Diagnostic Performance of Quantitative Shear Wave Elastography in the Evaluation of Solid Breast Masses: Determination of the Most Discriminatory Parameter
Bibliographic record
Abstract
OBJECTIVE: The purpose of this article is to assess the diagnostic performance of quantitative shear wave elastography in the evaluation of solid breast masses and to determine the most discriminatory parameter. SUBJECTS AND METHODS: B-mode ultrasound and shear wave elastography were performed before core biopsy of 123 masses in 112 women. The diagnostic performance of ultrasound and quantitative shear wave elastography parameters (mean elasticity, maximum elasticity, and elasticity ratio) were compared. The added effect of shear wave elastography on the performance of ultrasound was determined. RESULTS: The mean elasticity, maximum elasticity, and elasticity ratio were 24.8 kPa, 30.3 kPa, and 1.90, respectively, for 79 benign masses and 130.7 kPa, 154.9 kPa, and 11.52, respectively, for 44 malignant masses (p < 0.001). The optimal cutoff value for each parameter was determined to be 42.5 kPa, 46.7 kPa, and 3.56, respectively. The AUC of each shear wave elastography parameter was higher than that of ultrasound (p < 0.001); the AUC value for the elasticity ratio (0.943) was the highest. By adding shear wave elastography parameters to the evaluation of BI-RADS category 4a masses, about 90% of masses could be downgraded to BI-RADS category 3. The numbers of downgraded masses were 40 of 44 (91%) for mean elasticity, 39 of 44 (89%) for maximum elasticity, and 42 of 44 (95%) for elasticity ratio. The numbers of correctly downgraded masses were 39 of 40 (98%) for mean elasticity, 38 of 39 (97%) for maximum elasticity, and 41 of 42 (98%) for elasticity ratio. There was improvement in the diagnostic performance of ultrasound of mass assessment with shear wave elastography parameters added to BI-RADS category 4a masses compared with ultrasound alone. Combined ultrasound and elasticity ratio had the highest improvement, from 35.44% to 87.34% for specificity, from 45.74% to 80.77% for positive predictive value, and from 57.72% to 90.24% for accuracy (p < 0.0001). The AUC of combined ultrasound and elasticity ratio (0.914) was the highest compared with the other combined parameters. CONCLUSION: There was a statistically significant difference in the values of the quantitative shear wave elastography parameters of benign and malignant solid breast masses. By adding shear wave elastography parameters to BI-RADS category 4a masses, we found that about 90% of them could be correctly downgraded to BI-RADS category 3, thereby avoiding biopsy. Elasticity ratio (cutoff, 3.56) appeared to be the most discriminatory parameter.
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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 | 0.006 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".