Detection of structural abnormalities of cortical and subcortical gray matter in patients with MRI-negative refractory epilepsy using neurite orientation dispersion and density imaging

Rostampour, Masoumeh; Hashemi, Hassan; Najibi, Seyed Morteza; Oghabian, Mohammad Ali

doi:10.1016/j.ejmp.2018.03.005

Cited by 20 publications

(21 citation statements)

References 48 publications

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“…Interestingly, abnormal branching angles of apical dendrites have been revealed in HS histopathological tissues ( Thom, 2014 ), although their relationship with our findings should be elucidated by further comprehensive studies of dMRI and histopathology, as emphasized by a recent review ( Deleo et al, 2018 ). As for neurite dispersion, the most recent NODDI study of focal epilepsy suggested ODI changes ( Rostampour et al, 2018 ). Given that neurite density has been correlated with executive function ( Reyes et al, 2018 ), neurite dispersion might also be a candidate for future clinical research.…”

Section: Discussionmentioning

confidence: 99%

Abnormal neurite density and orientation dispersion in unilateral temporal lobe epilepsy detected by advanced diffusion imaging

Sone

Ota

Maikusa

et al. 2018

NeuroImage: Clinical

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BackgroundDespite recent advances in diffusion MRI (dMRI), there is still limited information on neurite orientation dispersion and density imaging (NODDI) in temporal lobe epilepsy (TLE). This study aimed to demonstrate neurite density and dispersion in TLE with and without hippocampal sclerosis (HS) using whole-brain voxel-wise analyses.Material and methodsWe recruited 33 patients with unilateral TLE (16 left, 17 right), including 14 patients with HS (TLE-HS) and 19 MRI-negative 18F-fluorodeoxyglucose positron emission tomography (FDG-PET)-positive patients (MRI-/PET+ TLE). The NODDI toolbox calculated the intracellular volume fraction (ICVF) and orientation dispersion index (ODI). Conventional dMRI metrics, that is, fractional anisotropy (FA) and mean diffusivity (MD), were also estimated. After spatial normalization, all dMRI parameters (ICVF, ODI, FA, and MD) of the patients were compared with those of age- and sex-matched healthy controls using Statistical Parametric Mapping 12 (SPM12). As a complementary analysis, we added an atlas-based region of interest (ROI) analysis of relevant white matter tracts using tract-based spatial statistics.ResultsWe found decreased neurite density mainly in the ipsilateral temporal areas of both right and left TLE, with the right TLE showing more severe and widespread abnormalities. In addition, etiology-specific analyses revealed a localized reduction in ICVF (i.e., neurite density) in the ipsilateral temporal pole in MRI-/PET+ TLE, whereas TLE-HS presented greater abnormalities, including FA and MD, in addition to a localized hippocampal reduction in ODI. The results of the atlas-based ROI analysis were consistent with the results of the SPM12 analysis.ConclusionNODDI may provide clinically relevant information as well as novel insights into the field of TLE. Particularly, in MRI-/PET+ TLE, neurite density imaging may have higher sensitivity than other dMRI parameters. The results may also contribute to better understanding of the pathophysiology of TLE with HS.

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Section: Discussionmentioning

confidence: 99%

Abnormal neurite density and orientation dispersion in unilateral temporal lobe epilepsy detected by advanced diffusion imaging

Sone

Ota

Maikusa

et al. 2018

NeuroImage: Clinical

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“…32 Representative images of these findings are shown in Figure 2. Cortical abnormalities on OD images in focal epilepsy have also been reported, 33 but a limitation was raised afterward. 34 At any rate, these findings would suggest a potential use for NODDI as a novel clinical biomarker for focal epilepsy treatment.…”

Section: Epilepsymentioning

confidence: 99%

<p>Neurite orientation and dispersion density imaging: clinical utility, efficacy, and role in therapy</p>

Sone¹

2019

RMI

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In the field of diffusion magnetic resonance imaging (MRI) for neuroimaging, white matter tracts have traditionally been analyzed using diffusion tensor imaging (DTI) measures, such as fractional anisotropy. However, recent advances in diffusion MRI have provided further information on brain microstructures using multi-shell protocols of diffusion MRI. Neurite orientation dispersion and density imaging (NODDI) is one such emerging advanced diffusion MRI method that enables investigation of the neurite density and neurite orientation dispersion of brain microstructures. NODDI was developed as a practical and clinically feasible diffusion MRI technique to evaluate the microstructural complexity of dendrites and axons. This review shed light on recent studies on the use of NODDI in human brain. Indeed, a growing number of studies are using NODDI to examine neurological and psychiatric disorders, with most reporting its clinical utility. The time has thus come, for us to seriously consider the clinical use of NODDI.

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“…Thus, the accuracy of f in quantification in gray matter is compromised by the first assumption. Though the measured NODDI f in or MEANS f in is not accurate in gray matter, it may still be able to provide some useful information about structural changes [46,47]. As for the second assumption, it is evident from Eq.…”

Section: Discussionmentioning

confidence: 99%

“…Second, MEANS estimates only one parameter. Diffusion-based microstructural modeling is generally associated with low signal-to-noise ratio and low image resolution [46,55]. Multi-shell diffusion data are needed to estimate extra parameters [11,26,29].…”

Section: Discussionmentioning

confidence: 99%

Comparison of NODDI and spherical mean signal for measuring intra-neurite volume fraction

Nikam

Kandula

et al. 2019

Magnetic Resonance Imaging

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Purpose: Neurite orientation dispersion and density imaging (NODDI) is a clinically feasible approach to measure intra-neurite volume fraction (f in). However, the sophisticated fitting procedure takes several hours. And the NODDI model relied on several questionable assumptions. Recent analytical work demonstrated that f in could be simply calculated from the spherical mean signal (MEANS) averaged over all gradient directions with a more solid theoretical foundation. The current study aims to compare NODDI and MEANS for measuring f in in human brain and investigate the potential of MEANS as a fast approach in clinics. Methods: NODDI f in and MEANS f in were measured and compared on the same dataset. NODDI f in was obtained using the NODDI MATLAB Toolbox. MEANS f in is the product of the spherical mean signal and 2 bD/π, where D is the intra-neurite intrinsic diffusivity. Results: NODDI f in and MEANS f in maps are similar. The voxel-by-voxel correlation suggests that NODDI f in and MEANS f in are approximately equivalent to each other. Conclusion: MEANS may have potential to serve a fast and simple approach to estimate f in in clinics.

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Detection of structural abnormalities of cortical and subcortical gray matter in patients with MRI-negative refractory epilepsy using neurite orientation dispersion and density imaging

Cited by 20 publications

References 48 publications

Abnormal neurite density and orientation dispersion in unilateral temporal lobe epilepsy detected by advanced diffusion imaging

Abnormal neurite density and orientation dispersion in unilateral temporal lobe epilepsy detected by advanced diffusion imaging

<p>Neurite orientation and dispersion density imaging: clinical utility, efficacy, and role in therapy</p>

Comparison of NODDI and spherical mean signal for measuring intra-neurite volume fraction

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