Analysis of bi-atrial function using CMR feature tracking and long-axis shortening approaches in patients with diastolic dysfunction and atrial fibrillation
Bibliographic record
Abstract
OBJECTIVES: Atrial function can be assessed using advancing cardiovascular magnetic resonance (CMR) post-processing methods: atrial feature tracking (FT) strain analysis or a long-axis shortening (LAS) technique. This study aimed to first compare the two FT and LAS techniques in healthy individuals and cardiovascular patients and then investigated how left (LA) and right atrial (RA) measurements are related to the severity of diastolic dysfunction or atrial fibrillation. METHODS: Sixty healthy controls and 90 cardiovascular disease patients with coronary artery disease, heart failure, or atrial fibrillation, underwent CMR. LA and RA were analyzed for standard volumetry as well as for myocardial deformation using FT and LAS for the different functional phases (reservoir, conduit, booster). Additionally, ventricular shortening and valve excursion measurements were assessed with the LAS module. RESULTS: The measurements for each of the LA and RA phases were correlated (p < 0.05) between the two approaches, with the highest correlation coefficients occurring in the reservoir phase (LA: r = 0.83, p < 0.01, RA: r = 0.66, p < 0.01). Both methods demonstrated reduced LA (FT: 26 ± 13% vs 48 ± 12%, LAS: 25 ± 11% vs 42 ± 8%, p < 0.01) and RA reservoir function (FT: 28 ± 15% vs 42 ± 15%, LAS: 27 ± 12% vs 42 ± 10%, p < 0.01) in patients compared to controls. Atrial LAS and FT decreased with diastolic dysfunction and atrial fibrillation. This mirrored ventricular dysfunction measurements. CONCLUSION: Similar results were generated for bi-atrial function measurements between two CMR post-processing approaches of FT and LAS. Moreover, these methods allowed for the assessment of incremental deterioration of LA and RA function with increasing left ventricular diastolic dysfunction and atrial fibrillation. A CMR-based analysis of bi-atrial strain or shortening discriminates patients with early-stage diastolic dysfunction prior to the presence of compromised atrial and ventricular ejection fractions that occur with late-stage diastolic dysfunction and atrial fibrillation. KEY POINTS: • Assessing right and left atrial function with CMR feature tracking or long-axis shortening techniques yields similar measurements and could potentially be used interchangeably based on the software capabilities of individual sites. • Atrial deformation and/or long-axis shortening allow for early detection of subtle atrial myopathy in diastolic dysfunction, even when atrial enlargement is not yet apparent. • Using a CMR-based analysis to understand the individual atrial-ventricular interaction in addition to tissue characteristics allows for a comprehensive interrogation of all four heart chambers. In patients, this could add clinically meaningful information and potentially allow for optimal therapies to be chosen to better target the dysfunction.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".