A comparison of various methods for measuring breast density and breast tissue composition in adolescent girls and women
Bibliographic record
Abstract
Abstract This study compared different approaches to measuring breast density and breast tissue composition (BTC) in adolescent girls (n = 42, aged 14–16 years) and their mothers (n = 39, aged 36–61 years) from a cohort in Santiago, Chile. Optical spectroscopy (OS) was used to measure collagen, water, and lipid concentrations, which were combined into a percent breast density index (%BDI). A clinical dual-energy X-ray absorptiometry (DXA) system calibrated to measure breast density provided percent fibroglandular volume (%FGV) from manually delineated images. After digitizing mammogram films, the percent mammographic breast density (%MBD) was measured using computer-assisted software. Partial correlation coefficients ( r partial ) were used to evaluate associations between breast density measures and BTC from these three different measurement approaches, adjusting for age and body mass index. %BDI from OS was associated with %FGV from DXA in adolescent girls ( r partial = 0.46, p -value = 0.003), but not in mothers ( r partial = 0.17, p -value = 0.32). In mothers, %FGV from DXA was associated with %MBD from mammograms ( r partial = 0.60, p -value < 0.001). These findings suggest that data from OS, DXA, and mammograms provide related but distinct information about breast density and BTC. Future studies should explore how the information provided by these different devices can be used for breast cancer risk prediction in cohorts of adolescent girls and women.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".