Bilateral symmetry of breast tissue composition by magnetic resonance in young women and adults
Bibliographic record
Abstract
BACKGROUND: Some reports suggest that there is a slightly higher frequency of breast cancer in the left breast compared with the right in middle-aged women. The reasons for this association are unknown. The water and fat content of both breasts was compared using magnetic resonance (MR). Breast water by MR reflects fibro-glandular tissue and is strongly positively correlated with percent mammographic density, a strong risk factor for breast cancer. METHODS: Magnetic resonance was used to measure fat and water content of the breast in 400 young women aged 15-30 years and a random sample of 100 of their mothers. All MR examinations were carried out using a 1.5T MR system, and 45 contiguous slices were obtained in the sagittal plane. One reader identified the breast tissue in the image, and subsequently, fat and water content was calculated using a three-point Dixon technique. Left- and right-sided images were read independently in random order. RESULTS: In young women, mean percent water was on average 0.84 % higher in the right compared with the left breast (p < 0.001) and total breast water was on average 6.42 cm(3) greater on the right side (p < 0.001). In mothers, there were no significant differences in any breast measure between right and left sides. CONCLUSION: The small differences in breast tissue composition in young women are unlikely to be associated with large differences in breast cancer risk between sides. The reported excess of left-sided breast cancer in older women is unlikely to be explained by differences in breast tissue composition.
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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 | 0.000 | 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".