Myocardial Stiffness and Work Assessment in Pediatrics by Ultrafast Ultrasound Imaging
Bibliographic record
Abstract
Non-invasive assessment of myocardial function in children with congenital or acquired heart disease remains a key clinical challenge due to the complex interplay of structural abnormalities, altered loading conditions, and developmental variability. Although genomic research has enhanced our understanding of the molecular causes of these diseases, the phenotypic expression remains heterogeneous, and the link between genotype and phenotype is still unclear. Conventional echocardiographic parameters, while widely used in clinical practice, are limited for pediatric populations due to variability in cardiac size, volume, and higher heart rates. Myocardial stiffness assessment via ultrafast ultrasound imaging (UUI) offers a promising complementary biomarker of cardiac function and is becoming more accessible in clinical settings. Unlike conventional echocardiographic parameters, myocardial stiffness is an intrinsic property of the tissue and provides information relevant to both diastolic and systolic function of the myocardium.This thesis explores the feasibility and clinical application of myocardial stiffness assessed using shear wave elastography (SWE) by UUI across various physiological and pathological conditions. Chapter II establishes normal reference values for myocardial stiffness in healthy children and young adults, demonstrating that ventricular geometry significantly influences stiffness measurements. Chapter III compares two methods for assessing myocardial stiffness—acoustic radiation force-induced shear waves and natural myocardial waves—highlighting their advantages in temporal resolution and clinical feasibility. Chapter IV applies SWE to both ventricles under physiological and pathological conditions, revealing regional and chamber-specific stiffness adaptations. In Chapter V, a novel framework is introduced to estimate myocardial work by combining stiffness, strain, and wall thickness over the cardiac cycle. This new parameter provides insights into myocardial energy efficiency. Chapter VI applies this methodology to pediatric patients with hypertrophic cardiomyopathy, distinguishing genotype-positive, phenotype-negative individuals from healthy controls and those with overt disease, suggesting the potential of myocardial work as a diagnostic tool. These studies establish SWE by UUI as a promising modality for non-invasive myocardial assessment in pediatric cardiovascular diseases, offering potential improvements in clinical diagnosis, disease monitoring, and early phenotype detection. Future research will focus on clinical validation in larger cohorts, real-time imaging integration, and expansion to ex-vivo heart transplant models and systemic diseases with cardiac involvement.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".