Development of custom RF coils for use in a small animal platform for magnetic resonance-guided focused ultrasound hyperthermia compatible with a clinical MRI scanner
Bibliographic record
Abstract
Three different magnetic resonance imaging (MRI) coils were developed and assessed for use with an experimental platform designed to generate hyperthermia in mice using magnetic resonance-guided focused ultrasound (MRgFUS). An ergonomic animal treatment bed was integrated with MRI coils. Three different coil designs optimized for small targets were tested, and performance in targeting and conducting accurate temperature imaging was evaluated. Two transmit/receive surface coils of different diameters (4 and 7 cm) and a transmit-only/receive-only (TORO) coil were used. A software platform was developed to provide real-time targeting and temperature maps and to deliver controlled ultrasound exposure. MR thermometry was conducted on different targets, including fresh chicken breasts and mouse cadavers. Multiple experiments were performed in which tissues were targeted with high reproducibility. The TORO coil was the most resilient to temperature drift, resulting in an increase in the calculated temperature of 0.29 ± 0.12 °C, compared to 1.27 ± 0.13 °C and 0.47 ± 0.04 °C for the medium and small coils, respectively. Controlled closed-loop hyperthermia exposure was successfully performed with all three coils. Considering all assessments, the TORO coil exhibited the best overall performance for thermometry acquisition when accounting for stability, precision, temperature spread and resilience to temperature drift. B1 maps of the three coils confirmed that the TORO coil exhibited the most homogeneous B1 field, which explained the improved thermometry performance. The use of coils specifically designed for small targets within the proposed experimental platform allowed accurate thermometry during hyperthermia.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".