BJR
HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS

This Article
Right arrow Abstract Freely available
Right arrow Figures Only
Right arrow Full Text (PDF)
Services
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Right arrow reprints & permissions
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Gillard, J H
Right arrow Articles by Pickard, J D
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Gillard, J H
Right arrow Articles by Pickard, J D
British Journal of Radiology 74 (2001),642-647 © 2001 The British Institute of Radiology

Short communication

MR diffusion tensor imaging of white matter tract disruption in stroke at 3 T

J H Gillard, BSc, MD, FRCR 1, N G Papadakis, PhD 2,5 K Martin 5 C J S Price, BSc, MRCP 3 E A Warburton, MA, DM, MRCP 3 N M Antoun, FRCP, FRCR 1 C L-H Huang, PhD 2 T A Carpenter, PhD 5 and J D Pickard, MA, MChir, FRCS 4,5

Departments of 1Radiology, 2Physiology, 3Neurology and 4Neurosurgery and 5The Wolfson Brain Imaging Centre, University of Cambridge, Cambridge CB2 2QQ, UK


    Abstract
 Top
 Abstract
 Introduction
 Methods and patients
 Results
 Discussion
 Conclusion
 References
 
Recent advances in MR diffusion weighted imaging (DWI) enable the identification of anisotropic white matter tracts with diffusion tensor imaging (DTI). We aimed to use a novel DTI technique to safely study patients with recent stroke in a high field (3 T) MR machine with its intrinsically higher spatial resolution and signal-to-noise ratio. Of ten patients studied, six had disruption of white matter tracts as determined by DTI. A further patient had distortion of white matter tracts around an infarct rather than actual disruption of the tracts themselves. The lack of tract destruction may imply a beneficial prognosis, information that is not available with conventional DWI.


    Introduction
 Top
 Abstract
 Introduction
 Methods and patients
 Results
 Discussion
 Conclusion
 References
 
Recent advances in MR methodologies now enable rapid identification of ischaemic tissue in acute stroke. Techniques such as diffusion weighted imaging (DWI) [1–3] appear to delineate infarcted tissue [4–6]. Abnormalities demonstrated using MR perfusion imaging [7] and MR spectroscopic imaging [8] potentially identify areas at risk of infarction in the ischaemic penumbra. The challenges in imaging of very early stroke are centred on the identification of potentially salvageable tissue and the assessment of whether there is a major vascular occlusion or not, the aim being to give appropriate targeted therapy to identifiable subtypes of stroke. A less well addressed problem relates to the use of imaging to provide prognostic information regarding clinical outcome.

DWI and the extracted apparent diffusion coefficient (ADC) maps examine diffusion only along a defined spatial direction. Biological tissues possess varying degrees of structural organization at the macromolecular, membrane and cellular levels. Their diffusion properties, therefore, are typically anisotropic [9–11] and consequently can only be fully characterized through the symmetric 3 x 3 diffusion tensor, which comprises six independent scalar elements at the macroscopic scale of an imaging voxel [12]. Diffusion tensor imaging (DTI) has recently been proposed [12] and implemented for the in vivo study of cerebral [13] and cardiac [14] disease, enabling complete directional descriptions to be made of the self-diffusion properties of water through the tissue structure.

The ability to identify white matter tract disruption in acute stroke may be a useful index of stroke severity and may allow insight into likely recovery and long-term disability. There have been limited studies using DTI at conventional MR field strengths (1.5 T) in subacute stroke. The advent of very high strength magnetic fields (=>3 T), with their increased spatial resolution and signal-to-noise ratio, potentially allows for clearer identification of white matter disruption. The aim of this preliminary study was to use a novel high field DTI technique in the assessment of patients with stroke in an environment that allows the safe monitoring of acutely unwell patients whilst they are being imaged.


    Methods and patients
 Top
 Abstract
 Introduction
 Methods and patients
 Results
 Discussion
 Conclusion
 References
 
Ten patients presenting with stroke were imaged. Their demographics are presented in Table 1Go. Experiments were performed on a 3 T whole body system consisting of a Bruker Medspec 30/100 spectrometer (Bruker Medical, Etlingen, Germany) attached to an Oxford 3.0 T, 910 mm bore whole body actively shielded magnet (Oxford Magnet Technology, Oxford, UK). The whole body gradient coil had an internal diameter of 63 cm (Bruker, BG630), was actively shielded and had a maximum strength per axis of 35 mT m-1, using 225 µs ramps. DTI was performed using a standard single shot, spin echo, echo planar imaging (EPI) pulse sequence, inserting a pair of diffusion weighted (DW) Stejskal–Tanner rectangular gradient pulses in it [15]. The duration {Delta} of the DW gradient pulses was 21 ms and their temporal spacing {delta} was 66 ms. The DTI protocol consisted of 63 acquisitions in total. The DW gradients were applied along 12 non-collinear spatial directions uniformly arranged [16]. For each direction, five DW images were acquired, each corresponding to a different b value [15]. These five b values were distributed equidistantly in the interval (0–1570) s mm-2, with 1570 s mm-2 corresponding to optimum noise performance for a 2-point ADC measurement [16, 17]. The adverse effects of eddy currents on single shot DW EPI [18] were efficiently eliminated by a robust adjustment of the pre-emphasis unit of the system, as described by Papadakis et al [19]. Multislice imaging was performed with 8–12 contiguous slices in the near axial plane, with 5 mm slice thickness and 25 cm field of view. The acquisition matrix was 128 x 128 and sampling dwell time was 5 µs. Asymmetric k-space coverage was performed along the phase encode direction (24% of the data acquired prior to reaching the centre of k-space). The echo time (TE) was 106 ms and the repetition time (TR) was 5070 ms. No other intermediate processing step, such as image realignment or correction (due to eddy current induced distortions), was required owing to the efficient elimination of eddy current induced distortions achieved by the robust pre-emphasis adjustment [19]. Subsequently, maps of the rotationally invariant isotropy index (mean value of the trace Tr(D) of the diffusion tensor D and the rotationally invariant anisotropy index relative anisotropy (RA) [13, 20]) were calculated.


View this table:
[in this window]
[in a new window]
 
Table 1. Patient demographic data

 
Patients underwent a full clinical examination prior to the MR study. The diffusion tensor images were reviewed both as soft and hard copy, as were the conventional T2 and proton density weighted images. Specific reference was made to whether there was white matter tract disruption or distortion.

Ethical approval was obtained from the Local Research Ethics Committee of Addenbrooke's Hospital. Informed consent was obtained from each subject.


    Results
 Top
 Abstract
 Introduction
 Methods and patients
 Results
 Discussion
 Conclusion
 References
 
DTI was successfully performed in nine patients, one study being a technical failure due to patient movement artefact. No patient died during the study period. DTI took approximately 5 min; total post-processing time was approximately 15 min. All patients demonstrated DWI changes acquired with b=1000 s mm-2. DTI was initially abnormal in seven patients. The abnormalities consisted of actual disruption of white matter tracts in six patients. Patient No. 3 demonstrated initial displacement of white matter tracts rather than tract breakdown (Figure 1Go), which was associated with good clinical outcome at 4 months. Patient No. 9, imaged 11 h from stroke onset, had no tract disruption at presentation, with only subtle changes in the DWI study. The study was repeated 6 days later when the DWI abnormality was more extensive and there was definite disruption of white matter tracts (Figure 2Go). No patient demonstrated white matter tract changes distant to the acute stroke.



View larger version (128K):
[in this window]
[in a new window]
 
Figure 1. Two representative slices from the diffusion tensor images (A,B) and the trace images (C,D) in a 55-year-old male smoker (patient No. 3) who presented with a right hemiplegia, right seventh nerve palsy and dysarthria. The diffusion tensor imaging demonstrates displacement of the internal and external capsules (arrows) by an acute stroke based on the left corpus striatum extending into the corona radiata. The trace images confirm an acute ischaemic event.

 


View larger version (113K):
[in this window]
[in a new window]
 
Figure 2. A 25-year-old smoker (patient No. 9) presented with dysphasia and a right hemiparesis. Diffusion tensor images (A,B) are normal. The initial trace images (C,D) demonstrate a subtle area of increased signal in the anterior left putamen. The patient was re-imaged at 6 days, which demonstrated disruption of white matter tracts in the left corona radiata (E) with associated trace map changes (F) confirming early ischaemia.

 

    Discussion
 Top
 Abstract
 Introduction
 Methods and patients
 Results
 Discussion
 Conclusion
 References
 
This study has demonstrated that it is feasible to image acutely unwell stroke patients at 3 T, and that the diffusion tensor images can be obtained quickly and are able to delineate disruption in white matter tracts with good spatial resolution without artefact from cerebral spinal fluid pulsation. Furthermore, the ability to demonstrate distortion of tracts as well as partial or complete disruption may enable the technique to provide an indicator of likely functional deficit or recovery. As the sequence did not allow whole brain coverage, we may have missed distal effects such as cerebellar diaschisis.

DWI has been shown to be an effective tool in the diagnosis of tumours [21], demyelination [22], head injury [23] and stroke [4–6] even though these methods only examine diffusion along a defined direction. Measurement of the self-diffusion tensor D on a pixel-by-pixel basis can also lead to the calculation of scalar quantities, known as indices of anisotropy [24]; they reflect the degree of anisotropy of water diffusion and hence are related to the degree of architectural and structural coherence of the tissue within each pixel. Since a loss of tissue order and organization often occurs in abnormal development, aging and degeneration, such quantities are of significant clinical value not only for tissue structural and functional [25] studies but also in conditions such as stroke [26], traumatic brain injury [27], schizophrenia [28] and Wallerian degeneration [29]. Most studies to date have been at a field strength of 1.5 T.

A number of optimizations were performed to refine the DTI sequence, which included appropriate positioning of the DW gradient pulses with maximum temporal separation (for a given TE) that resulted in efficient diffusion weighting. Asymmetric k-space coverage along the phase encode direction reduced the TE. It was found that the asymmetry used (24%) was optimum (further asymmetry would lead to image artefacts) and thus T2, T2* effects were minimized. Diffusion tensor sampling was optimized using 12 uniformly arranged DW directions [16].

Such sampling significantly increases the accuracy and precision of DTI compared with schemes using the standard 6–7 DW directions. The maximum b value (bmax) used corresponded to the optimum noise performance for a 2-point ADC measurement, with the ADC equal to the mean value of the trace for normal brain parenchyma (D=0.7 x 10-3 mm2 s-1) [16, 17]. The optimum noise performance for a 2-point ADC measurement was therefore used as an objective criterion for selection of bmax. Finally, since the protocol entailed five signal acquisitions per DW direction, there were two alternatives: (i) to have all these acquisitions at the same b value, bmax (signal averaging); or (ii) to have them at different b values equally spaced between 0 and bmax. We used the second approach because it leads to better estimation of the anisotropic diffusion tensor compared with the first approach [16].

Mismatch between MR perfusion and DWI provides insight into tissue at risk of infarction that might benefit from therapeutic interventions. The techniques have been used in the assessment of patients receiving thrombolysis for acute ischaemic stroke [30]. DTI may provide an additional indicator of stroke pathophysiology, possibly allowing further differentiation of different stroke subtypes that may require differing therapeutic strategies. Sorensen et al [31] have recently shown significant changes in anisotropy in white matter in patients undergoing acute stroke. They noted much smaller changes in grey matter, a finding that has been corroborated by Mukherjee et al [26]. Whilst we found DTI changes most marked within white matter, the complementary trace images provided important information concerning grey matter ischaemia, allowing for an integrated assessment. Normative DTI data are now becoming available [32]. The DTI study of patient No. 3 showed distortion of the internal and external capsules secondary to ischaemia in the putamen. Tract distortion from adjacent oedematous tissue is not unexpected, however we feel that the lack of tract destruction may imply a beneficial prognosis, information that is not available with conventional DWI.


    Conclusion
 Top
 Abstract
 Introduction
 Methods and patients
 Results
 Discussion
 Conclusion
 References
 
We have shown that it is possible to safely perform DTI at high field strength in patients with acute stroke. The technique has the ability to identify white matter tract disruption as well as distortion, which may prove to be useful in the diagnostic and therapeutic management of acute stroke.


    Acknowledgments
 
The help of Tim Donovan is greatly appreciated.


    Footnotes
 
Technology Foresight, Medical Research Council, funded this study. Back

Received for publication October 18, 2000. Revision received February 22, 2001. Accepted for publication April 4, 2001.


    References
 Top
 Abstract
 Introduction
 Methods and patients
 Results
 Discussion
 Conclusion
 References
 

  1. Taylor DG, Bushell MC. The spatial mapping of translational diffusion coefficients by the magnetic resonance imaging technique. Phys Med Biol 1985;30:345–9.[Medline]
  2. Merbolt KD, Hanicke W, Frahm F. Self-diffusion NMR imaging using stimulated echoes. J Magn Reson 1985;64:479–86.
  3. Le Bihan D, Breton E, Lallemand D, Grenier P, Cabanis E, Laval-Jeantet M. MR imaging of intravoxel incoherent motions: application to diffusion and perfusion in neurological disorders. Radiology 1986;161:401–7.[Abstract/Free Full Text]
  4. Moseley ME, Cohen Y, Mintorovitch J, Chileuitt L, Shimizu H, Kucharczyk J, et al. Early detection of regional cerebral ischaemia in cats: comparison of diffusion- and T2-weighted MRI and spectroscopy. Magn Reson Med 1990;14:330–46.[Medline]
  5. Warach S, Chien D, Li W, Ronthal M, Edelman RR. Fast magnetic resonance diffusion-weighted imaging of acute human stroke. Neurology 1992;42:1717–23.[Abstract/Free Full Text]
  6. de Crespigny AJ, Marks MP, Enzmann DR, Moseley ME. Navigated diffusion imaging of normal and ischemic human brain. Magn Reson Med 1995;33:720–8.[Medline]
  7. Sorensen AG, Buonanno FS, Gonzalez RG, Schwamm LH, Lev MH, Huang-Hellinger FR, et al. Hyperacute stroke: evaluation with combined multisection diffusion-weighted and hemodynamically weighted echo-planar MR imaging. Radiology 1996;199:391–401.[Abstract/Free Full Text]
  8. Gillard JH, Barker PB, Van Zijl PCM, Bryan RN, Oppenheimer SM. Proton MR spectroscopic imaging in acute middle cerebral artery stroke. Am J Neuroradiol 1996;17:873–86.[Abstract]
  9. Cleveland GG, Chang DC, Hazelwood CF, Rorschach HE. Nuclear magnetic resonance measurement of skeletal muscle: anisotropy of the diffusion coefficient of the intracellular water. Biophys J 1976;16:1043–53.[Medline]
  10. Moseley ME, Cohen Y, Kucharczyk J, Mintorovitch J, Asgari HS, Wendland MR, et al. Diffusion-weighted MR imaging of anisotropic water diffusion in cat central nervous system. Radiology 1990;176:439–46.[Abstract/Free Full Text]
  11. Hajnal JV, Doran M, Hall AS, Collins AG, Oatridge A, Pennock JM, et al. MR imaging of anisotropically restricted diffusion of water in the nervous system. Technical, anatomic and pathological considerations. J Comput Assist Tomogr 1991;15:1–18.[Medline]
  12. Basser PJ, Mattiello J, Le Bihan D. MR diffusion tensor spectroscopy and imaging. Biophys J 1994;66:259–67.[Medline]
  13. Pierpaoli C, Jezzard PJ, Basser PJ, Barnett A. Diffusion tensor MR imaging of the human brain. Radiology 1996;201:637–48.[Abstract/Free Full Text]
  14. Reese TG, Weisskoff RM, Smith RN, Rosen BR, Dinsmore RE, Wedeen VJ. Imaging myocardial fiber architecture in vivo with magnetic resonance. Magn Reson Med 1995;34:786–91.[Medline]
  15. Stejskal EO, Tanner JE. Spin diffusion measurements: spin-echoes in the presence of a time-dependent field gradient. J Chem Phys 1965;42:288–92.
  16. Papadakis NG, Xing D, Huang LH, Hall LD, Carpenter TA. A comparative study of acquisition schemes for diffusion tensor imaging using MRI. J Magn Reson 1999;137:67–82.[Medline]
  17. Xing D, Papadakis NG, Huang LH, Lee VM, Carpenter TA, Hall LD. Optimized diffusion-weighting for measurement of apparent diffusion coefficient (ADC) in human brain. Magn Reson Imaging 1997;15:771–84.[Medline]
  18. Jezzard P, Barnett AS, Pierpaoli C. Characterization of and correction for eddy current artefacts in echo planar diffusion imaging. Magn Reson Med 1998;39:801–12.[Medline]
  19. Papadakis NG, Martin KM, Pickard JD, Hall LD, Carpenter TA, Huang CLH. Gradient preemphasis calibration in diffusion weighted echo-planar imaging. Magn Reson Med 2000;44:616–24.[Medline]
  20. Pierpaoli C, Basser PJ. Towards a quantitative assessment of diffusion anisotropy. Magn Reson Med 1996;36:893–906.[Medline]
  21. Tsuruda JS, Chew WM, Moseley ME, Norman D. Diffusion-weighted MR imaging of extraaxial tumors. Magn Reson Med 1991;19:316–20.[Medline]
  22. Larsson HBW, Thomsen C, Frederiksen J, Stubgaard M, Henriksen O. In vivo magnetic resonance diffusion measurement in the brain of patients with multiple sclerosis. Magn Reson Imaging 1992;10:7–12.[Medline]
  23. Alsop DC, Murai H, Detre JA, McIntosh TK, Smith DH. Detection of acute pathologic changes following experimental traumatic brain injury using diffusion-weighted magnetic resonance imaging. J Neurotrauma 1996;13:515–21.[Medline]
  24. Basser PJ. Characterizing isotropic and anisotropic diffusion using diffusion tensor MRI. NMR Biomed 1995;8:333–44.[Medline]
  25. Makris N, Worth AJ, Sorensen AG, Papadimitriou GM, Wu O, Reese TG, et al. Morphometry of in vivo human white matter association pathways with diffusion-weighted magnetic resonance imaging. Ann Neurol 1997;42:951–62.[Medline]
  26. Mukherjee P, Bahn MM, McKinstry RC, Shimony JS, Cull TS, Akbudak E, et al. Differences between gray matter and white matter water diffusion in stroke: diffusion-tensor MR imaging in 12 patients. Radiology 2000;215:211–20.[Abstract/Free Full Text]
  27. Werring DJ, Clark CA, Barker GJM, Miller DH, Parker GJM, Brammer MJ, et al. The structural and functional mechanisms of motor recovery: complementary use of diffusion tensor and functional magnetic resonance imaging in a traumatic injury of the internal capsule. J Neurol Neurosurg Psychiatry 1998;65:863–9.[Abstract/Free Full Text]
  28. Buchsbaum MS, Tang CY, Peled S, Gudbjartsson H, Hazlett EA, Downhill J, et al. MRI white matter diffusion anisotropy and PET metabolic rate in schizophrenia. Neuroreport 1998;9:425–30.[Medline]
  29. Igarashi H, Katayama Y, Tsuganezawa T, Yamamuro M, Terashi A, Owan C. Three-dimensional anisotropy contrast (3DAC) magnetic resonance imaging of the human brain: application to assess Wallerian degeneration. Intern Med 1998;37:662–8.[Medline]
  30. Schellinger PD, Jansen O, Fiebach JB, Heiland S, Steiner T, Schwab S, et al. Monitoring intravenous recombinant tissue plasminogen activator thrombolysis for acute ischemic stroke with diffusion and perfusion MRI. Stroke 2000;31:1318–28.[Abstract/Free Full Text]
  31. Sorenson AG, Wu O, Copen WA, Davis TL, Gonzalez RG, Koroshetz WJ, et al. Human acute cerebral ischemia: detection of changes in water diffusion anisotropy by using MR imaging. Radiology 1999;212:785–92.[Abstract/Free Full Text]
  32. Shimony JS, McKinstry RC, Akbudak E, Aronovitz JA, Snyder AZ, Lori NF, et al. Quantitative diffusion-tensor anisotropy brain MR imaging: normative human data and anatomic analysis. Radiology 1999;212:770–84.[Abstract/Free Full Text]



This article has been cited by other articles:


Home page
RadiologyHome page
N. Morakkabati-Spitz, H. H. Schild, C. K. Kuhl, G. Lutterbey, M. von Falkenhausen, F. Traber, and J. Gieseke
Female Pelvis: MR Imaging at 3.0 T with Sensitivity Encoding and Flip-Angle Sweep Technique
Radiology, November 1, 2006; 241(2): 538 - 545.
[Abstract] [Full Text] [PDF]


Home page
Br. J. Radiol.Home page
A Pena, H A L Green, T A Carpenter, S J Price, J D Pickard, and J H Gillard
Enhanced visualization and quantification of magnetic resonance diffusion tensor imaging using the p:q tensor decomposition
Br. J. Radiol., February 1, 2006; 79(938): 101 - 109.
[Abstract] [Full Text] [PDF]


Home page
RadiologyHome page
C. K. Kuhl, J. Gieseke, M. von Falkenhausen, J. Textor, S. Gernert, C. Sonntag, and H. H. Schild
Sensitivity Encoding for Diffusion-weighted MR Imaging at 3.0 T: Intraindividual Comparative Study
Radiology, February 1, 2005; 234(2): 517 - 526.
[Abstract] [Full Text] [PDF]


Home page
J. Neurol. Neurosurg. PsychiatryHome page
M Symms, H R Jager, K Schmierer, and T A Yousry
A review of structural magnetic resonance neuroimaging
J. Neurol. Neurosurg. Psychiatry, September 1, 2004; 75(9): 1235 - 1244.
[Abstract] [Full Text] [PDF]


Home page
StrokeHome page
M. P. Goldberg and B. R. Ransom
New Light on White Matter
Stroke, February 1, 2003; 34(2): 330 - 332.
[Full Text] [PDF]


This Article
Right arrow Abstract Freely available
Right arrow Figures Only
Right arrow Full Text (PDF)
Services
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Right arrow reprints & permissions
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Gillard, J H
Right arrow Articles by Pickard, J D
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Gillard, J H
Right arrow Articles by Pickard, J D


HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
BJR DMFR IMAGING  ALL BIR JOURNALS