Literature DB >> 29519402

Evaluation of a commercial automatic treatment planning system for liver stereotactic body radiation therapy treatments.

Elena Gallio1, Francesca Romana Giglioli2, Andrea Girardi3, Alessia Guarneri4, Umberto Ricardi5, Roberto Ropolo2, Riccardo Ragona5, Christian Fiandra5.   

Abstract

PURPOSE: Automated treatment planning is a new frontier in radiotherapy. The Auto-Planning module of the Pinnacle3 treatment planning system (TPS) was evaluated for liver stereotactic body radiation therapy treatments.
METHODS: Ten cases were included in the study. Six plans were generated for each case by four medical physics experts. The first two planned with Pinnacle TPS, both with manual module (MP) and Auto-Planning one (AP). The other two physicists generated two plans with Monaco TPS (VM). Treatment plan comparisons were then carried on the various dosimetric parameters of target and organs at risk, monitor units, number of segments, plan complexity metrics and human resource planning time. The user dependency of Auto-Planning was also tested and the plans were evaluated by a trained physician.
RESULTS: Statistically significant differences (Anova test) were observed for spinal cord doses, plan average beam irregularity, number of segments, monitor units and human planning time. The Fisher-Hayter test applied to these parameters showed significant statistical differences between AP e MP for spinal cord doses and human planning time; between MP and VM for monitor units, number of segments and plan irregularity; for all those between AP and VM. The two plans created by different planners with AP were similar to each other.
CONCLUSIONS: The plans created with Auto-Planning were comparable to the manually generated plans. The time saved in planning enables the planner to commit more resources to more complex cases. The independence of the planner enables to standardize plan quality.
Copyright © 2018 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Auto-Planning; Automatic planning; Pinnacle; SBRT

Mesh:

Year:  2018        PMID: 29519402     DOI: 10.1016/j.ejmp.2018.01.016

Source DB:  PubMed          Journal:  Phys Med        ISSN: 1120-1797            Impact factor:   2.685


  10 in total

1.  A study on predicting cases that would benefit from proton beam therapy in primary liver tumors of less than or equal to 5 cm based on the estimated incidence of hepatic toxicity.

Authors:  Yusuke Uchinami; Norio Katoh; Ryusuke Suzuki; Takahiro Kanehira; Masaya Tamura; Seishin Takao; Taeko Matsuura; Naoki Miyamoto; Yoshihiro Fujita; Fuki Koizumi; Hiroshi Taguchi; Koichi Yasuda; Kentaro Nishioka; Isao Yokota; Keiji Kobashi; Hidefumi Aoyama
Journal:  Clin Transl Radiat Oncol       Date:  2022-05-17

2.  Personalized setting of plan parameters using feasibility dose volume histogram for auto-planning in Pinnacle system.

Authors:  Wenlong Xia; Fei Han; Jiayun Chen; Junjie Miao; Jianrong Dai
Journal:  J Appl Clin Med Phys       Date:  2020-05-04       Impact factor: 2.102

Review 3.  Applications and limitations of machine learning in radiation oncology.

Authors:  Daniel Jarrett; Eleanor Stride; Katherine Vallis; Mark J Gooding
Journal:  Br J Radiol       Date:  2019-06-05       Impact factor: 3.629

4.  Adapting automated treatment planning configurations across international centres for prostate radiotherapy.

Authors:  Dale Roach; Geert Wortel; Cesar Ochoa; Henrik R Jensen; Eugene Damen; Philip Vial; Tomas Janssen; Christian Rønn Hansen
Journal:  Phys Imaging Radiat Oncol       Date:  2019-04-24

5.  Personalized Automation of Treatment Planning for Linac-Based Stereotactic Body Radiotherapy of Spine Cancer.

Authors:  Savino Cilla; Francesco Cellini; Carmela Romano; Gabriella Macchia; Donato Pezzulla; Pietro Viola; Milly Buwenge; Luca Indovina; Vincenzo Valentini; Alessio G Morganti; Francesco Deodato
Journal:  Front Oncol       Date:  2022-02-02       Impact factor: 6.244

6.  Investigation the Efficacy of Fuzzy Logic Implementation at Image-Guided Radiotherapy.

Authors:  Ahmad Esmaili Torshabi
Journal:  J Med Signals Sens       Date:  2022-05-12

7.  Refining complex re-irradiation dosimetry through feasibility benchmarking and analysis for informed treatment planning.

Authors:  Seth R Duffy; Yiran Zheng; Jessica Muenkel; Rodney J Ellis; Tanvir N Baig; Brian Krancevic; Christian B Langmack; Kevin D Kelley; Serah Choi
Journal:  J Appl Clin Med Phys       Date:  2020-12-03       Impact factor: 2.243

8.  Automated treatment planning as a dose escalation strategy for stereotactic radiation therapy in pancreatic cancer.

Authors:  Savino Cilla; Anna Ianiro; Carmela Romano; Francesco Deodato; Gabriella Macchia; Pietro Viola; Milly Buwenge; Silvia Cammelli; Antonio Pierro; Vincenzo Valentini; Alessio G Morganti
Journal:  J Appl Clin Med Phys       Date:  2020-10-16       Impact factor: 2.243

9.  Personalized Treatment Planning Automation in Prostate Cancer Radiation Oncology: A Comprehensive Dosimetric Study.

Authors:  Savino Cilla; Carmela Romano; Vittoria E Morabito; Gabriella Macchia; Milly Buwenge; Nicola Dinapoli; Luca Indovina; Lidia Strigari; Alessio G Morganti; Vincenzo Valentini; Francesco Deodato
Journal:  Front Oncol       Date:  2021-06-01       Impact factor: 6.244

10.  Evaluation of Auto-Planning for Left-Side Breast Cancer After Breast-Conserving Surgery Based on Geometrical Relationship.

Authors:  Yijiang Li; Han Bai; Danju Huang; Feihu Chen; Yaoxiong Xia
Journal:  Technol Cancer Res Treat       Date:  2021 Jan-Dec
  10 in total

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