Document Type : Full Research Paper


1 Ph.D Student,Biomedical Engineering Group, Electrical and Computer Engineering Department, K.N. Toosi University of Technology

2 Professor, Biomedical Engineering Group, Electrical and Computer Engineering Department, K.N. Toosi University of Technology

3 Professor, Biophysics Group, Medical Department, Picardie University

4 Assistant Professor,Communication Engineering Group, Electrical Engineering Department, Shiraz University of Technology

5 Associate Professor, Neurophysiology Group, Medical Department, Picardie University



Reliable gradation of neonatal brain development is important for clinical investigation of neurological disorders. A prerequisite for such quantification of development is knowledge about an appropriate temporal resolvability. For this purpose, we investigated the evolution of macroscopic morphological features of the neonatal brain to estimate, for the first time, the required temporal interval in the early weeks after birth. In a first step, we constructed two neonatal templates for the age ranges of 39-40 and 41- 42 weeks' gestational age using T1-weighted MR images. We compared the spatial variation of anatomical landmarks and the average and the maximal length of spatial deformation in 25 subjects normalized to the two templates along x, y and z directions. MANOVA confirmed the significant difference between spatial variations of the above macroscopic features in the two age ranges. Furthermore, quantitative analysis of feature scattering yielded the same result even in features for which the null hypothesis was not rejected by MANOVA. We conclude that minimal temporal interval of two weeks is required for acute macroscopic morphological studies of the developing brain in the early weeks after birth.


Main Subjects

[1]     Rutherford, M., MRI of the neonatal brain, W. B. Saunders publication company, 2002.
[2]     Huppi, P.S., Schuknecht, B., Boesch, C., E. Bossi, Felblinger, J., Fusch, C., Herschkowitz, N., Structural and neurobehavioral delay in postnatal brain development of preterm infants, Pediatr Res., 1996, 39, 895-901.
[3]     Huppi, P.S., Warfield, S., Kikinis, R., Barnes, P.D., Zientara, G.P., Jolesz, F.A., Tsuji, M.K., Volpe, J.J., Quantitative magnetic resonance imaging of brain development in premature and mature newborns, Ann Neurol. 1998, 43, 224-235.
[4]     Dubois, J., Hertz-Pannier, L., Cachia, A., Mangin, J.F., Le Bihan, D., Dehaene-Lambertz, G., Structural asymmetries in the infant language and sensori-motor networks, Cereb Cortex, February 2009, 19(2), 414-423.
[5]     Golland, P., Grimson, W.E.L., Shenton, M.E., Kikinis, R., Detection and analysis of statistical differences in anatomical shape, Medical Image Analysis, 2005, 9, 69-86.
[6]     Murgasova, M.K., Aljabar, P., Srinivasan, L., Counsell, S.J., Doria, V., Serag, A., Gousias, I.S., J.P., Boardman, Rutherford, M.A., Edwards, A.D., Hajnal, J.V., Rueckert, D., A dynamic 4D probabilistic atlas of the developing brain, NeuroImage, 2011, 54, 2750-2763.
[7]     Aljabar, P., Bhatia, K.K., Murgasova, M., Hajnal, J.V., Boardman, J.P., Srinivasan, L., Rutherford, M.A., Dyet, L.E., Edwards, A.D., Rueckert, D., Assessment of brain growth in early childhood using deformation-based morphometry, NeuroImage, 2008, 39, 348–358.
[8]     Durston, S., Pol, H.H., Casey, B., Giedd, J., Buitelaar, J., van Engeland, H., Anatomical MRI of the developing human brain: what have we learned?, J. Am. Acad. Child Adolesc. Psych., 2001, 40(9), 1012–1020.
[9]     Mazziotta, J.C., Toga, A.W., Evans, A.W., Fox, P., Lancaster, J., A probabilistic atlas of the human brain: theory and rationale for its development, The International Consortium for Brain Mapping (ICBM), NeuroImage, 1995, 2, 89–101.
[10] Yoon, U., Fonov V.S., Perusse, D., Evans, A.C., The effect of template choice on morphometric analysis of pediatric brain data, NeuroImage, 2009, 45, 769–777.
[11] A. C. Evans, D. L. Collins, S. R. Mills, E. D. Brown, R. L. Kelly, T. M. Peters, 3D statistical neuroanatomical models from 305 MRI volumes, IEEE Nuclear Science Symposium, Medical Imaging Conference, 1995, pp: 1813–1817.
[12] R. P. Woods, S. T. Grafton, J. D. G. Watson, N. L. Sicotte, J. C. Mazziotta, Automated image registration: II. Intersubject validation of linear and nonlinear models, J. Computer Assisted Tomography, 1998, Vol. 22, No. 1, pp: 153-65.
[13] Gaillard, W.D., Grandin, C.B., Xu, B., Developmental aspects of pediatric fMRI: considerations for image acquisition, analysis, and interpretation, Neuroimage, 2001, 13, 239-249.
[14] Muzik, O., Chugani, D.C., Juhasz, C., Shen C., Chugani, H.T., Statistical parametric mapping: assessment of application in children, Neuroimage, 2000, 12, 538-549.
[15] Burgund, E.D., Kang, H.C., Kelly, J.E., Buckner, R.L., Snyder, A.Z., Petersen, S.E., Schlaggar, B.L., The feasibility of a common stereotactic space for children and adults in fMRI studies of development, Neuroimage, 2002, 17, 184- 200.
[16] Wilke, M., Schmithorst, V.J., Holland, S.K., Assessment of spatial normalization of whole-brain magnetic resonance images in children, Human Brain Mapping, 2002, 17, 48-60.
[17] Wilke, M., Schmithorst, V.J., Holland, S.K., Normative pediatric brain data for spatial normalization and segmentation differs from standard adult data, Magn Reson Med, 2003, 50, 749-757.
[18] Altaye, M., Holland, S.K., Wilke, M., Gaser, Ch., Infant brain probability templates for MRI segmentation and normalization, NeuroImage, 2008, 43, 721–730.
[19] Dehaene-Lambertz, G., Dehaene, S., Hertz- Pannier, L., Functional neuroimaging of speech perception in infants, Science, 2002, 298, 2013-2015.
[20] Prastawa, M., Gilmore, J.H., Lin, W., Gerig, G., Automatic segmentation of MR images of the developing newborn brain, Medical Image Anal, 2005, 9, 457-466.
[21] Kazemi, K., Abrishami Moghaddam, H., Grebe, R., Gondry-Jouet, C., Wallois, F., A neonatal atlas template for spatial normalization of whole-brain Magnetic Resonance Images of newborns: preliminary results, Neuroimage, 2007, 37, 463-473.
[22] Kazemi, K., Ghadimi, S., Abrishami Moghaddam, H., Grebe, R., Gondry-Jouet, C., Wallois, F., Neonatal probabilistic models for brain, CSF and skull using T1-MRI data: Preliminary results, 30th Annual International Conference of the IEEE, Engineering in Medicine and Biology Society, 2008, 3892-3895, Vancouver, BC.
[23] Kazemi, K., Abrishami Moghaddam, H., Grebe, R., Gondry-Jouet, C., Wallois, F., Design and construction of a brain phantom to simulate neonatal MR images, Computerized Medical Imaging and Graphics, 2011, 35, 237– 250.
[24] Shi, F., Yap, P., Fan, Y., Gilmore, J.H., Lin, W., Shen, D., Construction of multi-region-multi-reference atlases for neonatal brain MRI segmentation, NeuroImage, 2010, 51, 684–693.
[25] Serag, A., Aljabar, P., Ball, G., Counsell, S.J., Boardman, J.P., Rutherford, M.A., Edwards, A.D., Hajnal, J.V., Rueckert, D., Construction of a Consistent High- Definition Spatio-Temporal Atlas of the Developing Brain using Adaptive Kernel Regression, NeuroImage,2011,doi:10.1016/j.neuroimage.2011.09.062.
[26] Pienaar, R., Fischl, B., Caviness, V., Makris, N., Grant, P.E., A Methodology for Analyzing Curvature in the Developing Brain from Preterm to Adult, Wiley Periodicals, Inc., 2008, 18, 42–68.
[27] Kuczmarski, R.J., Ogde, C.L., Guo, S.S., 2000 CDC growth charts for the United States: Methods and development, National Center for Health Statistics, Vital Health Statistics, 2002, 11(246).
[28] Ashburner, J., Hutton, Ch., Frackowiak, R., Johnsrude, I., Price, C., Friston, K., Identifying Global Anatomical Differences: Deformation-Based Morphometry, Human Brain Mapping, 1998, 6, 348–357.
[29] Ashburner, J., Friston, K.J., Nonlinear spatial normalization using basis functions, Human Brain Mapping, 1999, 7, 254–266.
[30] GAREL, C., Le Développement Du Cerveau Foetal: Atlas Irm Et Biométrie, Sauramps Medical Montpellier, 2000.
[31] Dubois, J., Hertz-Pannier, L., Cachia, A., Mangin, J.F., Le Bihan, D., Dehaene-Lambertz, G., February Structural asymmetries in the infant language and sensori-motor networks, Cereb Cortex, 2009, 19(2), 414-423.
[32] Leroy, F., Glasel, H., Dubois, J., Hertz-Pannier, L., Thirion, B., Mangin, J.F., Dehaene-Lambertz, G., January, Early Maturation of the Linguistic Dorsal Pathway in Human Infants, Journal of Neuroscience, 2011, 31(4), 1500-1506.