Assessing the image quality of pelvic MR images acquired with a flat couch for radiotherapy treatment planning
Bibliographic record
Abstract
OBJECTIVES: To improve the integration of MRI with radiotherapy treatment planning, our department fabricated a flat couch top for our MR scanner. Setting up using this couch top meant that the patients were physically higher up in the scanner and, posteriorly, a gap was introduced between the patient and radiofrequency coil. METHODS: Phantom measurements were performed to assess the quantitative impact on image quality. A phantom was set up with and without the flat couch insert in place, and measurements of image uniformity and signal to noise were made. To assess clinical impact, six patients with pelvic cancer were recruited and scanned on both couch types. The image quality of pairs of scans was assessed by two consultant radiologists. RESULTS: The use of the flat couch insert led to a drop in image signal to noise of approximately 14%. Uniformity in the anteroposterior direction was affected the most, with little change in right-to-left and feet-to-head directions. All six patients were successfully scanned on the flat couch, although one patient had to be positioned with their arms by their sides. The image quality scores showed no statistically significant change between scans with and without the flat couch in place. CONCLUSION: Although the quantitative performance of the coil is affected by the integration of a flat couch top, there is no discernible deterioration of diagnostic image quality, as assessed by two consultant radiologists. Although the flat couch insert moved patients higher in the bore of the scanner, all patients in the study were successfully scanned.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".