Cluster Analysis of Multiparametric MR Imaging including ADC Maps and Relaxometry for Spatially High-Resolved Differentiation of Healthy and Ischemic Human Brain Tissue

  • Johannes Bernarding
  • Jürgen Braun
  • Joachim Hohmann
  • Mathias Hoehn-Berlage
  • Christian Stapf
  • Klaus-Jürgen Wolf
  • Thomas Tolxdorff


In experimental stroke models and ischemic human brain tissue the apparent diffusion coefficient (ADC) decreases in the acute phase, may normalize after reperfusion or may increase in the chronic stage, suggesting that the ADC may be used to monitor the physiologic state of affected tissue. However, a spatially high-resolved determination of the ADC for human brain tissue, required for the transfer of experimental results, is a complex task: (a) ischemic regions in human brain are often small, heterogeneous or irregularly shaped; (b) examination conditions and the complex human brain anatomy lead to widely scattered ADC values. To improve characterization of healthy and pathologic tissues, navigated diffusion-weighted images and ADC maps were incorporated in a new approach into a multidimensional parameter set of relaxation times (T1, T2) and T1-/T2-weighted images. Volunteers and patients with different neurologic deficits were examined. A supervised histogram-based analysis enabled the segmentation of healthy and pathologie tissue classes and the determination of their mean values and standard deviations. Healthy brain tissue was segmented by incorporating T1 relaxation in the data set. Acute and chronic ischemic regions were best differentiated by combining T2- or diffusion-weighted images with ADC maps. The results support findings that within the first week the mean ADC of human ischemic regions is reduced before approaching or exceeding normal values.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    M. E. Moseley, Y. Cohen, J. Mintorovitch, L. Chileuitt, H. Shimizu, J. Kucharczyk, M. F. Wendland, P. R. Weinstein, Early Detection of Regional Cerebral Ischemia in Cats: Comparison of Diffusion-weighted and T2-weighted MRI and Spectroscopy. Magn. Reson. Med. 14, 330–346 (1990).CrossRefGoogle Scholar
  2. 2.
    K. Minematsu, L. Li, M. Fisher, C. H. Sotak, M. A. Davis, M. S. Fiandaca, Diffusion-Weighted Magnetic Resonance Imaging: Rapid and Quantitative Detection of Focal Brain Ischemia. Neurology 42, 235–240 (1992).Google Scholar
  3. 3.
    M. E. Moseley, K. Butts, M. A. Yenari, M. Marks, A. de Crespigny, Clinical Aspects of DWI. NMR Biomed. 8, 387–396 (1995).CrossRefGoogle Scholar
  4. 4.
    K. M. A. Welch, J. Windham, R. A. Knight, V. Nagesh, J. W. Hugg, M. Jacobs, D. Peck, P. Booker, M. O. Dereski, S. R. Levine, A Model to Predict the Histopathology of Human Stroke Using Diffusion and T2-weighted Magnetic Resonance Imaging. Stroke 26, 1983–1989 (1995).CrossRefGoogle Scholar
  5. 5.
    M. P. Marks, A. de Crespigny, D. Lentz, D. R. Enzmann, G. W. Albers, M. E. Moseley, Acute and Chronic Stroke: Navigated Spin-echo Diffusion-weighted MR Imaging. Radiology 199, 403–408 (1996).Google Scholar
  6. 6.
    S. Warach, M. Moseley, G. A. Sorensen, W. Koroshetz, Time Course of Diffusion Imaging Abnormalities in Human Stroke. Note to the Editor. Stroke 27, 1254–1255 (1996).Google Scholar
  7. 7.
    K. M. A. Welch, S. R. Levine, M. Chopp, R. A. Knight, L. D’Olhaberriague, M. D. Boska, V. Nagesh, J. P. Windham, D. Peck, Response to: Time Course of Diffusion Imaging Abnormalities in Human Stroke. Note to the Editor. Stroke 27, 1255–1256 (1996).Google Scholar
  8. 8.
    S. Warach, J. F. Dashe, R. R. Edelman, 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 (1996).CrossRefGoogle Scholar
  9. 9.
    S. Warach, J. Gaa, B. Siewert, P. Wielopolski, R. R. Edelman, Acute Human Stroke Studied by Whole Brain Echo Planar Diffusion-weighted Magnetic Resonance Imaging. Ann. Neurol. 37, 231–241 (1995).CrossRefGoogle Scholar
  10. 10.
    A. J. de Crespigny, M. P. Marks, D. R. Enzmann, M. E. Moseley, Navigated Diffusion Imaging of Normal and Ischemic Human Brain. Magn. Reson. Med. 33, 720–728 (1995).CrossRefGoogle Scholar
  11. 11.
    K. Butts, A. de Crespigny, J. M. Pauly, M. Moseley, Diffusion-Weighted Interleaved Echo-Planar Imaging with a Pair of Orthogonal Navigator Echoes. Magn. Resort. Med. 35, 763–770 (1996).CrossRefGoogle Scholar
  12. 12.
    T. E. Conturo, R. C. McKinstry, J. A. Aronovitz, J. Neil, Diffusion MRJ: Precision, Accuracy and Flow Effects. NMR Biomed. 8, 307–332 (1995).CrossRefGoogle Scholar
  13. 13.
    J. Röther, A. de Crespigny, H. D’Arcueil, K. Iwai, M. Moseley, Recovery of Apparent Diffusion Coefficient after Ischemia-induced Spreading Depression Relates to Cerebral Perfusion Gradient. Stroke 27, 980–987 (1996).CrossRefGoogle Scholar
  14. 14.
    A. Mancuso, H. Karibe, W. D. Rooney, G. J. Zarow, S. H. Graham, M. W. Weiner, P. R. Weinstein, Correlation of early Reduction in the Apparent Diffusion Coefficient of Water with Blood Flow Reduction During Middle Cerebral Artery Occlusion in Rats. Magn. Reson. Med. 34, 368–377 (1995).CrossRefGoogle Scholar
  15. 15.
    K. Kohno, M. Hoehn-Berlage, G. Mies, T. Back, K. A. Hossmann, Relationship between diffusion-weighted MR-Images, cerebral blood flow, and energy state in experimental brain infarction. Magn. Reson. Imaging 13, 73–80 (1995).CrossRefGoogle Scholar
  16. 16.
    M. Hoehn-Berlage, M. Eis, T. Back, K. Kohno, K. Yamashita, Changes of Relaxation Times (T1, T2) and Apparent Diffusion Coefficient After Permanent Middle Cerebral Artery Occlusion in the Rat: Temporal Evolution, Regional Extent, and Comparison with Histology. Magn. Reson. Med. 34, 824–834 (1995).CrossRefGoogle Scholar
  17. 17.
    M. Hoehn-Berlage, Diffusion-weighted NMR imaging: application to experimental focal cerebral ischemia. NMR Biomed. 8, 345–358 (1995).CrossRefGoogle Scholar
  18. 18.
    K. A. Hossmann, M. Hoehn-Berlage, Diffusion and Perfusion MR Imaging of Cerebral Ischemia. Cerebrovascular and Brain Metabolism Reviews 7, 187–217 (1995).Google Scholar
  19. 19.
    K. Minematsu, M. Fisher, L. Limin, C. H. Sotak, Diffusion and Perfusion Magnetic Resonance Imaging Studies to Evaluate a Noncompetitive N-Methyl-D-Aspartate Antagonist and Reperfusion in Experimental Stroke in Rats. Stroke 24, 2074–2081 (1993).CrossRefGoogle Scholar
  20. 20.
    E. H. Lo, K. Matsumoto, A. R. Pierce, L. Garrido, D. Luttinger, Pharmacologic reversal of acute changes in diffusion-weighted magnetic resonance imaging in focal cerebral ischemia. J. Cereb. Blood Flow Metab. 14, 597–603 (1994).CrossRefGoogle Scholar
  21. 21.
    M. Hoehn-Berlage, K. A. Hossmann, E. Busch, M. Eis, B. Schmitz, M. L. Gyngell, Inhibition of nonselective cation channels reduces focal ischemic injury of rat brain. J. Cereb. Blood Flow Metab. 17, 534–542 (1997).CrossRefGoogle Scholar
  22. 22.
    E. Busch, K. Krüger, P. R. Allegrini, C. Kerskens, M. L. Gyngell, M. Hoehn-Berlage, K. A. Hossmann, Reperfusion after Thrombembolic Therapy of embolic Stroke in Rat: Magnetic Resonance and Biochemical Imaging. J. Cereb. Blood Flow Metab. 18, 407–418 (1998).CrossRefGoogle Scholar
  23. 23.
    K. Gersonde, L. Felsberg, T. Tolxdorff, D. Ratzel, B. Ströbel, Analysis of Multiple T2 Proton Relaxation Processes in Human Head and Imaging on the Basis of Selective and Assigned T2 Values. Magn. Reson. Med. 1, 463–477 (1984).CrossRefGoogle Scholar
  24. 24.
    M. Eis, H. Handels, K. Bohndorf, M. Drobnitzky, T. Tolxdorff, A. Stargardt, A New Method for Combined T1-Measurement and Multi-Exponential T2-Analysis in Tissue Characterizing MRI, in “Proc., SMRM, 8th Annual Meeting, 1989,” p. 770.Google Scholar
  25. 25.
    T. Tolxdorff, H. Handels, K. Bohndorf, Advantages of Multi-Exponential T2-Analysis, in “Tissue Characterizing in MR-Imaging” (H. P. Higer, G. Bielke, Eds.), pp 75–80, Springer, Berlin, 1990.Google Scholar
  26. 26.
    L. M. Fletcher, J. B. Barsotti, J. P. Hornak, A Multispectral Analysis of Brain Tissues. Magn. Reson. Med. 29, 623–630 (1993).CrossRefGoogle Scholar
  27. 27.
    B. Alfano, A. Brunetti, E. M. Covelli, M. Quarantelli, M. R. Panico, A. Ciarmiello, M. Salvatore, Unsupervised, Automated Segmentation of the Normal Brain Using a Multispectral Relaxometric Magnetic Resonance Approach. Magn. Reson. Med. 37, 84–93 (1997).CrossRefGoogle Scholar
  28. 28.
    M. Eis, H. Handels, M. Hoehn-Berlage, L. J. Wilmes, R.-I. Ernestus, O. Kloiber, T. Tolxdorff, K.-A. Hossmann, Fully Automatic Tissue Characterization in Rat Brain at 4.7 Tesla, in “Proc., SMRM, 10th Annual Scientific Meeting, 1991,” p. 1214.Google Scholar
  29. 29.
    M. Hoehn-Berlage, T. Tolxdorff, K. Bockhorst, Y. Okada, R.-L Ernestus, In Vivo NMR T2 Relaxation of Experimental Brain Tumors in the Cat: A Multiparameter Tissue Characterization. Magn. Reson. Imaing. 10, 935–947 (1992).CrossRefGoogle Scholar
  30. 30.
    A. W. Anderson, J. C. Gore, Analysis and Correction of Motion Artifacts in Diffusion Weighted Imaging. Magn. Reson. Med. 32, 379–387 (1994).CrossRefGoogle Scholar
  31. 31.
    H. Handels, T. Tolxdorff, A New Segmentation Algorithm for Knowledge Acquisition in Tissue-Characterizing Magnetic Resonance Imaging. J. Digital Imaging 3, 89–94 (1990).CrossRefGoogle Scholar
  32. 32.
    E. O. Stejskal, J. E. Tanner, Spin Diffusion Measurements: Spin Echoes in the Presence of a Time-dependent Field Gradient. J. Chem. Physics 42, 288–292 (1965).CrossRefGoogle Scholar
  33. 33.
    D. LeBihan, E. Breton, D. Lallemand, P. Grenier, E. Cabanis, M. Laval-Jeantet, MR Imaging of Intravoxel Incoherent Motions: Application to Diffusion and Perfusion in Neurologic Disorders. Radiology 161, 401–407 (1986).Google Scholar
  34. 34.
    K. Gersonde, T. Tolxdorff, L. Felsberg, Identification and Characterization of Tissues by T2-Selective Whole Body Proton NMR-Imaging. Magn. Reson. Med. 2, 390–401 (1985).CrossRefGoogle Scholar
  35. 35.
    H. Handels, T. Tolxdorff, K. Bohndorf, Preprocessing of Magnetization Decays to Improve Multiexponential T2-Analysis, in “Tissue Characterization in MR Imaging” (H. P. Higer, G. Bielke Eds.), 69–74, Springer, Berlin, 1990.Google Scholar
  36. 36.
    M. Eis, M. Hoehn-Berlage, A Time-efficient Method for Combined T1-and T2-Measurement in Magnetic Resonance Imaging: Evaluation for Multiparameter Tissue Characterization. MAGMA 2, 79–89 (1994).CrossRefGoogle Scholar
  37. 37.
    T. E. Conturo, A. H. Beth, R. F. Ahrensdorf, R. Price, Simplified Mathematical Description of Longitudinal Recovery in Multiple-Echo Sequences, Magn. Reson. Med. 4, 282–288 (1990).CrossRefGoogle Scholar
  38. 38.
    J. Bernarding, J. Braun, J. Hohmann, R. Kurth, K.-J. Wolf, T. Tolxdorff, Time course of the diffusion coefficient and relaxation times in human cerebral infarcts. MAGMA, 5 (Suppl.), 69 (1997).Google Scholar
  39. 39.
    R. J. Ordidge, J. A. Helpern, Z. X. Qing, R. A. Knight, V. Nagesh, Correction of Motional Artifacts in Diffusion-Weighted MR Images Using Navigator Echoes. Magn. Reson. Imaging 12, 455–460 (1994).CrossRefGoogle Scholar
  40. 40.
    D. Chien, R. B. Buxton, K. K. Kwong, T. J. Brady, B. R. Rosen, MR Diffusion Imaging of the Human Brain. J. Comput. Assist. Tomogr. 14, 514–520 (1990).CrossRefGoogle Scholar
  41. 41.
    D. LeBihan, J. Delannoy, R. Levin, J. Pekar, O. Le Dour, Temperature Dependence of Water Molecular Diffusion in Brain Tissue, in “Proc. SMRM, 8th Annual Meeting, Amsterdam, 1989,” p. 141.Google Scholar
  42. 42.
    H. Nabatame, N. Fujimoto, K. Nakamura, Y. Imura, Y. Dodo, H. Fukuyama, J. Kimura, High Intensity Areas on Noncontrast T1-weighted MR Images in Cerebral Infarction. J. Comput. Assist. Tomogr. 14, 521–526 (1990).CrossRefGoogle Scholar
  43. 43.
    W. G. Bradley, Hemorrhage and Brain Iron, in “Magnetic Resonance Imaging”, (D. D. Stark, W. G. Bradley, Eds.), pp 721–768, Mosby Year Book Inc., St. Louis, 1992.Google Scholar
  44. 44.
    A. van der Toorn, E. Sykova, R. M. Dijkhuizen, I. Vorisek, L. Vargova, E. Skobisova, M. van Lookeren Champagne, T. Reese, K. Nicolay, Dynamic changes in Water ADC, Energy Metabolism, Extracellular Space Volume, and Tortuosity in Neonatal Rat Brain during Global Ischemia. Magn. Reson. Med. 36, 52–60 (1996).CrossRefGoogle Scholar
  45. 45.
    J. Mintorovitch, M. E. Moseley, L. Chileuitt, H. Shimizu, Y. Cohen, P. R. Weinstein, Comparison of Diffusion-and T2-Weighted MRI for the Early Detection of Cerebral Ischemia and Reperfusion in Rats. Magn. Reson. Med. 18, 39–50 (1991).CrossRefGoogle Scholar
  46. 46.
    K.-A. Hossmann, M. Fischer, K. Bockhorst, M. Hoehn-Berlage, NMR imaging of the apparent diffusion coefficient (ADC) for the evaluation of metabolic suppression and recovery after prolonged cerebral ischemia. J. Cereb. Blood Flow Metab 14, 723–731 (1994).CrossRefGoogle Scholar
  47. 47.
    A. L. Busza, K. L. Allen, M. D. King, N. van Bruggen, S. R. Williams, D. G. Gadian, Diffusion-weighted imaging studies of cerebral ischemia in gerbils: potential relevance to energy failure. Stroke 23, 1602–1612 (1992).CrossRefGoogle Scholar
  48. 48.
    S. A. Wharton, Generalized Histogram Clustering Scheme for Multidimensional Image Data. Pattern Recognition 16, 193–199 (1983).CrossRefGoogle Scholar
  49. 49.
    D. LeBihan, R. Turner, P. Douek, N. Patronas, Diffusion MR Imaging: Clinical Applications, Am. J. Radiol 159, 591–599 (1992).Google Scholar
  50. 50.
    J. V. Hajnal, M. Doran, A. S. Hall, A. G. Collins, A. Oatridge, J. M. Pennock, I. R. Young, G. M. Bydder, MR Imaging of Anisotopically Restricted Diffusion of Water in the Nervous System: Technical, Anatomic, and Pathologic Considerations. J. Comput. Assist. Tomogr. 15, 1–18 (1991).CrossRefGoogle Scholar
  51. 51.
    D. Chien, K. Kwong, D. R. Gress, F. S. Buonanno, R. B. Buxton, B. R. Rosen, MR Diffusion Imaging of Cerebral Infarction in Humans. Am. J. Neuroradiology 13, 1097–1102 (1992).Google Scholar
  52. 52.
    C. Pierpaoli, P. Jezzard, P. J. Basser, A. Barnett, Quantitative diffusion tensor imaging of the human brain, in “Proc., ESMRMB, 13th Annual Meeting, 1996,” p. 70.Google Scholar
  53. 53.
    P. A. Bottomley, T. H. Foster, E. A. Raymond, L. M. Pfeifer, A Review of Normal Tissue Hydrogen NMR Relaxation Times and Relaxation Mechanisms from 1–100 MHz: Dependence on Tissue Types, NMR Frequency, Temperature, Species, Excision, and Age. Medical Physics, 11, 425 (1984).CrossRefGoogle Scholar
  54. 54.
    F. W. Wehrli, Principles of Magnetic Resonance, in “Magnetic Resonance Imaging,” (D. D. Stark, W. G. Bradley, Eds.), pp. 3–20, 2nd Edition, Mosby Year Book, St. Louis, 1992.Google Scholar
  55. 55.
    T. Back, M. Hoehn-Berlage, K. Kohno, K.-A. Hossmann, Diffusion Nuclear Magnetic Resonance Imaging in Experimental Stroke. Stroke 25, 494–500 (1994).CrossRefGoogle Scholar

Copyright information

© Friedr. Vieweg & Sohn Verlagsgesellschaft mbH, Braunschweig/Wiesbaden 1999

Authors and Affiliations

  • Johannes Bernarding
    • 1
  • Jürgen Braun
    • 1
  • Joachim Hohmann
    • 1
  • Mathias Hoehn-Berlage
    • 4
  • Christian Stapf
    • 3
  • Klaus-Jürgen Wolf
    • 2
  • Thomas Tolxdorff
    • 1
  1. 1.Departments of Medical Informatics, University Hospital Benjamin FranklinFree University of BerlinGermany
  2. 2.Radiology and Nuclear Medicine, University Hospital Benjamin FranklinFree University of BerlinGermany
  3. 3.Neurology (Stroke Unit), University Hospital Benjamin FranklinFree University of BerlinGermany
  4. 4.Max Planck Institute for Neurological ResearchCologneGermany

Personalised recommendations