Development of a Cardiac and Respiratory Phantom (CARP) for use in Radiosurgery Dosimetry
Bibliographic record
Abstract
Cardiac Radiosurgery is one of the newest modalities for management of ventricular tachyarrhythmia (VT). It precisely targets radiation to the heart using a high-dose single fraction treatment to scar or destroy cardiac tissue that is allowing irregular electrical signals. Patients often have ICDs with leads that have metal components close to the targets for treatment within the heart. These ICD leads are easily distinguished in kilovolt imaging avoiding any need for additional invasive surgery to implant fiducial markers within the patient. Although respiratory motion management techniques are well established in the radiotherapy setting, there are currently no commercially available systems that evaluate the effects of cardiac motion on respiratory tracking. The cardiac and respiratory phantom (CARP) is designed to mimic cardiac-coupled respiratory motion for use in determining the ability of a medical linear accelerator to track an ICD lead as a motion surrogate. The phantom displaces a platform, which can house ICD leads and dosimeters, in the cranio-caudal and medial-lateral directions. The cardiac and respiratory rates and displacements are user controlled through a computer which is coupled to the phantom by an Arduino. The CARP can achieve up to 150 breaths and 250 cardiac beats per minute to within a 1% error, for standard displacements. The total cardiac and respiratory travel ranges achieved are 3.5 and 4cm, respectively. The CARP can successfully be used as a quality assurance tool in the setting of tracked radiosurgery for cardiac targets.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".