Effect of lateral target motion on image registration accuracy in CT‐guided helical tomotherapy: A phantom study
Bibliographic record
Abstract
Optimisation of imaging modes for kilovoltage CT (kVCT) used for treatment planning and megavoltage CT (MVCT) image guidance used in ungated helical tomotherapy was investigated for laterally moving targets. Computed tomography images of the QUASAR Respiratory Motion Phantom were acquired without target motion and for lateral motion of the target, with 2-cm peak-to-peak amplitude and a period of 4 s. Reference kVCT images were obtained using a 16-slice CT scanner in standard fast helical CT mode, untagged average CT mode and various post-processed 4D-CT modes (0% phase, average and maximum intensity projection). Three sets of MVCT images with different inter-slice spacings of were obtained on a Hi-Art tomotherapy system with the phantom displaced by a known offset position. Eight radiation therapists performed co-registration of MVCT obtained with 2-, 4- and 6-mm slice spacing and kVCT studies independently for all 15 CT imaging combinations. In the investigated case, the untagged average kVCT and 4-mm slice spacing for the MVCT yielded more accurate registration in the transverse plane. The average residual uncertainty of this combination of imaging procedures was 0.61 +/- 0.16 mm in the longitudinal direction, 0.45 +/- 0.14 mm in the anterior-posterior direction and insignificant in the lateral direction. Manual registration of MVCT-kVCT study pairs is necessary to account for a target in significant lateral motion with respect to bony structures.
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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 | 0.002 | 0.000 |
| 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 | 0.000 | 0.001 |
| 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".