Department of Biomedical Engineering, University of Southern California, CA, USA.,Department of Radiology, Children's Hospital Los Angeles, CA, USA
| | - Jieshen Chen
- CIBORG laboratory, Department of Radiology, Children's Hospital Los Angeles, CA, USA.,Department of Electrical Engineering, University of Southern California, CA, USA
| | - Cristina Galarza
- CIBORG laboratory, Department of Radiology, Children's Hospital Los Angeles, CA, USA.,Keck School of Medicine, University of Southern California, CA, USA
| | - Maayke A Sluman
- Department of Cardiology, Academic Medical Center, Amsterdam, The Netherlands
| | - Botian Xu
- CIBORG laboratory, Department of Radiology, Children's Hospital Los Angeles, CA, USA.,Department of Electrical Engineering, University of Southern California, CA, USA
| | - Chau Q Vu
- Department of Biomedical Engineering, University of Southern California, CA, USA.,Department of Radiology, Children's Hospital Los Angeles, CA, USA
| | - Edo Richard
- Department of Neurology, Radboud University Medical Center, Amsterdam, The Netherlands
| | - Barbara Mulder
- Department of Cardiology, Academic Medical Center, Amsterdam, The Netherlands
| | - Benita Tamrazi
- Department of Radiology, Children's Hospital Los Angeles, CA, USA
| | - Natasha Lepore
- CIBORG laboratory, Department of Radiology, Children's Hospital Los Angeles, CA, USA.,Department of Biomedical Engineering, University of Southern California, CA, USA.,Department of Radiology, Children's Hospital Los Angeles, CA, USA
| | - Henri J M M Mutsaerts
- Sunnybrook Research Institute, University of Toronto, Toronto, Canada.,Department of Radiology, Academic Medical Center, Amsterdam, The Netherlands
| | - John C Wood
- Division of Cardiology, Children's Hospital Los Angeles, CA, USA
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36
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Galimberti D, Fenoglio C, Scarpini E. Progranulin as a therapeutic target for dementia. Expert Opin Ther Targets 2018; 22:579-585. [DOI: 10.1080/14728222.2018.1487951] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Affiliation(s)
- Daniela Galimberti
- Neurodegenerative Diseases Unit, University of Milan, Centro Dino Ferrari, Fondazione Cà Granda, IRCCS Ospedale Maggiore Policlinico, Milan, Italy
| | - Chiara Fenoglio
- Neurodegenerative Diseases Unit, University of Milan, Centro Dino Ferrari, Fondazione Cà Granda, IRCCS Ospedale Maggiore Policlinico, Milan, Italy
| | - Elio Scarpini
- Neurodegenerative Diseases Unit, University of Milan, Centro Dino Ferrari, Fondazione Cà Granda, IRCCS Ospedale Maggiore Policlinico, Milan, Italy
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37
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Petr J, Mutsaerts HJMM, De Vita E, Steketee RME, Smits M, Nederveen AJ, Hofheinz F, van den Hoff J, Asllani I. Effects of systematic partial volume errors on the estimation of gray matter cerebral blood flow with arterial spin labeling MRI. MAGNETIC RESONANCE MATERIALS IN PHYSICS BIOLOGY AND MEDICINE 2018; 31:725-734. [PMID: 29916058 DOI: 10.1007/s10334-018-0691-y] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/09/2018] [Revised: 05/22/2018] [Accepted: 05/23/2018] [Indexed: 11/25/2022]
Abstract
OBJECTIVE Partial volume (PV) correction is an important step in arterial spin labeling (ASL) MRI that is used to separate perfusion from structural effects when computing the mean gray matter (GM) perfusion. There are three main methods for performing this correction: (1) GM-threshold, which includes only voxels with GM volume above a preset threshold; (2) GM-weighted, which uses voxel-wise GM contribution combined with thresholding; and (3) PVC, which applies a spatial linear regression algorithm to estimate the flow contribution of each tissue at a given voxel. In all cases, GM volume is obtained using PV maps extracted from the segmentation of the T1-weighted (T1w) image. As such, PV maps contain errors due to the difference in readout type and spatial resolution between ASL and T1w images. Here, we estimated these errors and evaluated their effect on the performance of each PV correction method in computing GM cerebral blood flow (CBF). MATERIALS AND METHODS Twenty-two volunteers underwent scanning using 2D echo planar imaging (EPI) and 3D spiral ASL. For each PV correction method, GM CBF was computed using PV maps simulated to contain estimated errors due to spatial resolution mismatch and geometric distortions which are caused by the mismatch in readout between ASL and T1w images. Results were analyzed to assess the effect of each error on the estimation of GM CBF from ASL data. RESULTS Geometric distortion had the largest effect on the 2D EPI data, whereas the 3D spiral was most affected by the resolution mismatch. The PVC method outperformed the GM-threshold even in the presence of combined errors from resolution mismatch and geometric distortions. The quantitative advantage of PVC was 16% without and 10% with the combined errors for both 2D and 3D ASL. Consistent with theoretical expectations, for error-free PV maps, the PVC method extracted the true GM CBF. In contrast, GM-weighted overestimated GM CBF by 5%, while GM-threshold underestimated it by 16%. The presence of PV map errors decreased the calculated GM CBF for all methods. CONCLUSION The quality of PV maps presents no argument for the preferential use of the GM-threshold method over PVC in the clinical application of ASL.
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Affiliation(s)
- Jan Petr
- Helmholtz-Zentrum Dresden-Rossendorf, Institute of Radiopharmaceutical Cancer Research, Dresden, Germany.
- Department of Biomedical Engineering, Rochester Institute of Technology, Rochester, NY, USA.
| | - Henri J M M Mutsaerts
- Department of Biomedical Engineering, Rochester Institute of Technology, Rochester, NY, USA
- Sunnybrook Research Institute, Toronto, Canada
- Department of Radiology, Academic Medical Center Amsterdam, Amsterdam, The Netherlands
- Department of Radiology, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Enrico De Vita
- Lysholm Department of Neuroradiology, National Hospital for Neurology and Neurosurgery, London, UK
- Department of Biomedical Engineering, School of Biomedical Engineering and Imaging Sciences, Kings College London, Kings Health Partners, St Thomas Hospital, London, UK
| | - Rebecca M E Steketee
- Department of Radiology and Nuclear Medicine, Erasmus MC-University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Marion Smits
- Department of Radiology and Nuclear Medicine, Erasmus MC-University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Aart J Nederveen
- Department of Radiology, Academic Medical Center Amsterdam, Amsterdam, The Netherlands
| | - Frank Hofheinz
- Helmholtz-Zentrum Dresden-Rossendorf, Institute of Radiopharmaceutical Cancer Research, Dresden, Germany
| | - Jörg van den Hoff
- Helmholtz-Zentrum Dresden-Rossendorf, Institute of Radiopharmaceutical Cancer Research, Dresden, Germany
- Department of Nuclear Medicine, University Hospital Carl Gustav Carus, Technical University Dresden, Dresden, Germany
| | - Iris Asllani
- Department of Biomedical Engineering, Rochester Institute of Technology, Rochester, NY, USA
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