Effect of the transpulmonary pressure on the lungs’ vibroacoustic response: a first numerical perspective
Bibliographic record
Abstract
In the high-stakes environment of intensive care units (ICUs), managing transpulmonary pressure is crucial for providing breathing assistance to intubated patients, particularly when combining this intervention with respiratory therapy, such as high-frequency chest compression (HFCC). Despite the complexity of lung tissues, a computed tomography-based finite element model (CT-FEM), guided by Biot's theory, can be employed to numerically predict their vibroacoustic behavior at low frequencies, where the properties of the lungs align with the theory's principles. In this work, one aims to develop an analytical model of the lungs for two different levels of transpulmonary pressure—10 cm H2O (inflated lungs) and 20 cm H2O (healthy lungs)—to examine the poroviscoelastic behavior of the lungs and evaluate the generated analytical model using a CT-FEM of the human thorax like a digital twin of the human thorax. Biot's theory was utilized to predict the complex-valued shear wave speed, as well as the fast and slow compression wave speeds, across a frequency range between 5 and 100 Hz. The analytically computed values were tested using a previously validated CT-FEM of the human thorax to compare respiratory therapy outcomes for intubated patients under different transpulmonary pressure levels. Besides the frequency response function of the thorax, the kinetic energy density and the strain energy density were compared for these pressure levels. The CT-FEM demonstrated that all peak points fall within the range of 20–45 Hz; therefore, this range might be considered in ICUs settings. Kinetic energy density was nearly 2.2 times higher, and strain energy density was 1.46–1.26 times higher at the first and last peaks, respectively; therefore, inflated lungs experienced greater effects than healthy ones under the same respiratory therapy conditions. Overall, this study highlights how different transpulmonary pressures affect HFCC therapy, offering insights into gentle and effective conditions for intubated patients in ICUs while revealing the lungs’ 3D responses by integrating analytically predicted shear wave speed, fast and slow compression wave speeds.
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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 | 0.003 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".