NODDI: Practical in vivo neurite orientation dispersion and density imaging of the human brain

Zhang, Hui; Schneider, Torben; Wheeler‐Kingshott, Claudia A. M.; Alexander, Daniel C.

doi:10.1016/j.neuroimage.2012.03.072

Cited by 2,713 publications

(3,664 citation statements)

References 44 publications

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“…Through the combination of state‐of‐the‐art histology33 and post mortem NODDI26, 27 MRI, we show for the first time that neurite orientation dispersion is a marker of microstructural pathology, as it detects trends of reduced geometrical complexity of neurite architecture within multiple sclerosis lesions. In so doing, we report a heretofore undescribed layer of complexity of multiple sclerosis pathology.…”

Section: Discussionmentioning

confidence: 95%

“…From the fitted tensor, fractional anisotropy (FA), axial, radial, and mean diffusivities (AD, RD, and MD) were obtained in each MRI voxel. The relationship between NODDI and DTI metrics has been investigated in detail in previous works 26, 27. For instance, a decrease in DTI FA can be caused independently by a decrease in the density of axons or an increase in the orientation dispersion.…”

Section: Methodsmentioning

confidence: 99%

“…Furthermore, we aim to validate neurite orientation dispersion and density imaging (NODDI), a recent model‐based diffusion MRI technique 26. The clinical feasibility of NODDI in vivo has already been demonstrated,26, 27, 28, 29 and here we compare NODDI dispersion indices against histology to demonstrate that the new marker has strong clinical potential. NODDI belongs to the family of quantitative MRI methods, and unlike conventional radiographic readouts its metrics are designed to measure features of tissue microstructure at a length scale that is orders of magnitude smaller than the size of the imaging voxels.…”

Section: Introductionmentioning

confidence: 90%

“…Therefore, it models the amount of neurites within a voxels. ODI is obtained fitting a Watson distribution to the zero‐radius cylinder orientation distribution26, and is a metric designed to characterize neurite orientation variability, ranging from 0 (axon/dendrites all parallel) to 1 (axon/dendrites isotropically randomly oriented).…”

Section: Methodsmentioning

confidence: 99%

“…These two are key factors contributing to the diffusion MRI signal,26 and it is relevant to determine which is more important to explain the variability in NODDI metrics.…”

Section: Methodsmentioning

confidence: 99%

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Neurite dispersion: a new marker of multiple sclerosis spinal cord pathology?

Grussu

Schneider

Tur

et al. 2017

Ann Clin Transl Neurol

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ObjectiveConventional magnetic resonance imaging (MRI) of the multiple sclerosis spinal cord is limited by low specificity regarding the underlying pathological processes, and new MRI metrics assessing microscopic damage are required. We aim to show for the first time that neurite orientation dispersion (i.e., variability in axon/dendrite orientations) is a new biomarker that uncovers previously undetected layers of complexity of multiple sclerosis spinal cord pathology. Also, we validate against histology a clinically viable MRI technique for dispersion measurement (neurite orientation dispersion and density imaging, NODDI), to demonstrate the strong potential of the new marker.MethodsWe related quantitative metrics from histology and MRI in four post mortem spinal cord specimens (two controls; two progressive multiple sclerosis cases). The samples were scanned at high field, obtaining maps of neurite density and orientation dispersion from NODDI and routine diffusion tensor imaging (DTI) indices. Histological procedures provided markers of astrocyte, microglia, myelin and neurofilament density, as well as neurite dispersion.ResultsWe report from both NODDI and histology a trend toward lower neurite dispersion in demyelinated lesions, indicative of reduced neurite architecture complexity. Also, we provide unequivocal evidence that NODDI‐derived dispersion matches its histological counterpart (P < 0.001), while DTI metrics are less specific and influenced by several biophysical substrates.InterpretationNeurite orientation dispersion detects a previously undescribed and potentially relevant layer of microstructural complexity of multiple sclerosis spinal cord pathology. Clinically feasible techniques such as NODDI may play a key role in clinical trial and practice settings, as they provide histologically meaningful dispersion indices.

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Section: Discussionmentioning

confidence: 95%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 90%

Section: Methodsmentioning

confidence: 99%

“…These two are key factors contributing to the diffusion MRI signal,26 and it is relevant to determine which is more important to explain the variability in NODDI metrics.…”

Section: Methodsmentioning

confidence: 99%

See 3 more Smart Citations

Neurite dispersion: a new marker of multiple sclerosis spinal cord pathology?

Grussu

Schneider

Tur

et al. 2017

Ann Clin Transl Neurol

Self Cite

265

243

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Association of Visual Health With Depressive Symptoms and Brain Imaging Phenotypes Among Middle-Aged and Older Adults

et al. 2022

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ImportanceVision loss and depression are common conditions with major health implications. However, mechanisms of the association of visual health (across the full acuity spectrum) with depression remain unclear.ObjectiveTo characterize the association between visual health and depression and investigate the association between depression and brain microstructure and macrostructure in subgroups divided by visual acuity.Design, Setting, and ParticipantsIn the UK Biobank Study cohort, 114 583 volunteers were included at baseline from March to June 2006 to July 2010. Habitual distance visual acuity was examined using the logarithm of the minimum angle of resolution (LogMAR) characters. Depression was identified based on Patient Health Questionnaire (PHQ) or through an interview-based psychiatric diagnosis. Subgroup participants completed multimodal magnetic resonance imaging (MRI) of the brain and PHQ evaluation during the imaging visit after 2014. Data were analyzed from May 5 to August 9, 2022.Main Outcomes and MeasuresDepression, depressive symptoms, and imaging-derived phenotypes from T1-weighted and diffusion MRI.ResultsOf the 114 583 participants from the UK Biobank Study, 62 401 (54.5%) were women, and the mean (SD) age was 56.8 (8.1) years (range, 39-72 years). A 1-line worse visual acuity (0.1 LogMAR increase) was associated with 5% higher odds of depression (odds ratio, 1.05 [95% CI, 1.04-1.07]) after adjustment for age, sex, race and ethnicity, Townsend index, educational qualifications, smoking, alcohol consumption, obesity, physical activity, history of hypertension, diabetes, hyperlipidemia, and family history of depression. Of the 7844 participants eligible for MRI analysis, there were linear associations between PHQ score and the left volume of gray matter in supracalcarine cortex (coefficient, 7.61 [95% CI, 3.90-11.31]) and mean isotropic volume fraction (ISOVF) in the right fornix (cres) and/or stria terminalis (coefficient, 0.003 [95% CI, 0.001-0.004]) after correction for multiple comparison. In addition, their association could be moderated by visual acuity, whereby increased PHQ score was associated with higher ISOVF levels only among those with poorer visual acuity (P = .02 for interaction).Conclusions and RelevanceThis study suggests an association between visual health and depression and that the diffusion characteristic of ISOVF in the fornix (cres) and/or stria terminalis is associated with depressive symptoms in participants with poorer visual acuity.

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Pathological Networking of Gray Matter Dendritic Density With Classic Brain Morphometries in OCD

Zhang,

Zhou,

Chen

et al. 2023

JAMA Netw Open

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ImportanceThe pathogenesis of obsessive-compulsive disorder (OCD) may involve altered dendritic morphology, but in vivo imaging of neurite morphology in OCD remains limited. Such changes must be interpreted functionally within the context of the multimodal neuroimaging approach to OCD.ObjectiveTo examine whether dendritic morphology is altered in patients with OCD compared with healthy controls (HCs) and whether such alterations are associated with other brain structural metrics in pathological networks.Design, Setting, and ParticipantsThis case-control study used cross-sectional data, including multimodal brain images and clinical symptom assessments, from 108 patients with OCD and 108 HCs from 2014 to 2017. Patients with OCD were recruited from Shanghai Mental Health Center, Shanghai, China, and HCs were recruited via advertisements. The OCD group comprised unmedicated adults with a Diagnostic and Statistical Manual of Mental Disorders (Fourth Edition) (DSM-IV) diagnosis of OCD, while the HCs were adults without any DSM-IV diagnosis, matched for age, sex, and education level. Data were analyzed from September 2019 to April 2023.ExposureDSM-IV diagnosis of OCD.Main Outcomes and MeasuresMultimodal brain imaging was used to compare neurite microstructure and classic morphometries between patients with OCD and HCs. The whole brain was searched to identify regions exhibiting altered morphology in patients with OCD and explore the interplay between the brain metrics representing these alterations. Brain-symptom correlations were analyzed, and the performance of different brain metric configurations were evaluated in distinguishing patients with OCD from HCs.ResultsAmong 108 HCs (median [IQR] age, 26 [23-31] years; 50 [46%] female) and 108 patients with OCD (median [IQR] age, 26 [24-31] years; 46 [43%] female), patients with OCD exhibited deficient neurite density in the right lateral occipitoparietal regions (peak t = 3.821; P ≤ .04). Classic morphometries also revealed widely-distributed alterations in the brain (peak t = 4.852; maximum P = .04), including the prefrontal, medial parietal, cingulate, and fusiform cortices. These brain metrics were interconnected into a pathological brain network associated with OCD symptoms (global strength: HCs, 0.253; patients with OCD, 0.941; P = .046; structural difference, 0.572; P &lt; .001). Additionally, the neurite density index exhibited high discriminatory power in distinguishing patients with OCD from HCs (accuracy, ≤76.85%), and the entire pathological brain network also exhibited excellent discriminative classification properties (accuracy, ≤82.87%).Conclusions and RelevanceThe findings of this case-control study underscore the utility of in vivo imaging of gray matter dendritic density in future OCD research and the development of neuroimaging-based biomarkers. They also endorse the concept of connectopathy, providing a potential framework for interpreting the associations among various OCD symptom–related morphological anomalies.

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NODDI: Practical in vivo neurite orientation dispersion and density imaging of the human brain

Cited by 2,713 publications

References 44 publications

Neurite dispersion: a new marker of multiple sclerosis spinal cord pathology?

Neurite dispersion: a new marker of multiple sclerosis spinal cord pathology?

Association of Visual Health With Depressive Symptoms and Brain Imaging Phenotypes Among Middle-Aged and Older Adults

Pathological Networking of Gray Matter Dendritic Density With Classic Brain Morphometries in OCD

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