alexa Damage to the human cerebellum from prenatal alcohol exposure: the anatomy of a simple biometrical explanation.


Autism-Open Access

Author(s): Bookstein FL, Streissguth AP, Connor PD, Sampson PD

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Abstract Since 1973, it has become clear that exposure of otherwise normal human fetuses to high levels of alcohol damages a substantial number of the exposed brains in a wide variety of ways nowadays referred to collectively as the fetal alcohol spectrum disorders (FASDs). Averages of images and measurements of brains with these disorders are quantitatively different from normal, and the cerebellum is one of the structures at which differences are typically noted. The present article extends these techniques to a simple, practical, and enlightening detection rule for fetal alcohol damage in adolescents and adults known to have been heavily exposed. The data arise from 180 clinical MR brain images (half of adolescents, half of adults; half male, half female; one-third each fetal alcohol syndrome, fetal alcohol effects, and unexposed). The 180 cerebellums were represented by 328-semilandmark triangulations covering most of the cerebellar surface. Statistical analysis exploited the now-conventional methods of Procrustes analysis in three dimensions, along with a recent extension to incorporate size information explicitly. If we reduce the data complexity even further, to just 23 points along the silhouette of the cerebellum as viewed from above along the aqueductal axis, the analysis becomes more precise. Now a single multivariate summary score, very strongly correlated with size, supports a discrimination (diagnosed vs. unexposed) with about 75\% accuracy. About one-quarter of our FASD sample overlaps with the central range of the unexposed in the distribution of this size-based score, with the other three-quarters distinctly showing cerebellar damage. The finding, which corresponds quite closely to the fundamental finding of cerebellar hypoplasia in animal experiments, bears implications for fetal alcohol epidemiology, for geometric morphometrics, and for the geometric complexity of useful data structures derived from clinical brain imaging. (c) 2006 Wiley-Liss, Inc. This article was published in Anat Rec B New Anat and referenced in Autism-Open Access

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