Childhood socioeconomic status and adult brain size: childhood socioeconomic status influences adult hippocampal size.

OBJECTIVE: To investigate in older adults without dementia the relationships between socioeconomic status (SES) in childhood and magnetic resonance imaging (MRI)-derived brain volume measures typical of brain aging and Alzheimer's disease (AD). METHODS: Using a cross-sectional and longitudinal observation approach, we invited volunteers without dementia, all born in 1936, and who were participants in the 1947 Scottish Mental Survey, for MR brain imaging; 249 of 320 (77%) agreed. We measured whole brain and hippocampal volumes and recorded childhood SES history, the number of years of education undertaken, and adult SES history. Mental ability at age 11 years was recorded in 1947 and was also available. RESULTS: Analysis shows a significant association between childhood SES and hippocampal volume after adjusting for mental ability at age 11 years, adult SES, gender, and education. INTERPRETATION: A significant association between childhood SES and hippocampal volumes in late life is consistent with the established neurodevelopmental findings that early life conditions have an effect on structural brain development. This remains detectable more than 50 years later.

Shape analysis of 123I-N-omega-fluoropropyl-2-beta-carbomethoxy-3beta-(4-iodophenyl) nortropane single-photon emission computed tomography images in the assessment of patients with parkinsonian syndromes.

PURPOSE: The purpose of this study was to show the viability and performance of a shape-based pattern recognition technique applied to I-N-omega-fluoropropyl-2-beta-carbomethoxy-3beta-(4-iodophenyl) nortropane single-photon emission computed tomography (FP-CIT SPECT) in patients with parkinsonism. METHODS: A fully automated pattern recognition tool, based on the shape of FP-CIT SPECT images, was written using Java. Its performance was evaluated and compared with QuantiSPECT, a region-of-interest-based quantitation tool, and observer performance using receiver operating characteristic analysis and kappa statistics. The techniques were compared using a sample of patients and controls recruited from a prospective community-based study of first presentation of parkinsonian symptoms with longitudinal follow up (median 3 years). RESULTS: The shape-based technique as well as the conventional semiquantitative approach was performed by experienced observers. The technique had a high level of automation, thereby avoiding observer/operator variability. CONCLUSION: A pattern recognition approach is a viable alternative to traditional methods of analysis in FP-CIT SPECT and has additional advantages.