Comparison of Neurite Orientation Dispersion and Density Imaging and Two-Compartment Spherical Mean Technique Parameter Maps in Multiple Sclerosis

Background: Neurite orientation dispersion and density imaging (NODDI) and the spherical mean technique (SMT) are diffusion MRI methods providing metrics with sensitivity to similar characteristics of white matter microstructure. There has been limited comparison of changes in NODDI and SMT paramete...

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Veröffentlicht in:Frontiers in neurology Jg. 12; S. 662855
Hauptverfasser: Johnson, Daniel, Ricciardi, Antonio, Brownlee, Wallace, Kanber, Baris, Prados, Ferran, Collorone, Sara, Kaden, Enrico, Toosy, Ahmed, Alexander, Daniel C., Gandini Wheeler-Kingshott, Claudia A. M., Ciccarelli, Olga, Grussu, Francesco
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Switzerland Frontiers Media S.A 14.06.2021
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ISSN:1664-2295, 1664-2295
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Zusammenfassung:Background: Neurite orientation dispersion and density imaging (NODDI) and the spherical mean technique (SMT) are diffusion MRI methods providing metrics with sensitivity to similar characteristics of white matter microstructure. There has been limited comparison of changes in NODDI and SMT parameters due to multiple sclerosis (MS) pathology in clinical settings. Purpose: To compare group-wise differences between healthy controls and MS patients in NODDI and SMT metrics, investigating associations with disability and correlations with diffusion tensor imaging (DTI) metrics. Methods: Sixty three relapsing-remitting MS patients were compared to 28 healthy controls. NODDI and SMT metrics corresponding to intracellular volume fraction (v in ), orientation dispersion (ODI and ODE), diffusivity (D) (SMT only) and isotropic volume fraction (v iso ) (NODDI only) were calculated from diffusion MRI data, alongside DTI metrics (fractional anisotropy, FA; axial/mean/radial diffusivity, AD/MD/RD). Correlations between all pairs of MRI metrics were calculated in normal-appearing white matter (NAWM). Associations with expanded disability status scale (EDSS), controlling for age and gender, were evaluated. Patient-control differences were assessed voxel-by-voxel in MNI space controlling for age and gender at the 5% significance level, correcting for multiple comparisons. Spatial overlap of areas showing significant differences were compared using Dice coefficients. Results: NODDI and SMT show significant associations with EDSS (standardised beta coefficient −0.34 in NAWM and −0.37 in lesions for NODDI v in ; 0.38 and −0.31 for SMT ODE and v in in lesions; p < 0.05). Significant correlations in NAWM are observed between DTI and NODDI/SMT metrics. NODDI v in and SMT v in strongly correlated ( r = 0.72, p < 0.05), likewise NODDI ODI and SMT ODE ( r = −0.80, p < 0.05). All DTI, NODDI and SMT metrics detect widespread differences between patients and controls in NAWM (12.57% and 11.90% of MNI brain mask for SMT and NODDI v in , Dice overlap of 0.42). Data Conclusion: SMT and NODDI detect significant differences in white matter microstructure between MS patients and controls, concurring on the direction of these changes, providing consistent descriptors of tissue microstructure that correlate with disability and show alterations beyond focal damage. Our study suggests that NODDI and SMT may play a role in monitoring MS in clinical trials and practice.
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Reviewed by: Henrik Lundell, Copenhagen University Hospital, Denmark; Nagesh Adluru, University of Wisconsin-Madison, United States; Thijs Dhollander, Royal Children's Hospital, Australia
These authors have contributed equally to this work
Edited by: Itamar Ronen, Leiden University Medical Center, Netherlands
This article was submitted to Applied Neuroimaging, a section of the journal Frontiers in Neurology
ISSN:1664-2295
1664-2295
DOI:10.3389/fneur.2021.662855