ToF‐SWI: Simultaneous time of flight and fully flow compensated susceptibility weighted imaging
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
PURPOSE: To perform systematic investigations on parameter selection of a dual-echo sequence (ToF-SWI) for combined 3D time-of-flight (ToF) angiography and susceptibility weighted imaging (SWI). MATERIALS AND METHODS: ToF-SWI was implemented on 1.5 T and 3 T MR scanners with complete 3D first-order flow compensation of the second echo. The efficiency of flow compensating the SWI echo was studied based on phantom and in vivo examinations. Arterial and venous contrasts were examined in volunteers as a function of flip angle and compared with additionally acquired single-echo ToF and single-echo SWI data. RESULTS: Complete flow compensation is required to reduce arterial contamination in the SWI part caused by signal voids. A ramped flip angle of 20 degrees depicted arteries best while venous contrast was preserved. Comparing ToF-SWI with single-echo ToF demonstrated arteries with similar quality and delineated all major arteries equally well. Venous delineation was degraded due to lower SNR associated with the thinner slabs used with ToF-SWI compared to single-echo SWI acquisition. CONCLUSION: A dual-echo sequence (ToF-SWI) with full flow compensation of the second echo in a single scan is feasible. This sequence allows simultaneous visualization of intrinsically coregistered arteries and veins without spatial mis-registration of vessels caused by oblique flow and with minimal signal loss in arteries.
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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