Feasibility And Results Of Using Tissue Doppler Imaging To Assess Ventricular Function During Exercise
Bibliographic record
Abstract
Tissue Doppler Imaging (TDI) is a relatively new echocardiographic method which allows for the quantitative assessment of myocardial wall motion. Tissue velocities, tissue tracking, strain, and strain-rate have been measured in children at rest, however, limited information exists about what changes occur to TDI indices during exercise. PURPOSE To determine the feasibility of measuring TDI indices and their response to exercise. METHODS Twelve healthy children (9.3 yrs; 8.3–12.2 yrs) were studied. TDI was performed during semi-supine cycle ergometry at rest, peak exercise, immediately post- and 3 minutes post-exercise. The parasternal long axis (posterior wall=PW) and apical 4-chamber (lateral wall=LAT, interventricular septum=IVS, and right ventricular=RV wall) views were used to obtain measurements. Tissue velocities (S', E', A'), tissue tracking (TT), strain (ε), and strain-rate (S, E, A) were measured. TDI analyses were then performed off-line. RESULTS We could consistently measure S', E', A', ε, and TT, however, we could not reliably obtain strain rate measurements at peak exercise in any segments due to a high noise-to-signal ratio. For the PW and LAT wall, S', E', A', and TT were significantly higher at peak exercise when compared to resting conditions; while, in the IVS, only S' and E' were significantly higher (all p < 0.05 *). There were no significant increases in S', E', and A' from rest to peak-exercise in the RV wall (see Table 1). Strain did not increase with exercise in any of the segments we evaluated.TableCONCLUSIONS This preliminary study shows that TDI can be performed during exercise, although strain rate measurements cannot be reliably obtained at peak exercise. At peak exercise, TDI showed increases in tissue velocities (S', E', A') and displacement (TT) in both circumferential (PW) and longitudinal muscle fibers (LAT, IVS, RV). Our results are limited by a small sample size. Further studies are needed to confirm our preliminary results. Evolving technologies will help to overcome some of the technical difficulties of performing TDI during exercise.
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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".