TY - GEN
T1 - Longitudinal analysis of brain recovery after mild traumatic brain injury based on groupwise consistent brain network clusters
AU - Chen, Hanbo
AU - Iraji, Armin
AU - Jiang, Xi
AU - Lv, Jinglei
AU - Kou, Zhifeng
AU - Liu, Tianming
N1 - Publisher Copyright:
© Springer International Publishing Switzerland 2015.
PY - 2015
Y1 - 2015
N2 - Traumatic brain injury (TBI) affects over 1.5 million Americans each year, and more than 75% of TBI cases are classified as mild (mTBI). Several functional network alternations have been reported after mTBI; however, the network alterations on a large scale, particularly on connectome scale, are still unknown. To analyze brain network, in a previous work, 358 landmarks named dense individualized common connectivity based cortical landmarks (DICCCOL) were identified on cortical surface. These landmarks preserve structural connection consistency and maintain functional correspondence across subjects. Hence DICCCOLs have been shown powerful in identifying connectivity signatures in affected brains. However, on such fine scales, the longitudinal changes in brain network of mTBI patients were complicated by the noise embedded in the systems as well as the normal variability of individuals at different times. Faced with such problems, we proposed a novel framework to analyze longitudinal changes from the perspective of network clusters. Specifically, multiview spectral clustering algorithm was applied to cluster brain networks based on DICCCOLs. And both structural and functional networks were analyzed. Our results showed that significant longitudinal changes were identified from mTBI patients that can be related to the neurocognitive recovery and the brain’s effort to compensate the effect of injury.
AB - Traumatic brain injury (TBI) affects over 1.5 million Americans each year, and more than 75% of TBI cases are classified as mild (mTBI). Several functional network alternations have been reported after mTBI; however, the network alterations on a large scale, particularly on connectome scale, are still unknown. To analyze brain network, in a previous work, 358 landmarks named dense individualized common connectivity based cortical landmarks (DICCCOL) were identified on cortical surface. These landmarks preserve structural connection consistency and maintain functional correspondence across subjects. Hence DICCCOLs have been shown powerful in identifying connectivity signatures in affected brains. However, on such fine scales, the longitudinal changes in brain network of mTBI patients were complicated by the noise embedded in the systems as well as the normal variability of individuals at different times. Faced with such problems, we proposed a novel framework to analyze longitudinal changes from the perspective of network clusters. Specifically, multiview spectral clustering algorithm was applied to cluster brain networks based on DICCCOLs. And both structural and functional networks were analyzed. Our results showed that significant longitudinal changes were identified from mTBI patients that can be related to the neurocognitive recovery and the brain’s effort to compensate the effect of injury.
KW - Brain network clustering
KW - DTI
KW - fMRI
KW - Longitudinal analysis
KW - t-test
KW - Traumatic brain injury
UR - http://www.scopus.com/inward/record.url?scp=84950988979&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84950988979&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-24571-3_24
DO - 10.1007/978-3-319-24571-3_24
M3 - Conference contribution
AN - SCOPUS:84950988979
SN - 9783319245706
SN - 9783319245706
SN - 9783319245706
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 194
EP - 201
BT - Medical Image Computing and Computer-Assisted Intervention - MICCAI 2015 - 18th International Conference, Proceedings
A2 - Hornegger, Joachim
A2 - Frangi, Alejandro F.
A2 - Wells, William M.
A2 - Frangi, Alejandro F.
A2 - Navab, Nassir
A2 - Hornegger, Joachim
A2 - Navab, Nassir
A2 - Wells, William M.
A2 - Wells, William M.
A2 - Frangi, Alejandro F.
A2 - Hornegger, Joachim
A2 - Navab, Nassir
PB - Springer Verlag
T2 - 18th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2015
Y2 - 5 October 2015 through 9 October 2015
ER -