Abstract P3-02-06: Magnetic resonance imaging (MRI) surveillance for patients with dense breasts and a previous breast cancer (BC) and/or high risk lesion
Bibliographic record
Abstract
Abstract BACKGROUND AND PURPOSE The benefits of breast MRI for screening women at high risk of developing BC is established, but its role in women with a personal history of BC or dense breasts is unknown. We sought to estimate the performance of annual surveillance MRI added to mammography in women at moderately increased BC risk due to a personal history of breast cancer and/or a high-risk breast lesion and dense breasts. METHOD AND MATERIALS We performed a retrospective chart review of the clinical, radiological, and pathological parameters of women who received annual, concurrent surveillance breast MRI and mammography between 04/2013 and 12/2015. We included women who met all of the following criteria: age<69; prior diagnosis of high-risk lesion (ADH, ALH, LCIS), DCIS, or invasive BC; heterogeneously (50-75%) or extremely dense (>75%) breasts; and did not qualify for our provincial MRI screening program for high risk women (calculated lifetime BC risk ≥ 25%). Results of each scan were analyzed using descriptive statistics and Chi squared for comparisons between subgroups. RESULTS A total of 199 patients (267 MRI exams) were included in this study. The mean age at initial diagnosis was 45 years and at subsequent diagnosis of DCIS or invasive cancer was 53 years. Mean time to new diagnosis was 86 months (range 14-202). All 15 cancers diagnosed during the study period were MRI detected: 11 invasive stage I (66% IDC, 7% ILC) and 4 DCIS (27%). Of these 15, all but 1 were mammographically occult. Five (33%) were found in the breast ipsilateral to the original lesion. The cancer detection rate was 6% (12/199) on the first screening round and 4.7% (3/64) on the second screening round. Specificity and positive predictive value respectively for MRI exams increased from 77% and 22% on the first screening round to 88% and 30% on the second round. Of women who developed BC, 57% had a history of breast or ovarian cancer in a first degree relative. None of the 72 women who were on hormonal therapy at the time of surveillance imaging had a new cancer detected compared to 11% (14/125) of those who were not on hormonal therapy (p=0.0025). CONCLUSIONS The incremental early-stage BC detection rate and specificity of MRI in this population are comparable to what is observed in screening women at high risk. The addition of annual MRI to mammography should be considered for surveillance of women with a personal history of BC / premalignant lesion and heterogeneous / extremely dense breasts, particularly if they have a family history of BC and are not on hormonal therapy. Citation Format: Nadler M, Al Attar H, Curpen B, Martel AL, Balasingham S, Zhang L, Eisen A, Warner E. Magnetic resonance imaging (MRI) surveillance for patients with dense breasts and a previous breast cancer (BC) and/or high risk lesion [abstract]. In: Proceedings of the 2016 San Antonio Breast Cancer Symposium; 2016 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2017;77(4 Suppl):Abstract nr P3-02-06.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.003 | 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".