1. Preoperative localization of the sensorimotor area using independent component analysis of resting-state fMRI.
- Author
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Kokkonen SM, Nikkinen J, Remes J, Kantola J, Starck T, Haapea M, Tuominen J, Tervonen O, and Kiviniemi V
- Subjects
- Adolescent, Adult, Brain Neoplasms physiopathology, Female, Humans, Image Interpretation, Computer-Assisted methods, Male, Middle Aged, Motor Cortex physiopathology, Preoperative Care methods, Principal Component Analysis, Reproducibility of Results, Sensitivity and Specificity, Somatosensory Cortex physiopathology, Young Adult, Brain Neoplasms diagnosis, Brain Neoplasms surgery, Evoked Potentials, Motor, Evoked Potentials, Somatosensory, Magnetic Resonance Imaging methods, Motor Cortex pathology, Somatosensory Cortex pathology
- Abstract
Analysis of resting-state functional magnetic resonance imaging (fMRI) data is based on detecting low-frequency signal fluctuations in functionally connected brain areas. These synchronous fluctuations in resting-state networks have been observed in several studies with healthy subjects. In this study, we explored if independent component analysis (ICA) can be used to localize the sensorimotor area from resting-state fMRI data in patients with brain tumors. Finger-tapping activation task and resting-state blood-oxygenation-level-dependent fMRI data were acquired from 8 patients with brain tumors and 10 healthy volunteers. Sensorimotor task independent components (IC(task)) were used to verify resting-state independent components (IC(rest)) individually. In addition, sensorimotor IC(rest)s were compared between the groups and no significant differences were detected in volume, spatial correlation or temporal correlation. These results show that it is possible to localize a sensorimotor area from resting-state data using ICA in patients with brain tumors. This offers a complementary method for assessing the sensorimotor area in subjects with brain tumors who have difficulties in performing motor paradigms.
- Published
- 2009
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