To study the Multimodality End-to-end Testing for Bilateral Metallic Implant in Pelvis

医学 多模态 骨盆 植入 放射科 外科 万维网 计算机科学
作者
pawan kumar singh
出处
期刊:Turkish Journal of Oncology [LookUs Bilisim A.S.]
被引量:1
标识
DOI:10.5505/tjo.2023.3892
摘要

The end-to-end (E2E) testing method enables understanding the difficulties and uncertainties in treating any specific case type.This study was focused on bilateral metallic implant cases. METHODSThe study was performed on a cylindrical phantom of Perspex with holes for implant inserts.Two stainless steel metal rods of 7.5-8.0g/cc mass density were inserted in the phantom.The ionization chamber CC13 was kept at a 5 cm depth in the phantom.The phantom was scanned on a computed tomography simulator in pelvis protocol with a 1mm slice thickness.The scans were imported to the contouring station without applying artifacts correction.Chamber volume was contoured as gross tumor volume (GTV); margin to GTV, clinical target volume, and planning target volume were created.Four isocentric plans (Conventional, three-dimensional conformal radiotherapy[3D-CRT], intensity-modulated radiotherapy [IMRT], and volumetric-modulated radiotherapy [VMAT]) were generated for two Linac-sTruebeam (TB)-sTx and 2300-CD.The conventional plan was a single anterior field, 3D-CRT was four field box techniques, IMRT was seven field plan, and VMAT was with two complete arc.Pre-treatment verification was done using CBCT.Four plans were created on helical tomotherapy with different prescriptions and delivered using MVCT guidance. RESULTSIn conventional plans, variations were -1.40%, -1.57%, and for 3DCRT, variations were -5.08% and -4.93%, for IMRT, the differences between measured and TPS doses were 1.84 % and -1.55% for VMAT plans, and the variations were 0.68% and -0.88% for TB and 2300-CD, respectively.The tomotherapy plans with gradient showed deviations more significant than 3%.Similarly, the variations for single prescription plans were within 3%. CONCLUSIONThe phantom design used in the test provided a comprehensive understanding of simulation and delivery problems.

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