A gated deep inspiration breath‐hold radiation therapy technique using a linear position transducer
Bibliographic record
Abstract
For patients with thoracic and abdominal lesions, respiration-induced internal organ motion and deformations during radiation therapy are limiting factors for the administration of high radiation dose. To increase the dose to the tumor and to reduce margins, tumor movement during treatment must be minimized. Currently, several types of breath-synchronized systems are in use. These systems include respiratory gating, deep inspiration breath-hold, active breathing control, and voluntary breath-hold. We used a linear position transducer (LPT) to monitor changes in a patient's abdominal cross-sectional area. The LPT tracks changes in body circumference during the respiratory cycle using a strap connected to the LPT and wrapped around the patient's torso. The LPT signal is monitored by a computer that provides a real-time plot of the patient's breathing pattern. In our technique, we use a CT study with multiple gated acquisitions. The Philips Medical Systems Q series CT imaging system is capable of operating in conjunction with a contrast injector. This allows a patient performing the deep inspiration breath-hold maneuver to send a signal to trigger the CT scanner acquisitions. The LPT system, when interfaced to a LINAC, allows treatment to be delivered only during deep inspiration breath-hold periods. Treatment stops automatically if the lung volume drops from a preset value. The whole treatment can be accomplished with 1 to 3 breath-holds. This technique has been used successfully to combine automatically gated radiation delivery with the deep inspiration breath-hold technique. This improves the accuracy of treatment for moving tumors, providing better target coverage, sparing more healthy tissue, and saving machine time.
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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 | 0.001 |
| 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".