This analysis compares automated hyperarc planning and VMAT, revealing improved treatment efficiency and brain tissue sparing.
Purpose: This study compared automated HyperArc (HA) planning with manually designed VMAT plans for treating patients with multiple brain metastases. Materials and Methods: Ten patients with an average of 15 metastases (range: 10–23) were retrospectively analyzed. All underwent high-resolution CT imaging (1 mm slice thickness) registered to contrast-enhanced MRI. Targets were delineated by a radiation oncologist. For lesions ≥10 mm, the gross tumor volume (GTV) equaled the planning target volume (PTV); for smaller lesions, a 1 mm margin was added. VMAT plans used a single isocenter and non-coplanar arcs, while HA plans were generated with automated optimization. Prescribed doses ranged from 20 to 30 Gy, delivered over 3–5 fractions. Dosimetric parameters compared included conformity index (CI), gradient index (GI), homogeneity index (HI), healthy brain V10Gy and V12Gy, maximum and mean brainstem doses, and maximum doses to optic structures and lenses. Total monitor units (MU) were also assessed. Results: Target coverage was similar between VMAT and HA, with no significant differences in CI (p = 0.721) or GI (p = 0.241). HA showed improved homogeneity and significantly reduced doses to healthy brain (lower V10Gy) and critical structures including brainstem (p = 0.009) and optic chiasm (p = 0.013). HA also required about 65% fewer MUs than VMAT (p = 0.007), indicating shorter treatment times. Conclusion: HA planning provided superior sparing of healthy brain tissue and critical structures and improved treatment efficiency compared to VMAT. HA represents a promising automated approach for stereotactic radiosurgery in complex multi-target cases
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Şenkesen et al. (2025) studied this question.
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