Quantification of red blood cell aggregation using an ultrasound clinical imaging system
Bibliographic record
Abstract
An abnormal level of red blood cell (RBC) aggregation is a clinical condition associated with many cardiovascular disorders and other pathologies. Characterization of this phenomenon was made using the backscatter power spectral slope (BPSS) of radio-frequency (RF) data collected from a clinical phased array ultrasound scanner (GE Vivid Five). Porcine blood was circulated in a flow loop system containing a vascular phantom. Experiments were done with a linear array probe of the GE Vivid Five operating at a frequency of 7 MHz, and compared to results obtained with a 7.5 MHz nonfocused monoelement transducer (gold standard). They were oriented to the same spot within the vascular phantom. Raw RF data from both transducers were collected versus blood flow rate that was varied from 0 to 100 ml/min at hematocrits (H) of 5%, 16% and 45%. As well, measurements were done in a reference saline solution containing 7% of RBCs for comparison. No major differences were noted for BPSS measured with both transducers. In the case of the saline solution where no significant aggregation of RBCs can occur, the BPSS presented a constant value close to 4. In the case of whole blood where RBC aggregation is possible, the BPSS increased as the blood flow rate was increased. For H=5%, the variation was from 2.9 to 3.9. The BPSS increased from 2.9 to 4.1 in the case of H=16%, and from 2.4 to 3.3 for H=45%. No correction for attenuation was done for those data. In conclusion, for the saline solution containing RBCs, the ultrasound properties of blood had or were approaching the Rayleigh behavior since the BPSS was close to 4. Aggregation of RBCs appeared as the blood flow rate was decreased; a reduction of the BPSS was then observed. For the first time, we showed that it is possible to quantify the RBC aggregation with BPSS in a flow loop system simulating physiological flow rates with a clinical imaging system. The results were validated by a method
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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 | 0.000 |
| 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".