Exercise cardiac magnetic resonance imaging across the lifespan
Bibliographic record
Abstract
Abstract Introduction Exercise cardiac magnetic resonance imaging (cMRI) offers several advantages over contemporary stress imaging approaches, including improved spatial resolution, free of ionizing radiation. With exercise cMRI becoming increasingly popular, more work is needed to better understand the hemodynamic response across the lifespan. Purpose To compare the cMRI response to exercise across the lifespan. Methods To accomplish this purpose, we leveraged data from several ongoing imaging studies in which healthy control participants completed exercise cMRI across at least two discrete workloads, ranging in intensity from mild to moderate. Imaging was performed using either a 1.5T or 3T Phillips MRI scanner. Exercise was performed using an MR compatible ergometer (Cardio Step, Ergospect GmbH, Innsbruck, Austria). Volumetric data were measured from a stack of short axis images spanning the length of the left ventricle from base to apex. Results Exercise cardiac magnetic resonance images were available from 48 participants, ranging in age from 10 to 81 years. On average, end-diastolic volume remained unchanged with exercise (73±14 vs. 75±15 vs. 74±14 mL, rest vs. mild vs moderate, p = 0.107), while end-systolic volume was reduced (27±7 vs. 25±7 vs. 23±6 mL, p = <.001), resulting in a modest increase in stroke volume (46±9 vs. 50±10 vs. 51±10 mL, p = <.001). To evaluate the influence of age, we compared the youngest participants (n = 13, 10-30 yrs) against the oldest participants (n = 18, 65-81yrs). As illustrated in Figure 1, while baseline volumes differed significantly with age, the relative response to exercise was similar between groups. Likewise, to evaluate the influence of sex, we compared male (n = 21) versus female (n = 27) participants. As illustrated in panels D-F, ventricular volumes were greater in men compared with women, but the exercise relative responses were similar. Conclusions Taken together, these data add to a growing body of literature highlighting the feasibility of exercise cardiac magnetic resonance imaging across the lifespan, and begin to define the normative response for future clinical comparison.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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 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".