T2-mapping and T2*-mapping for detection of intramyocardial haemorrhage: a head-to-head comparison with T2-weighted imaging
Bibliographic record
Abstract
A variety of CMR methods for detecting intramyocardial haemorrhage (IMH) has been proposed, including T2-weighted imaging (T2w), T2-mapping and T2* mapping. IMH detected by T2w imaging is associated with adverse LV remodelling and adverse outcome post acute myocardial infarction (MI). We compare the sensitivity, specificity, CNR and SNR of the three IMH imaging techniques. Twenty patients underwent CMR at 3T (Achieva TX system, Philips Healthcare, Best, The Netherlands) within 3 days following reperfused ST-elevation MI. Black blood, cine, T2w, T2-mapping, T2*-mapping and LGE imaging (0.1mmol/kg gadolinium DTPA) were performed in identical short axis locations using the ‘3 of 5' approach. Data were evaluated offline using commercial software (cvi42 v4.1.5, Circle Cardiovascular Imaging Inc., Calgary, Canada). On the LGE images showing the largest infarct volume, infarct size was determined by using a semi-automated histogram-based thresholding method. This slice was evaluated for visual presence of IMH by the three methods. Signal intensity (SI) and respective standard deviation of SI (SD) were measured for the infarcted myocardium, remote myocardium and any IMH (if present). SNR was computed for each using the formula=0.655((SI)/(SD)). CNR was determined comparing contrast-to-noise of infarcted myocardium to IMH (SNR i -SNR IMH ). Of the twenty patients, 55% (n=11) had IMH on T2w-imaging. The mean (±standard deviation) SNR and CNR values are listed in Table 1 . The visual assessment of T2w imaging correlated strongly to T2-maps (r=0.69;p=0.001) and to the T2*-maps (r=0.60; p=0.005). The SNR for IMH and infarct zone were significantly different for only T2w imaging (Figure 1 ). Quantitative CNR for T2w imaging correlated strongly to visual assessment of all three imaging modalities (T2w- r=0.650; p=0.002, T2-map- r=0.454; p=0.04, T2*-map- r=0.603;p=0.005). The CNR for T2-maps and T2*-maps did not show similar correlation to the visual assessment. Box-plot of mean ± standard deviation (SD) of Signal-to-Noise-Ratio (SNR) for IMH and Infarct using the three imaging techniques. Quantitative and qualitative T2w-imaging assessment for IMH is superior to T2-mapping and T2*mapping.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".