Reduced neurite density in the brain and cervical spinal cord in relapsing–remitting multiple sclerosis: A NODDI study

Collorone, Sara; Cawley, Niamh; Grussu, Francesco; Prados, Ferrán; Tona, Francesca; Calvi, Alberto; Kanber, Baris; Schneider, Torben; Kipp, Lucas; Zhang, Hui; Alexander, Daniel C.; Thompson, Alan J.; Toosy, Ahmed; Wheeler-Kingshott, C; Ciccarelli, Olga

doi:10.1177/1352458519885107

Cited by 54 publications

(61 citation statements)

References 37 publications

(75 reference statements)

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“…For intraneurite volume fraction v in , our results point toward reduction in this metric in both lesions and NAWM in RRMS patients compared with healthy controls. Such reductions are consistent with previous findings (20,21,23,24), and may be indicative of diffuse axonal loss as well as secondary demyelination (19).…”

Section: Noddi Resultssupporting

confidence: 92%

“…Abnormal DTI measures are seen in both lesions and so-called normal appearing white matter (NAWM) (featuring no obvious pathology on conventional MRI scanning) (16)(17)(18). There is evidence that validates the use of NODDI in MS (19)(20)(21), which suggest that while FA might be the most sensitive metric to detect abnormalities, NODDI metrics are able to detect areas of abnormality where FA is normal (22,23). Investigations into NODDI in MS have generally concluded that intra-neurite volume fraction decreases in both lesions and NAWM (20,21,24) whilst findings on orientation dispersion vary (23,24).…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2021

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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 (vin), orientation dispersion (ODI and ODE), diffusivity (D) (SMT only) and isotropic volume fraction (viso) (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 vin; 0.38 and −0.31 for SMT ODE and vin in lesions; p < 0.05). Significant correlations in NAWM are observed between DTI and NODDI/SMT metrics. NODDI vin and SMT vin 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 vin, 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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Section: Noddi Resultssupporting

confidence: 92%

Section: Introductionmentioning

confidence: 99%

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

et al. 2021

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“…These metrics, indeed, are complementary to each other and their spatial distributions overlap with all regions with reduced FA. In particular, a reduced NDI was detected only in cerebral regions in L-TLE patients, which is consistent with possible widespread WM alteration as shown in a previous work in epilepsy [25] and other neurological diseases [26], [27]. L-TLE patients also showed an increased ODI in brainstem and right cerebellum, indicating that here there might be a change in morphology of microstructure rather than cellular density [28].…”

Section: Discussionsupporting

confidence: 90%

White matter microstructure characterisation in temporal lobe epilepsy

Rolandi

Palesi

Padelli

et al. 2021

Preprint

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Temporal lobe epilepsy (TLE) is the most common form of focal epilepsy. Parameters of microstructural abnormalities derived from diffusion tensor imaging(DTI) have been reported to be helpful in differentiating between Left and Right TLE (L-TLE and R-TLE) but few of them compared L-TLE and R-TLE with a voxelwise approach. In this study, a whole brain tract based spatial statistical analysis was performed on DTI, diffusion kurtosis and NODDI derived parameters of 88 subjects to identify specific white matter patterns of alteration in patient affected by L-TLE and R-TLE with respect to healthy controls. Our findings demonstrated the presence of specific patterns of white matter alterations, with L-TLE more widely affected both in cerebral and cerebellar regions. This result supports the need to consider patients separately, according to the side of their pathology.

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“…13 We detail significant clinical findings reported in all published clinical studies in On-line Table 2. In summary, it was noted that when reaching a statistically significant difference, NDI/V ic values were always lower in lesions compared with normal-appearing WM, 12,[14][15][16] in normal-appearing WM compared with the normal WM of healthy controls (both in brains 14,16,17 and spinal cord 13,17 ), and in the spinal cord normal-appearing GM compared with the GM of healthy controls. 13 These results were consistent across patients with relapsing-remitting [12][13][14][15][16][17] or secondary-progressive MS. 12,16,17 However, thus far, only values of NDI measured in both the cortex 18 and the spinal cord 17 were found to be associated with clinical disability measured with the Expanded Disability Status Scale 19 in patients with both relapsing-remitting 17,18 and secondary-progressive 17,18 MS.…”

Section: Neurite Orientation Dispersion and Density Imagingmentioning

confidence: 87%

Advanced Multicompartment Diffusion MRI Models and Their Application in Multiple Sclerosis

Lakhani

Schilling

et al. 2020

AJNR Am J Neuroradiol

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Conventional MR imaging techniques are sensitive to pathologic changes of the brain and spinal cord seen in MS, but they lack specificity for underlying axonal and myelin integrity. By isolating the signal contribution from different tissue compartments, newly developed advanced multicompartment diffusion MR imaging models have the potential to detect specific tissue subtypes and associated injuries with increased pathologic specificity. These models include neurite orientation dispersion and density imaging, diffusion basis spectrum imaging, multicompartment microscopic diffusion MR imaging with the spherical mean technique, and models enabled through high-gradient diffusion MR imaging. In this review, we provide an appraisal of the current literature on the physics principles, histopathologic validation, and clinical applications of each of these techniques in both brains and spinal cords of patients with MS. We discuss limitations of each of the methods and directions that future research could take to provide additional validation of their roles as biomarkers of axonal and myelin injury in MS. ABBREVIATIONS: AD ¼ axial diffusivity; D ax ¼ intra-axonal diffusivity; DBSI ¼ diffusion basis spectrum imaging; FF ¼ fiber fraction; IVF ¼ isotropic volume fraction; NDI ¼ neurite density index (also V ic , V in , or f icvf ); NODDI ¼ neurite orientation dispersion and density imaging; ODI ¼ orientation dispersion index; RD ¼ radial diffusivity; SMT ¼ spherical mean technique; V ax ¼ intra-axonal volume fraction

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Reduced neurite density in the brain and cervical spinal cord in relapsing–remitting multiple sclerosis: A NODDI study

Cited by 54 publications

References 37 publications

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

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

White matter microstructure characterisation in temporal lobe epilepsy

Advanced Multicompartment Diffusion MRI Models and Their Application in Multiple Sclerosis

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