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Comparison of arterial spin labeling registration strategies in the multi‐center GENetic frontotemporal dementia initiative (GENFI)
Author(s) -
Mutsaerts Henri J.M.M.,
Petr Jan,
Thomas David L.,
De Vita Enrico,
Cash David M.,
van Osch Matthias J.P.,
Golay Xavier,
Groot Paul F.C.,
Ourselin Sebastien,
van Swieten John,
Laforce Robert,
Tagliavini Fabrizio,
Borroni Barbara,
Galimberti Daniela,
Rowe James B.,
Graff Caroline,
Pizzini Francesca B.,
Finger Elizabeth,
Sorbi Sandro,
Castelo Branco Miguel,
Rohrer Jonathan D.,
Masellis Mario,
MacIntosh Bradley J.
Publication year - 2018
Publication title -
journal of magnetic resonance imaging
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.563
H-Index - 160
eISSN - 1522-2586
pISSN - 1053-1807
DOI - 10.1002/jmri.25751
Subject(s) - image registration , cerebral blood flow , masking (illustration) , computer science , artificial intelligence , nuclear medicine , pattern recognition (psychology) , medicine , image (mathematics) , art , visual arts
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.