6-020 Test-retest repeatability of free-breathing real-time cine cardiac MRI in patients with suspected coronary artery disease – A prospective comparative study
Bibliographic record
Abstract
Introduction Cardiovascular magnetic resonance (CMR) is established as the reference standard for cardiac volumetric assessment. Despite its accuracy and robustness, steady-state free precession (SSFP) cine imaging may prove challenging in patients with arrhythmia or in those who cannot perform repeated breath holds. An alternative method is a free-breathing real-time cine sequence. We have previously demonstrated good-excellent agreement of this technique in 202 clinical patients compared to standard SSFP in the same sitting.1 However, the repeatability of real-time cine between studies is unknown. This is pertinent for assessing serial changes in cardiac function following therapeutic interventions such as drug/device therapy or revascularisation. In this study, we investigated the repeatability of real-time cine imaging in patients with suspected coronary artery disease (CAD). Methods In this single-centre, prospective study, consecutive adults with suspected CAD underwent two research 3-Tesla CMR scans on different days. Subjects underwent a free-breathing, multi-slice, electrocardiogram-triggered, retrogated, real-time cine sequence that acquired an entire left ventricular (LV) short-axis stack in approximately 1 minute. Short-axis image dataset pairs were separated and blindly analysed using cvi42 software (Circle Cardiovascular Imaging, Calgary, Canada). Volumetric assessment utilised the cvi42 automated contouring tool with visual inspection and adjustments when necessary. LV end-diastolic volume (EDV), end-systolic volume (ESV), ejection fraction (EF) and LV mass (LVM) were calculated. Paired sample t-tests were used to compare within group differences, and agreement, using intraclass correlation coefficient (ICC) [95% confidence interval] and Bland-Altman plots. Interobserver variability was assessed by an external observer analysing a subset of 15 scans, blinded to previous results. Results Fifty patients (mean age 67 ± 10 years, 40% female) were studied. Baseline characteristics are presented in table 1. The median interval between CMR exams was 2 days [Q1-Q3, 1–3]. Baseline heart rate and systolic blood pressure were similar between studies (p=0.502 and p=0.772 respectively). There were no significant differences in EDV (151.2±31.6ml vs. 154.7±33.4ml, p=0.193), ESV (60.4±22.3ml vs. 62.8±23.2ml, p=0.083), EF (60.7±8.9% vs. 60.1±8.1%, p=0.304) or LVM (97.7±28.4g vs. 95.9±27.9g, p=0.370) between exams. All LV volumetric measurements exhibited good agreement between both real-time scans (EDV: ICC 0.83 [0.71–0.90], ESV: 0.91 [0.84–0.95], EF: 0.87 [0.78–0.92] and LVM: 0.87 [0.79–0.93]) with good interobserver agreement (table 2, figure 1A and B). Conclusions In patients with suspected CAD, real-time cine imaging demonstrates good repeatability for LV volumetric assessment. This accelerated imaging technique shows promise for routine integration within clinical practice, improving the tolerability and efficiency of CMR, whilst providing an accurate serial measure of cardiac function. Reference El Shibly M, Parke K, England R, Budgeon CA, Grafton-Clarke C, Xue H, et al. Comparison of standard breath-hold ssfp cardiac MRI with free-breathing real-time cine imaging among patients with known or suspected cardiac disease. Journal of Cardiovascular Magnetic Resonance. 2024;26.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".