KEY POINTS
- This retrospective technical study evaluated 20 clinical thoracic cases containing 2–21 targets per patient, with maximum target separations of 3.8–32.4 cm.
- K-means clustering generated candidate configurations ranging from one isocenter to one per target. Target-specific margins were calculated to maintain 95% coverage probability, assuming a baseline 5 mm translational margin and rotational uncertainties of 1°, 2°, and 3°.
- Total margin volumes were closely aligned with the reference hybrid optimization method. Median differences were 0.03%, 0.14%, and 0.19% for rotational uncertainties of 1°, 2°, and 3°, respectively, with no significant differences.
- Adding a second isocenter reduced median total margin volume by 31.0%, while moving from two to three isocenters produced a further 15.7% reduction. Benefits diminished with subsequent isocenters: 6.6%, 5.4%, and 3.7% for the fourth, fifth, and sixth isocenters.
- Median computation time was 0.19 seconds with k-means versus 306.9 seconds for hybrid optimization. The study did not evaluate resulting dose distributions, treatment delivery, organ-at-risk exposure, or clinical outcomes.
CLINICAL TAKEAWAY
K-means clustering could allow planners to rapidly assess the trade-off between treatment efficiency, number of isocenters, and additional margin volume in complex multi-target thoracic stereotactic ablative radiotherapy. However, the framework was tested only in thoracic cases using modeled setup uncertainties and requires integration into treatment planning and dosimetric validation before clinical adoption.