Circumferential strain and strain rates of the descending aorta as novel measures of aortic stiffness and wall mechanics from standard cardiac MRI
Bibliographic record
Abstract
Abstract During standard cardiovascular magnetic resonance (CMR) the horizontal long‐axis cine image (i.e., 4‐chamber) is captured which includes a cross‐section of the descending aorta. The aortic cross‐section can be used to assess aortic stiffness (distensibility; ∆area/pressure) or circumferential strain (percentage vascular deformation). We examined whether descending aortic strain from traditional CMR is sensitive to age‐ and disease‐related (heart failure with preserved ejection fraction; HFpEF) arteriosclerosis. We recruited 83 participants into three groups: (1) 34 young individuals (age: 22 ± 3 years; body mass index (BMI): 24.3 ± 2.8 kg/m 2 ); (2) 19 older individuals (age: 69 ± 5 years; BMI: 26.9 ± 4.7 kg/m 2 ) and (3) 26 patients with HFpEF (age: 69 ± 6 years; BMI: 35.8 ± 6.1 kg/m 2 ). All participants were studied in the same 3 T scanner (Phillips, Achieva). Descending aortic cross‐sectional area and circumferential strain were measured using cvi 42 software. Blood pressure was measured via a brachial oscillometric cuff. Data were compared via ANOVA. All data are reported as means ± standard deviation. Compared to the young group (71 ± 5 mmHg), mean arterial pressure was higher in the older (83 ± 9 mmHg, P < 0.001) and HFpEF groups (86 ± 10 mmHg, P < 0.001). Minimum and maximum aortic areas were greater in the older and HFpEF groups (both, P < 0.01). Peak descending aortic strain (young: 11.4% ± 2.2%; older: 4.8% ± 1.6%; HFpEF 3.8% ± 1.6%) and absolute distension were lower (all, P < 0.02) in the older and HFpEF groups compared to the young. Peak descending aortic strain and strain rates are sensitive to age and may provide a novel assessment of arterial stiffness for longitudinal studies that utilize or have utilized CMR.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".