The Effect of Volume Fraction on the Backscatter from Nucleated Cells at High Frequencies
Bibliographic record
Abstract
Small variations in scatterer volume fraction, which can result from changes in tissue microstructure due to cancer therapies or organ preservation, may have a significant impact on ultrasound backscatter. Although the effect of volume fraction has been studied for non-biological scatterers and red blood cells, this study addresses the case of nucleated cells. Suspensions with volume fractions up to 70% of acute myeloid leukemia cells were insonified with broadband 20 MHz and 40 MHz pulses. The resultant average normalized backscatter intensities plotted as a function of volume fraction demonstrated a better agreement with the Yagi-Nakayama continuum scattering theory rather than the Mo-Cobbold particle scattering model (using hard sphere packing). Normalized backscatter increased with cell volume fraction up to a maximum value, occurring between 20 and 30% volume fraction, varying with frequency and then decreased with further increases in volume fraction. This result may have implications in the development of new quantitative, ultrasound-based tissue characterization techniques.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".