Double delay alternating with nutation for tailored excitation facilitates banding‐free isotropic high‐resolution intracranial vessel wall imaging
Bibliographic record
Abstract
The purpose of this study was to evaluate the use of a double delay alternating with nutation for tailored excitation (D-DANTE)-prepared sequence for banding-free isotropic high-resolution intracranial vessel wall imaging (IC-VWI) and to compare its performance with regular DANTE in terms of signal-to-noise ratio (SNR) as well as cerebrospinal fluid (CSF) and blood suppression efficiency. To this end, a D-DANTE-prepared 3D turbo spin echo sequence was implemented by interleaving two separate DANTE pulse trains with different RF phase-cycling schemes, but keeping all other DANTE parameters unchanged, including the total number of pulses and total preparation time. This achieved a reduction of the banding distance compared with regular DANTE enabling banding-free imaging up to higher resolutions. Bloch simulations assuming static vessel wall and flowing CSF spins were performed to compare DANTE and D-DANTE in terms of SNR and vessel wall/CSF contrast. Similar image quality measures were assessed from measurements on 13 healthy middle-aged volunteers. Both simulation and in vivo results showed that D-DANTE had only slightly lower vessel wall/CSF and vessel wall/blood contrast-to-noise ratio values compared with regular DANTE, which originated from a 10%-15% reduction in vessel wall SNR but not from reduced CSF or blood suppression efficiency. As anticipated, IC-VWI acquisitions showed that D-DANTE can successfully remove banding artifacts compared with regular DANTE with equal scan time or DANTE preparation length. Moreover, application was demonstrated in a patient with an intracranial aneurysm, indicating improved robustness to slow flow artifacts compared with clinically available 3D turbo spin echo scans. In conclusion, D-DANTE provides banding artifact-free IC-VWI up to higher isotropic resolutions compared with regular DANTE. This allows for a more flexible choice of DANTE preparation parameters in high-resolution IC-VWI protocols.
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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".