Atormac
Neurology India
menu-bar5 Open access journal indexed with Index Medicus
  Users online: 2329  
 Home | Login 
About Editorial board Articlesmenu-bullet NSI Publicationsmenu-bullet Search Instructions Online Submission Subscribe Videos Etcetera Contact
  Navigate Here 
 Search
 
  
 Resource Links
    Similar in PUBMED
   Search Pubmed for
   Search in Google Scholar for
    Article in PDF (280 KB)
    Citation Manager
    Access Statistics
    Reader Comments
    Email Alert *
    Add to My List *
* Registration required (free)  

 
  In this Article
   References

 Article Access Statistics
    Viewed2201    
    Printed63    
    Emailed0    
    PDF Downloaded191    
    Comments [Add]    
    Cited by others 1    

Recommend this journal

 


 
Table of Contents    
EDITORIAL
Year : 2013  |  Volume : 61  |  Issue : 2  |  Page : 103-104

Resting state functional magnetic resonance imaging: An emerging clinical tool


Department of Radiology, Sree Chitra Tirunal Institute for Medical Sciences and Technology, Trivandrum, Kerala, India

Date of Submission02-Apr-2013
Date of Decision02-Apr-2013
Date of Acceptance04-Apr-2013
Date of Web Publication29-Apr-2013

Correspondence Address:
Chandrasekharan Kesavadas
Department of Radiology, Sree Chitra Tirunal Institute for Medical Sciences and Technology, Trivandrum - 695 011, Kerala
India
Login to access the Email id

Source of Support: None, Conflict of Interest: None


DOI: 10.4103/0028-3886.111107

Rights and Permissions



How to cite this article:
Kesavadas C. Resting state functional magnetic resonance imaging: An emerging clinical tool. Neurol India 2013;61:103-4

How to cite this URL:
Kesavadas C. Resting state functional magnetic resonance imaging: An emerging clinical tool. Neurol India [serial online] 2013 [cited 2019 Aug 25];61:103-4. Available from: http://www.neurologyindia.com/text.asp?2013/61/2/103/111107


In a routine clinical practice, functional magnetic resonance imaging (fMRI) is offered as a non-invasive means of pre-surgical functional mapping of eloquent cortex. [1],[2] The basic approach is to conduct the study while the patient performs a task designed to target a single domain such as language, vision, memory, sensory or motor function. The fMRI images thus obtained are used prior to surgery to identify the closeness of the lesion to regions of functional activity. This approach is now well-established and many centers around the world use the results of this technique for pre-surgical counseling, surgical planning and neurosurgical decision making. However, there are few limitations for this technique. Some patients can have difficulty in performing the required tasks, especially those who have neurological deficits such as weakness of limbs for performing motor function, lower intelligence to perform cognitive tasks and altered levels of consciousness. Infants and children may not be able to perform the task. Thus, if a patient is unable to perform the prescribed task, the presently available task-based functional mapping approaches may be unreliable or prove impossible. Secondly, specific task sets must be performed to target distinct functions. It is difficult to map multiple brain functions simultaneously.

Functional mapping based on spontaneous intrinsic activity, referred to as resting state fMRI, offers an alternative approach to pre-surgical mapping. Resting state fMRI measures spontaneous low-frequency fluctuations (<0.1 Hz) in the blood oxygen level dependent (BOLD) signal to investigate the functional architecture of the brain. In 1995, Biswal and colleagues were the first to present the functional significance of these fluctuations. [3] In their study, they showed that motor areas activated by actual motor movements could also be localized using spontaneous activity correlations. Following this publication, several studies have shown the application of this technique in identification of various resting state networks and functionally-related regions demonstrating synchronous BOLD fluctuations at rest. It has been used to map out brain regions linked to motor function, [3] vision, [4] audition, [5] language, [6] memory, [7] and attention. [8]

Lee et al., reviewed the various methods for analyzing resting-state fMRI data. [9] This includes seed-based approaches, independent component analysis, graph methods, clustering algorithms, neural networks, and pattern classifiers. Their review also describes the emerging clinical applications of this technique. One of the clinical applications that is showing great promise is in the pre-surgical planning for patients with brain tumor. Manglore et al., in their study, published in this issue of the journal, have aimed at establishing the utility of resting state fMRI as a clinical tool for mapping eloquent motor cortex in patients with brain tumors. [10] Their study results show that the findings of resting state fMRI in six patients with brain tumor were comparable to that of task based fMRI mapping of motor cortex. The study also reports disrupted functional connectivity on the side of tumor.

An earlier study by Zhang et al., has shown that resting state fMRI correlation mapping compares well with "gold standard" cortical stimulation mapping in motor cortex mapping in healthy volunteers and patients with brain tumor. [11] The utility of this technique in motor cortex mapping in patients with brain tumors have also been reported in the studies by Liu et al., and Kokkonen et al. [12],[13] These studies concluded that the task-free paradigm in resting state fMRI may provide a powerful approach to map functional anatomy in patients without task compliance and allow multiple brain systems to be determined in a single scanning session. Hence, the technique becomes useful in young children, patients with altered mental status, patients under sedation, sleep or anesthesia, and in patients with paresis or aphasia.

The other clinical application includes pre-surgical planning in patients with epilepsy. Resting state fMRI has been used to localize areas of increased connectivity for detecting the epileptogenic zone in patients with epilepsy. [14],[15] Studies have demonstrated the utility of this technique in identifying patients with Alzheimer disease. [16] Resting state studies have been used to distinguish patients with psychiatric diseases from controls, [17] identify autism spectrum disorder, [18] and attention deficit hyperactivity disorder. [19]

Fox and Greicius, in their review article, have discussed the guidelines for performing resting state research on clinical populations and have also identified the barriers to be addressed to facilitate the translation of resting state fMRI into the clinical realm. [20] Since the methods of resting state fMRI data analysis requires technical expertise, there is a need for close collaboration between the clinician and the biomedical engineer to make this technique clinically useful and feasible.

 
  References Top

1.Vaghela V, Kesavadas C, Thomas B. Functional magnetic resonance imaging of the brain: A quick review. Neurol India 2010;58:879-85.  Back to cited text no. 1
    
2.Kesavadas C, Thomas B. Clinical applications of functional MRI in epilepsy. Indian J Radiol Imaging 2008;18:210-7.  Back to cited text no. 2
[PUBMED]  Medknow Journal  
3.Biswal B, Yetkin FZ, Haughton VM, Hyde JS. Functional connectivity in the motor cortex of resting human brain using echo-planar MRI. Magn Reson Med 1995;34:537-41.  Back to cited text no. 3
    
4.Nir Y, Hasson U, Levy I, Yeshurun Y, Malach R. Widespread functional connectivity and fMRI fluctuations in human visual cortex in the absence of visual stimulation. Neuroimage 2006;30:1313-24.  Back to cited text no. 4
    
5.Hunter MD, Eickhoff SB, Miller TW, Farrow TF, Wilkinson ID, Woodruff PW. Neural activity in speech-sensitive auditory cortex during silence. Proc Natl Acad Sci U S A 2006;103:189-93.  Back to cited text no. 5
    
6.Tomasi D, Volkow ND. Resting functional connectivity of language networks: Characterization and reproducibility. Mol Psychiatry 2012;17:841-54.  Back to cited text no. 6
    
7.Vincent JL, Snyder AZ, Fox MD, Shannon BJ, Andrews JR, Raichle ME, et al. Coherent spontaneous activity identifies a hippocampal-parietal memory network. J Neurophysiol 2006;96:3517-31.  Back to cited text no. 7
    
8.Fox MD, Corbetta M, Snyder AZ, Vincent JL, Raichle ME. Spontaneous neuronal activity distinguishes human dorsal and ventral attention systems. Proc Natl Acad Sci U S A 2006;103:10046-51.  Back to cited text no. 8
    
9.Lee MH, Smyser CD, Shimony JS. Resting-State fMRI: A review of methods and clinical applications. AJNR Am J Neuroradiol 2012 [Epub ahead of print].  Back to cited text no. 9
    
10.Manglore S, Bharath RD, Panda R, George L, Thamodharan A, Gupta AK. Utility of resting fMRI and connectivity in patients with brain tumor. Neurol India 2013;61:144-51.  Back to cited text no. 10
  Medknow Journal  
11.Zhang D, Johnston JM, Fox MD, Leuthardt EC, Grubb RL, Chicoine MR, et al. Preoperative sensorimotor mapping in brain tumor patients using spontaneous fluctuations in neuronal activity imaged with functional magnetic resonance imaging: Initial experience. Neurosurgery 2009;65:226-36.  Back to cited text no. 11
    
12.Liu H, Buckner RL, Talukdar T, Tanaka N, Madsen JR, Stufflebeam SM. Task-free presurgical mapping using functional magnetic resonance imaging intrinsic activity. J Neurosurg 2009;111:746-54.  Back to cited text no. 12
    
13.Kokkonen SM, Nikkinen J, Remes J, Kantola J, Starck T, Haapea M, et al. Preoperative localization of the sensorimotor area using independent component analysis of resting-state fMRI. Magn Reson Imaging 2009;27:733-40.  Back to cited text no. 13
    
14.Stufflebeam SM, Liu H, Sepulcre J, Tanaka N, Buckner RL, Madsen JR. Localization of focal epileptic discharges using functional connectivity magnetic resonance imaging. J Neurosurg 2011;114:1693-7.  Back to cited text no. 14
    
15.Bettus G, Bartolomei F, Confort-Gouny S, Guedi P, Chauvel P, Cozzone PJ, et al. Role of resting state functional connectivity MRI in presurgical investigation of mesial temporal lobe epilepsy. J Neurol Neurosurg Psychiatry 2010;81:1147-54.  Back to cited text no. 15
    
16.Chen G, Ward BD, Xie C, Li W, Wu Z, Jones JL, et al. Classification of Alzheimer disease, mild cognitive impairment, and normal cognitive status with large-scale network analysis based on resting-state functional MR imaging. Radiology 2011;259:213-21.  Back to cited text no. 16
    
17.Bassett DS, Nelson BG, Mueller BA, Chamchong J, Lim KO. Altered resting state complexity in schizophrenia. Neuroimage 2012;59:2196-207.  Back to cited text no. 17
    
18.Anderson JS, Nielsen JA, Froehlich AL, DuBray MB, Druzgal TJ, Cariello AN, et al. Functional connectivity magnetic resonance imaging classification of autism. Brain 2011;134:3742-54.  Back to cited text no. 18
    
19.Zhu CZ, Zang YF, Cao QJ, Yan CG, He Y, Jiang TZ, et al. Fisher discriminative analysis of resting-state brain function for attention-deficit/hyperactivity disorder. Neuroimage 2008;40:110-20.  Back to cited text no. 19
    
20.Fox MD, Greicius M. Clinical Applications of Resting State Functional Connectivity. Front Syst Neurosci 2010;4:19.  Back to cited text no. 20
    



This article has been cited by
1 Resting state fMRI: A review on methods in resting state connectivity analysis and resting state networks
KA Smitha,K Akhil Raja,KM Arun,PG Rajesh,Bejoy Thomas,TR Kapilamoorthy,Chandrasekharan Kesavadas
The Neuroradiology Journal. 2017; 30(4): 305
[Pubmed] | [DOI]



 

Top
Print this article  Email this article
   
Online since 20th March '04
Published by Wolters Kluwer - Medknow