SU‐DD‐A3‐06: The Impact of Probe Angle and Tissue Elastic Module in Ultrasound‐Guided Prostate IMRT
Bibliographic record
Abstract
Purpose: An integrated ultrasound and CT‐Sim system can be used to assist the daily setup of prostate IMRT patient. The purpose of this study is to investigate the influence of probe angle and the tissue elastic module on the displacement of prostate during ultrasound localization using Finite Element Method (FEM). Method and Materials: An ultrasound localization system (Resonant Medical System, Montreal, Canada) integrated with a CT‐Sim was used to obtain a full set of 3‐D ultrasound (US)‐CT images. The patients' anatomical structures, such bone, bladder, and prostate, were contoured on the CT images by radiation oncologists. The ultrasound probe was positioned at 1cm inferior to bladder superior boundary. A 3D finite element model was generated for each of the patient. The corresponding displacement of prostate during ultrasound localization was calculated by FEM software (Ansys). Results: Under normal tissue elastic module (body (E=15kPa), bone (E=10GPa), bladder wall (E=300kPa), prostate (E=100kPa), and probe (E=3GPa)), when the angle of ultrasound probe increased from 10 to 60 degree to vertical plane with 2cm compression of ultrasound probe, the total displacement of prostate was 0.46∼0.6mm (0.43∼0.54mm inferior, 0.15∼0.25mm posterior). When the elastic module of bladder wall changed from 50kPa to 1MPa with the probe angle of 45 degree, the total displacement of prostate was increased from 0.26mm to 0.76mm (0.23 to 0.68mm inferior, 0.1 to 0.32mm posterior). There was almost no left and right displacement during compression. Conclusion: For the displacement of prostate, there was no significant dependent on the probe angle and limited dependent on the tissue elastic module. With proper controlled compression, the total prostate displacement can be limited within 2mm. This displacement can be corrected by FEM calculation.
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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) | 0.000 | 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 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".