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Article: MR diffusion kurtosis imaging for neural tissue characterization

TitleMR diffusion kurtosis imaging for neural tissue characterization
Authors
Issue Date2010
PublisherJohn Wiley & Sons Ltd. The Journal's web site is located at http://www3.interscience.wiley.com/cgi-bin/jhome/13087
Citation
Nmr In Biomedicine, 2010, v. 23 n. 7, p. 836-848 How to Cite?
AbstractIn conventional diffusion tensor imaging (DTI), water diffusion distribution is described as a 2nd-order three-dimensional (3D) diffusivity tensor. It assumes that diffusion occurs in a free and unrestricted environment with a Gaussian distribution of diffusion displacement, and consequently that diffusion weighted (DW) signal decays with diffusion factor (b-value) monoexponentially. In biological tissue, complex cellular microstructures make water diffusion a highly hindered or restricted process. Non-monoexponential decays are experimentally observed in both white matter and gray matter. As a result, DTI quantitation is b-value dependent and DTI fails to fully utilize the diffusion measurements that are inherent to tissue microstructure. Diffusion kurtosis imaging (DKI) characterizes restricted diffusion and can be readily implemented on most clinical scanners. It provides a higher-order description of water diffusion process by a 2nd-order 3D diffusivity tensor as in conventional DTI together with a 4th-order 3D kurtosis tensor. Because kurtosis is a measure of the deviation of the diffusion displacement profile from a Gaussian distribution, DKI analyses quantify the degree of diffusion restriction or tissue complexity without any biophysical assumption. In this work, the theory of diffusion kurtosis and DKI including the directional kurtosis analysis is revisited. Several recent rodent DKI studies from our group are summarized, and DKI and DTI compared for their efficacy in detecting neural tissue alterations. They demonstrate that DKI offers a more comprehensive approach than DTI in describing the complex water diffusion process in vivo. By estimating both diffusivity and kurtosis, it may provide improved sensitivity and specificity in MR diffusion characterization of neural tissues. © 2010 John Wiley & Sons, Ltd.
Persistent Identifierhttp://hdl.handle.net/10722/155594
ISSN
2015 Impact Factor: 2.983
2015 SCImago Journal Rankings: 1.533
ISI Accession Number ID
Funding AgencyGrant Number
Hong Kong Research Grant Council (RGC)GRF HKU7808/09M
Funding Information:

This work was supported by the Hong Kong Research Grant Council (RGC GRF HKU7808/09M). We thank Dr Edward S. Hui, Mr Kevin C. Chan and Dr Wutian Wu of University of Hong Kong, and D Liqun Qi of Hong Kong Polytechnic University for their technical assistance. We also thank Drs Joseph A. Helpern and Jens H. Jensen of New York University School of Medicine, and Dr Hanzhang Lu of University of Texas Southwestern Medical Center for their assistance and the human DKI data presented in this work.

References

 

DC FieldValueLanguage
dc.contributor.authorWu, EXen_US
dc.contributor.authorCheung, MMen_US
dc.date.accessioned2012-08-08T08:34:16Z-
dc.date.available2012-08-08T08:34:16Z-
dc.date.issued2010en_US
dc.identifier.citationNmr In Biomedicine, 2010, v. 23 n. 7, p. 836-848en_US
dc.identifier.issn0952-3480en_US
dc.identifier.urihttp://hdl.handle.net/10722/155594-
dc.description.abstractIn conventional diffusion tensor imaging (DTI), water diffusion distribution is described as a 2nd-order three-dimensional (3D) diffusivity tensor. It assumes that diffusion occurs in a free and unrestricted environment with a Gaussian distribution of diffusion displacement, and consequently that diffusion weighted (DW) signal decays with diffusion factor (b-value) monoexponentially. In biological tissue, complex cellular microstructures make water diffusion a highly hindered or restricted process. Non-monoexponential decays are experimentally observed in both white matter and gray matter. As a result, DTI quantitation is b-value dependent and DTI fails to fully utilize the diffusion measurements that are inherent to tissue microstructure. Diffusion kurtosis imaging (DKI) characterizes restricted diffusion and can be readily implemented on most clinical scanners. It provides a higher-order description of water diffusion process by a 2nd-order 3D diffusivity tensor as in conventional DTI together with a 4th-order 3D kurtosis tensor. Because kurtosis is a measure of the deviation of the diffusion displacement profile from a Gaussian distribution, DKI analyses quantify the degree of diffusion restriction or tissue complexity without any biophysical assumption. In this work, the theory of diffusion kurtosis and DKI including the directional kurtosis analysis is revisited. Several recent rodent DKI studies from our group are summarized, and DKI and DTI compared for their efficacy in detecting neural tissue alterations. They demonstrate that DKI offers a more comprehensive approach than DTI in describing the complex water diffusion process in vivo. By estimating both diffusivity and kurtosis, it may provide improved sensitivity and specificity in MR diffusion characterization of neural tissues. © 2010 John Wiley & Sons, Ltd.en_US
dc.languageengen_US
dc.publisherJohn Wiley & Sons Ltd. The Journal's web site is located at http://www3.interscience.wiley.com/cgi-bin/jhome/13087en_US
dc.relation.ispartofNMR in Biomedicineen_US
dc.subject.meshAnimalsen_US
dc.subject.meshBrain - Anatomy & Histologyen_US
dc.subject.meshDiffusion Tensor Imaging - Methodsen_US
dc.subject.meshHumansen_US
dc.subject.meshImage Interpretation, Computer-Assisted - Methodsen_US
dc.subject.meshImage Processing, Computer-Assisted - Methodsen_US
dc.subject.meshNerve Tissue - Anatomy & Histologyen_US
dc.subject.meshWater - Metabolismen_US
dc.titleMR diffusion kurtosis imaging for neural tissue characterizationen_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.doi10.1002/nbm.1506en_US
dc.identifier.pmid20623793-
dc.identifier.scopuseid_2-s2.0-78650475622en_US
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-78650475622&selection=ref&src=s&origin=recordpageen_US
dc.identifier.volume23en_US
dc.identifier.issue7en_US
dc.identifier.spage836en_US
dc.identifier.epage848en_US
dc.identifier.isiWOS:000283014300014-
dc.publisher.placeUnited Kingdomen_US
dc.identifier.scopusauthoridWu, EX=7202128034en_US
dc.identifier.scopusauthoridCheung, MM=24333907800en_US

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