SU‐GG‐J‐100: Guidelines for Optimizing Image Quality and Minimizing Technique‐Specific Uncertainties in 3D Ultrasound Imaging for Online Image Guided Radiotherapy of the Prostate
Bibliographic record
Abstract
Purpose: To provide guidelines for improving image quality of ultrasound scans and to suggest specific techniques for optimal visualization and contouring of the prostate gland. Method and Materials: The Clarity™ 3D U/S‐IGRT system (Resonant Medical Inc., Montreal, Canada) is currently in clinical use as the standard practice at our institution for daily imaging of the prostate gland. The CT and U/S images are fused in the Clarity Workstation where the positioning reference volume is developed as the reference volume relative to which daily shifts are made. Primary factors in ensuring high quality U/S scans are the patient bladder filling and the therapist scanning technique. Therapists were asked to try four different scan techniques on the same patient at the same treatment session: angled scans and more vertical scans, each scan being acquired initially with no U/S probe pressure and then repeated with a firm and steady probe pressure. Inter‐user variability was assessed by evaluating scan techniques of different therapists and associating these techniques with the couch shifts. Results: A moderately full bladder allows for proper propagation of the ultrasonic signal thereby facilitating visualization of the prostate gland at the prostate‐bladder/rectum interfaces. To minimize variability in bladder filling each patient is given a set of written instructions at the time of consult, which stresses the importance of a proper bladder filling. Inter‐user variability was found to be significant (up to 8 mm) in some instances and was related primarily to the scanning technique. A recommended scanning technique is to use steady pressure on the U/S probe while scanning through bladder at an angle to avoid the shadow zone caused by the pubic bone. Conclusion: Patient bladder filling and the therapist scanning technique were found to be important factors in optimizing image quality for IGRT‐based U/S imaging of the prostate.
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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 | 0.021 | 0.032 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.008 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.006 | 0.002 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.006 |
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".