Patient-specific quantification of cardiorespiratory motion for cardiac stereotactic radioablation treatment planning
Bibliographic record
Abstract
Background: Cardiac radioablation is a new treatment for patients with refractory ventricular tachycardia (VT). The target for cardiac radioablation is subject to cardiorespiratory motion (CRM), the heart's movement with breathing and cardiac contraction. Data regarding the magnitude of target CRM are limited but are highly important for treatment planning. Objectives: The study sought to assess CRM amplitude by using ablation catheter geometrical data. Methods: Electroanatomic mapping data of patients undergoing catheter ablation for VT at 3 academic centers were exported. The spatial position of the ablation catheter as a function of time while in contact with endocardium was analyzed and used to quantify CRM. Results: Forty-four patients with ischemic and nonischemic cardiomyopathy and VT contributed 1364 ablation lesions to the analysis. Average cardiac and respiratory excursion were 1.62 ± 1.21 mm and 12.12 ± 4.10 mm, respectively. The average ratio of respiratory to cardiac motion was approximately 11:1. CRM was greatest along the craniocaudal axis (9.66 ± 4.00 mm). Regional variations with respect to respiratory and cardiac motion were observed: basal segments had smaller displacements vs midventricular and apical segments. Patient characteristics (previous cardiac surgery, height, weight, body mass index, and left ventricular ejection fraction) had a statistically significant, albeit clinically moderate, impact on CRM. Conclusion: CRM is primarily determined by respiratory displacement and is modulated by the location of the target and the patient's biometric characteristics. The patient-specific quantification of CRM may allow to decrease treatment volume and reduce radiation exposure of surrounding organs at risk while delivering the therapeutic dose to the target.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".