P3D-3 Transmission Ultrasound Imaging to Guide Thermal Therapy
Bibliographic record
Abstract
Minimally Invasive Thermal Therapy (MITT) is an effective way to destroy diseased tissue and could replace surgery, chemotherapy or radiation. During MITT, temperatures in the range of 55-95degC are produced locally, resulting in tissue coagulation. A real-time imaging method is required to prevent damage to the nearby normal tissue during heating and to visualize the changes in size and shape of the diseased tissue. It is known that acoustic attenuation is sensitive to both the tissue temperature and the structural changes during thermal therapy. This work examines the potential of ultrasound attenuation imaging during MITT to quantitatively monitor lesion formation dynamics. A transmission ultrasound camera (AcoustoCam, Imperium Inc., Silver Spring, MD) was used to collect acoustic images. The AcoustoCam was initially calibrated using a set of 10 PVCP (Polyvinyl Chloride Plastisol) tissue-mimicking phantoms. The attenuation values were measured by an insertion technique and found to be in the range of 2.18-26.46 dB at a frequency of 4.76 MHz. The 8 bit mean pixel intensity displayed on the screen, and 14 bit mean pixel intensity from the camera's sensor were extracted. A laser fiber (2 cm long cylindrical diffuser, Photoglow, Yarmouth, MA) was used to locally heat albumen temperature- sensitive phantoms and bovine liver tissue. The 8 bit mean pixel intensity as well as temperature were recorded for the heating and cooling periods every two seconds in a region close to the laser fiber. The relationship between the AcoustoCam mean pixel intensity and acoustic attenuation was established. Heating the agar-albumen phantoms and bovine liver tissue increased the local temperature and resulted in an ellipsoidal lesion. In all heating experiments an initial rapid attenuation decrease at low temperatures was followed by a gradual increase in attenuation as temperature increased. During the cooling procedure, attenuation increased rapidly until it reached a steady state, and remained at an attenuation value greater than the value when no thermal lesion was present within the sample. The initial attenuation decrease and the final attenuation increase are reversible and are hypothesized to be a temperature effect, while the gradual change in attenuation at higher temperatures is assumed to be due to protein coagulation. In summary, it was shown that the acoustic camera could monitor in real time the dynamics of lesion formation and that the attenuation profile during heating follows a reproducible pattern.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".