Experimental investigation on the effect of concentration on the resonance frequency of lipid coated ultrasonically excited microbubbles
Bibliographic record
Abstract
This study presents an experimental investigation of the influence of MB concentration on the resonance frequency of lipid-coated microbubbles (MBs). Expanding on theoretical models and numerical simulations from previous research, this work experimentally investigates the effect of MB size on the rate of resonance frequency increase with concentration, a phenomenon observed across MBs with two different lipid compositions: propylene glycol (PG) and propylene glycol and glycerol (PGG). Employing a custom-designed ultrasound attenuation measurement setup, we measured the frequency-dependent attenuation of MBs, isolating MBs based on size to generate distinct monodisperse sub-populations for analysis. The resonance frequency of MBs was determined by identifying the attenuation peak in the broadband attenuation ultrasound attenuation measurements. Our experimental findings confirm that larger MBs (≈2.1μm) demonstrate a more significant shift in resonance frequency (≈ 5 MHz, ≈ 40%) as a function of MB concentration. In contrast, smaller MBs (≈1.3μm) show a minor shift in the resonant frequency (≈ 1.8 MHz, ≈ 8%), underlining the importance of size in determining acoustic behavior compared to changes in the lipid shell properties. Additionally, we observed that resonance frequency increase with concentration reaching a saturation point at higher concentrations. This plateau occurs at higher concentrations for larger MBs (≈2.1μm), while smaller MBs (≈1.6μm and ≈1.3μm) reach this saturation point at lower concentrations. Furthermore, the study highlights the small effect of bubble-bubble interactions on the resonance frequency of MB populations, particularly at lower MB concentrations and for smaller MBs. This insight is important for applications utilizing MB clusters, such as contrast-enhanced ultrasound imaging and MB-mediated therapies. While both size and lipid shell composition influence resonance frequency, MB size has a more significant effect. In conclusion, our findings affirm the need to consider both MB size and concentration when utilizing MBs for clinical and industrial ultrasonic applications.
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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".