TY - JOUR
T1 - Comparison of arterial spin labeling registration strategies in the multi-center GENetic frontotemporal dementia initiative (GENFI)
AU - GENFI investigators
AU - Mutsaerts, Henri J.M.M.
AU - Petr, Jan
AU - Thomas, David L.
AU - De Vita, Enrico
AU - Cash, David M.
AU - van Osch, Matthias J.P.
AU - Golay, Xavier
AU - Groot, Paul F.C.
AU - Ourselin, Sebastien
AU - van Swieten, John
AU - Laforce, Robert
AU - Tagliavini, Fabrizio
AU - Borroni, Barbara
AU - Galimberti, Daniela
AU - Rowe, James B.
AU - Graff, Caroline
AU - Pizzini, Francesca B.
AU - Finger, Elizabeth
AU - Sorbi, Sandro
AU - Castelo Branco, Miguel
AU - Rohrer, Jonathan D.
AU - Masellis, Mario
AU - MacIntosh, Bradley J.
AU - Rossor, Martin
AU - Fox, Nick
AU - Warren, Jason
AU - Bocchetta, Martina
AU - Dick, Katrina
AU - Pievani, Michela
AU - Ghidoni, Roberta
AU - Benussi, Luisa
AU - Padovani, Alessandro
AU - Cosseddu, Maura
AU - Mendonça, Alexandre
AU - Frisoni, Giovanni
AU - Premi, Enrico
AU - Archetti, Silvana
AU - Scarpini, Elio
AU - Fumagalli, Giorgio
AU - Arighi, Andrea
AU - Fenoglio, Chiara
AU - Prioni, Sara
AU - Redaelii, Veronica
AU - Grisoli, Marina
AU - Tiraboschi, Pietro
AU - Black, Sandra
AU - Rogaeva, Ekaterina
AU - Freedman, Morris
AU - Tartaglia, Maria Carmela
AU - Maruta, Carolina
N1 - Funding Information:
Contract grant sponsor: the Wellcome Trust; contract grant number: 103838 The authors thank D. Marcus and R. Herrick of Radiolog-ics for their support in setting up of the GENFI XNAT database and A.D. Robertson, PhD for providing the BET masks. The authors express their gratitude to the participants and their families for taking part in the GENFI, and thank the GENFI investigators: Martin Rossor, Nick Fox, Jason Warren, Martina Bocchetta, Katrina Dick, Michela Pievani, Roberta Ghidoni, Luisa Benussi, Alessandro Pado-vani, Maura Cosseddu, Alexandre Mendonc¸a, Giovanni Frisoni, Enrico Premi, Silvana Archetti, Elio Scarpini, Giorgio Fumagalli, Andrea Arighi, Chiara Fenoglio, Sara Prioni, Veronica Redaelii, Marina Grisoli, Pietro Tiraboschi, Sandra Black, Ekaterina Rogaeva, Morris Freedman, Maria Carmela Tartaglia, David Tang-Wai, Ron Keren, Jessica Panman, Lieke Meeter, Lize Jiskoot, Rick van Minkelen, Gemma Lombardi, Cristina Polito, Benedetta Nacmias, Vesna Jelic, Christin Andersson, Linn Oijerstedt€ , Marie Fallstr€om, Hakan Thonberg, Ana Verdelho, Carolina Maruta. Funding: This study was carried out within the context of the GENFI, which was supported by the UK Medical Research Council, the Italian Ministry of Health, and the Canadian Institutes of Health Research as part of a Centres of Excellence in Neurodegeneration grant. J.D.R. and M.R. acknowledge the support of the National Institute for Health Research Queen Square Dementia Biomedical Research Unit, Leonard Wolfson Experimental Neurology Centre, the Brain Research Trust, and the University College London Hospitals NHS Trust Biomedical Research Centre. CG acknowledges the support of Swedish Brain Power. H.M. and M.M. acknowledge the support of the Weston Brain Institute. B.M. and H.M. acknowledge the support of the Canadian Partnership for Stroke Recovery. D.T., E.V., D.C., X.G., M.R. and J.R. acknowledge the support of the UK Department of Health’s NIHR Biomedical Research Centres funding scheme. J.B.R is supported by the Wellcome Trust. M.M. acknowledges the support from the Department of Medicine at Sunnybrook Health Sciences Centre and University of Toronto, and from the Sunnybrook Foundation. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Funding Information:
Contract grant sponsor: the Wellcome Trust; contract grant number: 103838 The authors thank D. Marcus and R. Herrick of Radiologics for their support in setting up of the GENFI XNAT database and A.D. Robertson, PhD for providing the BET masks. The authors express their gratitude to the participants and their families for taking part in the GENFI, and thank the GENFI investigators: Martin Rossor, Nick Fox, Jason Warren, Martina Bocchetta, Katrina Dick, Michela Pievani, Roberta Ghidoni, Luisa Benussi, Alessandro Padovani, Maura Cosseddu, Alexandre Mendon?a, Giovanni Frisoni, Enrico Premi, Silvana Archetti, Elio Scarpini, Giorgio Fumagalli, Andrea Arighi, Chiara Fenoglio, Sara Prioni, Veronica Redaelii, Marina Grisoli, Pietro Tiraboschi, Sandra Black, Ekaterina Rogaeva, Morris Freedman, Maria Carmela Tartaglia, David Tang-Wai, Ron Keren, Jessica Panman, Lieke Meeter, Lize Jiskoot, Rick van Minkelen, Gemma Lombardi, Cristina Polito, Benedetta Nacmias, Vesna Jelic, Christin Andersson, Linn ?ijerstedt, Marie Fallstr?m, Hakan Thonberg, Ana Verdelho, Carolina Maruta. Funding: This study was carried out within the context of the GENFI, which was supported by the UK Medical Research Council, the Italian Ministry of Health, and the Canadian Institutes of Health Research as part of a Centres of Excellence in Neurodegeneration grant. J.D.R. and M.R. acknowledge the support of the National Institute for Health Research Queen Square Dementia Biomedical Research Unit, Leonard Wolfson Experimental Neurology Centre, the Brain Research Trust, and the University College London Hospitals NHS Trust Biomedical Research Centre. CG acknowledges the support of Swedish Brain Power. H.M. and M.M. acknowledge the support of the Weston Brain Institute. B.M. and H.M. acknowledge the support of the Canadian Partnership for Stroke Recovery. D.T., E.V., D.C., X.G., M.R. and J.R. acknowledge the support of the UK Department of Health's NIHR Biomedical Research Centres funding scheme. J.B.R is supported by the Wellcome Trust. M.M. acknowledges the support from the Department of Medicine at Sunnybrook Health Sciences Centre and University of Toronto, and from the Sunnybrook Foundation. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Publisher Copyright:
© 2017 International Society for Magnetic Resonance in Medicine
PY - 2018/1
Y1 - 2018/1
N2 - Purpose: To compare registration strategies to align arterial spin labeling (ASL) with 3D T1-weighted (T1w) images, with the goal of reducing the between-subject variability of cerebral blood flow (CBF) images. Materials and Methods: Multi-center 3T ASL data were collected at eight sites with four different sequences in the multi-center GENetic Frontotemporal dementia Initiative (GENFI) study. In a total of 48 healthy controls, we compared the following image registration options: (I) which images to use for registration (perfusion-weighted images [PWI] to the segmented gray matter (GM) probability map (pGM) (CBF-pGM) or M0 to T1w (M0-T1w); (II) which transformation to use (rigid-body or non-rigid); and (III) whether to mask or not (no masking, M0-based FMRIB software library Brain Extraction Tool [BET] masking). In addition to visual comparison, we quantified image similarity using the Pearson correlation coefficient (CC), and used the Mann-Whitney U rank sum test. Results: CBF-pGM outperformed M0-T1w (CC improvement 47.2% ± 22.0%; P < 0.001), and the non-rigid transformation outperformed rigid-body (20.6% ± 5.3%; P < 0.001). Masking only improved the M0-T1w rigid-body registration (14.5% ± 15.5%; P = 0.007). Conclusion: The choice of image registration strategy impacts ASL group analyses. The non-rigid transformation is promising but requires validation. CBF-pGM rigid-body registration without masking can be used as a default strategy. In patients with expansive perfusion deficits, M0-T1w may outperform CBF-pGM in sequences with high effective spatial resolution. BET-masking only improves M0-T1w registration when the M0 image has sufficient contrast. Level of Evidence: 1. Technical Efficacy: Stage 1. J. Magn. Reson. Imaging 2018;47:131–140.
AB - Purpose: To compare registration strategies to align arterial spin labeling (ASL) with 3D T1-weighted (T1w) images, with the goal of reducing the between-subject variability of cerebral blood flow (CBF) images. Materials and Methods: Multi-center 3T ASL data were collected at eight sites with four different sequences in the multi-center GENetic Frontotemporal dementia Initiative (GENFI) study. In a total of 48 healthy controls, we compared the following image registration options: (I) which images to use for registration (perfusion-weighted images [PWI] to the segmented gray matter (GM) probability map (pGM) (CBF-pGM) or M0 to T1w (M0-T1w); (II) which transformation to use (rigid-body or non-rigid); and (III) whether to mask or not (no masking, M0-based FMRIB software library Brain Extraction Tool [BET] masking). In addition to visual comparison, we quantified image similarity using the Pearson correlation coefficient (CC), and used the Mann-Whitney U rank sum test. Results: CBF-pGM outperformed M0-T1w (CC improvement 47.2% ± 22.0%; P < 0.001), and the non-rigid transformation outperformed rigid-body (20.6% ± 5.3%; P < 0.001). Masking only improved the M0-T1w rigid-body registration (14.5% ± 15.5%; P = 0.007). Conclusion: The choice of image registration strategy impacts ASL group analyses. The non-rigid transformation is promising but requires validation. CBF-pGM rigid-body registration without masking can be used as a default strategy. In patients with expansive perfusion deficits, M0-T1w may outperform CBF-pGM in sequences with high effective spatial resolution. BET-masking only improves M0-T1w registration when the M0 image has sufficient contrast. Level of Evidence: 1. Technical Efficacy: Stage 1. J. Magn. Reson. Imaging 2018;47:131–140.
KW - Arterial spin labeling
KW - Cerebral blood flow
KW - Image registration
UR - http://www.scopus.com/inward/record.url?scp=85019064293&partnerID=8YFLogxK
U2 - 10.1002/jmri.25751
DO - 10.1002/jmri.25751
M3 - Article
C2 - 28480617
AN - SCOPUS:85019064293
SN - 1053-1807
VL - 47
SP - 131
EP - 140
JO - Journal of Magnetic Resonance Imaging
JF - Journal of Magnetic Resonance Imaging
IS - 1
ER -