Literature DB >> 31740042

RapidPlan development of VMAT plans for cervical cancer patients in low- and middle-income countries.

Marisol Tinoco1, Erika Waga2, Kevin Tran2, Hieu Vo2, Jamie Baker2, Rachel Hunter2, Christine Peterson2, Nicolette Taku2, Laurence Court2.   

Abstract

Cervical cancer has a high incidence and mortality rate in low- and middle-income countries (LMICs) largely due to limited resources and insufficient staffing. Knowledge-based planning (KBP) could alleviate understaffing issues by streamlining the radiotherapy treatment planning process. Varian's KBP system (RapidPlan) was used to develop a model capable of producing volumetric modulated arc therapy (VMAT) plans for cervical cancer patients. Plan data from 46 patients previously treated at MD Anderson Cancer Center (MDACC) were used to create and train the model which was then applied to 32 patients excluded from the training process. Dose volume histogram (DVH) values for the planning target volume (PTV_High), bladder, rectum, and bowel were evaluated for the validation plans and found to have satisfied the required PTV coverage and organ-at-risk (OAR) dose constraints. The average value for PTV_High D95.0% was 48.0 Gy (sd = 3.0 Gy) for existing clinical plans and 48.4 Gy (sd = 2.6 Gy) for the validation plans. The mean dose for the bladder, rectum, and bowel was 39.8 Gy (sd = 3.9 Gy), 41.6 Gy (sd = 5.2 Gy), and 21.6 Gy (sd = 5.0 Gy) for existing clinical plans and 38.9 Gy (sd = 4.0 Gy), 40.3 Gy (sd = 4.8 Gy), and 21.5 Gy (sd = 4.6 Gy) for validation plans, respectively. A TOST test showed that the p values for the PTV_High D95.0% (p < 0.001), rectum V30Gy (p = 0.039), and mean dose to the bladder (p = 0.0014), rectum (p = 0.025), and bowel (p = 0.006) were statistically significant within a 5% equivalence margin of the clinical value thereby providing strong evidence of equivalence. Based on this statistical analysis, it was determined that the model was capable of generating treatable VMAT plans for cervical cancer patients.
Copyright © 2019 American Association of Medical Dosimetrists. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Cervical cancer; LMICs; RapidPlan; VMAT

Mesh:

Year:  2019        PMID: 31740042     DOI: 10.1016/j.meddos.2019.10.002

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


  8 in total

Review 1.  Automated Radiation Treatment Planning for Cervical Cancer.

Authors:  Dong Joo Rhee; Anuja Jhingran; Kelly Kisling; Carlos Cardenas; Hannah Simonds; Laurence Court
Journal:  Semin Radiat Oncol       Date:  2020-10       Impact factor: 5.934

2.  Artificial Intelligence in Radiation Therapy.

Authors:  Yabo Fu; Hao Zhang; Eric D Morris; Carri K Glide-Hurst; Suraj Pai; Alberto Traverso; Leonard Wee; Ibrahim Hadzic; Per-Ivar Lønne; Chenyang Shen; Tian Liu; Xiaofeng Yang
Journal:  IEEE Trans Radiat Plasma Med Sci       Date:  2021-08-24

3.  Study on the ability of 3D gamma analysis and bio-mathematical model in detecting dose changes caused by dose-calculation-grid-size (DCGS).

Authors:  Han Bai; Sijin Zhu; Xingrao Wu; Xuhong Liu; Feihu Chen; Jiawen Yan
Journal:  Radiat Oncol       Date:  2020-07-06       Impact factor: 3.481

4.  A pilot study of machine-learning based automated planning for primary brain tumours.

Authors:  Derek S Tsang; Grace Tsui; Chris McIntosh; Thomas Purdie; Glenn Bauman; Hitesh Dama; Normand Laperriere; Barbara-Ann Millar; David B Shultz; Sameera Ahmed; Mohammad Khandwala; David C Hodgson
Journal:  Radiat Oncol       Date:  2022-01-06       Impact factor: 3.481

5.  A novel knowledge-based prediction model for estimating an initial equivalent uniform dose in semi-auto-planning for cervical cancer.

Authors:  Cheng Tao; Bo Liu; Chengqiang Li; Jian Zhu; Yong Yin; Jie Lu
Journal:  Radiat Oncol       Date:  2022-08-29       Impact factor: 4.309

6.  Clinical acceptability of fully automated external beam radiotherapy for cervical cancer with three different beam delivery techniques.

Authors:  Dong Joo Rhee; Anuja Jhingran; Kai Huang; Tucker J Netherton; Nazia Fakie; Ingrid White; Alicia Sherriff; Carlos E Cardenas; Lifei Zhang; Surendra Prajapati; Stephen F Kry; Beth M Beadle; William Shaw; Frederika O'Reilly; Jeannette Parkes; Hester Burger; Chris Trauernicht; Hannah Simonds; Laurence E Court
Journal:  Med Phys       Date:  2022-07-26       Impact factor: 4.506

7.  Reducing variability among treatment machines using knowledge-based planning for head and neck, pancreatic, and rectal cancer.

Authors:  Hideaki Hirashima; Mitsuhiro Nakamura; Nobutaka Mukumoto; Ryo Ashida; Kota Fujii; Kiyonao Nakamura; Aya Nakajima; Katsuyuki Sakanaka; Michio Yoshimura; Takashi Mizowaki
Journal:  J Appl Clin Med Phys       Date:  2021-06-20       Impact factor: 2.102

8.  Development and clinical validation of Knowledge-based planning for Volumetric Modulated Arc Therapy of cervical cancer including pelvic and para aortic fields.

Authors:  Jamema Swamidas; Sangram Pradhan; Supriya Chopra; Subhajit Panda; Yashna Gupta; Sahil Sood; Samarpita Mohanty; Jeevanshu Jain; Kishore Joshi; Reena Ph; Lavanya Gurram; Umesh Mahantshetty; Jai Prakash Agarwal
Journal:  Phys Imaging Radiat Oncol       Date:  2021-05-26
  8 in total

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