Literature DB >> 21123004

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

Benjamin E Nelms1, Wolfgang A Tomé, Greg Robinson, James Wheeler.   

Abstract

PURPOSE: Anatomy contouring is critical in radiation therapy. Inaccuracy and variation in defining critical volumes will affect everything downstream: treatment planning, dose-volume histogram analysis, and contour-based visual guidance used in image-guided radiation therapy. This study quantified: (1) variation in the contouring of organs at risk (OAR) in a clinical test case and (2) corresponding effects on dosimetric metrics of highly conformal plans. METHODS AND MATERIALS: A common CT data set with predefined targets from a patient with oropharyngeal cancer was provided to a population of clinics, which were asked to (1) contour OARs and (2) design an intensity-modulated radiation therapy plan. Thirty-two acceptable plans were submitted as DICOM RT data sets, each generated by a different clinical team. Using those data sets, we quantified: (1) the OAR contouring variation and (2) the impact this variation has on dosimetric metrics. New technologies were employed, including a software tool to quantify three-dimensional structure comparisons.
RESULTS: There was significant interclinician variation in OAR contouring. The degree of variation is organ-dependent. We found substantial dose differences resulting strictly from contouring variation (differences ranging from -289% to 56% for mean OAR dose; -22% to 35% for maximum dose). However, there appears to be a threshold in the OAR comparison metric beyond which the dose differences stabilize.
CONCLUSIONS: The effects of interclinician variation in contouring organs-at-risk in the head and neck can be large and are organ-specific. Physicians need to be aware of the effect that variation in OAR contouring can play on the final treatment plan and not restrict their focus only to the target volumes.
Copyright © 2012 Elsevier Inc. All rights reserved.

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Year:  2010        PMID: 21123004     DOI: 10.1016/j.ijrobp.2010.10.019

Source DB:  PubMed          Journal:  Int J Radiat Oncol Biol Phys        ISSN: 0360-3016            Impact factor:   7.038


  54 in total

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2.  Can CT scan protocols used for radiotherapy treatment planning be adjusted to optimize image quality and patient dose? A systematic review.

Authors:  Anne T Davis; Antony L Palmer; Andrew Nisbet
Journal:  Br J Radiol       Date:  2017-05-23       Impact factor: 3.039

Review 3.  Vision 20/20: perspectives on automated image segmentation for radiotherapy.

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Journal:  Med Phys       Date:  2014-05       Impact factor: 4.071

4.  Automatic multiorgan segmentation in thorax CT images using U-net-GAN.

Authors:  Xue Dong; Yang Lei; Tonghe Wang; Matthew Thomas; Leonardo Tang; Walter J Curran; Tian Liu; Xiaofeng Yang
Journal:  Med Phys       Date:  2019-03-22       Impact factor: 4.071

5.  Quantifying the dosimetric impact of organ-at-risk delineation variability in head and neck radiation therapy in the context of patient setup uncertainty.

Authors:  Eric Aliotta; Hamidreza Nourzadeh; Jeffrey Siebers
Journal:  Phys Med Biol       Date:  2019-07-05       Impact factor: 3.609

6.  Modeling the dosimetry of organ-at-risk in head and neck IMRT planning: an intertechnique and interinstitutional study.

Authors:  Jun Lian; Lulin Yuan; Yaorong Ge; Bhishamjit S Chera; David P Yoo; Sha Chang; FangFang Yin; Q Jackie Wu
Journal:  Med Phys       Date:  2013-12       Impact factor: 4.071

7.  Hierarchical Vertex Regression-Based Segmentation of Head and Neck CT Images for Radiotherapy Planning.

Authors: 
Journal:  IEEE Trans Image Process       Date:  2018-02       Impact factor: 10.856

8.  Technical Note: More accurate and efficient segmentation of organs-at-risk in radiotherapy with convolutional neural networks cascades.

Authors:  Kuo Men; Huaizhi Geng; Chingyun Cheng; Haoyu Zhong; Mi Huang; Yong Fan; John P Plastaras; Alexander Lin; Ying Xiao
Journal:  Med Phys       Date:  2018-12-07       Impact factor: 4.071

9.  Delineating brachial plexus, cochlea, pharyngeal constrictor muscles and optic chiasm in head and neck radiotherapy: a CT-based model atlas.

Authors:  Domenico Genovesi; Francesca Perrotti; Marianna Trignani; Angelo Di Pilla; Annamaria Vinciguerra; Antonietta Augurio; Monica Di Tommaso; Massimo Caulo; Massimo Savastano; Armando Tartaro; Antonio Raffaele Cotroneo; Giampiero Ausili Cèfaro
Journal:  Radiol Med       Date:  2014-08-05       Impact factor: 3.469

10.  Segmentation editing improves efficiency while reducing inter-expert variation and maintaining accuracy for normal brain tissues in the presence of space-occupying lesions.

Authors:  M A Deeley; A Chen; R D Datteri; J Noble; A Cmelak; E Donnelly; A Malcolm; L Moretti; J Jaboin; K Niermann; Eddy S Yang; David S Yu; B M Dawant
Journal:  Phys Med Biol       Date:  2013-05-17       Impact factor: 3.609

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