Pediatric whole-body magnetic resonance imaging: Intra-individual comparison of technical quality, artifacts, and fixed structure visibility at 1.5 and 3 T
Bibliographic record
Abstract
PURPOSE: To compare whole-body magnetic resonance imaging (WBMRI) performed at 1.5 and 3 T for technical quality, artifacts, and visibility of selected fixed structures. PATIENTS AND METHODS: 21 children who had WBMRI at both 1.5 and 3 T scanners within a relatively short interval (3-13 months; average-8.6 months) were included. The images were objectively compared with scores from 4 to 1 for five parameters including severity of artifacts; visibility of liver, vertebral column, and marrow in legs; and overall image quality. Inter-observer agreement was calculated using Kendall's coefficient of Concordance (W) and scores were compared using Signed Rank test. RESULTS: There was substantial inter-observer agreement for all five categories at both field strengths. The difference between averages of mean scores of all five parameters for two field strengths was statistically significant (P < 0.05), indicating less artifact, better fixed structure visibility, and overall image quality at 1.5 T as compared to 3 T. However, scores at 3 T were also rated within a good range (around 3) indicating its feasibility for WBMRI in children. CONCLUSION: WBMRI at 1.5 T has significantly better image quality, fixed structure visibility, and fewer artifacts, as compared to WBMRI at 3 T in children. This difference is unlikely to significantly affect detection of pathology on 3 T WBMRI as the image quality score at 3 T was also within good range.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".