SU‐G‐IeP1‐09: MRI Evaluation of a Direction‐Modulated Brachytherapy (DMBT) Tandem Applicator for Cervical Cancer On 3T
Bibliographic record
Abstract
Purpose: To assess image quality and artifact extent of a novel direction modulated brachytherapy (DMBT) tandem applicator on a 3T MRI using various clinical imaging sequences. Methods: The tandem applicator is composed of a tungsten alloy with 6 peripheral grooves covered with a PEEK tip. An MR‐compatible phantom with similar dimensions to the female pelvis was manufactured. To visually assess the spatial shift of the applicator's tip, a mountable radial‐fiducial with 4 plastic rods, each of 3mm diameter, was designed to tightly fit on the applicator. The rods are separated by 16 mm and mounted at 90‐degree relative to one another. The pelvis phantom was filled with a solution of MnCl2 to mimic T2 relaxation time of the cervix (60‐80 ms at 3T).Imaging was performed on a 3T Philips Achieva using a 16‐channel Torso coil array. Four MR sequences were tested: T2‐weighted fast spin‐echo (T2w‐FSE), proton density weighted FSE (PDw‐FSE), T1‐weighted FSE (T1w‐FSE) and T1 weighted spoiled gradient echo (T1w‐GE). The spatial resolution was kept the same between all sequences: 0.6 × 0.6 × 3 mm3 with no slice gaps. Para‐sagittal images were acquired with the applicator fixed at a 30‐degree angle anterior to the B0‐ field to mimic clinical settings. Results: Minimal artifacts were observed on T2w‐FSE, PDw‐FSE and T1‐FSE, while significant artifacts were seen on T1w‐GE images. Artifacts induced in all 3 FSE sequences did not hinder accurate localisation of the tip and the applicator boundaries. The drift of the applicator's centreline from the radial fiducials was measured and found to be < 1 mm for the 3 FSE sequences. Conclusion: The tungsten–based DMBT applicator can be potentially used on 3T with various clinical sequences without inducing significant artifacts. Further validation on patients as well as the evaluation of relative SNR among the different sequences is required.
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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 | 0.000 | 0.001 |
| 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".