Micro Computed Tomography in Experimental Pulmonary Arterial Hypertension
Bibliographic record
Abstract
ight ventricular (RV) function is now recognized as one of the most important predictors of prognosis in many cardiovascular disease states, including pulmonary hypertension and left heart failure with reduced and persevered ejection fraction.1,2 This is particularly important for patients with pulmonary arterial hypertension (PAH) where RV failure not only drives symptomology but is also the leading cause of death.3,4 In prospective cohorts, the response of the RV to PAHtherapy is a critical prognostic marker with decreasing function portending a worsening prognosis, irrespective of any changes in pulmonary vascular resistance.5 The importance of assessing RV function is thus evident, yet detailed assessment of RV function remains difficult-even with contemporary imaging modalitiesgiven the complex 3-dimensional geometric shape, bellows-like motion, and load dependence of RV function.Small animals are frequently used in the evaluation of experimental PAH and right heart failure; their similarities to humans in cardiovascular physiology, relatively fast reproductive rate, and ease of animal handling make them ideal models for research.However, their small size and fast heart rates can limit in-vivo imaging and phenotyping of the RV.Echocardiography, magnetic resonance imaging (MRI), and microPET are established tools for the evaluation of RV function and physiology in small animal research.Although each imaging modality can be readily adapted from bench to bedside in translational research, the challenges of RV imaging in humans remain evident in small animal models.In clinical practice, powerful noninvasive imaging tools have emerged with capabilities extending beyond global RV assessment to now include regional and even molecular information.MRI is considered the 'gold-standard' for the noninvasive assessment of RV function, volumes, and mass, but imaging costs and accessibility continue to limit widespread clinical application.6 At most institutions, 2-dimensional echocardiography constitutes first-line imaging for patients with suspected right heart failure and pulmonary hypertension; limitations in qualitative assessment of function may be overcome with recent advancements in 3-dimensional echocardiography and speckle tracking/train imaging, yielding more reliable estimates of right ventricular ejection fraction with less operator dependence.7 Computed tomography (CT) has superior spatial resolution but inferior contrast resolution as compared to MRI.Indeed, this is particularly relevant for assessing ventricular volumes in rodents whose heart rates range from 300 to 600 bpm.The use of a contrast agent and fast gantry rotation times may help improve contrast and temporal resolution, respectively, to allow for a detailed assessment of ventricular volumes.8 It is important to note that all of these noninvasive assessments of RV function are dependent on RV preload and afterload and, therefore, do not fully characterize the intricacies of
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 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".