Comprehensive transthoracic cardiac imaging in mice using ultrasound biomicroscopy with anatomical confirmation by magnetic resonance imaging
Bibliographic record
Abstract
High-frequency ultrasound biomicroscopy (UBM) has recently emerged as a high-resolution means of phenotyping genetically altered mice and has great potential to evaluate the cardiac morphology and hemodynamics of mouse mutants. However, there is no standard procedure of in vivo transthoracic cardiac imaging using UBM to comprehensively phenotype the adult mice. In this paper, the characteristic mouse thoracic anatomy is elucidated using magnetic resonance (MR) imaging on fixed mice. Besides the left parasternal and apical windows commonly used for transthoracic ultrasound cardiac imaging, a very useful right parasternal window is found. We present strategies for optimal visualization using UBM of key cardiac structures including: 1) the right atrial inflow channels such as the right superior vena cava; 2) the right ventricular inflow tract via the tricuspid orifice; 3) the right ventricular outflow tract to the main pulmonary artery; 4) the left atrial inflow channel, e.g., pulmonary vein; 5) the left ventricular inflow tract via the mitral orifice; 6) the left ventricular outflow tract to the ascending aorta; 7) the left coronary artery; and 8) the aortic arch and associated branches. Two-dimensional ultrasound images of these cardiac regions are correlated to similar sections in the three-dimensional MR data set to verify anatomical details of the in vivo UBM imaging. Dimensions of the left ventricle and ascending aorta are measured by M-mode. Flow velocities are recorded using Doppler at six representative intracardiac locations: right superior vena cava, tricuspid orifice, main pulmonary artery, pulmonary vein, mitral orifice, and ascending aorta. The methodologies and baseline measurements of inbred mice provide a useful guide for investigators applying the high-frequency ultrasound imaging to mouse cardiac phenotyping.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".