Daily quality assurance phantom for ultrasound image guided radiation therapy
Bibliographic record
Abstract
A simple phantom was designed, constructed, tested, and clinically implemented for daily quality assurance (QA) of an ultrasound-image-guided radiation therapy (US-IGRT) system, the Restitu Ultrasound system (Resonant Medical, Montreal, QC). The phantom consists of a high signal echogenic background gel surrounding a low signal hypoechoic egg-shaped target. Daily QA checks involve ultrasound imaging of the phantom and segmenting of the embedded target using the automated tools available on the US-IGRT system. This process serves to confirm system hardware and software functions and, in particular, accurate determination of the target position. Experiments were conducted to test the stability of the phantom at room temperature, its tissue-mimicking properties, the reproducibility of target position measurements, and the usefulness of the phantom as a daily QA device. The phantom proved stable at room temperature, exhibited no evidence of bacterial or fungal invasion in 9 months, and showed limited desiccation (resulting in a monthly reduction in ultrasound-measured volume of approximately 0.2 cm3). Furthermore, the phantom was shown to be nearly tissue-mimicking, with speed of sound in the phantom estimated to be 0.8% higher than that assumed by the scanner calibration. The phantom performs well in a clinical setting, owing to its light weight and ease of operation. It provides reproducible measures of target position even with multiple users. At our center, the phantom is being used for daily QA of the US-IGRT system with clinically acceptable tolerances of +/-1 cm3 on target volume and +/-2 mm on target position. For routine daily QA, this phantom is a good alternative to the manufacturer-supplied calibration phantom, and we recommended that that larger phantom be reserved for less frequent, more detailed QA checks and system calibration.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 0.003 |
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".