Diagnosis of pericardial cysts using diffusion weighted magnetic resonance imaging: A case series
Bibliographic record
Abstract
INTRODUCTION: Congenital pericardial cysts are benign lesions that arise from the pericardium during embryonic development. The diagnosis is based on typical imaging features, but atypical locations and signal magnetic resonance imaging sequences make it difficult to exclude other lesions. Diffusion-weighted magnetic resonance imaging is a novel method that can be used to differentiate tissues based on their restriction to proton diffusion. Its use in differentiating pericardial cysts from other pericardial lesions has not yet been described. CASE PRESENTATION: We present three cases (a 51-year-old Caucasian woman, a 66-year-old Caucasian woman and a 77-year-old Caucasian woman) with pericardial cysts evaluated with diffusion-weighted imaging using cardiac magnetic resonance imaging. Each lesion demonstrated a high apparent diffusion coefficient similar to that of free water. CONCLUSION: This case series is the first attempt to investigate the utility of diffusion-weighted magnetic resonance imaging in the assessment of pericardial cysts. Diffusion-weighted imaging may be a useful noninvasive diagnostic tool for pericardial cysts when conventional imaging findings are inconclusive.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.002 |
| 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".