Poster — Thur Eve — 34: Evaluation of 4DCT on the GE lightspeed RT16 using a respiratory motion phantom
Bibliographic record
Abstract
Purpose: This study encompasses several quality assurance tests performed during the commissioning of the 4DCT technique on the GE Lightspeed RT16 CT scanner for SBRT at the Cancer Centre of Southeastern Ontario. The main purpose is to assess geometric position and volumetric delineation accuracy. A limited assessment of the image quality and dose was performed. Methods: The Quasar Respiratory Motion with a modified cylindrical moving insert was used. Clinically relevant breathing motion patterns analyzed were: sinusoidal with amplitudes of 5 and 15 mm, and periods of 3 s and 6 s; and a typical respiratory breathing motion of amplitude of 10 mm and period of 4 s. Results: Couch position errors were ≤ 1mm for maximum inspiration (Ph 0%) and expiration (Ph 50%) phases. errors were greater for mid‐phases, the largest being 8.1 mm (Ph 20%) for the typical respiratory pattern. MIP volume deviations ranged from −0.3 to −3.2 cm3; the greater deviations corresponding to larger amplitudes and shorter periods, where image distortion is also more severe. SUP and INF position error of MIP on coronal views for the lung window and level used in our centre ranged from −0.07 to 1.4 mm and from −0.04 to 1 mm on the SUP and INF direction respectively. The dose from a 4DCT acquisition was 2.8 times higher than in a free breading scan, while the noise was comparable. Conclusions: Although higher doses are obtained, 4DCT is a sufficiently accurate approach that could be used safely to account for breathing motion.
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 | 0.002 | 0.004 |
| 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 | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".