Functional connectivity networks for preoperative brain mapping in neurosurgery.
Journal of Neurosurgery
American Association of Neurological Surgeons
MetadataShow full item record
Hart, M., Price, S., & Suckling, J. (2017). Functional connectivity networks for preoperative brain mapping in neurosurgery.. Journal of Neurosurgery, 126 (6), 1941-1950. https://doi.org/10.3171/2016.6.JNS1662
OBJECTIVE Resection of focal brain lesions involves maximizing the resection while preserving brain function. Mapping brain function has entered a new era focusing on distributed connectivity networks at "rest," that is, in the absence of a specific task or stimulus, requiring minimal participant engagement. Central to this frame shift has been the development of methods for the rapid assessment of whole-brain connectivity with functional MRI (fMRI) involving blood oxygenation level-dependent imaging. The authors appraised the feasibility of fMRI-based mapping of a repertoire of functional connectivity networks in neurosurgical patients with focal lesions and the potential benefits of resting-state connectivity mapping for surgical planning. METHODS Resting-state fMRI sequences with a 3-T scanner and multiecho echo-planar imaging coupled to independent component analysis were acquired preoperatively from 5 study participants who had a right temporoparietooccipital glioblastoma. Seed-based functional connectivity analysis was performed with InstaCorr. Network identification focused on 7 major functional connectivity networks described in the literature and a putative language network centered on Broca's area. RESULTS All 8 functional connectivity networks were identified in each participant. Tumor-related topological changes to the default mode network were observed in all participants. In addition, each participant had at least 1 other abnormal network, and each network was abnormal in at least 1 participant. Individual patterns of network irregularities were identified with a qualitative approach and included local displacement due to mass effect, loss of a functional network component, and recruitment of new regions. CONCLUSIONS Resting-state fMRI can reliably and rapidly detect common functional connectivity networks in patients with glioblastoma and also has sufficient sensitivity for identifying patterns of network alterations. Mapping of functional connectivity networks offers the possibility to expand investigations to less commonly explored neuropsychological processes, such as executive control, attention, and salience. Changes in these networks may allow insights into mechanisms underlying the functional consequences of tumor growth, surgical intervention, and patient rehabilitation.
BOLD = blood oxygenation level–dependent, DMN = default mode network, InstaCorr, ME-ICA, ME-ICA = multiecho independent component analysis, MNI = Montreal Neurological Institut, SCA = seed-based connectivity analysis, SMN = sensorimotor network, default mode network, diagnostic and operative techniques, fMRI = functional MRI, functional connectivity, glioblastoma, multiecho independent component analysis, oncology, resting-state functional MRI, rsfMRI = resting-state fMRI, seed-based connectivity, Adult, Aged, Brain, Brain Mapping, Brain Neoplasms, Glioblastoma, Humans, Magnetic Resonance Imaging, Middle Aged, Nerve Net, Neural Pathways, Neurosurgical Procedures, Temporal Lobe
Dr. Price received funding for this study through a National Institute for Health Research (NIHR) (UK) - Clinician Scientist Award (ref: NIHR/CS/009/011). Mr. Hart is funded by the Wellcome Trust Neuroscience in Psychiatry Network with additional support from the National Institute for Health Research Cambridge Biomedical Research Centre.
Wellcome Trust (093875/Z/10/Z)
Embargo Lift Date
External DOI: https://doi.org/10.3171/2016.6.JNS1662
This record's URL: https://www.repository.cam.ac.uk/handle/1810/260665