Gray Matter Abnormalities in Idiopathic <scp>P</scp>arkinson's Disease: Evaluation by Diffusional Kurtosis Imaging and Neurite Orientation Dispersion and Density Imaging

Kamagata, Koji; Zalesky, Andrew; Hatano, Taku; Ueda, Ryo; Biase, Maria A Di; Okuzumi, Ayami; Shimoji, Keigo; Hori, Masaaki; Caeyenberghs, Karen; Pantelis, Christos; Hattori, Nobutaka; Aoki, Shigeki

doi:10.1002/hbm.23628

Cited by 89 publications

(95 citation statements)

References 93 publications

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“…Both ICVF and INVF have been proposed as biomarkers of highly anisotropic structures, such as neurons nuclei and glia, as suggested by previous studies on multiple sclerosis, 35 Alzheimer disease, 36 and Parkinson disease. 37 The within-lesion decreases are concordant with altered extracellular diffusion and increased extra-neurite volume measures performed on histology samples from surgical resections. 38 Those phenomena could also reflect the formation of additional diffusion barriers that may arise from loss of cortical stratification, deposits of extracellular matrix molecules, or F I G U R E 3 Multiple comparison test on the mean ranks of the image scores.…”

Section: Quantitative Lesion Profilingmentioning

confidence: 55%

“…Similarly, we found significant INVF decrease in suspected and confirmed FCD lesions. Both ICVF and INVF have been proposed as biomarkers of highly anisotropic structures, such as neurons nuclei and glia, as suggested by previous studies on multiple sclerosis, Alzheimer disease, and Parkinson disease . The within‐lesion decreases are concordant with altered extracellular diffusion and increased extra‐neurite volume measures performed on histology samples from surgical resections .…”

Section: Discussionmentioning

confidence: 66%

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MRI profiling of focal cortical dysplasia using multi‐compartment diffusion models

et al. 2020

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Objective Focal cortical dysplasia (FCD) lesion detection and subtyping remain challenging on conventional MRI. New diffusion models such as the spherical mean technique (SMT) and neurite orientation dispersion and density imaging (NODDI) provide measurements that potentially produce more specific maps of abnormal tissue microstructure. This study aims to assess the SMT and NODDI maps for computational and radiological lesion characterization compared to standard fractional anisotropy (FA) and mean diffusivity (MD). Methods SMT, NODDI, FA, and MD maps were calculated for 33 pediatric patients with suspected FCD (18 histologically confirmed). Two neuroradiologists scored lesion visibility on clinical images and diffusion maps. Signal profile changes within lesions and homologous regions were quantified using a surface‐based approach. Diffusion parameter changes at multiple cortical depths were statistically compared between FCD type IIa and type IIb. Results Compared to fluid‐attenuated inversion recovery (FLAIR) or T1‐weighted imaging, lesions conspicuity on NODDI intracellular volume fraction (ICVF) maps was better/equal/worse in 5/14/14 patients, respectively, while on SMT intra‐neurite volume fraction (INVF) in 3/3/27. Compared to FA or MD, lesion conspicuity on the ICVF was better/equal/worse in 27/4/2, while on the INVF in 20/7/6. Quantitative signal profiling demonstrated significant ICVF and INVF reductions in the lesions, whereas SMT microscopic mean, radial, and axial diffusivities were significantly increased. FCD type IIb exhibited greater changes than FCD type IIa. No changes were detected on FA or MD profiles. Significance FCD lesion‐specific signal changes were found in ICVF and INVF but not in FA and MD maps. ICVF and INVF showed greater contrast than FLAIR in some cases and had consistent signal changes specific to FCD, suggesting that they could improve current presurgical pediatric epilepsy imaging protocols and can provide features useful for automated lesion detection.

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Section: Quantitative Lesion Profilingmentioning

confidence: 55%

Section: Discussionmentioning

confidence: 66%

MRI profiling of focal cortical dysplasia using multi‐compartment diffusion models

et al. 2020

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“…Studies implementing the NODDI model in PD have shown reduced Vic in the substantia nigra (Kamagata et al, ), and reduced Vic along the pathway in which seeds are placed in the substantia nigra and globus pallidus (Andica et al, ). In a study using automated analysis of many regions (not including substantia nigra though), the authors found increases in Viso in the left and right caudate, and left putamen (Kamagata et al, ). Other studies have reported significant differences between PD and healthy control subjects in other brain regions using conventional diffusion tensor imaging measures (e.g., FA, mean diffusivity, and axial diffusivity); however, these results have also been inconsistent.…”

Section: Discussionmentioning

confidence: 99%

Neurite orientation dispersion and density imaging (NODDI) and free‐water imaging in Parkinsonism

Mitchell

Archer

Chu

et al. 2019

Human Brain Mapping

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Neurite orientation dispersion and density imaging (NODDI) uses a three‐compartment model to probe brain tissue microstructure, whereas free‐water (FW) imaging models two‐compartments. It is unknown if NODDI detects more disease‐specific effects related to neurodegeneration in Parkinson's disease (PD) and atypical Parkinsonism. We acquired multi‐ and single‐shell diffusion imaging at 3 Tesla across two sites. NODDI (using multi‐shell; isotropic volume [Viso]; intracellular volume [Vic]; orientation dispersion [ODI]) and FW imaging (using single‐shell; FW; free‐water corrected fractional anisotropy [FAt]) were compared with 44 PD, 21 multiple system atrophy Parkinsonian variant (MSAp), 26 progressive supranuclear palsy (PSP), and 24 healthy control subjects in the basal ganglia, midbrain/thalamus, cerebellum, and corpus callosum. There was elevated Viso in posterior substantia nigra across Parkinsonisms, and Viso, Vic, and ODI were altered in MSAp and PSP in the striatum, globus pallidus, midbrain, thalamus, cerebellum, and corpus callosum relative to controls. The mean effect size across regions for Viso was 0.163, ODI 0.131, Vic 0.122, FW 0.359, and FAt 0.125, with extracellular compartments having the greatest effect size. A key question addressed was if these techniques discriminate PD and atypical Parkinsonism. Both NODDI (AUC: 0.945) and FW imaging (AUC: 0.969) had high accuracy, with no significant difference between models. This study provides new evidence that NODDI and FW imaging offer similar discriminability between PD and atypical Parkinsonism, and FW had higher effect sizes for detecting Parkinsonism within regions across the basal ganglia and cerebellum.

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“…To address this issue, a biophysical model approach was developed in which model parameters, such as axonal volume fraction and compartmental diffusivities, are estimated from the measured diffusion MRI signal. To date, many such models have been proposed and used in clinical and experimental studies . However, it is emphasized that so far no definite consensus has been reached on how to parameterize the complex brain microstructure .…”

Section: Introductionmentioning

confidence: 99%

Diffusional kurtosis imaging and white matter microstructure modeling in a clinical study of major depressive disorder

et al. 2018

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Major depressive disorder (MDD) is a globally prevalent psychiatric disorder that results from disruption of multiple neural circuits involved in emotional regulation. Although previous studies using diffusion tensor imaging (DTI) found smaller values of fractional anisotropy (FA) in the white matter, predominantly in the frontal lobe, of patients with MDD, studies using diffusion kurtosis imaging (DKI) are scarce. Here, we used DKI whole‐brain analysis with tract‐based spatial statistics (TBSS) to investigate the brain microstructural abnormalities in MDD. Twenty‐six patients with MDD and 42 age‐ and sex‐matched control subjects were enrolled. To investigate the microstructural pathology underlying the observations in DKI, a compartment model analysis was conducted focusing on the corpus callosum. In TBSS, the patients with MDD showed significantly smaller values of FA in the genu and frontal portion of the body of the corpus callosum. The patients also had smaller values of mean kurtosis (MK) and radial kurtosis (RK), but MK and RK abnormalities were distributed more widely compared with FA, predominantly in the frontal lobe but also in the parietal, occipital, and temporal lobes. Within the callosum, the regions with smaller MK and RK were located more posteriorly than the region with smaller FA. Model analysis suggested significantly smaller values of intra‐neurite signal fraction in the body of the callosum and greater fiber dispersion in the genu, which were compatible with the existing literature of white matter pathology in MDD. Our results show that DKI is capable of demonstrating microstructural alterations in the brains of patients with MDD that cannot be fully depicted by conventional DTI. Though the issues of model validation and parameter estimation still remain, it is suggested that diffusion MRI combined with a biophysical model is a promising approach for investigation of the pathophysiology of MDD.

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Gray Matter Abnormalities in Idiopathic Parkinson's Disease: Evaluation by Diffusional Kurtosis Imaging and Neurite Orientation Dispersion and Density Imaging

Cited by 89 publications

References 93 publications

MRI profiling of focal cortical dysplasia using multi‐compartment diffusion models

MRI profiling of focal cortical dysplasia using multi‐compartment diffusion models

Neurite orientation dispersion and density imaging (NODDI) and free‐water imaging in Parkinsonism

Diffusional kurtosis imaging and white matter microstructure modeling in a clinical study of major depressive disorder

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