Effects of sex and gonadal hormones on manually segmented hypothalamic and pituitary gland volumes in young healthy adults
Bibliographic record
Abstract
Abstract The hypothalamus and pituitary regulate, amongst other functions, third order endocrine systems, and their volumes have been associated with normal and pathological outcomes. Yet, there are very few studies that examine their combined structural variations in vivo . This is due, in part, to their small size and a lack of comprehensive image segmentation protocols. In the current project we acquired high-resolution T1- (1mm isotropic) and T2-weighted (0.4mm in plane resolution) 3T magnetic resonance images (MRI) of the hypothalamus and pituitary gland, as well as salivary estradiol and testosterone from 31 (17M, 14F) young healthy adults. Women reported oral contraceptive use. Image preprocessing included non-uniformity correction, signal intensity normalization and standard stereotaxic space registration. We applied a comprehensive manual segmentation protocol of the whole hypothalamus, with detailed segmentation of the pituitary stalk, the anterior and posterior pituitary gland, and the posterior bright spot. We also propose a novel medial-lateral hypothalamic parcellation into medial preoptic, periventricular (PVN), and lateral hypothalamic regions. The protocol yielded good inter- (range: 0.78-0.92) and intra-rater (range: 0.79-0.94) Dice kappa overlap coefficients. We detected sex differences of the whole hypothalamus and each hemisphere, and a trend for the right preoptic region to be larger in males than in females, with a moderate effect size. Sex differences were maintained or enhanced when covarying for estradiol, but not when covarying for testosterone. In addition, testosterone was associated with the volume of the PVN, but only in women. In summary, these results suggest that there are morphometric differences at the level of the pituitary and hypothalamus that are likely driven by central regulation of gonadal hormones. The here described protocol allows the structural investigation of neuroendocrine effects in the central nervous system.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".