Abstract 16744: MR Lymphatic Burden in Fontan Correlates With Outcomes
Bibliographic record
Abstract
Introduction: The importance of the lymphatic circulation in Fontan physiology is incompletely understood and may have implications in Fontan ‘failure’. Non-invasive imaging of the lymphatic system with heavily T2-weighted MRI sequences could be a useful tool for patient surveillance and prognostication. We sought to quantify lymphatic burden in Fontan patients and correlate with clinical status. Methods: Consecutive pediatric Fontan patients, <18 years-old with clinical cardiac MRI that had routine acquisition of lymphatic 3D T2 FSE imaging performed from May 2017 to Oct 2019 were included. ‘Lymphatic burden’ was quantified by thresholding-based segmentation of the 3D T2 FSE maximum intensity projection image (fig), generating a surrogate measurement of lymphatic volume, and was performed by 2 independent readers blinded to patient status. Spearman correlation and Mann-Whitney tests were used. Results: There were 48 patients (27 males) with median age at MRI of 12.9 (9.4-14.7) years, age at Fontan of 3.3 (2.9-3.8) years, and time from Fontan at MRI of 9.2 (5.9-10.4) years. Inter-rater agreement for lymphatic burden was excellent (ICC 0.96 [0.94-0.98]). Greater lymphatic burden correlated with hospital length of stay and duration of chest tube drainage post-Fontan (r =0.423, p=0.003 and r=0.419, p=0.003). Median lymphatic burden was greater in patients that had chylous effusions post-Fontan (286 (157-492) ml vs 123 (60-271) ml, p=0.011) and in patients with composite adverse outcome (n=12) defined by heart failure (n=3), transplant assessment (n=2), recurrent effusions (n=8), Fontan thrombus (n=2), and/or PLE (n=6) post-Fontan; (458 (266-2016) ml vs 130 (272-256) ml, p=0.005). Pre-Fontan mean PA pressure and time from Fontan did not correlate with lymphatic burden (r=0.062, p=0.676 and r=0.139, p= 0.343). Conclusion: Quantification of MR lymphatic burden is a reliable tool to assess lymphatic status post-Fontan and is associated with clinical outcomes.
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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 | 0.004 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".