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Optimization and Quality Assurance of VMAT-Driven Lattice Radiotherapy in Large Tumors Across Anatomical Sites
1Department of Physics, GLA University, Mathura, Uttar Pradesh, India; Department of Radiation Oncology, Division of Medical Physics, Rajiv Gandhi Cancer Institute and Research Center, New Delhi, India.
Aims:
This study investigates the feasibility, dosimetric optimization, and validation of VMAT-based Lattice Radiotherapy (LRT) across head and neck, thoracic, and abdominal tumors using TrueBeam STx(Varian Medical Systems).
Materials And Methods:
60 patients with gross tumor volumes (GTVs) >550 cc and ≥10 lattice vertices were included. Planning CTs were acquired using a Siemens Somatom go.Sim. VMAT plans were generated in Eclipse (v15.1) with 6 MV FFF beams, using HD120 MLCs. Each spherical high-dose vertex received 20 Gy in 5 fractions. Optimization incorporated concentric dose rings (C1-C3) for valley dose control. Dosimetric parameters evaluated included D95%, Dmean, D50%, Homogeneity Index (HI), and Peak-to-Valley Dose Ratio (PVDR). Validation was performed using OSLDs in a Rando phantom and ArcCHECK gamma analysis (3%/3 mm).
Results:
Abdominal tumors showed the highest spatial modulation, with axial VPDR reaching 0.62, compared to 0.47 in head and neck and thoracic sites. Abdominal sphere doses exhibited the lowest standard deviation (Dmean = 2113.8 ± 47.1 cGy). Head and neck cases required higher modulation intensity (MU/deg = 3.8) due to OAR proximity, while abdominal cases required reduced gantry speeds (1.2°/sec) for sharper dose gradients. Gamma pass rates exceeded 96% across all sites, confirming delivery accuracy.
Conclusion:
VMAT-guided LRT provides robust peak-to-valley dose modulation and reproducible high-dose vertex delivery for large tumors. Anatomical location significantly affects vertex geometry, modulation requirements, and dosimetric outcomes. Abdominal plans demonstrated superior uniformity and spatial separation, whereas head and neck cases demanded more complex optimization. Standardized planning protocols and rigorous QA are essential for safe clinical translation of LRT.
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