liu.seSök publikationer i DiVA
Ändra sökning
RefereraExporteraLänk till posten
Permanent länk

Direktlänk
Referera
Referensformat
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Annat format
Fler format
Språk
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Annat språk
Fler språk
Utmatningsformat
  • html
  • text
  • asciidoc
  • rtf
Q-space trajectory imaging for multidimensional diffusion MRI of the human brain
Linköpings universitet, Institutionen för medicinsk teknik, Medicinsk informatik. Linköpings universitet, Tekniska fakulteten. Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
Linköpings universitet, Institutionen för medicinsk teknik, Medicinsk informatik. Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV. Linköpings universitet, Tekniska fakulteten.ORCID-id: 0000-0002-9091-4724
Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
Department of Medical Radiation Physics, Lund University, Lund, Sweden.
Visa övriga samt affilieringar
2016 (Engelska)Ingår i: NeuroImage, ISSN 1053-8119, E-ISSN 1095-9572, Vol. 135, s. 345-362Artikel i tidskrift (Refereegranskat) Published
Abstract [en]

This work describes a new diffusion MR framework for imaging and modeling of microstructure that we call q-space trajectory imaging (QTI). The QTI framework consists of two parts: encoding and modeling. First we propose q-space trajectory encoding, which uses time-varying gradients to probe a trajectory in q-space, in contrast to traditional pulsed field gradient sequences that attempt to probe a point in q-space. Then we propose a microstructure model, the diffusion tensor distribution (DTD) model, which takes advantage of additional information provided by QTI to estimate a distributional model over diffusion tensors. We show that the QTI framework enables microstructure modeling that is not possible with the traditional pulsed gradient encoding as introduced by Stejskal and Tanner. In our analysis of QTI, we find that the well-known scalar b-value naturally extends to a tensor-valued entity, i.e., a diffusion measurement tensor, which we call the b-tensor. We show that b-tensors of rank 2 or 3 enable estimation of the mean and covariance of the DTD model in terms of a second order tensor (the diffusion tensor) and a fourth order tensor. The QTI framework has been designed to improve discrimination of the sizes, shapes, and orientations of diffusion microenvironments within tissue. We derive rotationally invariant scalar quantities describing intuitive microstructural features including size, shape, and orientation coherence measures. To demonstrate the feasibility of QTI on a clinical scanner, we performed a small pilot study comparing a group of five healthy controls with five patients with schizophrenia. The parameter maps derived from QTI were compared between the groups, and 9 out of the 14 parameters investigated showed differences between groups. The ability to measure and model the distribution of diffusion tensors, rather than a quantity that has already been averaged within a voxel, has the potential to provide a powerful paradigm for the study of complex tissue architecture.

Ort, förlag, år, upplaga, sidor
Elsevier, 2016. Vol. 135, s. 345-362
Nyckelord [en]
DDE, DTI, Diffusion MRI, Diffusion tensor distribution, Microscopic anisotropy, Microscopic fractional anisotropy μFA, QTI, SDE, TDE, q-space, q-space trajectory
Nationell ämneskategori
Medicinteknik
Identifikatorer
URN: urn:nbn:se:liu:diva-129986DOI: 10.1016/j.neuroimage.2016.02.039ISI: 000378047600031PubMedID: 26923372OAI: oai:DiVA.org:liu-129986DiVA, id: diva2:945840
Anmärkning

Funding agencies:The authors acknowledge the NIH grants R01MH074794, R01MH092862, R01MH102377, R01AG042512, P41EB015902, P41EB015898, U01CA199459, and the Swedish Research Council (VR) grants 2012-3682, 2011-5176, 2014-3910, TUBITAK-EU COFUND project no. 114C015, ITEA/Vinnova/13031 BENEFIT, and Swedish Foundation for Strategic Research (SSF) grant AM13-0090.

Tillgänglig från: 2016-07-04 Skapad: 2016-07-04 Senast uppdaterad: 2017-11-28Bibliografiskt granskad

Open Access i DiVA

Fulltext saknas i DiVA

Övriga länkar

Förlagets fulltextPubMed

Personposter BETA

Westin, Carl-FredrikKnutsson, HansÖzarslan, Evren

Sök vidare i DiVA

Av författaren/redaktören
Westin, Carl-FredrikKnutsson, HansÖzarslan, Evren
Av organisationen
Medicinsk informatikTekniska fakultetenCentrum för medicinsk bildvetenskap och visualisering, CMIVInstitutionen för medicinsk teknik
I samma tidskrift
NeuroImage
Medicinteknik

Sök vidare utanför DiVA

GoogleGoogle Scholar

doi
pubmed
urn-nbn

Altmetricpoäng

doi
pubmed
urn-nbn
Totalt: 589 träffar
RefereraExporteraLänk till posten
Permanent länk

Direktlänk
Referera
Referensformat
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Annat format
Fler format
Språk
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Annat språk
Fler språk
Utmatningsformat
  • html
  • text
  • asciidoc
  • rtf