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OBJECTIVES: MRI has become an indispensable tool for brain volumetric studies, with the hippocampus an important region of interest. Automation of the MRI segmentation process has helped advance the field by facilitating the volumetric analysis of larger cohorts and more studies. FreeSurfer has emerged as the de facto standard tool for these analyses, but studies validating its output are all based on older versions. To characterize FreeSurfer’s validity, we compare several versions of FreeSurfer software with traditional hand-tracing. EXPERIMENTAL DESIGN: Using MRI images of 262 males and 402 females aged 38 to 84, we directly compare estimates of hippocampal volume from multiple versions of FreeSurfer, its hippocampal subfield routines, and our manual tracing protocol. We then use those estimates to assess asymmetry and atrophy, comparing performance of different estimators with each other and with brain atrophy measures. PRINCIPAL OBSERVATIONS: FreeSurfer consistently reports larger volumes than manual tracing. This difference is smaller in larger hippocampi or older people, with these biases weaker in version 6.0.0 than prior versions. All methods tested agree qualitatively on rightward asymmetry and increasing atrophy in older people. CONCLUSIONS: FreeSurfer saves time and money, and approximates the same atrophy measures as manual tracing, but it introduces biases that could require statistical adjustments in some studies.

Objectives To quantify associations between inflammatory biomarkers and hippocampal volume (HV) and to examine effect modification according to sex, race, and age. Design Cross-sectional analyses using generalized estimating equations to account for familial clustering; standardized β-coefficients adjusted for age, sex, race, and education. Setting Community cohorts in Jackson, Mississippi and Rochester, Minnesota. Participants The Genetic Epidemiology Network of Arteriopathy study. Measurements C-reactive protein (CRP), interleukin-6 (IL-6), and soluble tumor necrosis factor receptors 1 (sTNFR-1) and 2 (sTNFR-2) from peripheral blood were measured in a sample of 773 non-Hispanic whites (61% women, aged 60.2 ± 9.8) and 514 African Americans (70% women, aged 63.9 ± 8.1) who also underwent brain magnetic resonance imaging. Biomarkers were standardized and compared according to sex, race and age with HV. Results In the full sample, higher sTNFR-1 and sTNFR-2 were associated with smaller HV. Each standard deviation (SD) increase in sTNFR-1 was associated with 59.1 mm3 (95% confidence interval (CI) = −101.4 to −16.7 mm3) smaller HV and each SD increase in sTNFR-2 associated with 48.8 mm3 (95% CI = −92.2 to −5.3 mm3) smaller HV. Relationships were stronger for sTNFR-2 in men (HV = −116.6 mm3 for each SD increase, 95% CI = −201.0 to −32.1) than women (HV = −26.0 per SD increase, 95% CI = −72.4–20.5) and sTNFR-1 in non-Hispanic whites (HV = −84.7 mm3 per SD increase, 95% CI = −142.2 to −27.1) than African Americans (HV = −14.1 mm3 per SD increase, 95% CI = −78.3–50.1). Associations between IL-6 or CRP and HV were not supported. Conclusion Higher levels of sTNFRs were associated cross-sectionally with smaller hippocampi. Longitudinal data are needed to determine whether these biomarkers may help to identify risk of late-life cognitive impairment.

In the News Focus story “Waiting for the revolution” (4 February, p. [526][1]), E. Marshall discussed the use of genetic diagnostics in medicine. However, an analysis of the medical genetics revolution should focus not only on diagnostics but also on genetic manipulation. The genetic revolution is well under way in microbes and invertebrates. It's even enjoying great progress in mice and moderate progress in rats. The real progress in these organisms has come not from the ability to read their genes; rather, it is a result of our ability to write them. Improving modern treatments, including pharmaceuticals, based on genetic differences is certainly a valuable addition to our medical toolbox. But I predict that the advent of genetic manipulations in humans—whether in embryos or in adults, whether transient or permanent, whether purely genetic or epigenetic—will be considered the real beginning of the genetic revolution. Before we proceed down this road, we must address numerous risks and ethical questions. But we cannot experience any sort of genetic revolution in human medicine until we push through these obstacles and address the benefits to humanity of repairing the aberrantly expanded HTT gene in a middle-aged Huntington's patient or knocking in a copy of the CFTR gene in a child suffering from cystic fibrosis. Diagnostics are just viewing the toolbox through a window. Eventually, we'll need to figure out how to safely pick up the tools and make good use of them. [1]: /lookup/doi/10.1126/science.331.6017.526