Active breathing control in combination with ultrasound imaging: A feasibility study of image guidance in stereotactic body radiation therapy of liver lesions
Bibliographic record
Abstract
Purpose Accurate tumor positioning in stereotactic body radiation therapy (SBRT) of liver lesions is often hampered by motion and setup errors. We combined 3-dimensional ultrasound imaging (3DUS) and active breathing control (ABC) as an image guidance tool. Methods and Materials We tested 3DUS image guidance in the SBRT treatment of liver lesions for 11 patients with 88 treatment fractions. In 5 patients, 3DUS imaging was combined with ABC. The uncertainties of US scanning and US image segmentation in liver lesions were determined with and without ABC. Results In free breathing, the intraobserver variations were 1.4 mm in left-right (L-R), 1.6 mm in superior-inferior (S-I), and 1.3 mm anterior-posterior (A-P). and the interobserver variations were 1.6 mm (L-R), 2.8 mm (S-I), and 1.2 mm (A-P). The combined uncertainty of US scanning and matching (inter- and intraobserver) was 4 mm (1 SD). The combined uncertainty when ABC was used reduced by 1.7 mm in the S-I direction. For the L-R and A-P directions, no significant difference was observed. Conclusion 3DUS imaging for IGRT of liver lesions is feasible, although using anatomic surrogates in the close vicinity of the lesion may be needed. ABC-based breath-hold in midventilation during 3DUS imaging can reduce the uncertainty of US-based 3D table shift correction.
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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 | 0.000 | 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 | 0.000 |
| 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".