Presurgical Assessment of the Sensorimotor Cortex Using Resting-State fMRI

被引:29
|
作者
Schneider, F. C. [1 ,4 ]
Pailler, M. [1 ]
Faillenot, I. [2 ,5 ]
Vassal, F. [3 ,6 ]
Guyotat, J. [7 ]
Barral, F-G. [1 ,4 ]
Boutet, C. [1 ,4 ]
机构
[1] Univ Hosp St Etienne, Dept Radiol, St Etienne, France
[2] Univ Hosp St Etienne, Dept Neurol, St Etienne, France
[3] Univ Hosp St Etienne, Dept Neurosurg, St Etienne, France
[4] Univ St Etienne, Thrombosis Res Grp EA 3065, St Etienne, France
[5] Univ St Etienne, INSERM, Cent Integrat Pain, U1028, St Etienne, France
[6] Auvergne Univ, Image Guided Clin Neurosci & Connect EA 7282, Clermont Ferrand, France
[7] Univ Lyon 1, Hosp Civils Lyon, Dept Neurosurg, Lyon, France
关键词
SPONTANEOUS FLUCTUATIONS; INDEPENDENT COMPONENTS; RANDOM-FIELD;
D O I
10.3174/ajnr.A4472
中图分类号
R74 [神经病学与精神病学];
学科分类号
摘要
Task-based approaches to functional localization of the motor cortex have limitations such as long scanning times and exclusion of patients with severe functional or neurologic disabilities and children. Resting-state fMRI may avoid these difficulties because patients do not perform any goal-directed tasks. Nineteen patients were prospectively evaluated by using task-based and resting-state fMRI to localize sensorimotor function. Independent component analyses were performed to generate spatial independent components reflecting functional brain networks or noise. The motor cortex was successfully and consistently identified by using resting-state fMRI. Hand, foot, and face regions were defined in a comparable fashion with task-based fMRI. BACKGROUND AND PURPOSE: The functional characterization of the motor cortex is an important issue in the presurgical evaluation of brain lesions. fMRI noninvasively identifies motor areas while patients are asked to move different body parts. This task-based approach has some drawbacks in clinical settings: long scanning times and exclusion of patients with severe functional or neurologic disabilities and children. Resting-state fMRI can avoid these difficulties because patients do not perform any goal-directed tasks. MATERIALS AND METHODS: Nineteen patients with diverse brain pathologies were prospectively evaluated by using task-based and resting-state fMRI to localize sensorimotor function. Independent component analyses were performed to generate spatial independent components reflecting functional brain networks or noise. Three radiologists identified the motor components and 3 portions of the motor cortex corresponding to the hand, foot, and face representations. Selected motor independent components were compared with task-based fMRI activation maps resulting from movements of the corresponding body parts. RESULTS: The motor cortex was successfully and consistently identified by using resting-state fMRI by the 3 radiologists for all patients. When they subdivided the motor cortex into 3 segments, the sensitivities of resting-state and task-based fMRI were comparable. Moreover, we report a good spatial correspondence with the task-based fMRI activity estimates. CONCLUSIONS: Resting-state fMRI can reliably image sensorimotor function in a clinical preoperative routine. It is a promising opportunity for presurgical localization of sensorimotor function and has the potential to benefit a large number of patients affected by a wide range of pathologies.
引用
收藏
页码:101 / 107
页数:7
相关论文
共 50 条
  • [41] Assessment of disrupted brain functional connectome in tuberous sclerosis complex using resting-state fMRI
    Tsai, Jeng-Dau
    Ho, Ming-Chou
    Shen, Chao-Yu
    Weng, Jun-Cheng
    MEDICINE, 2022, 101 (11)
  • [42] AMYGDALA-PREFRONTAL CORTEX CONNECTIVITY IN PSYCHOTIC DISORDERS: A RESTING-STATE FMRI STUDY
    Sabharwal, Amri
    Petrone, Eric
    Kotov, Roman
    Mohanty, Aprajita
    PSYCHOPHYSIOLOGY, 2016, 53 : S21 - S21
  • [43] Nonlinear statistical properties of fMRI signals in human visual cortex during resting-state
    Lahmiri, Salim
    PHYSICS LETTERS A, 2018, 382 (34) : 2326 - 2333
  • [44] Diagnostic benefits of presurgical fMRI in patients with brain tumours in the primary sensorimotor cortex
    Martina Wengenroth
    M. Blatow
    J. Guenther
    M. Akbar
    V. M. Tronnier
    C. Stippich
    European Radiology, 2011, 21 : 1517 - 1525
  • [45] Machine learning in resting-state fMRI analysis
    Khosla, Meenakshi
    Jamison, Keith
    Ngo, Gia H.
    Kuceyeski, Amy
    Sabuncu, Mert R.
    MAGNETIC RESONANCE IMAGING, 2019, 64 : 101 - 121
  • [46] Resting-state fMRI in primary Sjogren syndrome
    Xing, Wu
    Shi, Wei
    Leng, Yueshuang
    Sun, Xianting
    Guan, Tingting
    Liao, Weihua
    Wang, Xiaoyi
    ACTA RADIOLOGICA, 2018, 59 (09) : 1091 - 1096
  • [47] Editorial: Origins of the Resting-State fMRI Signal
    Chen, J. Jean
    Herman, Peter
    Keilholz, Shella
    Thompson, Garth J.
    FRONTIERS IN NEUROSCIENCE, 2020, 14
  • [48] Explicability in resting-state fMRI for gender classification
    Raison, Adrien
    Bourdon, Pascal
    Habas, Christophe
    Helbert, David
    2021 SIXTH INTERNATIONAL CONFERENCE ON ADVANCES IN BIOMEDICAL ENGINEERING (ICABME), 2021, : 5 - 8
  • [49] Resting-State fMRI and Developmental Systems Neuroscience
    Uddin, Lucina Q.
    BIOLOGICAL PSYCHIATRY, 2012, 71 (08) : 22S - 22S
  • [50] Resting-state fMRI in the Human Connectome Project
    Smith, Stephen M.
    Beckmann, Christian F.
    Andersson, Jesper
    Auerbach, Edward J.
    Bijsterbosch, Janine
    Douaud, Gwenaelle
    Duff, Eugene
    Feinberg, David A.
    Griffanti, Ludovica
    Harms, Michael P.
    Kelly, Michael
    Laumann, Timothy
    Miller, Karla L.
    Moeller, Steen
    Petersen, Steve
    Power, Jonathan
    Salimi-Khorshidi, Gholamreza
    Snyder, Abraham Z.
    Vu, An T.
    Woolrich, Mark W.
    Xu, Junqian
    Yacoub, Essa
    Ugurbil, Kamil
    Van Essen, David C.
    Glasser, Matthew F.
    NEUROIMAGE, 2013, 80 : 144 - 168