Creating Healthy Age-Sex-matched Left Ventricular Velocity Atlases and Extracting Energy-based Hemodynamics Using 4D-flow MRI
Bibliographic record
Abstract
This study proposes a method to create a 4D-flow magnetic resonance imaging (4D-flow MRI) based left ventricular (LV) velocity atlas and extract hemodynamic parameters at the peak-systolic phase. Twenty-seven healthy controls without any cardiac disease (44% female) underwent a consistent standardized imaging protocol using 3T/MRI scanners. Phase-contrast MR angiography and an average heart were created. Contour-based segmentation was done for 30 phases covering the entire LV. For each age-and-sex-matched group (female/male and 20-40/41-61 years), an averaged 3D velocity field and a shared geometry were created by maximizing the overlap of all LVs non-rigidly utilizing affine registration. Normal velocity atlases were created by interpolating the absolute velocities (m/s) to the voxels of the shared geometry and averaged over all cases in the respective groups. Later, viscous energy dissipation and kinetic energy (VED, KE, mJ) were quantified. The average mean squared loss and dice coefficient were 14.45±3.1% and 0.84. VEDMeanand KEMeanwere reduced among the older cases (Female: KE=5.26±5.9 vs. 3.3±3.68, VED=0.19±1.94 vs. 0.05±0.3; Male: KE=4.58±4.21 vs. 2.09±2.41, VED=0.07±0.42 vs. 0.03±0.26; mJ). Older males exhibited a lower VelocityMeanthan older females and younger males (t=2.62, 2.52; p=0.02, 0.02; 23.81%, 38.46%; respectively). They also showed 36.67% lower KEMeanthan older females (t=2.37, p=0.05). Age was negatively correlated to KE (Females: r=-0.723, p=0.008; Males: r=-0.536, p=0.04), VED (Females: r=-0.786, p=0.002; Males: r=-0.748, p=0.001), and velocity (Females: r=-0.722, p=0.008; Males: r=-0.771, p<0.001). This study demonstrates the feasibility of velocity atlases for extracting a range of age-and-sex-matched energetics and highlights altered hemodynamics associated with aging.Clinical Relevance— This study demonstrates the utility of 4D-flow MRI-based velocity atlases for age-and-sex-matched hemodynamic assessment, offering a novel tool for identifying pathological conditions and refining cardiovascular diagnosis.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".