Literature DB >> 34111955

Tree-based exploration of the optimization objectives for automatic cervical cancer IMRT treatment planning.

Hanlin Wang1, Ruoxi Wang1, Jiacheng Liu1, Jian Zhang1, Kaining Yao1, Haizhen Yue1, Yibao Zhang1,2, Jing You1, Hao Wu1,2.   

Abstract

OBJECTIVE: To develop and evaluate a practical automatic treatment planning method for intensity-modulated radiation therapy (IMRT) in cervical cancer cases.
METHODS: A novel algorithm named as Optimization Objectives Tree Search Algorithm (OOTSA) was proposed to emulate the planning optimization process and achieve a progressively improving IMRT plan, based on the Eclipse Scripting Application Programming Interface (ESAPI). 30 previously treated cervical cancer cases were selected from the clinical database and comparison was made between the OOTSA-generated plans and clinical treated plans and RapidPlan-based (RP) plans.
RESULTS: In clinical evaluation, compared with plan scores of the clinical plans and the RP plans, 22 and 26 of the OOTSA plans were considered as clinically improved in terms of plan quality, respectively. The average conformity index (CI) for the PTV in the OOTSA plans was 0.86 ± 0.01 (mean ± 1 standard deviation), better than those in the RP plans (0.83 ± 0.02) and the clinical plans (0.71 ± 0.11). Compared with the clinical plans, the mean doses of femoral head, rectum, spinal cord and right kidney in the OOTSA plans were reduced by 2.34 ± 2.87 Gy, 1.67 ± 2.10 Gy, 4.12 ± 6.44 Gy and 1.15 ± 2.67 Gy. Compared with the RP plans, the mean doses of femoral head, spinal cord, right kidney and small intestine in the OOTSA plans were reduced by 3.31 ± 1.55 Gy, 4.25 ± 3.69 Gy, 1.54 ± 2.23 Gy and 3.33 ± 1.91 Gy, respectively. In the OOTSA plans, the mean dose of bladder was slightly increased, with 2.33 ± 2.55 Gy (versus clinical plans) and 1.37 ± 1.74 Gy (vs RP plans). The average elapsed time of OOTSA and clinical planning were 59.2 ± 3.47 min and 76.53 ± 5.19 min.
CONCLUSION: The plans created by OOTSA have been shown marginally better than the manual plans, especially in preserving OARs. In addition, the time of automatic treatment planning has shown a reduction compared to a manual planning process, and the variation of plan quality was greatly reduced. Although improvement on the algorithm is warranted, this proof-of-concept study has demonstrated that the proposed approach can be a practical solution for automatic planning. ADVANCES IN KNOWLEDGE: The proposed method is novel in the emulation strategy of the physicists' iterative operation during the planning process. Based on the existing optimizers, this method can be a simple yet effective solution for automated IMRT treatment planning.

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Year:  2021        PMID: 34111955      PMCID: PMC8248206          DOI: 10.1259/bjr.20210214

Source DB:  PubMed          Journal:  Br J Radiol        ISSN: 0007-1285            Impact factor:   3.629


  35 in total

1.  A methodology for automatic intensity-modulated radiation treatment planning for lung cancer.

Authors:  Xiaodong Zhang; Xiaoqiang Li; Enzhuo M Quan; Xiaoning Pan; Yupeng Li
Journal:  Phys Med Biol       Date:  2011-06-08       Impact factor: 3.609

2.  A conformation number to quantify the degree of conformality in brachytherapy and external beam irradiation: application to the prostate.

Authors:  A van't Riet; A C Mak; M A Moerland; L H Elders; W van der Zee
Journal:  Int J Radiat Oncol Biol Phys       Date:  1997-02-01       Impact factor: 7.038

Review 3.  Automation in intensity modulated radiotherapy treatment planning-a review of recent innovations.

Authors:  Mohammad Hussein; Ben J M Heijmen; Dirk Verellen; Andrew Nisbet
Journal:  Br J Radiol       Date:  2018-09-04       Impact factor: 3.039

4.  Software-based evaluation of a class solution for prostate IMRT planning.

Authors:  Sarah Clarke; Josie Goodworth; Justin Westhuyzen; Brendan Chick; Matthew Hoffmann; Jacqueline Pacey; Stuart Greenham
Journal:  Rep Pract Oncol Radiother       Date:  2017-08-30

5.  Simultaneous integrated intensity-modulated radiotherapy boost for locally advanced gynecological cancer: radiobiological and dosimetric considerations.

Authors:  Mariana Guerrero; X Allen Li; Lijun Ma; Jeanette Linder; Chad Deyoung; Beth Erickson
Journal:  Int J Radiat Oncol Biol Phys       Date:  2005-07-01       Impact factor: 7.038

6.  Knowledge-based prediction of three-dimensional dose distributions for external beam radiotherapy.

Authors:  Satomi Shiraishi; Kevin L Moore
Journal:  Med Phys       Date:  2016-01       Impact factor: 4.071

7.  Automatic VMAT planning for post-operative prostate cancer cases using particle swarm optimization: A proof of concept study.

Authors:  Luise A Künzel; Sara Leibfarth; Oliver S Dohm; Arndt-Christian Müller; Daniel Zips; Daniela Thorwarth
Journal:  Phys Med       Date:  2019-12-17       Impact factor: 2.685

8.  Assessment of a model based optimization engine for volumetric modulated arc therapy for patients with advanced hepatocellular cancer.

Authors:  Antonella Fogliata; Po-Ming Wang; Francesca Belosi; Alessandro Clivio; Giorgia Nicolini; Eugenio Vanetti; Luca Cozzi
Journal:  Radiat Oncol       Date:  2014-10-28       Impact factor: 3.481

9.  A dosimetric evaluation of knowledge-based VMAT planning with simultaneous integrated boosting for rectal cancer patients.

Authors:  Hao Wu; Fan Jiang; Haizhen Yue; Sha Li; Yibao Zhang
Journal:  J Appl Clin Med Phys       Date:  2016-11-08       Impact factor: 2.102

10.  Automated IMRT planning with regional optimization using planning scripts.

Authors:  Ilma Xhaferllari; Eugene Wong; Karl Bzdusek; Michael Lock; Jeff Chen
Journal:  J Appl Clin Med Phys       Date:  2013-01-07       Impact factor: 2.102

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  1 in total

1.  Benchmarking daily adaptation using fully automated radiotherapy treatment plan optimization for rectal cancer.

Authors:  Thyrza Z Jagt; Tomas M Janssen; Anja Betgen; Lisa Wiersema; Rick Verhage; Sanne Garritsen; Tineke Vijlbrief-Bosman; Peter de Ruiter; Peter Remeijer; Corrie A M Marijnen; Femke P Peters; Jan-Jakob Sonke
Journal:  Phys Imaging Radiat Oncol       Date:  2022-08-18
  1 in total

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