Investigating the effects of intensity threshold on high-frequency three-dimensional power Doppler ultrasound.
Bibliographic record
Abstract
High-frequency power Doppler ultrasound is a non-invasive vascular imaging modality ideal for a quantitative assessment of vascularity in preclinical models. Although it permits detecting slower blood flows than other ultrasound Doppler methods, it is limited by flow artifacts, complicating the interpretation of tumor vascularity metrics such as the vascularity index (VI). Our aim was to examine how parameters such as the intensity threshold affect the VI in in vivo xenograft models. Breast MDA-MB-231 tumors in the hind leg of SCID mice were treated with 0 or 8 Gy radiation, and imaged before and 24 h after treatment. A Vevo770 was used along with a 25-MHz center frequency transducer to obtain 3-D power Doppler images of tumors. Mice were again imaged while in the same position 1 min after sacrifice at 24 h. This was carried out for direct comparison of true blood flow signal to system noise level. The VI was computed for a range of intensity thresholds. The VI-threshold curves varied differently as a function of treatment, and preliminary data indicate an optimal plateau where the intensity threshold should be set, yielding a nearly true blood flow signal and minimizing noise signal. [Work funded by the Canadian Breast Cancer Foundation.]
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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 | 0.001 | 0.005 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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 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".