Quantification and discrimination of abnormal sulcal patterns in polymicrogyria.

Polymicrogyria (PMG) is a malformation of cortical development characterized by an irregular gyral pattern and its diagnosis and severity have been qualitatively judged by visual inspection of imaging features. We aimed to provide a quantitative description of abnormal sulcal patterns for individual PMG brains using our sulcal graph-based analysis and examined the association with language impairment. The sulcal graphs were constructed from magnetic resonance images in 26 typical developing and 18 PMG subjects and the similarity between sulcal graphs was computed by using their geometric and topological features. The similarities between typical and PMG groups were significantly lower than the similarities measured within the typical group. Furthermore, more lobar regions were determined to be abnormal in most patients when compared with the visual diagnosis of PMG involvement, suggesting that PMG may have more global effects on cortical folding than previously expected. Among the PMG, the group with intact language development showed sulcal patterns more closely matched with the typical than the impaired group in the left parietal lobe. Our approach shows the potential to provide a quantitative means for detecting the severity and extent of involvement of cortical malformation and a greater understanding of genotype-phenotype and clinical-imaging features correlations.

[1]  C. Walsh,et al.  A familial syndrome of unilateral polymicrogyria affecting the right hemisphere , 2006, Neurology.

[2]  C. Walsh,et al.  An autosomal recessive form of bilateral frontoparietal polymicrogyria maps to chromosome 16q12.2-21. , 2002, American journal of human genetics.

[3]  P. Ellen Grant,et al.  The relationship between the presence of sulcal pits and intelligence in human brains , 2011, NeuroImage.

[4]  Sang Won Seo,et al.  Sulcal morphology changes and their relationship with cortical thickness and gyral white matter volume in mild cognitive impairment and Alzheimer's disease , 2008, NeuroImage.

[5]  Pasko Rakic,et al.  Neuroscience. Genetic control of cortical convolutions. , 2004, Science.

[6]  Anders M. Dale,et al.  Cortical Surface-Based Analysis I. Segmentation and Surface Reconstruction , 1999, NeuroImage.

[7]  P Ellen Grant,et al.  Bilateral frontoparietal polymicrogyria: Clinical and radiological features in 10 families with linkage to chromosome 16 , 2003, Annals of neurology.

[8]  F. Cendes,et al.  Developmental language disorder associated with polymicrogyria , 2002, Neurology.

[9]  D. V. von Cramon,et al.  Deep sulcal landmarks provide an organizing framework for human cortical folding. , 2008, Cerebral cortex.

[10]  P. A. Narayana,et al.  Diffusion tensor imaging in polymicrogyria: a report of three cases , 2006, Neuroradiology.

[11]  K. Haginoya,et al.  Morphofunctional organization in three patients with unilateral polymicrogyria: Combined use of diffusion tensor imaging and functional magnetic resonance imaging , 2006, Brain and Development.

[12]  Anders M. Dale,et al.  Automated manifold surgery: constructing geometrically accurate and topologically correct models of the human cerebral cortex , 2001, IEEE Transactions on Medical Imaging.

[13]  Shen-Ju Chou,et al.  Area Patterning of the Mammalian Cortex , 2007, Neuron.

[14]  Moo K. Chung,et al.  Cortical thickness analysis in autism with heat kernel smoothing , 2005, NeuroImage.

[15]  廣瀬雄一,et al.  Neuroscience , 2019, Workplace Attachments.

[16]  A. Dale,et al.  Cortical Surface-Based Analysis II: Inflation, Flattening, and a Surface-Based Coordinate System , 1999, NeuroImage.

[17]  Sung Yong Shin,et al.  Spectral-based automatic labeling and refining of human cortical sulcal curves using expert-provided examples , 2010, NeuroImage.

[18]  Arnaud Cachia,et al.  In-vivo measurement of cortical morphology: means and meanings. , 2010, Current opinion in neurology.

[19]  D. Ledbetter,et al.  Differences in the gyral pattern distinguish chromosome 17–linked and X-linked lissencephaly , 1999, Neurology.

[20]  Alan C. Evans,et al.  A nonparametric method for automatic correction of intensity nonuniformity in MRI data , 1998, IEEE Transactions on Medical Imaging.

[21]  Paul M. Thompson,et al.  Increased local gyrification mapped in Williams syndrome , 2006, NeuroImage.

[22]  I. Scheffer,et al.  Clinical and imaging heterogeneity of polymicrogyria: a study of 328 patients. , 2010, Brain : a journal of neurology.

[23]  N. Makris,et al.  A methodology for analyzing curvature in the developing brain from preterm to adult , 2008, Int. J. Imaging Syst. Technol..

[24]  A. Barkovich,et al.  Nonlissencephalic cortical dysplasias: correlation of imaging findings with clinical deficits. , 1992, AJNR. American journal of neuroradiology.

[25]  William B. Dobyns,et al.  G Protein-Coupled Receptor-Dependent Development of Human Frontal Cortex , 2004, Science.

[26]  Y. Samson,et al.  "Sulcal root" generic model: a hypothesis to overcome the variability of the human cortex folding patterns. , 2005, Neurologia medico-chirurgica.

[27]  Anders M. Dale,et al.  An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest , 2006, NeuroImage.

[28]  R. Kuzniecky,et al.  A developmental and genetic classification for malformations of cortical development , 2005, Neurology.

[29]  M. Catani,et al.  A diffusion tensor imaging tractography atlas for virtual in vivo dissections , 2008, Cortex.

[30]  Paul M. Thompson,et al.  A curvature-based approach to estimate local gyrification on the cortical surface , 2006, NeuroImage.

[31]  Pasko Rakic,et al.  Genetic Control of Cortical Convolutions , 2004, Science.

[32]  P. Rakic Evolution of the neocortex: Perspective from developmental biology , 2010 .

[33]  Jerry L Prince,et al.  Cross-sectional and longitudinal analyses of anatomical sulcal changes associated with aging. , 2005, Cerebral cortex.

[34]  Bruce Fischl,et al.  Geometrically Accurate Topology-Correction of Cortical Surfaces Using Nonseparating Loops , 2007, IEEE Transactions on Medical Imaging.

[35]  Alan C. Evans,et al.  Brain size and cortical structure in the adult human brain. , 2008, Cerebral cortex.

[36]  P. Ellen Grant,et al.  Quantitative comparison and analysis of sulcal patterns using sulcal graph matching: A twin study , 2011, NeuroImage.

[37]  D. Ledbetter,et al.  LIS1 and XLIS (DCX) mutations cause most classical lissencephaly, but different patterns of malformation. , 1998, Human molecular genetics.

[38]  H. Chugani,et al.  Arcuate fasciculus and speech in congenital bilateral perisylvian syndrome. , 2011, Pediatric neurology.

[39]  Nikos Makris,et al.  Automatically parcellating the human cerebral cortex. , 2004, Cerebral cortex.

[40]  O. Sporns,et al.  White matter maturation reshapes structural connectivity in the late developing human brain , 2010, Proceedings of the National Academy of Sciences.

[41]  Alan C. Evans,et al.  Spatial distribution of deep sulcal landmarks and hemispherical asymmetry on the cortical surface. , 2010, Cerebral cortex.

[42]  R. Kuzniecky,et al.  Bilateral parasagittal parietooccipital polymicrogyria and epilepsy , 1997, Annals of neurology.

[43]  Shen-Ju Chou,et al.  Cortical area size dictates performance at modality-specific behaviors , 2007, Proceedings of the National Academy of Sciences.

[44]  P. Rakic Specification of cerebral cortical areas. , 1988, Science.

[45]  A. Barkovich MRI analysis of sulcation morphology in polymicrogyria , 2010, Epilepsia.

[46]  E. Andermann,et al.  Genetics of the polymicrogyria syndromes , 2005, Journal of Medical Genetics.

[47]  R. Kuzniecky,et al.  Congenital bilateral perisylvian syndrome: study of 31 patients , 1993, The Lancet.

[48]  J. Rubenstein,et al.  Frontal cortex subdivision patterning is coordinately regulated by Fgf8, Fgf17, and Emx2 , 2008, The Journal of comparative neurology.

[49]  A J Barkovich,et al.  Bilateral generalized polymicrogyria (BGP) , 2004, Neurology.

[50]  A. M. Dale,et al.  A hybrid approach to the skull stripping problem in MRI , 2004, NeuroImage.

[51]  A J Barkovich,et al.  Bilateral frontal polymicrogyria , 2000, Neurology.

[52]  S. Shergill,et al.  Cortical Thickness Reduction of Normal Appearing Cortex in Patients with Polymicrogyria , 2010, Journal of neuroimaging : official journal of the American Society of Neuroimaging.

[53]  Martial Hebert,et al.  A spectral technique for correspondence problems using pairwise constraints , 2005, Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1.