Literature DB >> 25413413

Contouring variations and the role of atlas in non-small cell lung cancer radiation therapy: Analysis of a multi-institutional preclinical trial planning study.

Yunfeng Cui1, Wenzhou Chen2, Feng-Ming Spring Kong3, Lindsey A Olsen4, Ronald E Beatty5, Peter G Maxim6, Timothy Ritter7, Jason W Sohn8, Jane Higgins9, James M Galvin10, Ying Xiao10.   

Abstract

PURPOSE: To quantify variations in target and normal structure contouring and evaluate dosimetric impact of these variations in non-small cell lung cancer (NSCLC) cases. To study whether providing an atlas can reduce potential variation. METHODS AND MATERIALS: Three NSCLC cases were distributed sequentially to multiple institutions for contouring and radiation therapy planning. No segmentation atlas was provided for the first 2 cases (Case 1 and Case 2). Contours were collected from submitted plans and consensus contour sets were generated. The volume variation among institution contours and the deviation of them from consensus contours were analyzed. The dose-volume histograms for individual institution plans were recalculated using consensus contours to quantify the dosimetric changes. An atlas containing targets and critical structures was constructed and was made available when the third case (Case 3) was distributed for planning. The contouring variability in the submitted plans of Case 3 was compared with that in first 2 cases.
RESULTS: Planning target volume (PTV) showed large variation among institutions. The PTV coverage in institutions' plans decreased dramatically when reevaluated using the consensus PTV contour. The PTV contouring consistency did not show improvement with atlas use in Case 3. For normal structures, lung contours presented very good agreement, while the brachial plexus showed the largest variation. The consistency of esophagus and heart contouring improved significantly (t test; P < .05) in Case 3. Major factors contributing to the contouring variation were identified through a survey questionnaire.
CONCLUSIONS: The amount of contouring variations in NSCLC cases was presented. Its impact on dosimetric parameters can be significant. The segmentation atlas improved the contour agreement for esophagus and heart, but not for the PTV in this study. Quality assurance of contouring is essential for a successful multi-institutional clinical trial.
Copyright © 2015 American Society for Radiation Oncology. Published by Elsevier Inc. All rights reserved.

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Year:  2014        PMID: 25413413      PMCID: PMC4355315          DOI: 10.1016/j.prro.2014.05.005

Source DB:  PubMed          Journal:  Pract Radiat Oncol        ISSN: 1879-8500


  20 in total

1.  Variations in the contouring of organs at risk: test case from a patient with oropharyngeal cancer.

Authors:  Benjamin E Nelms; Wolfgang A Tomé; Greg Robinson; James Wheeler
Journal:  Int J Radiat Oncol Biol Phys       Date:  2010-12-01       Impact factor: 7.038

2.  Three-dimensional conformal radiation may deliver considerable dose of incidental nodal irradiation in patients with early stage node-negative non-small cell lung cancer when the tumor is large and centrally located.

Authors:  Lujun Zhao; Ming Chen; Randall Ten Haken; Indrin Chetty; Olivier Chapet; James A Hayman; Feng-Ming Kong
Journal:  Radiother Oncol       Date:  2007-02-06       Impact factor: 6.280

3.  Variations in target volume definition for postoperative radiotherapy in stage III non-small-cell lung cancer: analysis of an international contouring study.

Authors:  Femke O B Spoelstra; Suresh Senan; Cecile Le Péchoux; Satoshi Ishikura; Francesc Casas; David Ball; Allan Price; Dirk De Ruysscher; John R van Sörnsen de Koste
Journal:  Int J Radiat Oncol Biol Phys       Date:  2009-06-27       Impact factor: 7.038

4.  The effect of delineation method and observer variability on bladder dose-volume histograms for prostate intensity modulated radiotherapy.

Authors:  Tara Rosewall; Andrew J Bayley; Peter Chung; Lisa W Le; Jason Xie; Siddhartha Baxi; Charles N Catton; Geoffrey Currie; Janelle Wheat; Michael Milosevic
Journal:  Radiother Oncol       Date:  2011-08-22       Impact factor: 6.280

5.  Differences in target outline delineation from CT scans of brain tumours using different methods and different observers.

Authors:  M Yamamoto; Y Nagata; K Okajima; T Ishigaki; R Murata; T Mizowaki; M Kokubo; M Hiraoka
Journal:  Radiother Oncol       Date:  1999-02       Impact factor: 6.280

6.  Target delineation in post-operative radiotherapy of brain gliomas: interobserver variability and impact of image registration of MR(pre-operative) images on treatment planning CT scans.

Authors:  Giovanni Mauro Cattaneo; Michele Reni; Giovanna Rizzo; Pietro Castellone; Giovanni Luca Ceresoli; Cesare Cozzarini; Andrés José Maria Ferreri; Paolo Passoni; Riccardo Calandrino
Journal:  Radiother Oncol       Date:  2005-05       Impact factor: 6.280

7.  Stereotactic body radiation therapy and 3-dimensional conformal radiotherapy for stage I non-small cell lung cancer: A pooled analysis of biological equivalent dose and local control.

Authors:  Niraj Mehta; Christopher R King; Nzhde Agazaryan; Michael Steinberg; Amanda Hua; Percy Lee
Journal:  Pract Radiat Oncol       Date:  2011-12-03

8.  Reduction of observer variation using matched CT-PET for lung cancer delineation: a three-dimensional analysis.

Authors:  Roel J H M Steenbakkers; Joop C Duppen; Isabelle Fitton; Kirsten E I Deurloo; Lambert J Zijp; Emile F I Comans; Apollonia L J Uitterhoeve; Patrick T R Rodrigus; Gijsbert W P Kramer; Johan Bussink; Katrien De Jaeger; José S A Belderbos; Peter J C M Nowak; Marcel van Herk; Coen R N Rasch
Journal:  Int J Radiat Oncol Biol Phys       Date:  2005-09-28       Impact factor: 7.038

9.  Impact of anatomical location on value of CT-PET co-registration for delineation of lung tumors.

Authors:  Isabelle Fitton; Roel J H M Steenbakkers; Kenneth Gilhuijs; Joop C Duppen; Peter J C M Nowak; Marcel van Herk; Coen R N Rasch
Journal:  Int J Radiat Oncol Biol Phys       Date:  2007-11-05       Impact factor: 7.038

10.  Discrepancies in volume calculations between different radiotherapy treatment planning systems.

Authors:  T Ackerly; J Andrews; D Ball; M Guerrieri; B Healy; I Williams
Journal:  Australas Phys Eng Sci Med       Date:  2003-06       Impact factor: 1.430

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  10 in total

1.  The role of delineation education programs for improving interobserver variability in target volume delineation in gastric cancer.

Authors:  Cem Onal; Mustafa Cengiz; Ozan C Guler; Yemliha Dolek; Serdar Ozkok
Journal:  Br J Radiol       Date:  2017-03-24       Impact factor: 3.039

2.  Bridging the Gap in Global Advanced Radiation Oncology Training: Impact of a Web-Based Open-Access Interactive Three-Dimensional Contouring Atlas on Radiation Oncologist Practice in Russia.

Authors:  Shearwood McClelland; Marina Chernykh; Natalia Dengina; Erin F Gillespie; Anna Likhacheva; Sergey Usychkin; Alexandr Pankratov; Ekaterina Kharitonova; Yulia Egorova; Ilya Tsimafeyeu; Sergei Tjulandin; Charles R Thomas; Timur Mitin
Journal:  J Cancer Educ       Date:  2019-10       Impact factor: 2.037

Review 3.  Artificial intelligence in radiation oncology.

Authors:  Elizabeth Huynh; Ahmed Hosny; Christian Guthier; Danielle S Bitterman; Steven F Petit; Daphne A Haas-Kogan; Benjamin Kann; Hugo J W L Aerts; Raymond H Mak
Journal:  Nat Rev Clin Oncol       Date:  2020-08-25       Impact factor: 66.675

4.  Real-world analysis of manual editing of deep learning contouring in the thorax region.

Authors:  Femke Vaassen; Djamal Boukerroui; Padraig Looney; Richard Canters; Karolien Verhoeven; Stephanie Peeters; Indra Lubken; Jolein Mannens; Mark J Gooding; Wouter van Elmpt
Journal:  Phys Imaging Radiat Oncol       Date:  2022-05-14

Review 5.  Magnetic resonance imaging in precision radiation therapy for lung cancer.

Authors:  Hannah Bainbridge; Ahmed Salem; Rob H N Tijssen; Michael Dubec; Andreas Wetscherek; Corinne Van Es; Jose Belderbos; Corinne Faivre-Finn; Fiona McDonald
Journal:  Transl Lung Cancer Res       Date:  2017-12

6.  Use of Crowd Innovation to Develop an Artificial Intelligence-Based Solution for Radiation Therapy Targeting.

Authors:  Raymond H Mak; Michael G Endres; Jin H Paik; Rinat A Sergeev; Hugo Aerts; Christopher L Williams; Karim R Lakhani; Eva C Guinan
Journal:  JAMA Oncol       Date:  2019-05-01       Impact factor: 31.777

Review 7.  Challenges in the target volume definition of lung cancer radiotherapy.

Authors:  Susan Mercieca; José S A Belderbos; Marcel van Herk
Journal:  Transl Lung Cancer Res       Date:  2021-04

8.  Dose-volume-based evaluation of convolutional neural network-based auto-segmentation of thoracic organs at risk.

Authors:  Noémie Johnston; Jeffrey De Rycke; Yolande Lievens; Marc van Eijkeren; Jan Aelterman; Eva Vandersmissen; Stephan Ponte; Barbara Vanderstraeten
Journal:  Phys Imaging Radiat Oncol       Date:  2022-07-25

9.  Clinical validation of deep learning algorithms for radiotherapy targeting of non-small-cell lung cancer: an observational study.

Authors:  Ahmed Hosny; Danielle S Bitterman; Christian V Guthier; Jack M Qian; Hannah Roberts; Subha Perni; Anurag Saraf; Luke C Peng; Itai Pashtan; Zezhong Ye; Benjamin H Kann; David E Kozono; David Christiani; Paul J Catalano; Hugo J W L Aerts; Raymond H Mak
Journal:  Lancet Digit Health       Date:  2022-09

10.  Deep Learning Improved Clinical Target Volume Contouring Quality and Efficiency for Postoperative Radiation Therapy in Non-small Cell Lung Cancer.

Authors:  Nan Bi; Jingbo Wang; Tao Zhang; Xinyuan Chen; Wenlong Xia; Junjie Miao; Kunpeng Xu; Linfang Wu; Quanrong Fan; Luhua Wang; Yexiong Li; Zongmei Zhou; Jianrong Dai
Journal:  Front Oncol       Date:  2019-11-13       Impact factor: 6.244

  10 in total

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