Quantifying the timecourse of recovery from mild traumatic brain injury using diffusion tensor imaging

Min Jing, T.Martin McGinnity, SA Coleman, Armin Fuchs, Fred Steinberg, J.A.Scott Kelso

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Recent studies on mild traumatic brain injury (mTBI) by diffusion tensor imaging (DTI) rely on quantitative comparison of diffusion scalar maps such as fractional anisotropy (FA) and mean diffusivity (MD) between groups, quantitative tractography and tract-based spatial statistics (TBSS). However there is a lack of longitudinal DTI studies of mTBI and an effective approach to quantify temporal changes during recovery from mTBI. Furthermore, existing methods require large data samples which are not suitable for small sample case studies.In this preliminary study, we propose a group based independent component analysis (GICA) to study the temporal change of diffusion patterns during recovery from mTBI. By applying group based ICA, the common spatial pattern within the grouped maps can be separated from noise and artifact, and the temporal information during recovery can be revealed by the corresponding timecourse. The results from quantitative comparison within a mask based on the mean FA skeleton further reveal the trend of recovery. The proposed method not only provides an effective solution to quantify temporal changes in longitudinal studies, but also has the potential to be applied to individual case studies in clinical applications.
LanguageEnglish
Title of host publicationUnknown Host Publication
Number of pages1
Publication statusPublished - 10 Jun 2012
EventThe 18th Annual Meeting of the Organization for Human Brain Mapping (OHBM) - Beijing, China
Duration: 10 Jun 2012 → …

Conference

ConferenceThe 18th Annual Meeting of the Organization for Human Brain Mapping (OHBM)
Period10/06/12 → …

Fingerprint

brain
anisotropy
diffusivity
skeleton
artifact
method
comparison

Keywords

  • diffusion tensor imaging
  • mild traumatic brain injury
  • group independent component analysis

Cite this

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title = "Quantifying the timecourse of recovery from mild traumatic brain injury using diffusion tensor imaging",
abstract = "Recent studies on mild traumatic brain injury (mTBI) by diffusion tensor imaging (DTI) rely on quantitative comparison of diffusion scalar maps such as fractional anisotropy (FA) and mean diffusivity (MD) between groups, quantitative tractography and tract-based spatial statistics (TBSS). However there is a lack of longitudinal DTI studies of mTBI and an effective approach to quantify temporal changes during recovery from mTBI. Furthermore, existing methods require large data samples which are not suitable for small sample case studies.In this preliminary study, we propose a group based independent component analysis (GICA) to study the temporal change of diffusion patterns during recovery from mTBI. By applying group based ICA, the common spatial pattern within the grouped maps can be separated from noise and artifact, and the temporal information during recovery can be revealed by the corresponding timecourse. The results from quantitative comparison within a mask based on the mean FA skeleton further reveal the trend of recovery. The proposed method not only provides an effective solution to quantify temporal changes in longitudinal studies, but also has the potential to be applied to individual case studies in clinical applications.",
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Jing, M, McGinnity, TM, Coleman, SA, Fuchs, A, Steinberg, F & Kelso, JAS 2012, Quantifying the timecourse of recovery from mild traumatic brain injury using diffusion tensor imaging. in Unknown Host Publication. The 18th Annual Meeting of the Organization for Human Brain Mapping (OHBM), 10/06/12.

Quantifying the timecourse of recovery from mild traumatic brain injury using diffusion tensor imaging. / Jing, Min; McGinnity, T.Martin; Coleman, SA; Fuchs, Armin; Steinberg, Fred; Kelso, J.A.Scott.

Unknown Host Publication. 2012.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

TY - GEN

T1 - Quantifying the timecourse of recovery from mild traumatic brain injury using diffusion tensor imaging

AU - Jing, Min

AU - McGinnity, T.Martin

AU - Coleman, SA

AU - Fuchs, Armin

AU - Steinberg, Fred

AU - Kelso, J.A.Scott

PY - 2012/6/10

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N2 - Recent studies on mild traumatic brain injury (mTBI) by diffusion tensor imaging (DTI) rely on quantitative comparison of diffusion scalar maps such as fractional anisotropy (FA) and mean diffusivity (MD) between groups, quantitative tractography and tract-based spatial statistics (TBSS). However there is a lack of longitudinal DTI studies of mTBI and an effective approach to quantify temporal changes during recovery from mTBI. Furthermore, existing methods require large data samples which are not suitable for small sample case studies.In this preliminary study, we propose a group based independent component analysis (GICA) to study the temporal change of diffusion patterns during recovery from mTBI. By applying group based ICA, the common spatial pattern within the grouped maps can be separated from noise and artifact, and the temporal information during recovery can be revealed by the corresponding timecourse. The results from quantitative comparison within a mask based on the mean FA skeleton further reveal the trend of recovery. The proposed method not only provides an effective solution to quantify temporal changes in longitudinal studies, but also has the potential to be applied to individual case studies in clinical applications.

AB - Recent studies on mild traumatic brain injury (mTBI) by diffusion tensor imaging (DTI) rely on quantitative comparison of diffusion scalar maps such as fractional anisotropy (FA) and mean diffusivity (MD) between groups, quantitative tractography and tract-based spatial statistics (TBSS). However there is a lack of longitudinal DTI studies of mTBI and an effective approach to quantify temporal changes during recovery from mTBI. Furthermore, existing methods require large data samples which are not suitable for small sample case studies.In this preliminary study, we propose a group based independent component analysis (GICA) to study the temporal change of diffusion patterns during recovery from mTBI. By applying group based ICA, the common spatial pattern within the grouped maps can be separated from noise and artifact, and the temporal information during recovery can be revealed by the corresponding timecourse. The results from quantitative comparison within a mask based on the mean FA skeleton further reveal the trend of recovery. The proposed method not only provides an effective solution to quantify temporal changes in longitudinal studies, but also has the potential to be applied to individual case studies in clinical applications.

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