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  NODDI-DTI: Estimating neurite orientation and dispersion parameters from a diffusion tensor in healthy white matter

Edwards, L., Pine, K., Ellerbrock, I., Weiskopf, N., & Mohammadi, S. (2017). NODDI-DTI: Estimating neurite orientation and dispersion parameters from a diffusion tensor in healthy white matter. Frontiers in Neuroscience, 11: 720. doi:10.3389/fnins.2017.00720.

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Datensatz-Permalink: https://hdl.handle.net/11858/00-001M-0000-002E-A23C-A Versions-Permalink: https://hdl.handle.net/21.11116/0000-0003-ABA4-3
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 Urheber:
Edwards, Luke1, 2, Autor           
Pine, Kerrin1, 2, Autor           
Ellerbrock, Isabel3, Autor
Weiskopf, Nikolaus1, 2, Autor           
Mohammadi, Siawoosh1, 2, 3, Autor
Affiliations:
1Department Neurophysics (Weiskopf), MPI for Human Cognitive and Brain Sciences, Max Planck Society, ou_2205649              
2Wellcome Trust Centre for Neuroimaging, University College London, United Kingdom, ou_persistent22              
3Department of Systems Neuroscience, University Medical Center Hamburg-Eppendorf, Germany, ou_persistent22              

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Schlagwörter: Diffusion MRI; NODDI; DTI; Axonal density; Orientation dispersion
 Zusammenfassung: The NODDI-DTI signal model is a modification of the NODDI signal model that formally allows interpretation of standard single-shell DTI data in terms of biophysical parameters in healthy human white matter (WM). The NODDI-DTI signal model contains no CSF compartment, restricting application to voxels without CSF partial-volume contamination. This modification allowed derivation of analytical relations between parameters representing axon density and dispersion, and DTI invariants (MD and FA) from the NODDI-DTI signal model. These relations formally allow extraction of biophysical parameters from DTI data. NODDI-DTI parameters were estimated by applying the proposed analytical relations to DTI parameters estimated from the first shell of data, and compared to parameters estimated by fitting the NODDI-DTI model to both shells of data (reference dataset) in the WM of 14 in vivo diffusion datasets recorded with two different protocols, and in simulated data. The first two datasets were also fit to the NODDI-DTI model using only the first shell (as for DTI) of data. NODDI-DTI parameters estimated from DTI, and NODDI-DTI parameters estimated by fitting the model to the first shell of data gave similar errors compared to two-shell NODDI-DTI estimates. The simulations showed the NODDI-DTI method to be more noise-robust than the two-shell fitting procedure. The NODDI-DTI method gave unphysical parameter estimates in a small percentage of voxels, reflecting voxelwise DTI estimation error or NODDI-DTI model invalidity. In the course of evaluating the NODDI-DTI model, it was found that diffusional kurtosis strongly biased DTI-based MD values, and so, making assumptions based on healthy WM, a novel heuristic correction requiring only DTI data was derived and used to mitigate this bias. Since validations were only performed on healthy WM, application to grey matter or pathological WM would require further validation. Our results demonstrate NODDI-DTI to be a promising model and technique to interpret restricted datasets acquired for DTI analysis in healthy white matter with greater biophysical specificity, though its limitations must be borne in mind.

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Sprache(n): eng - English
 Datum: 2017-06-122017-12-112017-12-20
 Publikationsstatus: Online veröffentlicht
 Seiten: -
 Ort, Verlag, Ausgabe: -
 Inhaltsverzeichnis: -
 Art der Begutachtung: Expertenbegutachtung
 Identifikatoren: DOI: 10.3389/fnins.2017.00720
PMID: 29326546
PMC: PMC5742359
Anderer: eCollection 2017
 Art des Abschluß: -

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Projektinformation

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Projektname : Non-invasive in vivo histology in health and disease using Magnetic Resonance Imaging (MRI) / HMRI
Grant ID : 616905
Förderprogramm : FP7 (ERC-2013-CoG)
Förderorganisation : European Commission (EC)
Projektname : NEURON-Verbund hMRTofScl: Entschlüsselung der pathophysiologischen Prozesse induziert durch eine Querschnittslähmung: Anwendung von MRT basierter in vivo und ex vivo Histologie / Era-Net NEURON
Grant ID : 01EW1711B
Förderprogramm : ERA-NET NEURON Call "Entwicklungsstörungen im Nervensystem" (ERA-NET NEURON JTC2016)
Förderorganisation : German Federal Ministry of Education and Research (BMBF)
Projektname : Mesoscopic characterization of human white-matter: A computational in-vivo MRI framework / MWMI
Grant ID : 658589
Förderprogramm : Horizon 2020
Förderorganisation : European Commission (EC)
Projektname : -
Grant ID : 0915/Z/10/Z
Förderprogramm : -
Förderorganisation : Wellcome Trust
Projektname : -
Grant ID : 2397/4-1
Förderprogramm : -
Förderorganisation : Deutsche Forschungsgemeinschaft (DFG)
Projektname : -
Grant ID : -
Förderprogramm : Forschungsforderungsfond der Medizinischen Fakultat (FFM) Postdoctoral Fellowship
Förderorganisation : University Medical Center Hamburg-Eppendorf

Quelle 1

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Titel: Frontiers in Neuroscience
  Andere : Front Neurosci
Genre der Quelle: Zeitschrift
 Urheber:
Affiliations:
Ort, Verlag, Ausgabe: Lausanne, Switzerland : Frontiers Research Foundation
Seiten: - Band / Heft: 11 Artikelnummer: 720 Start- / Endseite: - Identifikator: ISSN: 1662-4548
ISSN: 1662-453X
CoNE: https://pure.mpg.de/cone/journals/resource/1662-4548