Evaluation of the orbit using contrast-enhanced radial 3D fat-suppressed<i>T</i><sub>1</sub>weighted gradient echo (Radial-VIBE) sequence
Bibliographic record
Abstract
OBJECTIVE: Contrast-enhanced fat-suppressed T1 weighted (T1W) two-dimensional (2D) turbo spin echo (TSE) and magnetization-prepared gradient echo (MPRAGE) sequences with water excitation are routinely obtained to evaluate orbit pathology. However, these sequences can be marred by artefacts. The radial-volume-interpolated breath-hold examination (VIBE) sequence is a motion-robust fat-suppressed T1W sequence which has demonstrated value in paediatric and body imaging. The purpose of our study was to evaluate its role in assessing the orbit and to compare it with routinely acquired sequences. METHODS: A Health Insurance Portability and Accountability Act-compliant and institutional review board-approved retrospective study was performed in 46 patients (age range: 1-81 years) who underwent orbit studies on a 1.5-T MRI system using contrast-enhanced Radial-VIBE, MPRAGE and 2D TSE sequences. Two radiologists blinded to the sequence analysed evaluated multiple parameters of image quality including motion artefact, degree of fat suppression, clarity of choroidal enhancement, intraorbital vessels, extraocular muscles, optic nerves, brain parenchyma and evaluation of pathology. Each parameter was assessed on a 5-point scale, with a higher score indicating the more optimal examination. Mix model analysis of variance and interobserver variability were assessed. RESULTS: Radial-VIBE demonstrated superior quality (p < 0.001) for all orbit parameters when compared with MPRAGE and 2D TSE. Interobserver agreement demonstrated average fair-to-good agreement for degree of motion artefact (0.745), fat suppression (0.678), clarity of choroidal enhancement (0.688), vessels (0.655), extraocular muscles (0.675), optic nerves (0.518), brain parenchyma (0.710) and evaluation of pathology (0.590). CONCLUSION: Radial-VIBE sequence demonstrates superior image quality when evaluating the orbits as compared with conventional MPRAGE and 2D TSE sequences. ADVANCES IN KNOWLEDGE: Radial-VIBE employs unique non-Cartesian k-space sampling in a radial or spoke-wheel fashion which provides superior image quality improving diagnostic capability in the evaluation of the orbits.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| 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) | 0.002 | 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".