Delayed three-dimensional inversion recovery-prepared fast low-angle shot for airway imaging in children: More than myocardial fibrosis assessment
Bibliographic record
Abstract
BACKGROUND: To investigate the ability of a delayed respiratory-navigated, electrocardiographically-gated three-dimensional inversion recovery-prepared fast low-angle shot (3D IR FLASH) sequence to evaluate the lower airways in children undergoing routine cardiovascular magnetic resonance (CMR). METHODS: This retrospective study included pediatric patients (0-18 years) who underwent clinical CMR where a delayed 3D IR FLASH sequence was performed between July 2020 and April 2021. The airway image quality and extent of lower airway visibility were graded by two blinded readers using a four-point ordinal scale (0-3). Lower airway anatomical variants and abnormalities were recorded. RESULTS: One hundred and eighty patients were included with a median age of 11.7 (4.6-15.3) years. Fifty-one of 180 (28%) were under general anesthesia. Overall, the median grading of airway image quality was 3 (2-3) and the extent of lower airway visibility was 3 (3-3). Interrater agreement was almost perfect (κ = 0.867 and κ = 0.956, respectively). Image quality correlated with extent of lower airway visibility (r = 0.62, p < 0.01). Delayed 3D IR FLASH was able to characterize the segmental bronchi in 137/180 (76%) and lobar bronchi in 172/180 (96%) of patients. Lower airway abnormalities were identified in 37/180 (21%) of patients and 33/129 (26%) with congenital heart disease (CHD). Identified abnormalities included tracheobronchial branching anomalies in 6/180 (3%), abnormal tracheobronchial situs in 6/180 (3%), and extrinsic vascular compression in 25/180 (14%). CONCLUSION: Delayed 3D IR FLASH has excellent performance for evaluation of the lower airway anatomy and can simultaneously assess for myocardial late gadolinium enhancement. Lower airway abnormalities are not infrequently seen in children undergoing routine CMR for CHD.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".