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Diffusion tensor fiber tracking of human brain connectivity: aquisition methods, reliability analysis and biological results

  1. N. F. Lori1,2,
  2. E. Akbudak1,
  3. J. S. Shimony1,
  4. T. S. Cull1,
  5. A. Z. Snyder1,
  6. R. K. Guillory1,
  7. T. E. Conturo1,2,*

Article first published online: 5 DEC 2002

DOI: 10.1002/nbm.779

Issue

NMR in Biomedicine

NMR in Biomedicine

Special Issue: Diffusion tensor imaging and axonal mapping - state of the art

Volume 15, Issue 7-8, pages 494–515, November - December 2002

Additional Information

How to Cite

Lori, N. F., Akbudak, E., Shimony, J. S., Cull, T. S., Snyder, A. Z., Guillory, R. K. and Conturo, T. E. (2002), Diffusion tensor fiber tracking of human brain connectivity: aquisition methods, reliability analysis and biological results. NMR Biomed., 15: 494–515. doi: 10.1002/nbm.779

Author Information

  1. 1

    Mallinckrodt Institute of Radiology, Washington University School of Medicine, 4525 Scott Avenue, St Louis, MO 63110, USA

  2. 2

    Department of Physics, Washington University, 1 Brookings Drive, St Louis, MO 63130, USA

*Neuroimaging Laboratories, Mallinckrodt Institute of Radiology, Washington University School of Medicine, 4525 Scott Ave, St Louis, MO 63110, USA

Publication History

  1. Issue published online: 5 DEC 2002
  2. Article first published online: 5 DEC 2002
  3. Manuscript Revised: 9 DEC 2002
  4. Manuscript Accepted: 16 MAY 2002
  5. Manuscript Received: 24 JUL 2001

Funded by

  • NIH. Grant Numbers: R01 NS39538, P01 NS06833, P20 MH62130

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Keywords:

  • brain function;
  • brain anatomy;
  • white matter;
  • MRI;
  • diffusion tensor;
  • connectivity

Abstract

  1. Top of page
  2. Abstract
  3. REFERENCES

We present a description, biological results and a reliability analysis for the method of diffusion tensor tracking (DTT) of white matter fiber pathways. In DTT, diffusion-tensor MRI (DT-MRI) data are collected and processed to visualize the line trajectories of fiber bundles within white matter (WM) pathways of living humans. A detailed description of the data acquisition is given. Technical aspects and experimental results are illustrated for the geniculo-calcarine tract with broad projections to visual cortex, occipital and parietal U-fibers, and the temporo-calcarine ventral pathway. To better understand sources of error and to optimize the method, accuracy and precision were analyzed by computer simulations. In the simulations, noisy DT-MRI data were computed that would be obtained for a WM pathway having a helical trajectory passing through gray matter. The error vector between the real and ideal track was computed, and random errors accumulated with the square root of track length consistent with a random-walk process. Random error was most dependent on signal-to-noise ratio, followed by number of averages, pathway anisotropy and voxel size, in decreasing order. Systematic error only occurred for a few conditions, and was most dependent on the stepping algorithm, anisotropy of the surrounding tissue, and non-equal voxel dimensions. Both random and systematic errors were typically below the voxel dimension. Other effects such as track rebound and track recovery also depended on experimental conditions. The methods, biological results and error analysis herein may improve the understanding and optimization of DTT for use in various applications in neuroscience and medicine. Copyright © 2002 John Wiley & Sons, Ltd.

REFERENCES

  1. Top of page
  2. Abstract
  3. REFERENCES
  • 1
    Mori S, Crain BJ, Chacko VP, van Zijl PC. Three-dimensional tracking of axonal projections in the brain by magnetic resonance imaging. Ann. Neurol. 1999; 45: 265–269.
    Direct Link:
  • 2
    Lori NF, Cull TS, Akbudak E, Snyder AZ, Shimony JS, Burton H, Raichle ME, Conturo TE. Tracking neuronal fibers in the living human brain with diffusion MRI. In Proceedings of International Society for Magnetic Resonance in Medicine: Philadelphia, PA, May 1999; 324.
  • 3
    Conturo TE, Lori NF, Cull TS, Akbudak E, Snyder AZ, Shimony JS, McKinstry RC, Burton H, Raichle ME. Tracking neuronal fiber pathways in the living human brain. Proc. Natl Acad. Sci. USA 1999; 96: 10422–10427.
  • 4
    Basser PJ, Pajevic S, Pierpaoli C, Duda J, Aldroubi A. In vivo fiber tractography using DT-MRI data. Magn. Reson. Med. 2000; 44: 625–632.
    Direct Link:
  • 5
    Poupon C, Clark CA, Frouin V, Regis J, Bloch I, Le Bihan D, Mangin J. Regularization of diffusion-based direction maps for the tracking of brain white matter fascicles. NeuroImage 2000; 12: 184–195.
  • 6
    LaVail JH. The retrograde transport method. Fed. Proc. 1975; 34: 1618–1624.
  • 7
    Holstege JC, Vrensen GF. Anterograde tracing in the brain using autoradiography and HRP-histochemistry. A comparison at the ultrastructural level. J. Microsc. 1988; 150: 233–243.
  • 8
    Steinbusch HW, Wouterlood FG, de Vente J, Bol JG, Berkenbosch F. Immunohistochemical localization of monoamines and cyclic nucleotides. Their application in quantitative immunofluorescence studies and tracing monoaminergic neuronal connections. Acta Histochem. Suppl. 1988; 35: 86–106.
  • 9
    Honig MG, Hume RI. Dil and diO: versatile fluorescent dyes for neuronal labelling and pathway tracing. Trends Neurosci. 1989; 12: 333–335, 340–341.
  • 10
    Veenman CL, Reiner A, Honig MG. Biotinylated dextran amine as an anterograde tracer for single- and double-labeling studies. J. Neurosci. Meth. 1992; 41: 239–254.
  • 11
    Ding SL, Elberger AJ. A modification of biotinylated dextran amine histochemistry for labeling the developing mammalian brain. J. Neurosci. Meth. 1995; 57: 67–75.
  • 12
    Godement P, Vanselow J, Thanos S, Bonhoeffer F. A study in developing visual systems with a new method of staining neurones and their processes in fixed tissue. Development 1987; 101: 697–713.
  • 13
    Burton H, Fabri M. Ipsilateral intracortical connections of physiologically defined cutaneous representations in areas 3b and 1 of macaque monkeys: Projections in the vicinity of the central sulcus. J. Comp. Neurol. 1995; 355: 508–538.
    Direct Link:
  • 14
    Lin CP, Tseng WY, Cheng HC, Chen JH. Validation of diffusion tensor magnetic resonance axonal fiber imaging with registered manganese-enhanced optic tracts. NeuroImage 2001; 14: 1035–1047.
  • 15
    Crick F, Jones E. Backwardness of human neuroanatomy. Nature 1993; 361: 109–110.
  • 16
    Dejerine J. Anatomie des Centres Nerveux, Vol. 1. Rueff: Paris, 1895.
  • 17
    Critchley M. The Parietal Lobe. Hafner: New York, 1966.
  • 18
    Yagishita A, Nakano I, Oda M, Hirano A. Location of the corticospinal tract in the internal capsule at MR imaging. Radiology 1994; 191: 455–460; Rademacher J, Engelbrecht V, Burgel U, Freund H-J, Zilles K, Measuring in vivo myelination of human white matter fiber tracts with magnetization transfer MR. NeuroImage 1999; 9: 393–406.
  • 19
    Fox PT, Raichle ME. Focal physiological uncoupling of cerebral blood flow and oxidative metabolism during somatosensory stimulation in human subjects. Proc. Natl Acad. Sci. USA 1986; 83: 1140–1144.
  • 20
    Raichle ME. Images of the mind: Studies with modern imaging techniques. Amu. Rev. Psychol. 1994; 45: 333–356.
  • 21
    Ogawa S, Tank DW, Menon R, Ellerman JM, Kim SG, Merkle HH, Ugurbil K. Intrinsic signal changes accompanying sensory stimulation: functional brain mapping with magnetic resonance imaging. Proc. Natl Acad. Sci. USA 1992; 89: 5951–5955.
  • 22
    Kwong KK, Belliveau JW, Chesler DA, Goldberg IE, Weisskoff RM, Poncelet BP, Kennedy DN, Hoppel BE, Cohen MS, Turner R, Cheng H-M, Brady TJ, Rosen BR. Dynamic magnetic resonance imaging of human brain activation during primary sensory stimulation. Proc. Natl Acad. Sci. USA 1992; 89: 5675–5679.
  • 23
    Bandettini PA, Wong EC, Hinks RS, Tikofsky RS, Hyde JS. Time course EPI of human brain function during task activation. Magn. Reson. Med. 1992; 25: 390–397.
    Direct Link:
  • 24
    Darquie A, Poline JB, Poupon C, Saint-Jalmes H, Le Bihan D. Transient decrease in water diffusion observed in human occipital cortex during visual stimulation. Proc. Natl Acad. Sci. USA 2001; 98: 9391–9395.
  • 25
    Xue R, van Zijl PC, Crain BJ, Solaiyappan M, Mori S. In vivo three-dimensional reconstruction of rat brain axonal projections by diffusion tensor imaging. Magn. Reson. Med. 1999; 42: 1123–1127.
    Direct Link:
  • 26
    Le Bihan D. What to expect from MRI in the investigation of the central nervous system? C. R. Acad. Sci. III 2000; 323: 341–350.
  • 27
    Basser PJ, Mattiello J, Le Bihan D. MR diffusion tensor spectroscopy and imaging. Biophys. J. 1994; 66: 259–267.
  • 28
    van Gelderen P, de Vleeschouwer MH, DesPres D, Pekar J, van Zijl PC, Moonen CT. Water diffusion and acute stroke. Magn. Reson. Med. 1994; 31: 154–163.
    Direct Link:
  • 29
    Sorensen AG, Buonanno FS, Gonzalez RG, Schwamm LH, Lev MH, Huang-Hellinger FR, Reese TG, Weisskoff RM, Davis TL, Suwanwela N, Can U, Moreira JA, Copen WA, Look RB, Finklestein SP, Rosen BR, Koroshetz WJ. Hyperacute stroke: evaluation with combined multisection diffusion-weighted and hemodynamically weighted echo-planar MR imaging. Radiology 1996; 199: 391–401.
  • 30
    Basser PJ, Mattiello J, Le Bihan D. Anisotropic diffusion: MR diffusion tensor imaging. In Diffusion and Perfusion Magnetic Resonance Imaging: Applications to Functional MRI, Le Bihan D (ed.). Raven Press: New York, 1995; 140–149.
  • 31
    Basser PJ, Pierpaoli C. Microstructural and physiological features of tissues elucidated by quantitative-diffusion-tensor MRI. J. Magn. Reson. B 1996; 111: 209–219.
  • 32
    Conturo TE, McKinstry RC, Akbudak E, Robinson BH. Encoding of anisotropic diffusion with tetrahedral gradients: a general mathematical diffusion formalism and experimental results. Magn. Reson. Med. 1996; 35: 399–412.
  • 33
    Pierpaoli C, Jezzard P, Basser PJ, Barnett A, Di Chiro G. Diffusion tensor MR imaging of the human brain. Radiology 1996; 201: 637–648.
  • 34
    Moseley ME, Kucharczyk J, Mintorovitch J, Cohen Y, Kurhanewicz J, Derugin N, Asgari H, Norman D. Diffusion-weighted MR imaging of acute stroke: correlation with T2-weighted and magnetic susceptibility-enhanced MR imaging in cats. Am. J. Neuroradiol. 1990; 11: 423–429.
  • 35
    Chenevert TL, Brunberg JA, Pipe JG. Anisotropic diffusion in human white matter: demonstration with MR techniques in vivo. Radiology 1990; 177: 401–405.
  • 36
    Doran M, Hajnal JV, Van Bruggen N, King MD, Young IR, Bydder GM. Normal and abnormal white matter tracts shown by MR imaging using directional diffusion weighted sequences. J. Comput. Assist. Tomogr. 1990; 14: 865–873.
  • 37
    Henkelman RM, Stanisz GJ, Kim JK, Bronskill MJ. Anisotropy of NMR properties of tissues. Magn. Reson. Med. 1994; 32: 592–601.
    Direct Link:
  • 38
    Hsu EW, Mori S. Analytical expressions for the NMR apparent diffusion coefficients in an anisotropic system and a simplified method for determining fiber orientation. Magn. Reson. Med. 1995; 34: 194–200.
    Direct Link:
  • 39
    Conturo TE, McKinstry RC, Aronovitz JA, Neil JJ. Diffusion MRI: precision, accuracy and flow effects. NMR Biomed. 1995; 8: 307–332.
    Direct Link:
  • 40
    Skare S, Hedehus M, Moseley ME, Li TQ. Condition number as a measure of noise performance of diffusion tensor data acquisition schemes with MRI. J. Magn. Reson. 2000; 147: 340–352.
  • 41
    Jones DK, Horsfield MA, Simmons A. Optimal strategies for measuring diffusion in anisotropic systems by magnetic resonance imaging. Magn. Reson. Med. 1999; 42: 515–525.
    Direct Link:
  • 42
    Muthupallai R, Holder CA, Song AW, Dixon WT. Navigator aided, multishot EPI diffusion images of brain with complete orientation and anisotropy information. In Proceedings of the International Society for Magnetic Resonance Medicine: Philadelphia, PA, 1999; 1825.
  • 43
    Papadakis NG, Xing D, Huang CL, Hall LD, Carpenter TA. A comparative study of acquisition schemes for diffusion tensor imaging using MRI. J. Magn. Reson. 1999; 137: 67–82.
  • 44
    Lori NF. Diffusion Tensor Tracking of Neuronal Fiber Pathways in the Living Human Brain. PhD Thesis, Physics. Washington University: St Louis, MO, 2001.
  • 45
    Lori NF, Akbudak EA, Shimony JS, Cull TS, Snyder AZ, Guillory RK, Conturo TE. Diffusion tensor fiber tracking: Methods, experimental results, and error simulations. In Diffusion NMR and MRI: From the Single Molecule to the Entire Human Brain, CohenY (ed.), 26–30 August, 2001, 57–72.
  • 46
    Lori NF, Akbudak E, Shimony JS, Snyder AZ, Raichle ME, Burton H, Price JL, Conturo TE. Diffusion MRI tracking of amygdalo-calcarine pathways: replication and detailed error study. Soc. Neurosci. Abstr. 2001; 27: 83.15.
  • 47
    Shimony JS, McKinstry RC, Akbudak E, Aronovitz JA, Snyder AZ, Lori NF, Cull TS, Conturo TE. Quantitative diffusion-tensor anisotropy brain MR imaging: normative human data and anatomic analysis. Radiology 1999; 212: 770–784.
  • 48
    Hasan KM, Parker DL, Alexander AL. Comparison of gradient encoding schemes for diffusion-tensor MRI. J. Magn. Reson. Imag. 2001; 13: 769–780.
    Direct Link:
  • 49
    Snyder AZ. Difference image vs. ratio image error function forms in PET-PET realignment. In: Quantification of Brain Function Using PET. MyersR, CunninghamV, BaileyD, JonesT (eds). Academic Press: San Diego, CA, 1995; 131–137.
  • 50
    Haselgrove JC, Moore JR. Correction for distortion of echo-planar images used to calculate the apparent diffusion coefficient. Magn. Reson. Med. 1996; 36: 960–964.
    Direct Link:
  • 51
    Mattiello J, Basser PJ, Le Bihan D. Analytical expressions for the b-matrix in MR diffusion imaging and spectroscopy. J. Magn. Reson. 1994; 108: 131–141.
  • 52
    Press WH. Numerical Recipes in C: the Art of Scientific Computing. Cambridge University Press: Cambridge, 1992.
  • 53
    Crank J. The Mathematics of Diffusion. Clarendon Press: Oxford, 1975.
  • 54
    Tuch DS, Weisskoff RM, Belliveau JW, Wedeen VJ. High angular resolution diffusion imaging of the human brain. In Proceedings of the International Society for Magnetic Resonance in Medicine: Philadelphia, PA, 1999; 321.
  • 55
    Wedeen VJ, Reese TG, Tuch DS, Weigel MR, Dou J-G, Weiskoff RM, Chessler D. Mapping fiber orientation spectra in cerebral white matter with Fourier-transform diffusion MRI. In Proceedings of the International Society for Magnetic Resonance in Medicine, Denver, CO, 2000; 82.
  • 56
    Lori NF, Conturo TE. Diffusion time assignment and q-space formalism for finite-duration diffusion-encoding gradients: simulation of 3D random walks. In Diffusion MRI: Biophysical Issues, Saint-Malo, France, 10–12 March, 2002; 9–12.
  • 57
    Pierpaoli C, Basser PJ. Toward a quantitative assessment of diffusion anisotropy Magn. Reson. Med.1996; 36: 893–906 [Published erratum appears in Magn. Reson. Med. 1997; 37: 972].
  • 58
    Ulug AM, van Zijl PC. Orientation-independent diffusion imaging without tensor diagonalization: anisotropy definitions based on physical attributes of the diffusion ellipsoid. J. Magn. Reson. Imag. 1999; 9: 804–813.
    Direct Link:
  • 59
    Napel S, Lee DH, Frayne R, Rutt BK. Visualizing three-dimensional flow with simulated streamlines and three-dimensional phase contrast MR imaging. J. Magn. Reson. Imag. 1992; 2: 143–153.
    Direct Link:
  • 60
    Lori NF, Akbudak E, Snyder AZ, Shimony JS, Conturo TE. Diffusion tensor tracking of human neuronal fiber bundles: simulation of effects of noise, voxel size, and data interpolation. In Proceedings of the International Society for Magnetic Resonance in Medicine, Denver, CO, 2000; 775.
  • 61
    Lazar M, Alexander A. Error analysis of white matter tracking algorithms (streamlines and tensorlines) for DT-MRI. In Proceedings of the International Society for Magnetic Resonance Medicine: Glasgow, Scotland, 2001; 506.
  • 62
    Cantor CR, Shimmel PR. Biophysical Chemistry Part I: the Conformation of Biological Macromolecules. WH Freeman: San Francisco, CA, 1980.
  • 63
    Neil JJ, Ackerman JJH. Detection of pseudodiffusion in rat brain following blood substitution with perfluorocarbon. J. Magn. Reson. 1992; 97: 194–201.
  • 64
    Henkelman RM. Measurement of signal intensities in the presence of noise in MR images. Med. Phys. 1985; 12: 232–233.
  • 65
    Edelstein WA, Bottomley PA, Hart HR, Smith LS. Signal, noise, and contrast in nuclear magnetic resonance (NMR) imaging. J. Comput. Assist. Tomogr. 1983; 7: 391–401.
  • 66
    Amaral DG, Price JL. Amygdalo-cortical projections in the monkey (Macaca fascicularis). J. Comp. Neurol. 1984; 230: 465–496.
    Direct Link:
  • 67
    Lori NF, Shimony JS, Snyder AZ, Akbudak E, Conturo TE. Numerical modeling of accuracy and precision in human diffusion tensor tracking. NeuroImage 2001; 13: S28.
  • 68
    Anderson AW. Theoretical analysis of the effects of noise on diffusion tensor imaging. Magn. Reson. Med. 2001; 46: 1174–1188.
    Direct Link:
  • 69
    Stieltjes B, Kaufmann WE, van Zijl PC, Fredericksen K, Pearlson GD, Solaiyappan M, Mori S. Diffusion tensor imaging and axonal tracking in the human brainstem. NeuroImage 2001; 14: 723–735.
  • 70
    Leon-Garcia A. Probability and Random Processes for Electrical Engineers. Addison-Wesley: Reading, MA, 1994.
  • 71
    Conturo TE, Smith GD. Signal-to-noise in phase angle reconstruction: dynamic range extension using phase reference offsets. Magn. Reson. Med. 1990; 15: 420–437.
    Direct Link:
  • 72
    Peled S, Yeshurun Y. Superresolution in MRI: application to human white matter fiber tract visualization by diffusion tensor imaging. Magn. Reson. Med. 2001; 45: 29–35.
    Direct Link:
  • 73
    Bastin ME, Armitage PA, Marshall I. A theoretical study of the effect of experimental noise on the measurement of anisotropy in diffusion imaging. Magn. Reson. Imag. 1998; 16: 773–785.
  • 74
    Pierpaoli C, Basser PJ. Toward a quantitative assessment of diffusion anisotropy. Magn. Reson. Med. 1996; 36: 893–906.
    Direct Link:
  • 75
    Basser PJ, Pajevic S. Statistical artifacts in diffusion tensor MRI (DT-MRI) caused by background noise. Magn. Reson. Med. 2000; 44: 41–50.
    Direct Link:
  • 76
    Dietrich O, Heiland S, Sartor K. Noise correction for the exact determination of apparent diffusion coefficients at low SNR. Magn. Reson. Med. 2001; 45: 448–453.
    Direct Link:
  • 77
    Miller AJ, Joseph PM. The use of power images to perform quantitative analysis on low SNR MR images. Magn. Reson. Imag. 1993; 11: 1051–1056.
  • 78
    Armitage PA, Bastin ME. Utilizing the diffusion-to-noise ratio to optimize magnetic resonance diffusion tensor acquisition strategies for improving measurements of diffusion anisotropy. Magn. Reson. Med. 2001; 45: 1056–1065.
    Direct Link:
  • 79
    Skare S, Li T, Nordell B, Ingvar M. Noise considerations in the determination of diffusion tensor anisotropy. Magn. Reson. Imag. 2000; 18: 659–669.
Abbreviations used:
DTT

diffusion tensor tracking

DT-MRI

diffusion tensor MRI

EPI

echo planar imaging

GCT

geniculo-calcarine tract

GM

gray matter

RA

relative anisotropy

SNR

signal-to-noise ratio

SSV

spatial selection volume

WM

white matter

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