Corticospinal Tractography with Morphological, Functional and Diffusion Tensor MRI: a Comparative Study of Four Deterministic Algorithms Used in Clinical Routine

Overview

Journal Surg Radiol Anat

Specialties Anatomy & Histology
General Surgery
Radiology

Date 2012 Mar 20

PMID 22427107

Citations 6

Authors

Romuald Seizeur

Nicolas Wiest-Daessle

Sylvain Prima

Camille Maumet

Jean-Christophe Ferre

Xavier Morandi

Affiliations

Soon will be listed here.

Abstract

Purpose: Diffusion tensor imaging permits study of white matter fibre bundles; however, its main limitation is lack of validation on anatomical data, especially in crossing fibre regions. Our study aimed to compare four deterministic tractography algorithms used in clinical routine. We studied the corticospinal tract, the bundle mediating voluntary movement. Our study seeks to evaluate tractography provided by algorithms through comparative analysis by expert neuroradiologists.

Methods: MRI data from 15 right-handed volunteers (30.8 years) were studied. Regions of interest (ROIs) were segmented on morphological and functional MRI. Diffusion weighted images (15 directions) were performed, then for each voxel the tensor was estimated. Tractography of the corticospinal tract was performed using four fibre-tracking algorithms. Three numerical integration methods Euler, Runge-Kutta second (RK2) and fourth order (RK4), and a tensor deflection method (TEND). Quantitative measurement was performed. Qualitative evaluation was carried out by two expert neuroradiologists using Kappa test concordance.

Results: For the quantitative aspect, only RK2 and TEND presented no significant difference concerning the number of fibres (p = 0.58). There was no difference between right and left side for each algorithm. Regarding the qualitative aspects, there was a lack of fibres from the ventrolateral part of the functional ROIs. Comparison by expert neuroradiologists revealed low rather than high concordance. The algorithm ranked first was RK2 according to expert preferences.

Conclusions: Different algorithms used in clinical routine failed to show realistic anatomical bundles. The most mathematically robust algorithm was not selected, nor was the algorithm defining more fibres. Validation of anatomical data provided by tractography remains a challenge.

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References

Mori S, Barker P . Diffusion magnetic resonance imaging: its principle and applications. Anat Rec. 1999; 257(3):102-9. DOI: 10.1002/(SICI)1097-0185(19990615)257:3<102::AID-AR7>3.0.CO;2-6. View

Ciccarelli O, Parker G, Toosy A, Wheeler-Kingshott C, Barker G, Boulby P . From diffusion tractography to quantitative white matter tract measures: a reproducibility study. Neuroimage. 2003; 18(2):348-59. DOI: 10.1016/s1053-8119(02)00042-3. View

Iwasaki S, Nakagawa H, Fukusumi A, Kichikawa K, Kitamura K, Otsuji H . Identification of pre- and postcentral gyri on CT and MR images on the basis of the medullary pattern of cerebral white matter. Radiology. 1991; 179(1):207-13. DOI: 10.1148/radiology.179.1.2006278. View

Lotze M, Erb M, Flor H, Huelsmann E, Godde B, Grodd W . fMRI evaluation of somatotopic representation in human primary motor cortex. Neuroimage. 2000; 11(5 Pt 1):473-81. DOI: 10.1006/nimg.2000.0556. View

Hasan K, Walimuni I, Abid H, Hahn K . A review of diffusion tensor magnetic resonance imaging computational methods and software tools. Comput Biol Med. 2010; 41(12):1062-72. PMC: 3135778. DOI: 10.1016/j.compbiomed.2010.10.008. View

Fillard P, Descoteaux M, Goh A, Gouttard S, Jeurissen B, Malcolm J . Quantitative evaluation of 10 tractography algorithms on a realistic diffusion MR phantom. Neuroimage. 2011; 56(1):220-34. DOI: 10.1016/j.neuroimage.2011.01.032. View

Lawes I, Barrick T, Murugam V, Spierings N, Evans D, Song M . Atlas-based segmentation of white matter tracts of the human brain using diffusion tensor tractography and comparison with classical dissection. Neuroimage. 2007; 39(1):62-79. DOI: 10.1016/j.neuroimage.2007.06.041. View

Ciccarelli O, Catani M, Johansen-Berg H, Clark C, Thompson A . Diffusion-based tractography in neurological disorders: concepts, applications, and future developments. Lancet Neurol. 2008; 7(8):715-27. DOI: 10.1016/S1474-4422(08)70163-7. View

OLDFIELD R . The assessment and analysis of handedness: the Edinburgh inventory. Neuropsychologia. 1971; 9(1):97-113. DOI: 10.1016/0028-3932(71)90067-4. View

10.

Lazar M, Weinstein D, Tsuruda J, Hasan K, Arfanakis K, Meyerand M . White matter tractography using diffusion tensor deflection. Hum Brain Mapp. 2003; 18(4):306-21. PMC: 6871932. DOI: 10.1002/hbm.10102. View

11.

Caulo M, Briganti C, Mattei P, Perfetti B, Ferretti A, Romani G . New morphologic variants of the hand motor cortex as seen with MR imaging in a large study population. AJNR Am J Neuroradiol. 2007; 28(8):1480-5. PMC: 8134386. DOI: 10.3174/ajnr.A0597. View

12.

Johansen-Berg H, Behrens T . Just pretty pictures? What diffusion tractography can add in clinical neuroscience. Curr Opin Neurol. 2006; 19(4):379-85. PMC: 3119814. DOI: 10.1097/01.wco.0000236618.82086.01. View

13.

Lin C, Tseng W, Cheng H, Chen J . Validation of diffusion tensor magnetic resonance axonal fiber imaging with registered manganese-enhanced optic tracts. Neuroimage. 2001; 14(5):1035-47. DOI: 10.1006/nimg.2001.0882. View

14.

Chung H, Chou M, Chen C . Principles and limitations of computational algorithms in clinical diffusion tensor MR tractography. AJNR Am J Neuroradiol. 2010; 32(1):3-13. PMC: 7964942. DOI: 10.3174/ajnr.A2041. View

15.

Wedeen V, Hagmann P, Tseng W, Reese T, Weisskoff R . Mapping complex tissue architecture with diffusion spectrum magnetic resonance imaging. Magn Reson Med. 2005; 54(6):1377-86. DOI: 10.1002/mrm.20642. View

16.

Qazi A, Radmanesh A, ODonnell L, Kindlmann G, Peled S, Whalen S . Resolving crossings in the corticospinal tract by two-tensor streamline tractography: Method and clinical assessment using fMRI. Neuroimage. 2008; 47 Suppl 2:T98-106. PMC: 2746909. DOI: 10.1016/j.neuroimage.2008.06.034. View

17.

Yamada K, Sakai K, Hoogenraad F, Holthuizen R, Akazawa K, Ito H . Multitensor tractography enables better depiction of motor pathways: initial clinical experience using diffusion-weighted MR imaging with standard b-value. AJNR Am J Neuroradiol. 2007; 28(9):1668-73. PMC: 8134192. DOI: 10.3174/ajnr.A0640. View

18.

Conturo T, Lori N, Cull T, Akbudak E, Snyder A, Shimony J . Tracking neuronal fiber pathways in the living human brain. Proc Natl Acad Sci U S A. 1999; 96(18):10422-7. PMC: 17904. DOI: 10.1073/pnas.96.18.10422. View

19.

Schimrigk S, Bellenberg B, Schluter M, Stieltjes B, Drescher R, Rexilius J . Diffusion tensor imaging-based fractional anisotropy quantification in the corticospinal tract of patients with amyotrophic lateral sclerosis using a probabilistic mixture model. AJNR Am J Neuroradiol. 2007; 28(4):724-30. PMC: 7977339. View

20.

Jones D, Horsfield M, Simmons A . Optimal strategies for measuring diffusion in anisotropic systems by magnetic resonance imaging. Magn Reson Med. 1999; 42(3):515-25. View