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Using three-dimensional fractal dimension to analyze the complexity of fetal cortical surface from magnetic resonance images

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Abstract

This study aims to investigate the complexity of the developing fetal cortical surface based on the notion of fractal dimension (FD). Forty-four fetal MR images were selected at 22–36 weeks of gestational age (GA) and distributed between two groups: 32 normal fetal brains (excluding twins) and 12 abnormal fetal brains, including twins, mild ventricular dilatation, Cornelia de Lange syndrome (small brain), and cortical dysplasia (developmental delay). We adopted the commonly used box-counting (BC) method to estimate the FD of the developing fetal cortical surface. Results from normal fetal brains show that the increase of cortical complexity is highly correlated with fetal developing weeks of GA. In addition, after 28 weeks of GA, the value of FD increases more rapidly because of the faster development of convolved folds. In comparison with results from the normal fetal group, the abnormal fetal brains were examined and the results show that: (1) mild ventricular dilatation has no significant developing difference compared with normal fetal brains; (2) twins had lower FD than that of normal fetal brains, which may be a delay of 2–3 weeks; (3) the case of cortical dysplasia also had low FD, indicating that developing delay may mean less cortical complexity. The results of the normal group are in good agreement with fetal brain development and demonstrate the effectiveness of FD as a promising means for the quantification of complexity of the fetal cortical surface.

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References

  1. Prayer, D., Kasprian, G., Krampl, E., Ulm, B., Witzani, L., Prayer, L., Brugger, P.C.: MRI of normal fetal brain development. Eur. J. Radiol. 57, 199–216 (2006)

    Article  Google Scholar 

  2. Garel, C.: MRI of the Fetal Brain. Springer, New York (2004)

    Google Scholar 

  3. Havlin, S., Buldyrev, S.V., Goldberger, A.L., Mantegna, R.N., Ossandnik, S.M., Peng, C.K., Simons, M., Stanley, H.E.: Fractals in biology and medicine. Chaos Solitons Fractals 6, 171–201 (1995)

    Article  MATH  MathSciNet  Google Scholar 

  4. Mandelbrot, B.B.: The Fractal Geometry of Nature. Freeman, New York (1982)

    MATH  Google Scholar 

  5. Ghafari, S.H., Golnaraghi, F., Ismail, F.: Effect of localized faults on chaotic vibration of rolling element bearings. Nonlinear Dyn. 53(4), 287–301 (2008)

    Article  MATH  Google Scholar 

  6. Lin, G., Feeny, B.F., Das, T.: Fractional derivative reconstruction of forced oscillators. Nonlinear Dyn. 55(3), 239–250 (2009)

    Article  MATH  Google Scholar 

  7. Sharkovsky, A.N.: Ideal turbulence. Nonlinear Dyn. 44(1–4), 15–27 (2006)

    Article  MATH  MathSciNet  Google Scholar 

  8. Hofman, M.A.: The fractal geometry of convoluted brains. J. Hirnforsch. 32(1), 103–111 (1991)

    Google Scholar 

  9. Majumdar, S., Prasad, R.R.: The fractal dimension of cerebral surfaces using magnetic resonance images. Comput. Phys. 2(6), 69–73 (1988)

    Google Scholar 

  10. Bullmore, E., Brammer, M., Harvey, I., Persaud, R., Murray, R., Ron, M.: Fractal analysis of the boundary between white matter and cerebral cortex in magnetic resonance images: A controlled study of schizophrenic and manic-depressive patients. Psychol. Med. 24, 771–781 (1994)

    Article  Google Scholar 

  11. Free, S.L., Sisodiya, S.M., Cook, M.J., Fish, D.R., Shorvon, S.D.: Three-dimensional fractal analysis of the white matter surface from magnetic resonance images of the human brain. Cereb. Cortex 6, 830–836 (1996)

    Article  Google Scholar 

  12. Lee, J.M., Yoon, U., Kim, J.J., Kim, I.Y., Lee, D.S., Kwon, J.S., Kim, S.I.: Analysis of the hemispheric asymmetry using fractal dimension of a skeletonized cerebral surface. IEEE Trans. Biomed. Eng. 51(8), 1494–1498 (2004)

    Article  Google Scholar 

  13. Thompson, P.M., Schwartz, C., Lin, R.T., Khan, A.A., Toga, A.W.: Three-dimensional statistical analysis of sulcal variability in the human brain. J. Neurosci. 16, 4261–4274 (1996)

    Google Scholar 

  14. Kiselev, V.G., Hahn, K.R., Auer, D.P.: Is the brain cortex a fractal? Neuroimage 20(3), 1765–1774 (2003)

    Article  Google Scholar 

  15. Rybaczuk, M., Kedzia, A., Blaszczyk, E.: Fractal description of cerebellum surface during fetal period. Folia Morphol. 55(4), 434–436 (1996)

    Google Scholar 

  16. Blanton, R.E., Levitt, J.G., Thompson, P.M., Narr, K.L., Capetillo-Cunliffe, L., Nobel, A., Singerman, J.D., McCracken, J.T., Toga, A.W.: Mapping cortical asymmetry and complexity patterns in normal children. Psychiatry Res. 107, 29–43 (2001)

    Article  Google Scholar 

  17. Zhang, L., Liu, J.Z., Dean, D., Sahgal, V., Yue, G.H.: A three-dimensional fractal analysis method for quantifying white matter structure in human brain. J. Neurosci. Methods 150(2), 242–253 (2006)

    Article  Google Scholar 

  18. Gonzalez, R.C., Woods, R.E.: Digital Image Processing. Addison–Wesley, New York (1993)

    Google Scholar 

  19. Kass, M., Witkin, Terzopoulos, D.: Snakes: Active contour models. Int. J. Comput. Vis. 1(4), 321–331 (1987)

    Article  Google Scholar 

  20. Peitgen, H.O., Jurgens, H., Saupe, D.: Chaos and Fractals New Frontiers of Science. Springer, New York (1992)

    MATH  Google Scholar 

  21. Vicsek, T.: Fractal Growth Phenomena. World Scientific, Singapore (1990)

    Google Scholar 

  22. Liu, S.: Fractals and their Applications in Condensed Matter Physics. Academic Press, New York (1986)

    Google Scholar 

  23. Buchnicek, M., Nezadal, M., Zmeskal, O.: Numeric calculation of fractal dimension. In: Proceedings of the Third Conference on Prediction, Synergetic and More (2000)

  24. Nezadal, M., Zmeskal, O., Buchnicek, M.: The box-counting: Critical study. In: Proceedings of the Fourth Conference on Prediction, Synergetic and More (2001)

  25. Chi, J.G., Dooling, E.C., Gilles, F.H.: Gyral development of the human brain. Ann. Neurol. 1, 86–93 (1977)

    Article  Google Scholar 

  26. Herbert, F.J., Fernandez, E.: Neurons and fractals: how reliable and useful are calculations of fractal dimensions? J. Neurosci. Methods 81(1–2), 9–18 (1998)

    Google Scholar 

  27. Smith, T.G., Behar, T.N., Lange, G.D., Sheriff, W.H., Neale, E.A.: A fractal analysis of cell images. J. Neurosci. Methods 27, 173–180 (1989)

    Article  Google Scholar 

  28. Garel, C., Chantrel, E., Brisse, H., Elmaleh, M., Luton, D., Oury, J.F., Sebag, G., Hassan, M.: Fetal cerebral cortex: normal gestational landmarks identified using prenatal MR imaging. AJNR 22(1), 184–189 (2001)

    Google Scholar 

  29. Kedzia, A., Rybaczuk, M., Andrzejak, R.: Fractal dimensions of human brain cortex vessels during the fetal period. Med. Sci. Monit. 8(3), MT46-51 (2002)

    Google Scholar 

  30. Guo, W.Y., Wong, T.T.: Screening of fetal CNS anomalies by MR imaging. Child’s Nerv. Syst. 19, 410–414 (2003)

    Article  Google Scholar 

  31. Cook, M.J., Free, S.L., Manford, M.R.A., Fish, D.R., Shorvon, S.D., Stevens, J.M.: Fractal description of cerebral cortical patterns in frontal lobe epilepsy. Eur. Neurol. 35, 327–335 (1995)

    Article  Google Scholar 

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Correspondence to Tzong-Rong Chen.

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Wu, YT., Shyu, KK., Chen, TR. et al. Using three-dimensional fractal dimension to analyze the complexity of fetal cortical surface from magnetic resonance images. Nonlinear Dyn 58, 745–752 (2009). https://doi.org/10.1007/s11071-009-9515-y

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  • DOI: https://doi.org/10.1007/s11071-009-9515-y

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