Abstract
This paper presents a systematic evaluation of cortical folding, or complexity, in autism. It introduces two novel measures to analyze folding in a specific region of interest, which, unlike traditional measures, produce an intuitive easily-interpretable description of folding and inform the nature of folding change by incorporating local surface-patch orientation. This study reports new findings of increased cortical folding in autistics in the frontal, parietal, and temporal lobes, as compared to controls. These differences are stronger in children than adolescents. The paper validates part of the findings using the new measures based on comparisons with traditional measures. Unlike studies in the literature, this paper reports new findings, via a fully 3D folding analysis on all brain lobes, based on the consensus of virtually all 6 folding measures used (2 new, 4 traditional) via rigorous statistical permutation testing. In these ways, this paper not only strengthens some previous clinical findings, but also extends the state of the art in autism research.
Chapter PDF
Similar content being viewed by others
Keywords
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
References
Courchesne, E., Press, G., Yeung-Courchesne, R.: Parietal lobe abnormalities deteced with MR in patients with infantile autism. Am. J. Rad. 160, 387–393 (1993)
Carper, R.A., Moses, P., Tigue, Z.D., Courchesne, E.: Cerebral lobes in autism: Early hyperplasia and abnormal age effects. NeuroImage 16(4), 1038–1051 (2002)
Aylward, E., Minshew, N., Field, K., Sparks, B., Singh, N.: Effects of age on brain volume and head circumference in autism. Neurology 59, 175–183 (2002)
Hardan, A., Muddasani, S., Vemulapalli, M., Keshavan, M., Minshew, N.: An MRI study of increased cortical thickness in autism. Am. J. Psych. 163(7), 1290–1292 (2006)
Neeley, E.S., Bigler, E.D., Krasny, L., Ozonoff, S., McMahon, W., Lainhart, J.E.: Quantitative temporal lobe differences: Autism distinguished from controls using classification and regression tree analysis. Brain and Develop. 29(7), 389–399 (2007)
Mostofsky, S., Burgess, M., Gidley-Larson, J.: Increased motor cortex white matter volume predicts motor impairment in autism. Brain 130, 2117–2122 (2007)
Levitt, J., Blanton, R., Smalley, S., Thompson, P., Guthrie, D., McCracken, J., Sadoun, T., Heinichen, L., Toga, A.: Cortical sulcal maps in autism. Cerebral Cortex 13(7), 728–735 (2003)
Nordahl, C., Dierker, D., Mostafavi, I., Schumann, C., Rivera, S., Amaral, D., Van-Essen, D.: Cortical folding abnormalities in autism revealed by surface-based morphometry. Journal of Neuroscience 27(43), 11725–11735 (2007)
Armstrong, E., Schleicher, A., Omran, H., Curtis, M., Zilles, K.: The ontogeny of human gyrification. Cerebral Cortex 5, 56–63 (1995)
Piven, J., Berthier, M., Starkstein, S., Nehme, E., Pearlson, G., Folstein, S.: Magnetic resonance imaging evidence for a defect of cerebral cortical development in autism. Am. J. Psych. 147, 734–739 (1990)
Bailey, A., Luthert, Dean, Harding, Janota, Montgomery, Rutter, Lantos: A clinicopathological study of autism. Brain 121(5), 889–905 (1998)
Sztriha, L., Guerrini, R., Harding, B., Stewart, F., Chelloug, N., Johansen, J.: Clinical, MRI, and pathological features of polymicrogyria in chromosome 22q11 deletion syndrome. Am. J. Med. Genetics 127(A), 313–317 (2004)
Hardan, A., Jou, R., Keshavan, Varma, Minshew, N.: Increased frontal cortical folding in autism: a preliminary MRI study. Psyc. Res. 131(3), 263–268 (2004)
Van-Essen, D., Drury, H.: Structural and functional analyses of human cerebral cortex using a surface-based ATLAS. J. Neuroscience 17(18), 7079–7102 (1997)
Batchelor, P.G., Castellano-Smith, A.D., Hill, D.L.G., Hawkes, D.J., Cox, T.C.S., Dean, A.F.: Measures of folding applied to the development of the human fetal brain. IEEE Trans. Medical Imaging 21(8), 953–965 (2002)
Tosun, D., Duchesne, S., Rolland, Y., Toga, A., Verin, M., Barillot, C.: 3D analysis of cortical morphometry in differential diagnosis of Parkinson’s Plus Syndromes. In: Med. Imag. Comput. and Comp. Assist. Intervention, pp. 891–899 (2007)
Koenderink, J., van Doorn, A.: Surface shape and curvature scales. Image and Vision Computing 10(8), 557–565 (1992)
Zeng, X., Staib, L., Schultz, R., Duncan, J.: Segmentation and measurement of the cortex from 3D MR images using coupled surfaces propagation. IEEE Trans. Medical Imaging 18(10), 100–111 (1999)
Shattuck, D.W., Leahy, R.M.: Brainsuite: An automated cortical surface identification tool. Medical Image Analysis 6(2), 129–142 (2002)
Awate, S.P., Tasdizen, T., Foster, N.L., Whitaker, R.T.: Adaptive Markov modeling for mutual-information-based unsupervised MRI brain-tissue classification. Medical Image Analysis 10(5), 726–739 (2006)
Awate, S.P., Zhang, H., Gee, J.C.: A fuzzy, nonparametric segmentation framework for DTI and MRI analysis: With applications to DTI tract extraction. IEEE Trans. Med. Imag. 26(11), 1525–1536 (2007)
Osher, S., Paragios, N.: Geometric Level Set Methods in Imaging, Vision, and Graphics. Springer, Heidelberg (2003)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2008 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Awate, S.P., Win, L., Yushkevich, P., Schultz, R.T., Gee, J.C. (2008). 3D Cerebral Cortical Morphometry in Autism: Increased Folding in Children and Adolescents in Frontal, Parietal, and Temporal Lobes. In: Metaxas, D., Axel, L., Fichtinger, G., Székely, G. (eds) Medical Image Computing and Computer-Assisted Intervention – MICCAI 2008. MICCAI 2008. Lecture Notes in Computer Science, vol 5241. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-85988-8_67
Download citation
DOI: https://doi.org/10.1007/978-3-540-85988-8_67
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-85987-1
Online ISBN: 978-3-540-85988-8
eBook Packages: Computer ScienceComputer Science (R0)