MRI Monitoring Strategies for Cardiac Repair Therapies in Myocardial Infarction
Bibliographic record
Abstract
Myocardial infarction (MI) is the most common cause of heart failure (HF). Cardiac regenerative therapies, including injection of pluripotent stem cell-derived cardiomyocytes (PSC-CM), offer a promising alternative to restore heart function. Imaging biomarkers that can resolve graft local structure and function of the heart may be useful in guiding and evaluating such therapies. However, their translation to clinical practice requires rigorous evaluation of graft-host integration, therapeutic efficacy, and impact on myocardial structure and function. This dissertation develops and employs magnetic resonance imaging (MRI) to comprehensively assess the structural and functional outcomes of PSC-CM therapy in a guinea pig model of MI.The first aim of this work was to characterize the microstructural properties of immature and mature PSC-CM grafts using diffusion tensor imaging (DTI). Mature PSC-CMs exhibited a similar fractional anisotropy and mean diffusivity to that of healthy tissue. These findings showcase the utility of DTI to characterize exogenous PSC-CMs in an ex vivo guinea pig model of MI. The second aim focused on evaluating the longitudinal functional effects of PSC-CM therapy using cine MRI and late gadolinium enhancement (LGE). PSC-CM-treated guinea pig hearts demonstrated attenuated LV remodeling, preserved end-systolic and end-diastolic volumes, and significantly improved regional wall thickening in scar+graft regions compared to vehicle-treated controls. While ejection fraction trends were positive, structural and functional stabilization highlighted the therapeutic potential of PSC-CMs in mitigating post-MI remodeling. The third aim integrated DTI and cine MRI to establish structure-function correlations between PSC-CM graft characteristics and cardiac recovery. Lower mean diffusivity in graft regions correlated with enhanced wall thickening, while greater helix angle transmurality in remote myocardium was associated with reduced LV dilation. These results reveal the mechanistic role of PSC-CM structural integration in improving cardiac function and demonstrate the utility of imaging biomarkers for monitoring regenerative therapies. This work establishes MRI as a platform for evaluating the efficacy of regenerative therapies, providing insights into the structural and functional mechanisms underlying PSC-CM therapy. This dissertation paves the way for future studies using MRI for preclinical applications of cardiac regeneration.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".