The diagnostic accuracy of truncated cardiovascular MR protocols for detecting non-ischemic cardiomyopathies
Bibliographic record
Abstract
Cardiovascular magnetic resonance imaging is one of the most important diagnostic modalities in the evaluation of cardiomyopathies. However, significant limitations are the complex and time-consuming workflows and the need of contrast agents. The aim of this multi-center retrospective study was to assess workflows and diagnostic value of a short, contrast agent-free cardiac magnetic resonance protocol. 160 patients from Heidelberg, Germany and 119 patients from Montreal, Canada with suspected cardiomyopathy and 20 healthy volunteers have been enrolled. Scans were performed at a 1.5Tesla or 3Tesla scanner in Heidelberg and at a 3Tesla scanner in Montreal. We used single-slice T1 map only. A stepwise analysis of images has been performed. The possible differential diagnosis after each step has been defined. T1-values and color-encoded T1 maps significantly contributed to the differential diagnosis in 54% of the cases (161/299); the final diagnosis has been done without late gadolinium enhancement images in 83% of healthy individuals, in 99% of patients with dilated cardiomyopathy, in 93% of amyloidosis patients, in 94% of patients with hypertrophic cardiomyopathy and in 85% of patients with hypertensive heart disease, respectively. Comparing the scan time with (48 ± 7 min) vs. without contrast agent (23 ± 5 min), significant time saving could be reached by the short protocol. Subgroup analysis showed the most additional diagnostic value of T1 maps in amyloidosis and hypertrophic cardiomyopathy or in confirmation of normal findings. In patients with unclear left ventricular hypertrophy, a short, non-contrast protocol can be used for diagnostic decision-making, if the quality of the T1 map is diagnostic, even if only one slice is available.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.005 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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 teacher head, 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".