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In fetal alcohol spectrum disorders (FASD), brain growth deficiency is a hallmark of subjects with both fetal alcohol syndrome (FAS) and nonsyndromic FASD (NS‐FASD, that is, those without specific diagnostic features). Although previous studies have suggested that the deep grey matter is heterogeneously affected at the group level, it has not yet been established within proper scaling modeling, nor has it been given a place in the FASD diagnostic criteria where neuroanatomical features still contribute almost nothing to diagnostic specificity. We segmented a 1.5T T1‐weighted brain MRI dataset of 90 monocentric FASD patients (53 FAS, 37 NS‐FASD) and 95 typically developing controls (ages 6–20), using volBrain‐vol2Brain as reference, and both Freesurfer‐SAMSEG and FSL‐FIRST to estimate result robustness. The segmentation resulted in seven anatomical volumes: total brain (TBV), total deep grey matter, caudate, putamen, globus pallidus, thalamus, and accumbens. After adjusting for confounds, we fitted the scaling relationship between deep grey matter nuclei volumes (Vi) and TBV (Vi = b × TBVa) and evaluated the effect of FAS on scaling. We then estimated the volumetric deviation from typical scaling (vDTS) for each deep grey nucleus volume in the FAS sample. Finally, we tested the improvement of FAS versus control classifiers based on total deep grey matter vDTS or total brain deviation from typical volume, by adding the five nuclear vDTS, both in terms of performance and generalizability to NS‐FASD. Scaling was significantly different between the FAS and control groups for all deep grey matter nuclei (p < 0.05). We confirmed the undersizing of total deep grey matter in FAS (vDTS = −6%) and identified a pattern of volumetric undersizing, most pronounced in the caudate (−13%) and globus pallidus (−11%), less so in the thalamus (−4%) and putamen (−2%) and sparing the accumbens (0%). These findings were consistent across segmentation tools, despite variations in magnitude. The pattern‐based classifier was more efficient than the one based on total deep grey matter alone (p < 0.001) and identified 32.4% of the NS‐FASD as having a FAS‐like deep grey matter phenotype, compared to 18.9% with the classifier based on total deep grey matter alone (p = 0.113). Added to a classifier based on TBV only, the pattern improved the performance (p = 0.033) of the model and increased identification of NS‐FASD with a FAS‐like neuroanatomical phenotype from 37.8% to 62.2% (p = 0.002). This study details the volumetric undersizing of deep grey matter in a large series of FASD patients. It reveals a differential pattern of vulnerability to prenatal alcohol exposure partially convergent across automatic segmentation tools. It also strongly suggests that this pattern of volumetric undersizing in the deep grey matter may contribute to a neuroanatomical signature of FAS that is usable to improve the probabilistic diagnosis of NS‐FASD by means of MRI‐based diagnostic classifiers. Using MRI‐based normative scaling analysis, we identified a robust pattern of deep grey matter undersizing in fetal alcohol syndrome (FAS). This novel neuroanatomical marker boosted the performances of brain size‐based classifiers and their generalizability to fetal alcohol spectrum disorders lacking FAS‐specific clinical features, supporting its use to improve diagnostic reliability.

Background In an effort to improve the screening and diagnosis of individuals with Fetal Alcohol Spectrum Disorder (FASD), research has focused on the identification of a unique neurodevelopmental profile characteristic of this population. The objective of this review was to identify any existing neurodevelopmental profiles of FASD and review their classification function in order to identify gaps and limitations of the current literature. Methods A systematic search for studies published up to the end of December 2016 reporting an identified neurodevelopmental profile of FASD was conducted using multiple electronic bibliographic databases. The search was not limited geographically or by language of publication. Original research published in a peer-reviewed journal that involved the evaluation of the classification function of an identified neurodevelopmental profile of FASD was included. Results Two approaches have been taken to determine the pathognomonic neurodevelopmental features of FASD, namely the utilization of i) behavioral observations/ratings by parents/caregivers and ii) subtest scores from standardized test batteries assessing a variety of neurodevelopmental domains. Both approaches show some promise, with the former approach (which is dominated by research on the Neurobehavioral Screening Tool) having good sensitivity (63% to 98%), but varying specificity (42% to 100%), and the latter approach having good specificity (72% to 96%), but varying sensitivity (60% to 88%). Conclusions The current review revealed that research in this area remains limited and a definitive neurodevelopmental profile of FASD has not been established. However, the identification of a neurodevelopmental profile will aid in the accurate identification of individuals with FASD, by adding to the armamentarium of clinicians. The full review protocol is available in PROSPERO ( http://www.crd.york.ac.uk/PROSPERO/ ); registration number CRD42016039326; registered 20 May 2016.

BackgroundWhen examining the association between prenatal alcohol exposure and fetal effects, the timing and intensity of exposure have been ignored in epidemiological studies. The effect of using dose, pattern and timing of consumption (“composite” method) was investigated in this study, to examine the association between prenatal alcohol exposure and fetal effects.MethodsThe composite method resulted in six categories of exposure (abstinent, low, moderate, binge

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