TU‐A‐9A‐04: Development of a Thermally Stable Phantom for Photoacoustic and Magnetic Resonance Temperature Imaging
Bibliographic record
Abstract
Purpose: Photoacoustic‐ultrasonic (PAUS) imaging, which utilizes an ultrasound transducer to provide co‐registered photoacoustic and pulse‐echo ultrasound images, is capable of measuring temperature non‐invasively while simultaneously providing anatomical images. The sub‐millimeter resolution and centimeter‐order penetration depths achievable with PAUS imaging have the potential to deliver active monitoring of both a targeted tumor microenvironment and nearby healthy tissue during thermal ablation. These characteristics make PAUS imaging a promising new technique for guidance and monitoring during photothermal ablations of solid tumors. In order to assess the potential clinical role of PAUS imaging, the technique was validated against the clinically accepted magnetic resonance thermal imaging approach (MRTI). Methods: To facilitate co‐registration between modalities, the phantom had inclusions of gold nanoshells encapsulating super‐paramagnetic iron oxide (SPIO) particles, where gold enhances the PA signal and SPIOs provide negative contrast on MRI. Several phantom designs were assessed for resilience to heating. PA images were acquired on a Vevo LAZR (FUJIFILM VisualSonics Inc., Toronto, Ontario) PAultrasound small‐animal imaging system (21MHz) operating at 710nm. MRTI experiments were performed using a 6‐channel flex coil (GE Healthcare, Waukesha, WI) on a 3T MRI scanner (Discovery MR750, GE Healthcare, Waukesha, WI) using a fast multi gradient echo acquisition (16 echoes, 128×128 acquisition matrix, 25.6×25.6cm field of view, 3mm slice thickness, 60ms TR, 20° flip angle, 2.9ms minimum TE and 1.6ms echo spacing). The accuracy and spatio‐temporal resolution of PA thermography was cross‐validated with both MRTI and a fluoroptic temperature sensor (LumaSense Technologies, Santa Clara, CA) in the custom‐designed phantom. Results: A thermally stable, dual‐modality phantom was created for cross‐validation of photoacoustic thermography and MRTI. Axial and lateral resolutions of PA images were sub‐millimeter with a temporal resolution of 0.2s, which will accommodate precise real‐time guidance and monitoring. Conclusion: These results indicate that a PA thermography technique offers tremendous promise for real‐time thermal monitoring of ablative therapy. Funding support provided by Cancer Prevention Research Institute of Texas and Julia Jones Matthews family. No disclosures or conflicts of interest.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".