MR cholangiopancreatography at 3.0 T in children: diagnostic quality and ability in assessment of common paediatric pancreatobiliary pathology
Bibliographic record
Abstract
OBJECTIVE: To assess the diagnostic quality of MR cholangiopancreatography (MRCP) at 3.0 T in children and to assess its diagnostic ability in answering the clinical query. Also, to determine the frequency of artefacts and anatomic variations in ductal anatomy. METHODS: Consecutive MRCPs performed in children using a 3-T scanner were retrospectively reviewed to note indications, findings, imaging diagnosis, normal variants, quality and artefacts. Analysis was performed based on the final diagnosis assigned by pathology or the combination of clinical, laboratory, imaging features and follow-up to determine whether it was possible to answer the clinical query by MRCP findings. RESULTS: There were 82 MRCPs performed at 3.0 T on 77 children. 42/82 (51%) MRCPs were of good quality, 35/82 (43%) MRCPs were suboptimal but diagnostic and the remaining 5/82 (6%) MRCPs were non-diagnostic. MRCP answered the clinical query in 61/82 (74%) cases; however, it did not answer the clinical query in 11/82 (14%) cases and was equivocal in 10/82 (12%) cases. There was significant association between the quality of MRCP and the ability of MRCP to answer the clinical query (p<0.0001). 64/82 (78%) MRCP examinations had at least 1 artefact. Variation in the bile duct anatomy was seen in 27/77 (35%) children. CONCLUSION: MRCP performed at 3.0 T is of diagnostic quality in most cases and is able to provide an answer to the clinical query in the majority of cases. ADVANCES IN KNOWLEDGE: 3-T MRCP is feasible and useful in the assessment of pancreatobiliary abnormalities in children.
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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 | 0.004 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".