Cardiovascular Magnetic Resonance Imaging of Atrial Fibrillation: An Advanced Hemodynamic Perspective
Bibliographic record
Abstract
Atrial fibrillation (AF) patients can be referred to cardiac magnetic resonance imaging (MRI) for an accurate assessment of cardiac function and left atrial structure. Cardiac MRI is the gold standard for the quantification of heart volumes and allows the noninvasive tissue characterization of the heart. In addition, advanced flow assessment can be achieved using 4D-flow MRI to elegantly depict the hemodynamic efficiency of the left atrium (LA) and left ventricle (LV) throughout the cardiac cycle. Patients with AF may have occult LV disease and thrombus formation. Biomarkers based on 4D-flow MRI may unmask the presence of LA/LV disease by quantifying 3D stasis, flow distribution, and vortex formation. These biomarkers have proved to characterize AF stages, to complement standard risk scores, and bring new insights on heart hemodynamic performance. This chapter aims to present a standard cardiac MRI protocol for atrial fibrillation and the innovative usefulness of advanced flow imaging in clinical settings.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.014 | 0.011 |
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".