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Article: Towards better MR characterization of neural tissues using directional diffusion kurtosis analysis

TitleTowards better MR characterization of neural tissues using directional diffusion kurtosis analysis
Authors
KeywordsDiffusion kurtosis
Diffusion kurtosis tensor
Directional kurtosis
DKI
Non-Gaussian diffusion
Orthogonal transformation
Restricted diffusion
Water diffusion
Issue Date2008
PublisherAcademic Press. The Journal's web site is located at http://www.elsevier.com/locate/ynimg
Citation
Neuroimage, 2008, v. 42 n. 1, p. 122-134 How to Cite?
AbstractMR diffusion kurtosis imaging (DKI) was proposed recently to study the deviation of water diffusion from Gaussian distribution. Mean kurtosis, the directionally averaged kurtosis, has been shown to be useful in assessing pathophysiological changes, thus yielding another dimension of information to characterize water diffusion in biological tissues. In this study, orthogonal transformation of the 4th order diffusion kurtosis tensor was introduced to compute the diffusion kurtoses along the three eigenvector directions of the 2nd order diffusion tensor. Such axial (K//) and radial (K{box drawings light up and horizontal}) kurtoses measured the kurtoses along the directions parallel and perpendicular, respectively, to the principal diffusion direction. DKI experiments were performed in normal adult (N = 7) and formalin-fixed rat brains (N = 5). DKI estimates were documented for various white matter (WM) and gray matter (GM) tissues, and compared with the conventional diffusion tensor estimates. The results showed that kurtosis estimates revealed different information for tissue characterization. For example, K// and K{box drawings light up and horizontal} under formalin fixation condition exhibited large and moderate increases in WM while they showed little change in GM despite the overall dramatic decrease of axial and radial diffusivities in both WM and GM. These findings indicate that directional kurtosis analysis can provide additional microstructural information in characterizing neural tissues. © 2008 Elsevier Inc. All rights reserved.
Persistent Identifierhttp://hdl.handle.net/10722/155476
ISSN
2023 Impact Factor: 4.7
2023 SCImago Journal Rankings: 2.436
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorHui, ESen_US
dc.contributor.authorCheung, MMen_US
dc.contributor.authorQi, Len_US
dc.contributor.authorWu, EXen_US
dc.date.accessioned2012-08-08T08:33:41Z-
dc.date.available2012-08-08T08:33:41Z-
dc.date.issued2008en_US
dc.identifier.citationNeuroimage, 2008, v. 42 n. 1, p. 122-134en_US
dc.identifier.issn1053-8119en_US
dc.identifier.urihttp://hdl.handle.net/10722/155476-
dc.description.abstractMR diffusion kurtosis imaging (DKI) was proposed recently to study the deviation of water diffusion from Gaussian distribution. Mean kurtosis, the directionally averaged kurtosis, has been shown to be useful in assessing pathophysiological changes, thus yielding another dimension of information to characterize water diffusion in biological tissues. In this study, orthogonal transformation of the 4th order diffusion kurtosis tensor was introduced to compute the diffusion kurtoses along the three eigenvector directions of the 2nd order diffusion tensor. Such axial (K//) and radial (K{box drawings light up and horizontal}) kurtoses measured the kurtoses along the directions parallel and perpendicular, respectively, to the principal diffusion direction. DKI experiments were performed in normal adult (N = 7) and formalin-fixed rat brains (N = 5). DKI estimates were documented for various white matter (WM) and gray matter (GM) tissues, and compared with the conventional diffusion tensor estimates. The results showed that kurtosis estimates revealed different information for tissue characterization. For example, K// and K{box drawings light up and horizontal} under formalin fixation condition exhibited large and moderate increases in WM while they showed little change in GM despite the overall dramatic decrease of axial and radial diffusivities in both WM and GM. These findings indicate that directional kurtosis analysis can provide additional microstructural information in characterizing neural tissues. © 2008 Elsevier Inc. All rights reserved.en_US
dc.languageengen_US
dc.publisherAcademic Press. The Journal's web site is located at http://www.elsevier.com/locate/ynimgen_US
dc.relation.ispartofNeuroImageen_US
dc.subjectDiffusion kurtosis-
dc.subjectDiffusion kurtosis tensor-
dc.subjectDirectional kurtosis-
dc.subjectDKI-
dc.subjectNon-Gaussian diffusion-
dc.subjectOrthogonal transformation-
dc.subjectRestricted diffusion-
dc.subjectWater diffusion-
dc.subject.meshAlgorithmsen_US
dc.subject.meshAnimalsen_US
dc.subject.meshDiffusion Magnetic Resonance Imaging - Methodsen_US
dc.subject.meshImage Enhancement - Methodsen_US
dc.subject.meshImage Interpretation, Computer-Assisted - Methodsen_US
dc.subject.meshRatsen_US
dc.subject.meshRats, Sprague-Dawleyen_US
dc.subject.meshReproducibility Of Resultsen_US
dc.subject.meshSensitivity And Specificityen_US
dc.titleTowards better MR characterization of neural tissues using directional diffusion kurtosis analysisen_US
dc.typeArticleen_US
dc.identifier.emailWu, EX:ewu1@hkucc.hku.hken_US
dc.identifier.authorityWu, EX=rp00193en_US
dc.description.naturelink_to_subscribed_fulltexten_US
dc.identifier.doi10.1016/j.neuroimage.2008.04.237en_US
dc.identifier.pmid18524628-
dc.identifier.scopuseid_2-s2.0-45849112507en_US
dc.identifier.hkuros141499-
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-45849112507&selection=ref&src=s&origin=recordpageen_US
dc.identifier.volume42en_US
dc.identifier.issue1en_US
dc.identifier.spage122en_US
dc.identifier.epage134en_US
dc.identifier.eissn1095-9572-
dc.identifier.isiWOS:000258105000014-
dc.publisher.placeUnited Statesen_US
dc.identifier.scopusauthoridHui, ES=16175117100en_US
dc.identifier.scopusauthoridCheung, MM=24333907800en_US
dc.identifier.scopusauthoridQi, L=7202149952en_US
dc.identifier.scopusauthoridWu, EX=7202128034en_US
dc.identifier.citeulike6099743-
dc.identifier.issnl1053-8119-

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