TY - GEN
T1 - Connectional fingerprint of mild cognitive impairment based on FDG-PET and PiB-PET
AU - Son, Seong Jin
AU - Kim, Mansu
AU - Lee, Seung Hak
AU - Park, Hyunjin
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2018/11/12
Y1 - 2018/11/12
N2 - Connectional fingerprint provides important information to characterize patterns related to mild cognitive impairment (MCI) which is a brain function syndrome involving the onset and evolution of cognitive impairment. Here, we defined connectional fingerprint of normal control (NC) and MCI patients using fludeoxyglucose (FDG)- and Pittsburgh compound B (PiB)-positron emission tomography (PET) to identify the characterized patterns. A connectivity analysis was implemented using whole brain network. Group-wise differences between NC and MCI patients were assessed using betweenness centrality. Lingual L and putamen R showed a significant decrease the value of BC from NC to MCI in FDG-PET. Fusiform also showed a significant decrease in PiB-PET. Finally, ten brain regions, showed a large difference between NC and MCI, were used to characterize the unique patterns in connectional fingerprint. Using connectional fingerprint, this study identified unique patterns differentially affected by MCI progression.
AB - Connectional fingerprint provides important information to characterize patterns related to mild cognitive impairment (MCI) which is a brain function syndrome involving the onset and evolution of cognitive impairment. Here, we defined connectional fingerprint of normal control (NC) and MCI patients using fludeoxyglucose (FDG)- and Pittsburgh compound B (PiB)-positron emission tomography (PET) to identify the characterized patterns. A connectivity analysis was implemented using whole brain network. Group-wise differences between NC and MCI patients were assessed using betweenness centrality. Lingual L and putamen R showed a significant decrease the value of BC from NC to MCI in FDG-PET. Fusiform also showed a significant decrease in PiB-PET. Finally, ten brain regions, showed a large difference between NC and MCI, were used to characterize the unique patterns in connectional fingerprint. Using connectional fingerprint, this study identified unique patterns differentially affected by MCI progression.
UR - https://www.scopus.com/pages/publications/85058442055
U2 - 10.1109/NSSMIC.2017.8532989
DO - 10.1109/NSSMIC.2017.8532989
M3 - Conference contribution
AN - SCOPUS:85058442055
T3 - 2017 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2017 - Conference Proceedings
BT - 2017 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2017 - Conference Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2017 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2017
Y2 - 21 October 2017 through 28 October 2017
ER -