Advertisement

Acta Neurochirurgica

, Volume 153, Issue 8, pp 1561–1572 | Cite as

A software tool for interactive exploration of intrinsic functional connectivity opens new perspectives for brain surgery

  • Joachim BöttgerEmail author
  • Daniel S. Margulies
  • Peter Horn
  • Ulrich W. Thomale
  • Ilana Podlipsky
  • Irit Shapira-Lichter
  • Shereen J. Chaudhry
  • Christine Szkudlarek
  • Karsten Mueller
  • Gabriele Lohmann
  • Talma Hendler
  • Georg Bohner
  • Jochen B. Fiebach
  • Arno Villringer
  • Peter Vajkoczy
  • Alexander Abbushi
Clinical Article

Abstract

Background

Functional connectivity analysis of resting-state functional magnetic resonance imaging data (fcrs-fMRI) has been shown to be a robust non-invasive method for localization of functional networks (without using specific tasks) and to be promising for presurgical planning. However, in order to transfer the approach to everyday clinical practice, fcrs-fMRI needs to be further validated and made easily accessible to neurosurgeons. This paper addresses the latter by presenting a software tool designed for neurosurgeons for analyzing and visualizing fcrs-fMRI data.

Methods

A prototypical interactive visualization tool was developed to enable neurosurgeons to explore functional connectivity data and evaluate its usability. The implementation builds upon LIPSIA, an established software package for the assessment of functional neuroimaging data, and integrates the selection of a region-of-interest with the computation and visualization of functionally connected areas. The tool was used to explore data from a healthy participant and eight brain lesion patients. The usability of the software was evaluated with four neurosurgeons previously unacquainted with the methodology, who were asked to identify prominent, large-scale cortical networks.

Findings

With this novel tool, previously published findings, such as tumor displacement of the sensorimotor cortex and other disturbances of functional networks, were reproduced. The neurosurgeons were able to consistently obtain results similar to the results of an expert, with the exception of the language network. Immediate feedback helped to pinpoint functional networks quickly and intuitively, with even inexperienced users requiring less than 3 min per network.

Conclusions

Although fcrs-fMRI is a nascent method still undergoing evaluation with respect to established standards, the interactive software is nonetheless a promising tool for non-invasive exploration of individual functional connectivity networks in neurosurgical practice, both for well-known networks and for those less typically addressed.

Keywords

Resting-state fMRI Visualization Interactivity Surgical planning 

Notes

Conflicts of interest

None.

Supplementary material

701_2011_985_MOESM1_ESM.pdf (129 kb)
Online Resource 1 Textual description of the methods used to generate Fig. 1, the comparison of resting-state and task-based fMRI and DTI-based fiber tracking. (PDF 129 kb)
Online Resource 2

Video that demonstrates interaction with our functional connectivity tool and four functional networks. (MOV 4713 kb)

701_2011_985_Fig6_ESM.gif (27 kb)
Online Resource 3

The edema under the tumor area is distinguishable from the surrounding healthy brain tissue in the fMRI scan. (GIF 27 kb)

701_2011_985_MOESM3_ESM.tif (1.4 mb)
High resoultion image. (TIFF 1,450 kb)

References

  1. 1.
    Biswal B, Yetkin FZ, Haughton VM, Hyde JS (1995) Functional connectivity in the motor cortex of resting human brain using echo-planar MRI. Magn Reson Med 34:537–541PubMedCrossRefGoogle Scholar
  2. 2.
    Buckner RL, Andrews-Hanna JR, Schacter DL (2008) The brain's default network: anatomy, function, and relevance to disease. Ann NY Acad Sci 1124:1–38PubMedCrossRefGoogle Scholar
  3. 3.
    Chen S, Ross TJ, Zhan W, Myers CS, Chuang K, Heishman SJ, Stein EA, Yang Y (2008) Group independent component analysis reveals consistent resting-state networks across multiple sessions. Brain Res 1239:141–151PubMedCrossRefGoogle Scholar
  4. 4.
    Damoiseaux JS, Rombouts SARB, Barkhof F, Scheltens P, Stam CJ, Smith SM, Beckmann CF (2006) Consistent resting-state networks across healthy subjects. Proc Natl Acad Sci 103:13848–13853PubMedCrossRefGoogle Scholar
  5. 5.
    De Luca M, Beckmann C, De Stefano N, Matthews P, Smith S (2006) fMRI resting state networks define distinct modes of long-distance interactions in the human brain. Neuroimage 29:1359–1367PubMedCrossRefGoogle Scholar
  6. 6.
    Desmond JE, Annabel Chen SH (2002) Ethical issues in the clinical application of fMRI: factors affecting the validity and interpretation of activations. Brain Cogn 50:482–497PubMedCrossRefGoogle Scholar
  7. 7.
    Di Martino A, Scheres A, Margulies D, Kelly A, Uddin L, Shehzad Z, Biswal B, Walters J, Castellanos F, Milham M (2008) Functional connectivity of human striatum: a resting state fMRI study. Cereb Cortex 18:2735–2747PubMedCrossRefGoogle Scholar
  8. 8.
    Feldman S, Chu D, Schulder M, Barry M, Cho E, Liu W (2009) The blood oxygen level-dependent functional MR imaging signal can be used to identify brain tumors and distinguish them from normal tissue. AJNR Am J Neuroradiol 30:389–395PubMedCrossRefGoogle Scholar
  9. 9.
    Fox MD, Greicius M (2010) Clinical applications of resting state functional connectivity. Front Syst Neurosci 4:19PubMedGoogle Scholar
  10. 10.
    Fox MD, Raichle ME (2007) Spontaneous fluctuations in brain activity observed with functional magnetic resonance imaging. Nat Rev Neurosci 8:700–711PubMedCrossRefGoogle Scholar
  11. 11.
    Fukunaga M, Horovitz SG, van Gelderen P, de Zwart JA, Jansma JM, Ikonomidou VN, Chu R, Deckers RHR, Leopold DA, Duyn JH (2006) Large-amplitude, spatially correlated fluctuations in BOLD fMRI signals during extended rest and early sleep stages. Magn Reson Imaging 24:979–992PubMedCrossRefGoogle Scholar
  12. 12.
    Fukunaga M, Horovitz SG, de Zwart JA, van Gelderen P, Balkin TJ, Braun AR, Duyn JH (2008) Metabolic origin of BOLD signal fluctuations in the absence of stimuli. J Cereb Blood Flow Metab 28:1377–1387PubMedCrossRefGoogle Scholar
  13. 13.
    Greicius M (2008) Resting-state functional connectivity in neuropsychiatric disorders. Curr Opin Neurol 24:424–430CrossRefGoogle Scholar
  14. 14.
    Greicius MD, Kiviniemi V, Tervonen O, Vainionpää V, Alahuhta S, Reiss AL, Menon V (2008) Persistent default-mode network connectivity during light sedation. Hum Brain Mapp 29:839–847PubMedCrossRefGoogle Scholar
  15. 15.
    Habas C, Kamdar N, Nguyen D, Prater K, Beckmann CF, Menon V, Greicius MD (2009) Distinct cerebellar contributions to intrinsic connectivity networks. J Neurosci 29:8586–8594PubMedCrossRefGoogle Scholar
  16. 16.
    Hampson M, Peterson BS, Skudlarski P, Gatenby JC, Gore JC (2002) Detection of functional connectivity using temporal correlations in MR images. Hum Brain Mapp 15:247–262PubMedCrossRefGoogle Scholar
  17. 17.
    He BJ, Snyder AZ, Vincent JL, Epstein A, Shulman GL, Corbetta M (2007) Breakdown of functional connectivity in frontoparietal networks underlies behavioral deficits in spatial neglect. Neuron 53:905–918PubMedCrossRefGoogle Scholar
  18. 18.
    van den Heuvel M, Mandl R, Hulshoff Pol H (2008) Normalized cut group clustering of resting-state FMRI data. PLoS ONE 3:e2001PubMedCrossRefGoogle Scholar
  19. 19.
    Heuvel MPVD, Mandl RC, Kahn RS, Pol HEH (2009) Functionally linked resting-state networks reflect the underlying structural connectivity architecture of the human brain. Hum Brain Mapp 30:3127–3141PubMedCrossRefGoogle Scholar
  20. 20.
    Kelly C, Uddin LQ, Shehzad Z, Margulies DS, Castellanos FX, Milham MP, Petrides M (2010) Broca’s region: linking human brain functional connectivity data and non-human primate tracing anatomy studies. Eur J Neurosci 32:383–398PubMedCrossRefGoogle Scholar
  21. 21.
    Kiviniemi V, Kantola J, Jauhiainen J, Hyvärinen A, Tervonen O (2003) Independent component analysis of nondeterministic fMRI signal sources. Neuroimage 19:253–260PubMedCrossRefGoogle Scholar
  22. 22.
    Kiviniemi V, Starck T, Remes J, Long X, Nikkinen J, Haapea M, Veijola J, Moilanen I, Isohanni M, Zang Y, Tervonen O (2009) Functional segmentation of the brain cortex using high model order group PICA. Hum Brain Mapp 30:3865–3886PubMedCrossRefGoogle Scholar
  23. 23.
    Krienen FM, Buckner RL (2009) Segregated fronto-cerebellar circuits revealed by intrinsic functional connectivity. Cereb Cortex 19:2485–2497PubMedCrossRefGoogle Scholar
  24. 24.
    Liu H, Buckner RL, Talukdar T, Tanaka N, Madsen JR, Stufflebeam SM (2009) Task-free presurgical mapping using functional magnetic resonance imaging intrinsic activity. J Neurosurg 111:746–754PubMedCrossRefGoogle Scholar
  25. 25.
    Lohmann G, Muller K, Bosch V, Mentzel H, Hessler S, Chen L, Zysset S, von Cramon DY (2001) Lipsia-a new software system for the evaluation of functional magnetic resonance images of the human brain. Comput Med Imaging Graph 25:449–457PubMedCrossRefGoogle Scholar
  26. 26.
    Lohmann G, Hoehl S, Brauer J, Danielmeier C, Bornkessel-Schlesewsky I, Bahlmann J, Turner R, Friederici A (2010) Setting the frame: the human brain activates a basic low-frequency network for language processing. Cereb Cortex 20:1286–1292PubMedCrossRefGoogle Scholar
  27. 27.
    Margulies DS, Kelly AC, Uddin LQ, Biswal BB, Castellanos FX, Milham MP (2007) Mapping the functional connectivity of anterior cingulate cortex. Neuroimage 37:579–588PubMedCrossRefGoogle Scholar
  28. 28.
    Mesulam M (2009) Defining neurocognitive networks in the BOLD new world of computed connectivity. Neuron 62:1–3PubMedCrossRefGoogle Scholar
  29. 29.
    Nioche C, Cabanis E, Habas C (2009) Functional connectivity of the human red nucleus in the brain resting state at 3T. AJNR Am J Neuroradiol 30:396–403PubMedCrossRefGoogle Scholar
  30. 30.
    Nir Y, Mukamel R, Dinstein I, Privman E, Harel M, Fisch L, Gelbard-Sagiv H, Kipervasser S, Andelman F, Neufeld MY, Kramer U, Arieli A, Fried I, Malach R (2008) Interhemispheric correlations of slow spontaneous neuronal fluctuations revealed in human sensory cortex. Nat Neurosci 11:1100–1108PubMedCrossRefGoogle Scholar
  31. 31.
    O'Reilly JX, Beckmann CF, Tomassini V, Ramnani N, Johansen-Berg H (2010) Distinct and overlapping functional zones in the cerebellum defined by resting state functional connectivity. Cereb Cortex 20:953–965PubMedCrossRefGoogle Scholar
  32. 32.
    Pouratian N, Bookheimer SY (2010) The reliability of neuroanatomy as a predictor of eloquence: a review. Neurosurg Focus 28:E3PubMedCrossRefGoogle Scholar
  33. 33.
    Raichle ME, MacLeod AM, Snyder AZ, Powers WJ, Gusnard DA, Shulman GL (2001) A default mode of brain function. Proc Natl Acad Sci USA 98:676–682PubMedCrossRefGoogle Scholar
  34. 34.
    Seeley WW, Menon V, Schatzberg AF, Keller J, Glover GH, Kenna H, Reiss AL, Greicius MD (2007) Dissociable intrinsic connectivity networks for salience processing and executive control. J Neurosci 27:2349–2356PubMedCrossRefGoogle Scholar
  35. 35.
    Shimony JS, Zhang D, Johnston JM, Fox MD, Roy A, Leuthardt EC (2009) Resting-state spontaneous fluctuations in brain activity: a new paradigm for presurgical planning using fMRI. Acad Radiol 16:578–583PubMedCrossRefGoogle Scholar
  36. 36.
    Stark DE, Margulies DS, Shehzad ZE, Reiss P, Kelly AMC, Uddin LQ, Gee DG, Roy AK, Banich MT, Castellanos FX, Milham MP (2008) Regional variation in interhemispheric coordination of intrinsic hemodynamic fluctuations. J Neurosci 28:13754–13764PubMedCrossRefGoogle Scholar
  37. 37.
    Vincent JL, Kahn I, Snyder AZ, Raichle ME, Buckner RL (2008) Evidence for a frontoparietal control system revealed by intrinsic functional connectivity. J Neurophysiol 100:3328–3342PubMedCrossRefGoogle Scholar
  38. 38.
    Vlieger E, Majoie CB, Leenstra S, den Heeten GJ (2004) Functional magnetic resonance imaging for neurosurgical planning in neurooncology. Eur Radiol 14:1143–1153PubMedCrossRefGoogle Scholar
  39. 39.
    Zhang D, Johnston JM, Fox MD, Leuthardt EC, Grubb RL, Chicoine MR, Smyth MD, Snyder AZ, Raichle ME, Shimony JS (2009) Preoperative sensorimotor mapping in brain tumor patients using spontaneous fluctuations in neuronal activity imaged with functional magnetic resonance imaging. Neurosurgery 65:ons226–ons236CrossRefGoogle Scholar
  40. 40.
    Zhang D, Snyder AZ, Fox MD, Sansbury MW, Shimony JS, Raichle ME (2008) Intrinsic functional relations between human cerebral cortex and thalamus. J Neurophysiol 100:1740–1748PubMedCrossRefGoogle Scholar

Copyright information

© Springer-Verlag 2011

Authors and Affiliations

  • Joachim Böttger
    • 1
    Email author
  • Daniel S. Margulies
    • 2
    • 3
  • Peter Horn
    • 1
  • Ulrich W. Thomale
    • 1
  • Ilana Podlipsky
    • 4
  • Irit Shapira-Lichter
    • 4
  • Shereen J. Chaudhry
    • 2
    • 3
  • Christine Szkudlarek
    • 1
  • Karsten Mueller
    • 3
  • Gabriele Lohmann
    • 3
  • Talma Hendler
    • 4
    • 5
  • Georg Bohner
    • 6
  • Jochen B. Fiebach
    • 7
  • Arno Villringer
    • 2
    • 3
  • Peter Vajkoczy
    • 1
  • Alexander Abbushi
    • 1
  1. 1.Department of NeurosurgeryCharité-Universitätsmedizin BerlinBerlinGermany
  2. 2.Mind & Brain Institute and Berlin School of Mind and BrainHumboldt UniversitätBerlinGermany
  3. 3.Max Planck Institute for Human Cognitive and Brain SciencesLeipzigGermany
  4. 4.Wohl Institute for Advanced ImagingTel-Aviv Sourasky Medical CenterTel AvivIsrael
  5. 5.Sackler Faculty of MedicineTel Aviv UniversityTel AvivIsrael
  6. 6.Department of NeuroradiologyCharité-Universitätsmedizin BerlinBerlinGermany
  7. 7.Center for Stroke Research BerlinCharité-Universitätsmedizin BerlinBerlinGermany

Personalised recommendations