Female children with autism spectrum disorder: An insight from mass-univariate and pattern classification analyses. Calderoni S, Retico A, Biagi L, Tancredi R, Muratori F, Tosetti M. IRCCS Stella Maris Foundation, Viale del Tirreno 331, 56018 Calambrone, Pisa, Italy; Division of Child Neurology and Psychiatry, University of Pisa, Pisa, Italy. Several studies on structural MRI in children with autism spectrum disorders (ASD) have mainly focused on samples prevailingly consisting of males. Sex differences in brain structure are observable since infancy and therefore caution is required in transferring to females the results obtained for males. The neuroanatomical phenotype of female children with ASD (ASDf) represents indeed a neglected area of research. In this study, we investigated for the first time the anatomic brain structures of a sample entirely composed of ASDf (n=38; 2-7years of age; mean=53months; SD=18) with respect to 38 female age and non verbal IQ matched controls, using both mass-univariate and pattern classification approaches. The whole brain volumes of each group were compared using voxel-based morphometry (VBM) with diffeomorphic anatomical registration through exponentiated lie algebra (DARTEL) procedure, allowing us to build a study-specific template. Significantly more gray matter (GM) was found in the left superior frontal gyrus (SFG) in ASDf subjects compared to controls. The GM segments obtained in the VBM-DARTEL preprocessing are also classified with a support vector machine (SVM), using the leave-pair-out cross-validation protocol. Then, the recursive feature elimination (SVM-RFE) approach allows for the identification of the most discriminating voxels in the GM segments and these prove extremely consistent with the SFG region identified by the VBM analysis. Furthermore, the SVM-RFE map obtained with the most discriminating set of voxels corresponding to the maximum Area Under the Receiver Operating Characteristic Curve (AUC(max)=0.80) highlighted a more complex circuitry of increased cortical volume in ASDf, involving bilaterally the SFG and the right temporo-parietal junction (TPJ). The SFG and TPJ abnormalities may be relevant to the pathophysiology of ASDf, since these structures participate in some core atypical features of autism.
A view into the brain of female children with autism pectrum disorder: Morphometric regional alterations detected by structural MRI mass-univariate and pattern classification analisys
CALDERONI S;MURATORI, FILIPPO;
2011-01-01
Abstract
Female children with autism spectrum disorder: An insight from mass-univariate and pattern classification analyses. Calderoni S, Retico A, Biagi L, Tancredi R, Muratori F, Tosetti M. IRCCS Stella Maris Foundation, Viale del Tirreno 331, 56018 Calambrone, Pisa, Italy; Division of Child Neurology and Psychiatry, University of Pisa, Pisa, Italy. Several studies on structural MRI in children with autism spectrum disorders (ASD) have mainly focused on samples prevailingly consisting of males. Sex differences in brain structure are observable since infancy and therefore caution is required in transferring to females the results obtained for males. The neuroanatomical phenotype of female children with ASD (ASDf) represents indeed a neglected area of research. In this study, we investigated for the first time the anatomic brain structures of a sample entirely composed of ASDf (n=38; 2-7years of age; mean=53months; SD=18) with respect to 38 female age and non verbal IQ matched controls, using both mass-univariate and pattern classification approaches. The whole brain volumes of each group were compared using voxel-based morphometry (VBM) with diffeomorphic anatomical registration through exponentiated lie algebra (DARTEL) procedure, allowing us to build a study-specific template. Significantly more gray matter (GM) was found in the left superior frontal gyrus (SFG) in ASDf subjects compared to controls. The GM segments obtained in the VBM-DARTEL preprocessing are also classified with a support vector machine (SVM), using the leave-pair-out cross-validation protocol. Then, the recursive feature elimination (SVM-RFE) approach allows for the identification of the most discriminating voxels in the GM segments and these prove extremely consistent with the SFG region identified by the VBM analysis. Furthermore, the SVM-RFE map obtained with the most discriminating set of voxels corresponding to the maximum Area Under the Receiver Operating Characteristic Curve (AUC(max)=0.80) highlighted a more complex circuitry of increased cortical volume in ASDf, involving bilaterally the SFG and the right temporo-parietal junction (TPJ). The SFG and TPJ abnormalities may be relevant to the pathophysiology of ASDf, since these structures participate in some core atypical features of autism.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
