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Comparison between Volumetric Modulated arc Therapy based Coplanar and Noncoplanar Planning for Stereotactic Body Radiation Therapy of Liver

Research output: Contribution to journalArticlepeer-review

Abstract

Background: The study aims to investigate potential dosimetric benefits between non-coplanar and coplanar beam arrangements of Volumetric-Modulated Arc Therapy (VMAT) plans for liver stereotactic body radiotherapy (SBRT). Methods: Thirteen patients who had undergone liver SBRT treatment in our department were chosen retrospectively for the study. Two sets of SBRT-VMAT plans namely, non-coplanar (NC-VMAT) and Coplanar (C-VMAT) were generated in Monaco(v5.11) planning system for Elekta Versa HD Linac using unflatten 6MV photon. The NC-VMAT plans were created by two/three non-coplanar partial arcs with couch rotation of ±150 and had an arc span of 1300 to 1600 whereas the C-VMAT plans consisted of a full arc. Both plans were compared by statistically analyzing various dosimetric and technical parameters. Results: There is no statistically significant difference observed between the C-VMAT and NC-VMAT plans for planning target volume (PTV) coverage. However, the spine dose (D1cc) was much less in the NC-VMAT plan compared to the C-VMAT plan, with mean values of 6.127 ± 3.08Gy and 9.058 ± 4.76Gy, respectively (p-value=0.002). The low dose spillage to the healthy tissue was compared by the volume receiving 5Gy (V5Gy) and 10Gy (V10Gy). V5Gy of the NC-VMAT plan was 2399.23±1870.76cc while that of C-VMAT plans was 2835.36±1930.20cc with the p-value <0.001. Moreover, the monitor units(MU) were less with NC-VMAT than with C-VMAT SBRT plans (p=0.015). Conclusion: The plan quality of NC-VMAT plans was favorable compared to C-VMAT plans for liver SBRT especially in reducing spine dose, low dose spillage to healthy tissue, and MU.

Original languageEnglish
Pages (from-to)1383-1390
Number of pages8
JournalAsian Pacific Journal of Cancer Prevention
Volume25
Issue number4
DOIs
Publication statusPublished - 2024

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

All Science Journal Classification (ASJC) codes

  • Epidemiology
  • Oncology
  • Public Health, Environmental and Occupational Health
  • Cancer Research

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