A comparison of phase imaging and quantitative susceptibility mapping in the imaging of multiple sclerosis lesions at ultrahigh field.
OBJECTIVE
The aim of this study was to compare the use of high-resolution phase and QSM images acquired at ultra-high field in the investigation of multiple sclerosis (MS) lesions with peripheral rings, and to discuss their usefulness for drawing inferences about underlying tissue composition.


METHODS
Thirty-nine Subjects were scanned at 7 T, using 3D T 2*-weighted and T 1-weighted sequences. Phase images were then unwrapped and filtered, and quantitative susceptibility maps were generated using a thresholded k-space division method. Lesions were compared visually and using a 1D profiling algorithm.


RESULTS
Lesions displaying peripheral rings in the phase images were identified in 10 of the 39 subjects. Dipolar projections were apparent in the phase images outside of the extent of several of these lesions; however, QSM images showed peripheral rings without such projections. These projections appeared ring-like in a small number of phase images where no ring was observed in QSM. 1D profiles of six well-isolated example lesions showed that QSM contrast corresponds more closely to the magnitude images than phase contrast.


CONCLUSIONS
Phase images contain dipolar projections, which confounds their use in the investigation of tissue composition in MS lesions. Quantitative susceptibility maps correct these projections, providing insight into the composition of MS lesions showing peripheral rings.
Brain Imaging and Analysis Centre, Duke University, Durham, NC, 27710, USA.|Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham, NG7 2RD, UK.
Matthew John
http://orcid.org/0000-0002-3474-6949
MJ
Cronin
Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham, NG7 2RD, UK.
Samuel
S
Wharton
Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham, NG7 2RD, UK.|Department of Medical Imaging, Faculty of Allied Health Sciences, Hashemite University, Zarqa, Jordan.
Ali
A
Al-Radaideh
Sir Peter Mansfield Imaging Centre, Queens Medical Centre, University of Nottingham, Nottingham, NG7 2RD, UK.
Cris
C
Constantinescu
Sir Peter Mansfield Imaging Centre, Queens Medical Centre, University of Nottingham, Nottingham, NG7 2RD, UK.
Nikos
N
Evangelou
Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham, NG7 2RD, UK.
Richard
R
Bowtell
Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham, NG7 2RD, UK. penny.gowland@nottingham.ac.uk.
Penny Anne
PA
Gowland
D000328:Adult; D000465:Algorithms; D001931:Brain Mapping / Q000379:methods; D015331:Cohort Studies; D005583:Fourier Analysis; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods; D007091:Image Processing, Computer-Assisted; D007501:Iron / Q000737:chemistry; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008875:Middle Aged; D009103:Multiple Sclerosis / Q000000981:diagnostic imaging* / Q000473:pathology; D009186:Myelin Sheath / Q000737:chemistry; D059629:Signal-To-Noise Ratio; D066127:White Matter / Q000000981:diagnostic imaging / Q000473:pathology; D055815:Young Adult
D007501:Iron
Iron; Magnetic resonance imaging; Multiple sclerosis; Myelin; White matter