Role of Transcytolemmal Water-Exchange in Magnetic Resonance Measurements of Diffuse Myocardial Fibrosis in Hypertensive Heart Disease
Bibliographic record
Abstract
BACKGROUND: The myocardial extracellular volume fraction (MECVF) has been used to detect diffuse fibrosis. Estimation of MECVF relies on quantification of the T1 relaxation time after contrast enhancement, which can be sensitive to equilibrium transcytolemmal water-exchange. We hypothesized that MECVF, quantified with a parsimonious 2-space water-exchange model, correlates positively with the connective tissue volume fraction in a rodent model of hypertensive heart disease, whereas the widely used analysis based on assuming fast transcytolemmal water-exchange could result in a significant underestimate of MECVF. METHODS AND RESULTS: Nω-nitro-L-arginine-methyl-ester (L-NAME) or placebo was administered to 22 and 15 wild-type mice, respectively. MECVF was measured at baseline and 7-week follow-up by pre- and postcontrast T1 cardiac magnetic resonance imaging at 4.7 T, using a 2-space water-exchange model. Connective tissue volume fraction was quantified, using Masson trichrome stain. L-NAME induced hypertrophy (weight-indexed left-ventricular mass 2.2±0.3 versus 4.1±0.4 μg/g, P<0.001), and increased connective tissue volume fraction (8.6%±1.5 versus 2.58%±0.6, P<0.001), were compared with controls. MECVF was higher in L-NAME-treated animals (0.43±0.09 versus 0.26±0.03, P<0.001), and correlated with connective tissue volume fraction and weight-indexed left-ventricular mass (r=0.842 and r=0.737, respectively, both P<0.0001). Neglecting transcytolemmal water-exchange caused a significant underestimate of MECVF changes. Ten patients with history of hypertension had significantly higher MECVF (0.446±0.063) compared with healthy controls (0.307±0.030, P<0.001). CONCLUSIONS: Cardiac magnetic resonance allowed detection of myocardial extracellular matrix expansion in a mouse model and in patients with a history of hypertension. Accounting for the effects of transcytolemmal water-exchange can result in a substantial difference of MECVF, compared with assuming fast transcytolemmal water-exchange.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".