Tissue thermal conductivity by magnetic resonance thermometry and focused ultrasound heating
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 investigate the combined use of magnetic resonance (MR) temperature imaging and focused ultrasound (FUS) for the noninvasive determination of tissue thermal properties. MATERIALS AND METHODS: Brief, spatial impulses of temperature elevation were created in tissue using a spherical, air-backed transducer operating at 1.68 MHz and measured using MR temperature imaging in a 1.5-Tesla clinical scanner. A novel technique based on thermal washout is applied in an analysis of the acquired MR temperature images to estimate tissue thermal conductivity and perfusion. RESULTS: Numerical simulations and experiments in vitro and in vivo demonstrate that thermal conductivity can be measured to within 10% of the true value with MR thermometry at 1.5 Tesla. With the temperature precision available at 1.5 Tesla, however, robust perfusion estimation is feasible only in highly perfused organs or tumors. CONCLUSION: This study has developed a method for determining tissue thermal properties specific to the patient and organ at the site of interest, and allows repeated application. This capability is relevant in thermal therapy planning of tumor ablation using MR-guided FUS systems.
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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