Dosimetric Comparison of CyberKnife and Conventional Linac Prostate Stereotactic Body Radiation Therapy Plans: Analysis of the PACE-B Study
Bibliographic record
Abstract
Purpose In the PACE-B study, a nonrandomized comparison of toxicity outcomes between stereotactic body radiation therapy (SBRT) platforms revealed fewer urinary side effects with CyberKnife (CK) compared with conventional linac (CL) SBRT. This analysis compares baseline characteristics and planning dosimetry between the CK-SBRT and CL-SBRT cohorts in PACE-B, aiming to provide insight into possible reasons for differing toxicity outcomes between the platforms. Methods and Materials Dosimetric parameters for the surrogate urethra (SU), contoured urethra, bladder, bladder trigone (BT), and rectum were extracted from available computed tomography planning scans of PACE-B SBRT patients. The SU and BT were retrospectively delineated. Dose levels analyzed included maximum point dose (Dmax), D2, D50, and D95, where D(n) represents the dose (Gy) to (n)% of the structure. Baseline characteristics and planning dosimetry between the CK-SBRT and CL-SBRT cohorts were compared using Mann-Whitney U tests, t tests, and χ 2 tests. Results Of the 414 patients who received SBRT, 169 (41%) were treated with CK-SBRT and 245 (59%) with CL-SBRT, with dosimetric parameters available for 94% of patients (390/414). There was a nonstatistically significant trend toward more low-risk prostate cancer in the CK-SBRT cohort (12% vs 6% P = .02 [nonsignificant]). Margins were similar between platforms, except posteriorly, where CK-SBRT had smaller margins. CK-SBRT plans had significantly higher median SU Dmax (45.9 Gy vs 42.8 Gy, P < .0001), D2%, and D50% compared with CL-SBRT plans. Additionally, CK-SBRT plans had significantly higher median BT Dmax (43.4 Gy vs 41.6 Gy, P < .0001), D2%, and D95%, as well as higher median bladder Dmax, D50%, and D95%. CK-SBRT plans had lower median rectal D2% (35.5 Gy vs 36.0 Gy, P < .0001) but higher rectal D50% and D95%. Conclusions Although the CK-SBRT cohort showed lower urinary toxicity, the planned doses to urinary substructures were actually higher, likely due to heterogeneous dose planning. Factors like intrafraction tracking or other confounding variables may explain the differences in toxicity outcomes between the treatment platforms.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".