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Impact of fMRI-guided advanced DTI fiber tracking techniques on their clinical applications in patients with brain tumors

  • Functional Neuroradiology
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Abstract

Introduction

White matter tractography based on diffusion tensor imaging has become a well-accepted non-invasive tool for exploring the white matter architecture of the human brain in vivo. There exist two main key obstacles for reconstructing white matter fibers: firstly, the implementation and application of a suitable tracking algorithm, which is capable of reconstructing anatomically complex fascicular pathways correctly, as, e.g., areas of fiber crossing or branching; secondly, the definition of an appropriate tracking seed area for starting the reconstruction process. Large intersubject, anatomical variations make it difficult to define tracking seed areas based on reliable anatomical landmarks. An accurate definition of seed regions for the reconstruction of a specific neuronal pathway becomes even more challenging in patients suffering from space occupying pathological processes as, e.g., tumors due to the displacement of the tissue and the distortion of anatomical landmarks around the lesion.

Methods

To resolve the first problem, an advanced tracking algorithm, called advanced fast marching, was applied in this study. The second challenge was overcome by combining functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI) in order to perform fMRI-guided accurate definition of appropriate seed areas for the DTI fiber tracking. In addition, the performance of the tasks was controlled by a MR-compatible power device.

Results

Application of this combined approach to eight healthy volunteers and exemplary to three tumor patients showed that it is feasible to accurately reconstruct relevant fiber tracts belonging to a specific functional system.

Conclusion

fMRI-guided advanced DTI fiber tracking has the potential to provide accurate anatomical and functional information for a more informed therapeutic decision making.

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References

  1. Arfanakis K, Gui M, Lazar M (2006) Optimization of white matter tractography for pre-surgical planning and image-guided surgery. Oncol Rep 15:1061–1064

    PubMed  Google Scholar 

  2. Bammer R, Auer M, Keeling SL, Augustin M, Stables LA, Prokesch RW, Stollberger R, Moseley ME, Fazekas F (2002) Diffusion tensor imaging using single-shot SENSE-EPI. Magn Reson Med 48:128–136. doi:10.1002/mrm.10184

    Article  PubMed  Google Scholar 

  3. Basser PJ, Mattiello J, LeBihan D (1994) MR diffusion tensor spectroscopy and imaging. Biophys J 66:259–267. doi:10.1016/S0006-3495(94)80775-1

    Article  CAS  PubMed  Google Scholar 

  4. Basser PJ, Pajevic S (2000) Statistical artifacts in diffusion tensor MRI (DT-MRI) caused by background noise. Magn Reson Med 44:41–50. doi:10.1002/1522-2594(200007)44:1<41::AID-MRM8>3.0.CO;2-O

    Article  CAS  PubMed  Google Scholar 

  5. Basser PJ, Pajevic S, Pierpaoli C, Duda J, Aldroubi A (2000) In vivo fiber tractography using DT-MRI data. Magn Reson Med 44:625–632. doi:10.1002/1522-2594(200010)44:4<625::AID-MRM17>3.0.CO;2-O

    Article  CAS  PubMed  Google Scholar 

  6. Batchelor PG, Atkinson D, Hill DL, Calamante F, Connelly A (2003) Anisotropic noise propagation in diffusion tensor MRI sampling schemes. Magn Reson Med 49:1143–1151. doi:10.1002/mrm.10491

    Article  CAS  PubMed  Google Scholar 

  7. Beisteiner R, Lanzenberger R, Novak K, Edward V, Windischberger C, Erdler M, Cunnington R, Gartus A, Streibl B, Moser E, Czech T, Deecke L (2000) Improvement of presurgical patient evaluation by generation of functional magnetic resonance risk maps. Neurosci Lett 290:13–16. doi:10.1016/S0304-3940(00)01303-3

    Article  CAS  PubMed  Google Scholar 

  8. Filippi M, Cercignani M, Inglese M, Horsfield MA, Comi G (2001) Diffusion tensor magnetic resonance imaging in multiple sclerosis. Neurology 56:304–311

    CAS  PubMed  Google Scholar 

  9. Frackowiak RSJ, Friston KJ, Frith C (2004) Human brain function. Academic, New York

    Google Scholar 

  10. Genovese CR, Lazar NA, Nichols T (2002) Thresholding of statistical maps in functional neuroimaging using the false discovery rate. Neuroimage 15:870–878. doi:10.1006/nimg.2001.1037

    Article  PubMed  Google Scholar 

  11. Goebell E, Fiehler J, Ding XQ, Paustenbach S, Nietz S, Heese O, Kucinski T, Hagel C, Westphal M, Zeumer H (2006) Disarrangement of fiber tracts and decline of neuronal density correlate in glioma patients—a combined diffusion tensor imaging and 1H-MR spectroscopy study. AJNR Am J Neuroradiol 27:1426–1431

    CAS  PubMed  Google Scholar 

  12. Goebell E, Paustenbach S, Vaeterlein O, Ding XQ, Heese O, Fiehler J, Kucinski T, Hagel C, Westphal M, Zeumer H (2006) Low-grade and anaplastic gliomas: differences in architecture evaluated with diffusion-tensor MR imaging. Radiology 239:217–222. doi:10.1148/radiol.2383050059

    Article  PubMed  Google Scholar 

  13. Guye M, Parker GJ, Symms M, Boulby P, Wheeler-Kingshott CA, Salek-Haddadi A, Barker GJ, Duncan JS (2003) Combined functional MRI and tractography to demonstrate the connectivity of the human primary motor cortex in vivo. Neuroimage 19:1349–1360. doi:10.1016/S1053-8119(03)00165-4

    Article  PubMed  Google Scholar 

  14. Helton KJ, Phillips NS, Khan RB, Boop FA, Sanford RA, Zou P, Li CS, Langston JW, Ogg RJ (2006) Diffusion tensor imaging of tract involvement in children with pontine tumors. AJNR Am J Neuroradiol 27:786–793

    CAS  PubMed  Google Scholar 

  15. Inoue T, Ogasawara K, Beppu T, Ogawa A, Kabasawa H (2005) Diffusion tensor imaging for preoperative evaluation of tumor grade in gliomas. Clin Neurol Neurosurg 107:174–180. doi:10.1016/j.clineuro.2004.06.011

    Article  PubMed  Google Scholar 

  16. Jaermann T, Crelier G, Pruessmann KP, Golay X, Netsch T, van Muiswinkel AM, Mori S, van Zijl PC, Valavanis A, Kollias S, Boesiger P (2004) SENSE-DTI at 3 T. Magn Reson Med 51:230–236. doi:10.1002/mrm.10707

    Article  CAS  PubMed  Google Scholar 

  17. Jones DK (2003) Determining and visualizing uncertainty in estimates of fiber orientation from diffusion tensor MRI. Magn Reson Med 49:7–12. doi:10.1002/mrm.10331

    Article  PubMed  Google Scholar 

  18. Jones DK, Basser PJ (2004) “Squashing peanuts and smashing pumpkins”: how noise distorts diffusion-weighted MR data. Magn Reson Med 52:979–993. doi:10.1002/mrm.20283

    Article  PubMed  Google Scholar 

  19. Karonen JO, Liu Y, Vanninen RL, Ostergaard L, Kaarina Partanen PL, Vainio PA, Vanninen EJ, Nuutinen J, Roivainen R, Soimakallio S, Kuikka JT, Aronen HJ (2000) Combined perfusion- and diffusion-weighted MR imaging in acute ischemic stroke during the 1st week: a longitudinal study. Radiology 217:886–894

    CAS  PubMed  Google Scholar 

  20. Karonen JO, Vanninen RL, Liu Y, Ostergaard L, Kuikka JT, Nuutinen J, Vanninen EJ, Partanen PL, Vainio PA, Korhonen K, Perkio J, Roivainen R, Sivenius J, Aronen HJ (1999) Combined diffusion and perfusion MRI with correlation to single-photon emission CT in acute ischemic stroke. Ischemic penumbra predicts infarct growth. Stroke 30:1583–1590

    CAS  PubMed  Google Scholar 

  21. Lazar M, Alexander AL (2003) An error analysis of white matter tractography methods: synthetic diffusion tensor field simulations. Neuroimage 20:1140–1153. doi:10.1016/S1053-8119(03)00277-5

    Article  PubMed  Google Scholar 

  22. Lazar M, Alexander AL (2005) Bootstrap white matter tractography (BOOT-TRAC). Neuroimage 24:524–532. doi:10.1016/j.neuroimage.2004.08.050

    Article  PubMed  Google Scholar 

  23. Lazar M, Alexander AL, Thottakara PJ, Badie B, Field AS (2006) White matter reorganization after surgical resection of brain tumors and vascular malformations. AJNR Am J Neuroradiol 27:1258–1271

    CAS  PubMed  Google Scholar 

  24. Lazar M, Weinstein DM, Tsuruda JS, Hasan KM, Arfanakis K, Meyerand ME, Badie B, Rowley HA, Haughton V, Field A, Alexander AL (2003) White matter tractography using diffusion tensor deflection. Hum Brain Mapp 18:306–321. doi:10.1002/hbm.10102

    Article  PubMed  Google Scholar 

  25. Maldjian JA, Grossman RI (2001) Future applications of DWI in MS. J Neurol Sci 186(Suppl 1):S55–S57. doi:10.1016/S0022-510X(01)00494-4

    Article  PubMed  Google Scholar 

  26. Mori S, Barker PB (1999) Diffusion magnetic resonance imaging: its principle and applications. Anat Rec 257:102–109. doi:10.1002/(SICI)1097-0185(19990615)257:3<102::AID-AR7>3.0.CO;2-6

    Article  CAS  PubMed  Google Scholar 

  27. Mori S, van Zijl PC (2002) Fiber tracking: principles and strategies - a technical review. NMR Biomed 15:468–480. doi:10.1002/nbm.781

    Article  PubMed  Google Scholar 

  28. Netsch T, vanMuiswinkel A (2004) Quantitative evaluation of image-based distortion correction in diffusion tensor imaging. IEEE Trans Med Imaging 23:789–798. doi:10.1109/TMI.2004.827479

    Article  PubMed  Google Scholar 

  29. Nimsky C, Ganslandt O, Hastreiter P, Wang R, Benner T, Sorensen AG, Fahlbusch R (2005) Preoperative and intraoperative diffusion tensor imaging-based fiber tracking in glioma surgery. Neurosurgery 56:130–137 discussion 138

    PubMed  Google Scholar 

  30. Parker GJM, Wheeler-Kingshott CAM, Barker GJ (2002) Estimating distributed anatomical connectivity using fast marching methods and diffusion tensor imaging. IEEE Trans Med Imaging 21:505–512. doi:10.1109/TMI.2002.1009386

    Article  PubMed  Google Scholar 

  31. Pierpaoli C, Jezzard P, Basser PJ, Barnett A, Di Chiro G (1996) Diffusion tensor MR imaging of the human brain. Radiology 201:637–648

    CAS  PubMed  Google Scholar 

  32. Pruessmann KP, Weiger M, Scheidegger MB, Boesiger P (1999) SENSE: sensitivity encoding for fast MRI. Magn Reson Med 42:952–962. doi:10.1002/(SICI)1522-2594(199911)42:5<952::AID-MRM16>3.0.CO;2-S

    Article  CAS  PubMed  Google Scholar 

  33. Rovaris M, Bozzali M, Iannucci G, Ghezzi A, Caputo D, Montanari E, Bertolotto A, Bergamaschi R, Capra R, Mancardi GL, Martinelli V, Comi G, Filippi M (2002) Assessment of normal-appearing white and gray matter in patients with primary progressive multiple sclerosis: a diffusion-tensor magnetic resonance imaging study. Arch Neurol 59:1406–1412. doi:10.1001/archneur.59.9.1406

    Article  PubMed  Google Scholar 

  34. Rovaris M, Gallo A, Valsasina P, Benedetti B, Caputo D, Ghezzi A, Montanari E, Sormani MP, Bertolotto A, Mancardi G, Bergamaschi R, Martinelli V, Comi G, Filippi M (2005) Short-term accrual of gray matter pathology in patients with progressive multiple sclerosis: an in vivo study using diffusion tensor MRI. Neuroimage 24:1139–1146. doi:10.1016/j.neuroimage.2004.10.006

    Article  PubMed  Google Scholar 

  35. Schonberg T, Pianka P, Hendler T, Pasternak O, Assaf Y (2006) Characterization of displaced white matter by brain tumors using combined DTI and fMRI. Neuroimage 30:1100–1111. doi:10.1016/j.neuroimage.2005.11.015

    Article  PubMed  Google Scholar 

  36. Schwamm LH, Koroshetz WJ, Sorensen AG, Wang B, Copen WA, Budzik R, Rordorf G, Buonanno FS, Schaefer PW, Gonzalez RG (1998) Time course of lesion development in patients with acute stroke: serial diffusion- and hemodynamic-weighted magnetic resonance imaging. Stroke 29:2268–2276

    CAS  PubMed  Google Scholar 

  37. Smits M, Vernooij MW, Wielopolski PA, Vincent AJ, Houston GC, van der Lugt A (2007) Incorporating functional MR imaging into diffusion tensor tractography in the preoperative assessment of the corticospinal tract in patients with brain tumors. AJNR Am J Neuroradiol 28:1354–1361. doi:10.3174/ajnr.A0538

    Article  CAS  PubMed  Google Scholar 

  38. Staempfli P, Jaermann T, Crelier GR, Kollias S, Valavanis A, Boesiger P (2006) Resolving fiber crossing using advanced fast marching tractography based on diffusion tensor imaging. Neuroimage 30:110–120. doi:10.1016/j.neuroimage.2005.09.027

    Article  CAS  PubMed  Google Scholar 

  39. Staempfli P, Jaermann T, Valavanis A, Boesiger P, Kollias S (2004) fMRI based fiber tracking using SENSE-DTI at 3 Tesla. Presented at Proc Intl Soc Magn Reson Med, Kyoto, Japan, 2004.

  40. Staempfli P, Reischauer C, Jaermann T, Valavanis A, Kollias S, Boesiger P (2008) Combining fMRI and DTI: a framework for exploring the limits of fMRI-guided DTI fiber tracking and for verifying DTI-based fiber tractography results. Neuroimage 39:119–126. doi:10.1016/j.neuroimage.2007.08.025

    Article  CAS  PubMed  Google Scholar 

  41. Staempfli P, Rienmueller A, Reischauer C, Valavanis A, Boesiger P, Kollias S (2007) Reconstruction of the human visual system based on DTI fiber tracking. J Magn Reson Imaging 26:886–893. doi:10.1002/jmri.21098

    Article  PubMed  Google Scholar 

  42. Tournier JD, Calamante F, King MD, Gadian DG, Connelly A (2002) Limitations and requirements of diffusion tensor fiber tracking: an assessment using simulations. Magn Reson Med 47:701–708. doi:10.1002/mrm.10116

    Article  PubMed  Google Scholar 

  43. Upadhyay J, Ducros M, Knaus TA, Lindgren KA, Silver A, Tager-Flusberg H, Kim DS (2007) Function and connectivity in human primary auditory cortex: a combined fMRI and DTI study at 3 Tesla. Cereb Cortex 17:2420–2432. doi:10.1093/cercor/bhl150

    Article  PubMed  Google Scholar 

  44. Warach S, Dashe JF, Edelman RR (1996) Clinical outcome in ischemic stroke predicted by early diffusion-weighted and perfusion magnetic resonance imaging: a preliminary analysis. J Cereb Blood Flow Metab 16:53–59. doi:10.1097/00004647-199601000-00006

    Article  CAS  PubMed  Google Scholar 

  45. Watts R, Liston C, Niogi S, Ulug AM (2003) Fiber tracking using magnetic resonance diffusion tensor imaging and its applications to human brain development. Ment Retard Dev Disabil Res Rev 9:168–177. doi:10.1002/mrdd.10077

    Article  PubMed  Google Scholar 

  46. Weinstein D, Kindlmann G, Lundberg E (1999) Tensorlines: advection-diffusion based propagation through diffusion tensor fields. IEEE Visualisation:249–253.

  47. Westin CF, Maier SE, Mamata H, Nabavi A, Jolesz FA, Kikinis R (2002) Processing and visualization for diffusion tensor MRI. Med Image Anal 6:93–108. doi:10.1016/S1361-8415(02)00053-1

    Article  PubMed  Google Scholar 

  48. Witwer BP, Moftakhar R, Hasan KM, Deshmukh P, Haughton V, Field A, Arfanakis K, Noyes J, Moritz CH, Meyerand ME, Rowley HA, Alexander AL, Badie B (2002) Diffusion-tensor imaging of white matter tracts in patients with cerebral neoplasm. J Neurosurg 97:568–575

    Article  PubMed  Google Scholar 

  49. Yasargil MG (1994) CNS tumors. Thieme Medical, New York

    Google Scholar 

  50. Yu CS, Li KC, Xuan Y, Ji XM, Qin W (2005) Diffusion tensor tractography in patients with cerebral tumors: a helpful technique for neurosurgical planning and postoperative assessment. Eur J Radiol 56:197–204. doi:10.1016/j.ejrad.2005.04.010

    Article  PubMed  Google Scholar 

  51. Zhang S, Bastin ME, Laidlaw DH, Sinha S, Armitage PA, Deisboeck TS (2004) Visualization and analysis of white matter structural asymmetry in diffusion tensor MRI data. Magn Reson Med 51:140–147. doi:10.1002/mrm.10673

    Article  PubMed  Google Scholar 

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Acknowledgments

The authors are grateful for the continuing support of Philips Medical Systems and the financial support by the Strategic Excellence Project Program (SEP) of the ETH Zurich.

Conflict of interest statement

We declare that we have no conflict of interest.

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Authors and Affiliations

  1. Institute of Neuroradiology, University Hospital Zurich, Frauenklinikstrasse 10, 8091, Zürich, Switzerland

    Raimund Kleiser, Philipp Staempfli, Anton Valavanis & Spyros Kollias

  2. Institute for Biomedical Engineering, University and ETH Zurich, Zürich, Switzerland

    Philipp Staempfli & Peter Boesiger

  3. Oö. Gesundheits- und Spitals-AG, Institute of Radiology, Landes-Nervenklinik Wagner-Jauregg, Wagner-Jauregg-Weg 15, 4020, Linz, Austria

    Raimund Kleiser

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  1. Raimund Kleiser
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  2. Philipp Staempfli
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Correspondence to Raimund Kleiser.

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Raimund Kleiser and Philipp Staempfli contributed equally to this work.

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Kleiser, R., Staempfli, P., Valavanis, A. et al. Impact of fMRI-guided advanced DTI fiber tracking techniques on their clinical applications in patients with brain tumors. Neuroradiology 52, 37–46 (2010). https://doi.org/10.1007/s00234-009-0539-2

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  • DOI: https://doi.org/10.1007/s00234-009-0539-2

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