Intracranial arterial wall imaging using three‐dimensional high isotropic resolution black blood MRI at 3.0 Tesla
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Bibliographic record
Abstract
PURPOSE: To develop a high isotropic-resolution sequence to evaluate intracranial vessels at 3.0 Tesla (T). MATERIALS AND METHODS: Thirteen healthy volunteers and 4 patients with intracranial stenosis were imaged at 3.0T using 0.5-mm isotropic-resolution three-dimensional (3D) Volumetric ISotropic TSE Acquisition (VISTA; TSE, turbo spin echo), with conventional 2D-TSE for comparison. VISTA was repeated for 6 volunteers and 4 patients at 0.4-mm isotropic-resolution to explore the trade-off between SNR and voxel volume. Wall signal-to-noise-ratio (SNR(wall) ), wall-lumen contrast-to-noise-ratio (CNR(wall-lumen) ), lumen area (LA), wall area (WA), mean wall thickness (MWT), and maximum wall thickness (maxWT) were compared between 3D-VISTA and 2D-TSE sequences, as well as 3D images acquired at both resolutions. Reliability was assessed by intraclass correlations (ICC). RESULTS: Compared with 2D-TSE measurements, 3D-VISTA provided 58% and 74% improvement in SNR(wall) and CNR(wall-lumen) , respectively. LA, WA, MWT and maxWT from 3D and 2D techniques highly correlated (ICCs of 0.96, 0.95, 0.96, and 0.91, respectively). CNR(wall-lumen) using 0.4-mm resolution VISTA decreased by 27%, compared with 0.5-mm VISTA but with reduced partial-volume-based overestimation of wall thickness. Reliability for 3D measurements was good to excellent. CONCLUSION: The 3D-VISTA provides SNR-efficient, highly reliable measurements of intracranial vessels at high isotropic-resolution, enabling broad coverage in a clinically acceptable time.
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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 it