Lymphoscintigraphy of Chylous Anomalies: Chylothorax, Chyloperitoneum, Chyluria, and Lymphangiomatosis—15-Year Experience in a Pediatric Setting and Review of the Literature
Bibliographic record
Abstract
In the pediatric setting, lymphoscintigraphy is used mostly for the evaluation of lymphedema. Only a few cases of chylous anomalies and lymphatic malformations imaged with lymphoscintigraphy have been reported in the literature. The aim of this study was to review the use of lymphoscintigraphy in those pathologies. Methods: All lymphoscintigraphy studies performed for chylous anomalies between 2001 and 2017 in our hospital were retrospectively reviewed. The results were correlated to clinical and radiologic findings. Lymphoscintigraphy consisted of sequential imaging after injection of 3.7–9.25 MBq (100–250 μCi) of 99mTc-filtered sulfur colloid at the level of the feet or hands. Results: Twenty-five studies were performed on 21 patients. Fourteen studies were obtained for the evaluation of chylothorax. Eleven were performed for chyloperitoneum, chyluria, chylopericardium, exudative enteropathy, or lymphangiomatosis. Ten studies were positive for lymphatic leakage, and 1 had uncertain results. After correlation with radiologic findings and follow-up, there were 7 true-negative and 5 false-negative results (previous 67Ga-interfering activity in 1, injection in only the hands in 3, and a low-fat diet in 1). One study became positive after injection in the feet, and another became positive after a switch to a high-fat diet. Conclusion: Lymphoscintigraphy is a useful tool for imaging lymphatic anomalies in children. Suggestions to optimize results include placing the patient on a high-fat diet, withholding octreotide, injecting the 4 extremities, and imaging with SPECT/CT.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".