Evaluation and correlation of mammographically suspicious lesions with histopathology at Addington Hospital, Durban
Bibliographic record
Abstract
BACKGROUND: Stereotactic core-needle biopsies (SCNBs) are a reliable alternative to surgical biopsy for microcalcifications. The positive predictive value (PPV) of SCNB has been shown to be reproducible in several studies using the Breast Imaging Reporting and Data System (BIRADS) classification, which is the current gold standard in mammographic reporting. At this stage, no study has been done in KwaZulu-Natal to assess local outcomes against BIRADS. The current standard of care utilises vacuum-assisted breast biopsy, but is not available in a resource-constrained environment such as ours. The need, therefore, is for constant evaluation of existing practice to ensure that it is optimised for the challenges and limitations facing local radiologists. OBJECTIVE: To assess the PPV of SCNB in Addington Hospital, and to compare it with that of BIRADS. Material and methods. Mammographically detected lesions were assigned to 3 categories: benign, indeterminate and suspicious. A retrospective review of 67 SCNBs was performed for lesions falling within the suspicious category, and the PPV and rates of ductal carcinoma in situ (DCIS) were determined. RESULTS: Our study demonstrated a PPV of 20.9%. This correlated well with international studies for BIRADS 4 and 5 lesions. DCIS accounted for 21.4% of detected malignancies, which is in keeping with current literature. CONCLUSION: Despite resource limitations, local outcomes were comparable to those of BIRADS. Given our fairly general categorisation of lesions, however, it should be emphasised that BIRADS allows better organisation, consistency and clarity in breast imaging reporting, as well as accurate data comparison between centres facing limitations similar to our own.
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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 | 0.001 | 0.001 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".