A four‐dimensional dynamic conformal arc approach for real‐time tumor tracking: A retrospective treatment planning study
Bibliographic record
Abstract
PURPOSE: For many thoracic tumors, patient respiration can introduce a significant amount of variability in tumor position that must be accounted for during radiotherapy. Of all existing techniques, real-time dynamic tumor tracking (DTT) represents the most ideal motion management strategy but can be limited by the treatment delivery technique. Our objective was to analyze the dosimetric performance of a dynamic conformal arc (DCA) approach to tumor tracking on standard linear accelerators that may offer similar dosimetric benefit, but with less complexity compared to intensity-modulated radiation therapy (IMRT) or volumetric modulated arc therapy (VMAT). METHODS: Ten patients who previously received free-breathing VMAT for lung cancer were retrospectively analyzed. Patient 4D-CT and respiratory traces were simultaneously acquired prior to treatment and re-planned with DCA and VMAT using the Eclipse v15.6 Treatment Planning System with gated, deep inspiration breath hold (DIBH), and motion encompassment techniques taken into consideration, generating seven new plans per patient. DTT with DCA was simulated using an in-house MATLAB script to parse the radiation dose into each phase of the 4D-CT based on the patient's respiratory trace. Dose distributions were normalized to the same prescription and analyzed using dose volume histograms (DVHs). DVH metrics were assessed using ANOVA with subsequent paired t-tests. RESULTS: The DCA-based DTT plans outperformed or showed comparable performance in their DVH metrics compared to all other combinations of treatment techniques while using motion management in normal lung sparing (p < 0.05). Normal lung sparing was not significantly different when comparing DCA-based DTT to gated and DIBH VMAT (p > 0.05), while both outperformed the corresponding DCA plans (p < 0.05). Simulated treatment times using DCA-based DTT were significantly shorter than both gating and DIBH plans (p < 0.05). CONCLUSIONS: A DCA-based DTT technique showed significant advantages over conventional motion encompassment treatments in lung cancer radiotherapy, with comparable performance to stricter techniques like gating and DIBH while conferring greater time-saving benefits.
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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 | 0.001 |
| 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".