Delayed Gadolinium-enhanced MR Imaging of Articular Cartilage: Three-dimensional T1 Mapping with Variable Flip Angles and B<sub>1</sub>Correction
Bibliographic record
Abstract
PURPOSE: To develop and verify the accuracy of a rapid imaging protocol for delayed gadolinium-enhanced magnetic resonance (MR) imaging of cartilage that was based on three-dimensional (3D) spoiled gradient-recalled acquisition in the steady state (SPGR) sequences with variable flip angles (FAs) (VFAs) and where a correction method for B(1) field inhomogeneities was applied. MATERIALS AND METHODS: The institutional research ethics board approved this study. Written informed consent was obtained from all subjects. A B(1) field inhomogeneity correction method was applied to a 3D SPGR pulse sequence with VFAs (repetition time msec/echo time msec, 7.1/3.3; FAs, 2 degrees , 5 degrees , 10 degrees , and 20 degrees ) and was used to perform delayed gadolinium-enhanced MR imaging of cartilage 3D T1 measurements at 1.5 T. The 3D T1 measurements were validated with the reference standard (the results of T1 mapping by using a single-section two-dimensional [2D] inversion-recovery [IR] fast spin-echo [SE] pulse sequence in vitro and in vivo) in six healthy volunteers. RESULTS: T1 values calculated from 3D T1 maps were not significantly different from reference T1 values in vitro (P = .195) and in vivo (P = .52) when a B(1) field inhomogeneity correction method was applied. In vivo T1 mapping of the articular surface of the whole femoropatellar joint, including data acquisition, was performed in approximately 8 minutes of acquisition time at a spatial resolution of 0.55 x 0.55 x 3.00 mm. CONCLUSION: Rapid T1 mapping by using 3D SPGR acquisitions with a VFA approach and a correction for B(1) field inhomogeneities can be used for delayed gadolinium-enhanced MR imaging of cartilage. T1 measurements performed in vitro and in vivo by using this approach are highly accurate when compared with those performed by using standard 2D IR fast SE T1 mapping as a reference.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".