The impact of preoperative breast magnetic resonance imaging (MRI) on surgical decision-making in young patients with breast cancer.
Bibliographic record
Abstract
Abstract Abstract #4012 Recent data suggests that breast MRI is a more sensitive diagnostic test for detecting invasive breast cancer than mammography or breast ultrasound. Breast MRI may be particularly useful in younger premenopausal women with higher density breast tissue for differentiating between dense fibroglandular breast tissue and breast malignancies. The primary objective of this study was to determine the impact of pre-operative breast MRI on surgical decision-making in young women with breast cancer. Methods: A retrospective review of 32 patients with newly diagnosed invasive breast cancer and age ≤ 50 was performed. All patients underwent a physical examination, preoperative mammogram, breast ultrasound, and bilateral breast MRI. Two breast cancer surgeons reviewed the preoperative mammogram report, breast ultrasound report, and physical examination summary for each case and were asked if they would recommend a lumpectomy, quandrantectomy, or mastectomy. A few weeks later, the two surgeons were shown the same information with the breast MRI report and were asked what type of surgery they would now recommend. In each case, MRI was classified by two adjudicators as having affected the surgical outcome in a positive, negative, or neutral fashion. A 'Positive Impact' was defined as the situation where breast MRI detected additional disease that was not found on physical exam, mammogram, or breast ultrasound and led to an appropriate change in surgical management. A 'Negative Impact' was defined as the situation where the breast MRI results led the surgeon to recommend more extensive surgery, with less extensive disease actually found at pathology. 'No Impact' was defined as the situation where MRI findings did not alter surgical recommendations or outcome. Results: The median age was 41.5 years. The pathologic diagnosis was invasive ductal carcinoma in 94% (30/32) and invasive lobular carcinoma in 6% (2/32) of cases. For surgeon A, clinical management was altered in 21/32 (66%) of cases, and for surgeon B, management was altered in 13/32 (41%) of cases. The most common change in surgical decision-making after breast MRI was from breast conserving surgery to a mastectomy. Mastectomy rates were similar between both surgeons after breast MRI. After reviewing the pathology results and comparing them with the breast MRI results, it was determined that breast MRI led to a positive outcome in 13/32 cases (41%). Breast MRI led to no change in surgical management in 15/32 (47%) cases and resulted in a negative change in surgical management in 4/32 (13%) cases. Bilateral breast MRI detected a contralateral breast cancer in 2/32 (6%) patients. Conclusions: Preoperative breast MRI appears to result in a change in surgical management in a significant proportion of younger women. Further research is needed to determine if this change in surgical decision-making will result in improved local control. Citation Information: Cancer Res 2009;69(2 Suppl):Abstract nr 4012.
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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 | 0.015 |
| 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".