Contrast-Enhanced Mammography as a Functional Biomarker in Breast Cancer: Correlation of Enhancement Patterns with Ki-67 and Histological Grade
Bibliographic record
Abstract
Background: Contrast-Enhanced Spectral Mammography (CESM) combines anatomical and functional imaging, showing promise in breast cancer diagnosis. Despite well-established lesion detection accuracy, few studies have investigated the link between CESM enhancement patterns and tumor aggressiveness biomarkers. Methods: We retrospectively evaluated 100 patients (mean age 59.5 years) undergoing CESM with complete histopathological data. Lesions were categorized by enhancement intensity (high, medium, low) and contrast homogeneity (homogeneous vs. heterogeneous), correlated with Ki-67 index and histological grade. Results: Lesion size measured by CESM closely matched histology (mean 2.16 cm vs. 2.25 cm). Mass-like lesions corresponded mainly to invasive ductal carcinoma, while non-mass patterns aligned with lobular or in situ carcinomas. Enhancement intensity correlated moderately with Ki-67 (Spearman ρ = 0.56, p < 0.001), and contrast heterogeneity showed a weaker but significant correlation with tumor grade (ρ = 0.22, p < 0.05). Conclusions: CESM accurately assesses tumor size and provides functional insight into tumor biology. Enhancement intensity may serve as a non-invasive proliferation marker, while contrast heterogeneity offers additional prognostic data, supporting CESM’s role in personalized breast cancer management.
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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".