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Bibliographic record
Abstract
The clinical translation of MRI-guided cardiovascular catheterization has been limited by the unavailability of devices that are both visible and safe under MRI. In par-ticular, rigid metallic guidewires are essential for most catheterization procedures and are at risk of heating during MR imaging [1]. Here we present an MRI method that simultaneously improves the visualization of commercially available nitinol guidewires and mini-mizes RF induced heating. Methods RF-efficient gradient echo spiral imaging was chosen to minimize heating (8 interleaves, TE/TR = 0.86/10ms, flip angle = 10°). Through-slice dephasing generated a positive contrast “device image ” [2], exploiting local field inhomo-geneity such that the metallic guidewire appears hyperin-tense with background signal suppressed. An anatomical image and a device image were interleaved in alternating frames. Image processing (signal thresholding and selec-tion of elongated structures) was performed on the device image to isolate the guidewire signal from other sources of field inhomogeneity. Imaging was performed on a 1.5T MRI scanner (Aera, Siemens, Erlangen, Germany). MRI-guided left heart catheterization was performed in a pig using a 0.035 ” com-mercially available nitinol guidewire (Nitrex, Covidien, Ply-mouth, MN). The RF induced temperature rise at the tip of an insulated nitinol rod during MR imaging was mea-sured in the ASTM 2182 gel phantom using a fiberoptic temperature probe (OpSense, Quebec, Canada). Results A pair of anatomical and device images were generated with a temporal resolution of 160ms (80ms per image), or 6.25 frames/s. Image processing occurred in real-time and a color overlay of the device on the anatomy was dis-played to the operator for guidance during catheterization
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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