Literature DB >> 32532613

Dosimetric and planning efficiency comparison for lung SBRT: CyberKnife vs VMAT vs knowledge-based VMAT.

Suhong Yu1, Huijun Xu2, Asa Sinclair3, Xin Zhang3, Ulrich Langner3, Kimberley Mak3.   

Abstract

This is the first study that compared treatment plan quality and planning efficiency for lung stereotactic body radiation therapy (SBRT) using CyberKnife (CK) Multiplan vs Varian Eclipse treatment planning systems, including volumetric modulated arc therapy (VMAT) and knowledge-based VMAT (KBP-VMAT). Thirteen lung SBRT patients treated with 50 to 55 Gy in 3 or 5 fractions were retrospectively included in this study. CK plans created with Multiplan V. 4.6.1 using 2 fixed circular cones were previously approved used for treatment. For the comparison, the computed tomography (CT) data sets and contours from the CK plans were used to generate VMAT and KBP-VMAT plans (University of California San Diego publicly-shared RapidPlan model) using Eclipse V. 13.7. Metrics used for the comparison of CK, VMAT, and KBP-VMAT plans included monitor units (MUs), conformity indices, dose heterogeneity, high-dose spillage, low-dose spillage, adjacent organs at risk (OAR) doses, and treatment planning time. One-way analysis of variance with post-hoc Tukey tests and paired t-tests were used to analyze the difference of these metrics corresponding to the different planning techniques. All of the 3 planning techniques achieved our clinical goals. With similar planning target volume (PTV) coverage, CK plans yielded the most MU (p< 0.001), the least dose homogeneity (p < 0.002), and the least D2cm dose (p < 0.001), while KBP-VMAT plans resulted in the most OAR sparing. No significant difference was found among other dosimetric metrics such as high-dose spillage, lung V20 and volume receiving 50% of the prescription dose. Compared to VMAT, KBP-VMAT improved OAR sparing (p < 0.05), but required significantly more MU (p < 0.001). KBP-VMAT was associated with the shortest planning time. Eclipse-based VMAT can achieve comparable plan quality for lung SBRT as CK, in a more efficient manner. RapidPlan can facilitate the planning process of KBP-VMAT, with potentially better OAR sparing but higher MU requirements. Further improvement for KBP-VMAT is likely achievable by developing site-specific patient models.
Copyright © 2020 American Association of Medical Dosimetrists. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Cyberknife; Knowledge-based planning; RapidPlan; SBRT; VMAT; lung SBRT

Year:  2020        PMID: 32532613     DOI: 10.1016/j.meddos.2020.04.004

Source DB:  PubMed          Journal:  Med Dosim        ISSN: 1873-4022            Impact factor:   1.482


  3 in total

1.  An Automated knowledge-based planning routine for stereotactic body radiotherapy of peripheral lung tumors via DCA-based volumetric modulated arc therapy.

Authors:  Justin Visak; Gary Y Ge; Ronald C McGarry; Marcus Randall; Damodar Pokhrel
Journal:  J Appl Clin Med Phys       Date:  2020-12-03       Impact factor: 2.102

2.  Knowledge-based planning in robotic intracranial stereotactic radiosurgery treatments.

Authors:  Suhong Yu; Huijun Xu; Yin Zhang; Xin Zhang; Michael A Dyer; Ariel E Hirsch; Minh Tam Truong; Heming Zhen
Journal:  J Appl Clin Med Phys       Date:  2021-02-09       Impact factor: 2.102

3.  Machine learning for dose-volume histogram based clinical decision-making support system in radiation therapy plans for brain tumors.

Authors:  Pawel Siciarz; Salem Alfaifi; Eric Van Uytven; Shrinivas Rathod; Rashmi Koul; Boyd McCurdy
Journal:  Clin Transl Radiat Oncol       Date:  2021-09-15
  3 in total

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