Late Gadolinium Enhancement of the right ventricular myocardium: Is it really different from the left ?
Bibliographic record
Abstract
It has been suggested that, in late gadolinium enhancement, the signal of right ventricular myocardium is nulled at a shorter inversion time than the left. While we initially made the same observation, we believe that the difference is not real, but results from artifacts. We present 7 cases as well as computer simulations to describe the nature of these artifacts and explain how they can create the impression of different inversion times for the right and left ventricle. At inversion times that are shorter than ideal for the myocardium a black rim can be seen at the border of the myocardium with blood on the inside and with fat on the outside. This is most likely a partial volume effect. The thin myocardium of the right ventricle is sandwiched between these black rims and, at a low spatial resolution, is no longer visible. In this case, the adjacent black rims may then be misinterpreted as myocardium. While black rims also occur on the left side, the myocardium is thicker and remains discernable as a separate layer. As a consequence, the optimal inversion time for the right ventricle only appears different from that for the left. In fact, in the presence of hypertrophy of the right ventricle or during systolic wall thickening we did not find a difference in inversion times between the left and right ventricle. We conclude that sufficient spatial resolution is important for adequate late gadolinium enhancement of the right ventricle.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".