Visibility of microcalcification clusters and masses in breast tomosynthesis image volumes and digital mammography: A 4AFC human observer study
Bibliographic record
Abstract
PURPOSE: To investigate the visibility of simulated lesions in digital breast tomosynthesis (BT) image volumes compared with 2D digital mammography (DM). METHODS: Simulated lesions (masses and microcalcifications) were added to images of the same women acquired on a DM system (Mammomat Novation, Siemens) and a BT prototype. The same beam quality was used for the DM and BT acquisitions. The total absorbed dose resulting from a 25-projection BT acquisition and reconstruction (BT(25)) was approximately twice that of a single DM view. By excluding every other projection image from the reconstruction (BT(13)), approximately the same dose as in DM was effected. Simulated microcalcifications were digitally added with varying contrast to the DM and BT images. Simulated masses with 8 mm diameter were also added to BT images. A series of 4-alternative forced choice (4AFC) human observer experiments were conducted. Four medical physicists participated in all experiments, each consisting of 60 trials per experimental condition. The observers interpreted the BT image volumes in cine-mode at a fixed image sequence speed. The required threshold contrast (S(t)) to achieve a detectability index (d') of 2.5 (i.e., 92.5% correct decisions) was determined. RESULTS: The S(t) for mass detection in DM was approximately a factor of 2 higher than required in BT indicating that the detection of masses was improved under BT conditions compared to DM. S(t) for microcalcification detection was higher for BT than for DM at both BT dose levels (BT(25) and BT(13)), with a statistically significant difference in S(t) between DM and BT(13). These results indicate a dose-dependent decrease in detection performance in BT for detection of microcalcifications. CONCLUSIONS: In agreement with previous investigations, masses of size 8 mm can be detected with less contrast in BT than in DM indicating improved detection performance for BT. However, for the investigated microcalcifications, the results of this study indicate potentially worse performance for BT than for DM at the same dose level.
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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 | 0.001 |
| 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".