Myocardial T2 signal enhancement in hypertrophic cardiomyopathy: prevalence, clinical profile and pathologic correlation
Bibliographic record
Abstract
Background Abnormal myocardial T2 signal has been described in a minority of patients with hypertrophic cardiomyopathy (HCM). This phenomenon has been associated with arrhythmic outcomes and, given its more restrictive prevalence versus late gadolinium enhancement (LGE), offers a potentially useful biomarker for risk stratification. To date, postulated mechanisms include active tissue disease or unique collagen species, however, no histopathologic correlation has been reported. In this study, we examine the prevalence of T2 signal abnormalities among patients with HCM and examine for associations with other imaging-based markers of HCM phenotypic expression. Incrementally, we provide comprehensive histopathologic correlation of a patient undergoing cardiac transplantation receiving detailed in-vivo and ex-vivo (explanted heart) imaging. Methods Consecutive patients with HCM underwent a standardized imaging protocol using a 3-Tesla MR system. This was inclusive of T2-weighted imaging using a short-Tau inversion-recovery (STIR) fast spin echo sequence in serial short axis imaging planes both with and without body surface coils. Cine and LGE imaging was performed in identical slice orientations. Blinded analysis of left ventricular (LV) wall thickness, LV volumes, T2 signal enhancement and LGE signal abnormalities were performed using commercial software. In a patient planned for transplantation, a detailed in-vivo and ex-vivo imaging protocol was performed, the latter performing high-resolution isotropic T2-weighted imaging. Tissue was sampled from regions with and without abnormal T2 signal and exposed to comprehensive histologic examination. Results
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".