Naftali Raz

The hippocampus is a heterogeneous structure with cytoarchitectonically distinct subfields that exhibit heterogeneous lifespan trajectories and are differentially susceptible to diseases. Advances in high‐resolution imaging have accelerated research on these structures, yet variability in segmentation protocols limits cross‐study comparability. The Hippocampal Subfields Group (HSG) is an international consortium addressing this challenge by developing a reliable, accessible, and freely available segmentation protocol for high‐resolution T2‐weighted 3T MRI scans ( http://www.hippocampalsubfields.com ). Here, we present the harmonized protocol for the posterior portion of the hippocampus (the “tail”), complementing the previously established “body” protocol, and with an anterior “head” protocol under development. The tail protocol provides standardized definitions of the external boundaries for the posterior‐most extent of the hippocampus, facilitating consistent segmentation from surrounding tissues. The research community was extensively involved through an online survey that incorporated comprehensive protocol details, feasibility assessments, tutorial videos, and illustrative segmentations. Through this collaborative process, consensus emerged to exclude subfield labeling in the hippocampal tail due to limited visibility of internal landmarks and substantial anatomical variability in this region. All proposed boundary guidelines were deemed clear and agreed upon via a Delphi procedure. The harmonized tail protocol has high intra‐ (Averaged ICC(2, 1) > 0.98; Averaged Dice Similarity Coefficient = 0.92) and inter‐rater reliability (Averaged ICC(2, k ) > 0.98; Averaged Dice Similarity Coefficient = 0.86) and offers a practical framework for replicable segmentation. By establishing standardized guidelines, this protocol enhances comparability of findings across developmental, aging, and clinical research and is compatible with ongoing technological advances.

White matter hyperintensities are ubiquitous in magnetic resonance imaging scans of older adults and reflect multiple pathological causes, particularly cardiovascular and metabolic disease risk factors. Elevated white matter hyperintensity burden is a predictor of dementia, but the relationship between white matter hyperintensity progression and cognitive change in typical aging remains unclear, arguably due to the scarcity of longitudinal evidence. Here, we estimated white matter hyperintensity volume in 67 participants of the Detroit Aging Brain Study, aged 50-77 at baseline, over four occasions spanning 7 years. The white matter hyperintensity volume increased over time, especially around the frontal horns of the lateral ventricles, and accelerated with advanced age. Greater baseline white matter hyperintensity volume predicted faster progression across all regions. Men had a greater white matter hyperintensity burden than women, independent of age, but did not differ in progression rate. Of all examined cognitive abilities, only perceptual speed slowing was associated with faster white matter hyperintensity progression in parietal and occipital lobes. Thus, not only does white matter hyperintensity volume increase over time in normative aging, but the change is linked to declines in a quintessential age-sensitive cognitive skill.

Hippocampal subfields differentially develop and age, and they vary in vulnerability to neurodegenerative diseases. Innovation in high‐resolution imaging has accelerated clinical research on human hippocampal subfields, but substantial differences in segmentation protocols impede comparisons of results across laboratories. The Hippocampal Subfields Group (HSG) is an international organization seeking to address this issue by developing a histologically valid, reliable, and freely available segmentation protocol for high‐resolution T ₂ ‐weighted 3 T MRI ( http://www.hippocampalsubfields.com ). Here, we report the first portion of the protocol focused on subfields in the hippocampal body; protocols for the head and tail are in development. The body protocol includes definitions of the internal boundaries between subiculum, Cornu Ammonis (CA) 1–3 subfields, and dentate gyrus, in addition to the external boundaries of the hippocampus apart from surrounding white matter and cerebrospinal fluid. The segmentation protocol is based on a novel histological reference dataset labeled by multiple expert neuroanatomists. With broad participation of the research community, we voted on the segmentation protocol via an online survey, which included detailed protocol information, feasibility testing, demonstration videos, example segmentations, and labeled histology. All boundary definitions were rated as having high clarity and reached consensus agreement by Delphi procedure. The harmonized body protocol yielded high inter‐ and intra‐rater reliability. In the present paper we report the procedures to develop and test the protocol, as well as the detailed procedures for manual segmentation using the harmonized protocol. The harmonized protocol will significantly facilitate cross‐study comparisons and provide increased insight into the structure and function of hippocampal subfields across the lifespan and in neurodegenerative diseases.

Hippocampal subfields differentially develop and age, and they vary in vulnerability to neurodegenerative diseases. Innovation in high-resolution imaging has accelerated clinical research on human hippocampal subfields, but substantial differences in segmentation protocols impede comparisons of results across laboratories. The Hippocampal Subfields Group (HSG) is an international organization seeking to address this issue by developing a histologically-valid, reliable, and freely available segmentation protocol for high-resolution T ₂ -weighted 3 tesla MRI ( http://www.hippocampalsubfields.com ). Here, we report the first portion of the protocol focused on subfields in the hippocampal body; protocols for the head and tail are in development. The body protocol includes definitions of the internal boundaries between subiculum, Cornu Ammonis (CA) 1-3 subfields, and dentate gyrus, in addition to the external boundaries of the hippocampus apart from surrounding white matter and cerebrospinal fluid. The segmentation protocol is based on a novel histological reference data set labeled by multiple expert neuroanatomists. With broad participation of the research community, we voted on the segmentation protocol via online survey, which included detailed protocol information, feasibility testing, demonstration videos, example segmentations, and labeled histology. All boundary definitions were rated as having high clarity and reached consensus agreement by Delphi procedure. The harmonized body protocol yielded high inter- and intra-rater reliability. In the present paper we report the procedures to develop and test the protocol, as well as the detailed procedures for manual segmentation using the harmonized protocol. The harmonized protocol will significantly facilitate cross-study comparisons and provide increased insight into the structure and function of hippocampal subfields across the lifespan and in neurodegenerative diseases.

Using Phosphorus Magnetic Resonance Spectroscopy (³¹P MRS), we examined five metabolites associated with brain energy cycle, and cellular membrane production and degradation in 11 brain regions of 48 children (age 6–15), and 80 middle‐aged and older adults (age 52–87). Levels of phosphomonoesters (PMEs) and phosphodiesters (PDEs), gamma plus alpha adenosine triphosphate (γαATP), phosphocreatine (PCr) and inorganic phosphate (Pi), were residualized on the total amplitude value. PMEs were greater in children compared to adults, whereas PDEs showed the opposite age difference. Higher γαATP and lower Pi were found in children compared to adults. The age group differences were particularly salient in the association cortices and anterior white matter. Among children, age correlated negatively with PMEs and positively with PDEs in association cortices. Compared to children, adults had lower intracellular pH. The results suggest reduction in membrane synthesis and increase in membrane degradation in adolescents and to a greater degree in adults compared to younger children. Concomitant reduction in γαATP and increase in Pi are consistent with reduced energy consumption in adolescents and further drop in middle‐aged and older adults, although it is impossible to distinguish declines in energy supply from reduced demand due to shrinking neuropil, without longitudinal studies.

Automatic segmentation methods for in vivo magnetic resonance imaging are increasing in popularity because of their high efficiency and reproducibility. However, automatic methods can be perfectly reliable and consistently wrong, and the validity of automatic segmentation methods cannot be taken for granted. Quality control (QC) by trained and reliable human raters is necessary to ensure the validity of automatic measurements. Yet QC practices for applied neuroimaging research are underdeveloped. We report a detailed QC and correction procedure to accompany our validated atlas for hippocampal subfield segmentation. We document a two‐step QC procedure for identifying segmentation errors, along with a taxonomy of errors and an error severity rating scale. This detailed procedure has high between‐rater reliability for error identification and manual correction. The latter introduces at maximum 3% error variance in volume measurement. All procedures were cross‐validated on an independent sample collected at a second site with different imaging parameters. The analysis of error frequency revealed no evidence of bias. An independent rater with a third sample replicated procedures with high within‐rater reliability for error identification and correction. We provide recommendations for implementing the described method along with hypothesis testing strategies. In sum, we present a detailed QC procedure that is optimized for efficiency while prioritizing measurement validity and suits any automatic atlas.

The Cambridge Handbook of Intelligence and Cognitive Neuroscience - July 2021