Quantitative assessment of myocardial T2 relaxation times in cardiac amyloidosis
Bibliographic record
Abstract
PURPOSE: To evaluate cardiac MRI (CMR) in the diagnosis of cardiac amyloidosis by comparing the T2 relaxation times of left ventricular myocardium in a pilot patient group to a normal range established in healthy controls. MATERIALS AND METHODS: Forty-nine patients with suspected amyloidosis-related cardiomyopathy underwent comprehensive CMR examination, which included assessment of myocardial T2 relaxation times, ventricular function, resting myocardial perfusion, and late gadolinium enhancement (LGE) imaging. T2-weighted basal, mid, and apical left ventricular slices were acquired in each patient using a multislice T2 magnetization preparation spiral sequence. Slice averaged T2 relaxation times were subsequently calculated offline and compared to the previously established normal range. RESULTS: Twelve of the 49 patients were confirmed to have cardiac amyloidosis by biopsy. There was no difference in mean T2 relaxation times between the amyloid cases and normal controls (51.3 +/- 8.1 vs. 52.1 +/- 3.1 msec, P = 0.63). Eleven of the 12 amyloid patients had abnormal findings by CMR, eight having LGE involving either ventricles or atria and four demonstrating resting subendocardial perfusion defects. CONCLUSION: CMR is a potentially valuable tool in the diagnosis of cardiac amyloidosis. However, calculation of myocardial T2 relaxation times does not appear useful in distinguishing areas of amyloid deposition from normal myocardium.
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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 | 0.003 |
| 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".