Evaluation of tumor cell death response in locally-advanced breast cancer patients to chemotherapy treatment by scattering property estimates using ultrasound backscatter
Bibliographic record
Abstract
Breast cancer tumor response to chemotherapy in twenty nine patients was examined using quantitative ultrasound techniques. Backscatter parameters, such as the average scatterer diameter (ASD) and average acoustic concentration (AAC), were estimated from regions-of-interest in tumors prior to treatment onset and at four times during neoadjuvant chemotherapy treatment (weeks 1, 4, 8 and prior to surgery). Gaussian and Anderson form factor models were used over an analysis bandwidth of 4.5 to 9 MHz to obtain ASD and AAC estimates. The Gaussian model did not fit with the measured data as well as Anderson model. The AAC estimates yielded significant differences with therapy times in clinically treatment responded patients. Data indicated increases of 6.6 dB/cm in acoustic concentration obtained maximum at week 8 in treatment responding tumors. Non-responding tumors didn't show any significant difference in the parameters during treatment. This study demonstrates that the scattering parameters have the potential to being used in quantifying the changes in tumors during treatment noninvasively and distinguishing treatment responders and non-responders early after of treatment initiation.
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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 | 0.001 |
| 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 | 0.000 |
| 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".