Investigating the feasibility of using Ethos generated treatment plans for head and neck cancer patients

被引:4
作者
El-qmache, Adam [1 ]
McLellan, John [1 ]
机构
[1] Aberdeen Royal Infirm, Radiotherapy Phys, Med Phys, Foresterhill Hlth Campus,Foresterhill Rd, Aberdeen AB25 2ZN, Scotland
来源
TECHNICAL INNOVATIONS & PATIENT SUPPORT IN RADIATION ONCOLOGY | 2023年 / 27卷
关键词
Ethos; Intelligent optimisation engine; Treatment planning; H &N cancer; IMRT;
D O I
10.1016/j.tipsro.2023.100216
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
The Varian Ethos treatment platform is designed to automatically create complex RT treatment plans, reducing both workload and operator variability in plan quality. The aim of this study is to evaluate the quality of Ethosgenerated head and neck (H&N) treatment plans. Ethos plans were created for ten previous H&N patients and these were compared with the original clinical plans generated in Eclipse. Ethos automatically creates several plans with different field arrangements for each patient. All plans were compared quantitatively using: dose-volume metrics; dose conformity; dose heterogeneity and monitor units (MU). In addition, two H&N Oncologists assessed the clinical acceptability of the Ethos plans. Consultant 1 judged there to be at least three clinically acceptable Ethos plans for 9 out of 10 patients reviewed. Consultant 2 approved of at least two Ethos plans for 5 out of 5 patients reviewed. The Ethos plans' average dose metrics were comparable to the clinical plans. The average plan MU was similar for Eclipse and Ethos VMAT plans. The average plan MU for Ethos IMRT plans was larger with respect to all VMAT plans. The Ethos Treatment Planning system is capable of automatically creating good quality treatment plans for a range of H&N cancer patients.
引用
收藏
页数:4
相关论文
共 8 条
  • [1] Archambault Y., 2020, MED PHYS INT J, V8, P77
  • [2] Varian ethos online adaptive radiotherapy for prostate cancer: Early results of contouring accuracy, treatment plan quality, and treatment time
    Byrne, Mikel
    Archibald-Heeren, Ben
    Hu, Yunfei
    Teh, Amy
    Beserminji, Rhea
    Cai, Emma
    Liu, Guilin
    Yates, Angela
    Rijken, James
    Collett, Nick
    Aland, Trent
    [J]. JOURNAL OF APPLIED CLINICAL MEDICAL PHYSICS, 2022, 23 (01):
  • [3] Evaluation of an automated template-based treatment planning system for radiotherapy of anal, rectal and prostate cancer
    Calmels, Lucie
    Sibolt, Patrik
    Astroem, Lina M.
    Serup-Hansen, Eva
    Lindberg, Henriette
    Fromm, Anna-Lene
    Persson, Gitte
    Sjoestroem, David
    Geertsen, Poul
    Behrens, Claus P.
    [J]. TECHNICAL INNOVATIONS & PATIENT SUPPORT IN RADIATION ONCOLOGY, 2022, 22 : 30 - 36
  • [4] State of the art on dose prescription, reporting and recording in Intensity-Modulated Radiation Therapy (ICRU report No. 83)
    Gregoire, V.
    Mackie, T. R.
    [J]. CANCER RADIOTHERAPIE, 2011, 15 (6-7): : 555 - 559
  • [5] Online Adaptive Radiation Therapy
    Lim-Reinders, Stephanie
    Keller, Brian M.
    Al-Ward, Shahad
    Sahgal, Arjun
    Kim, Anthony
    [J]. INTERNATIONAL JOURNAL OF RADIATION ONCOLOGY BIOLOGY PHYSICS, 2017, 99 (04): : 994 - 1003
  • [6] Assessment of efficacy in automated plan generation for Varian Ethos intelligent optimization engine
    Pokharel, Shyam
    Pacheco, Abilio
    Tanner, Suzanne
    [J]. JOURNAL OF APPLIED CLINICAL MEDICAL PHYSICS, 2022, 23 (04):
  • [7] Metrics to evaluate the performance of auto-segmentation for radiation treatment planning: A critical review
    Sherer, Michael, V
    Lin, Diana
    Elguindi, Sharif
    Duke, Simon
    Tan, Li-Tee
    Cacicedo, Jon
    Dahele, Max
    Gillespie, Erin F.
    [J]. RADIOTHERAPY AND ONCOLOGY, 2021, 160 : 185 - 191
  • [8] Varian, 2019, Publication.