Literature DB >> 19215827

Variability of target and normal structure delineation for breast cancer radiotherapy: an RTOG Multi-Institutional and Multiobserver Study.

X Allen Li1, An Tai, Douglas W Arthur, Thomas A Buchholz, Shannon Macdonald, Lawrence B Marks, Jean M Moran, Lori J Pierce, Rachel Rabinovitch, Alphonse Taghian, Frank Vicini, Wendy Woodward, Julia R White.   

Abstract

PURPOSE: To quantify the multi-institutional and multiobserver variability of target and organ-at-risk (OAR) delineation for breast-cancer radiotherapy (RT) and its dosimetric impact as the first step of a Radiation Therapy Oncology Group effort to establish a breast cancer atlas. METHODS AND MATERIALS: Nine radiation oncologists specializing in breast RT from eight institutions independently delineated targets (e.g., lumpectomy cavity, boost planning target volume, breast, supraclavicular, axillary and internal mammary nodes, chest wall) and OARs (e.g., heart, lung) on the same CT images of three representative breast cancer patients. Interobserver differences in structure delineation were quantified regarding volume, distance between centers of mass, percent overlap, and average surface distance. Mean, median, and standard deviation for these quantities were calculated for all possible combinations. To assess the impact of these variations on treatment planning, representative dosimetric plans based on observer-specific contours were generated.
RESULTS: Variability in contouring the targets and OARs between the institutions and observers was substantial. Structure overlaps were as low as 10%, and volume variations had standard deviations up to 60%. The large variability was related both to differences in opinion regarding target and OAR boundaries and approach to incorporation of setup uncertainty and dosimetric limitations in target delineation. These interobserver differences result in substantial variations in dosimetric planning for breast RT.
CONCLUSIONS: Differences in target and OAR delineation for breast irradiation between institutions/observers appear to be clinically and dosimetrically significant. A systematic consensus is highly desirable, particularly in the era of intensity-modulated and image-guided RT.

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Year:  2009        PMID: 19215827      PMCID: PMC2911777          DOI: 10.1016/j.ijrobp.2008.10.034

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


  37 in total

1.  An intercomparison of IMRT delivery techniques: a case study for breast treatment.

Authors:  M Partridge; S Aldridge; E Donovan; P M Evans
Journal:  Phys Med Biol       Date:  2001-07       Impact factor: 3.609

2.  Intensity modulated versus non-intensity modulated radiotherapy in the treatment of the left breast and upper internal mammary lymph node chain: a comparative planning study.

Authors:  B C John Cho; Coen W Hurkmans; Eugene M F Damen; Lambert J Zijp; Ben J Mijnheer
Journal:  Radiother Oncol       Date:  2002-02       Impact factor: 6.280

3.  Intensity modulation for breast treatment using static multi-leaf collimators.

Authors:  Y C Lo; G Yasuda; T J Fitzgerald; M M Urie
Journal:  Int J Radiat Oncol Biol Phys       Date:  2000-01-01       Impact factor: 7.038

4.  Quality assurance in radiotherapy of breast cancer--variability in planning target volume delineation.

Authors:  M A Pitkänen; K A Holli; A T Ojala; P Laippala
Journal:  Acta Oncol       Date:  2001       Impact factor: 4.089

5.  Image-guided radiation therapy: from concept to practice.

Authors:  David A Jaffray
Journal:  Semin Radiat Oncol       Date:  2007-10       Impact factor: 5.934

6.  An improved breast irradiation technique using three-dimensional geometrical information and intensity modulation.

Authors:  B van Asselen; C P Raaijmakers; P Hofman; J J Lagendijk
Journal:  Radiother Oncol       Date:  2001-03       Impact factor: 6.280

7.  Variability in target volume delineation on CT scans of the breast.

Authors:  C W Hurkmans; J H Borger; B R Pieters; N S Russell; E P Jansen; B J Mijnheer
Journal:  Int J Radiat Oncol Biol Phys       Date:  2001-08-01       Impact factor: 7.038

8.  Optimizing breast cancer treatment efficacy with intensity-modulated radiotherapy.

Authors:  Frank A Vicini; Michael Sharpe; Larry Kestin; Alvaro Martinez; Christina K Mitchell; Michelle F Wallace; Richard Matter; John Wong
Journal:  Int J Radiat Oncol Biol Phys       Date:  2002-12-01       Impact factor: 7.038

9.  The potential use of intensity modulated radiotherapy (IMRT) in women with pectus excavatum desiring breast-conserving therapy.

Authors:  B S Teh; H H Lu; S Sobremonte; D Bellezza; J K Chiu; L S Carpenter; W S Dennis; S Y Woo; E B Butler
Journal:  Breast J       Date:  2001 Jul-Aug       Impact factor: 2.431

10.  Reduction of cardiac and lung complication probabilities after breast irradiation using conformal radiotherapy with or without intensity modulation.

Authors:  Coen W Hurkmans; B C John Cho; Eugene Damen; Lambert Zijp; Ben J Mijnheer
Journal:  Radiother Oncol       Date:  2002-02       Impact factor: 6.280

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  107 in total

1.  Critical discussion of evaluation parameters for inter-observer variability in target definition for radiation therapy.

Authors:  I Fotina; C Lütgendorf-Caucig; M Stock; R Pötter; D Georg
Journal:  Strahlenther Onkol       Date:  2012-01-27       Impact factor: 3.621

2.  Development and validation of a heart atlas to study cardiac exposure to radiation following treatment for breast cancer.

Authors:  Mary Feng; Jean M Moran; Todd Koelling; Aamer Chughtai; June L Chan; Laura Freedman; James A Hayman; Reshma Jagsi; Shruti Jolly; Janice Larouere; Julie Soriano; Robin Marsh; Lori J Pierce
Journal:  Int J Radiat Oncol Biol Phys       Date:  2010-04-24       Impact factor: 7.038

3.  Influence of the type of imaging on the delineation process during the treatment planning.

Authors:  Weronika Jackowiak; Bartosz Bąk; Anna Kowalik; Adam Ryczkowski; Małgorzata Skórska; Małgorzata Paszek-Widzińska
Journal:  Rep Pract Oncol Radiother       Date:  2015-06-18

4.  Development of a software for quantitative evaluation radiotherapy target and organ-at-risk segmentation comparison.

Authors:  Jayashree Kalpathy-Cramer; Musaddiq Awan; Steven Bedrick; Coen R N Rasch; David I Rosenthal; Clifton D Fuller
Journal:  J Digit Imaging       Date:  2014-02       Impact factor: 4.056

5.  Assessment of a guideline-based heart substructures delineation in left-sided breast cancer patients undergoing adjuvant radiotherapy : Quality assessment within a randomized phase III trial testing a cardioprotective treatment strategy (SAFE-2014).

Authors:  Giulio Francolini; Isacco Desideri; Icro Meattini; Carlotta Becherini; Francesca Terziani; Emanuela Olmetto; Camilla Delli Paoli; Donato Pezzulla; Mauro Loi; Pierluigi Bonomo; Daniela Greto; Silvia Calusi; Marta Casati; Stefania Pallotta; Lorenzo Livi
Journal:  Strahlenther Onkol       Date:  2018-11-07       Impact factor: 3.621

6.  Simplified rules for everyday delineation of lymph node areas for breast cancer radiotherapy.

Authors:  Y M Kirova; P Castro Pena; R Dendale; V Servois; M A Bollet; N Fournier-Bidoz; F Campana; A Fourquet
Journal:  Br J Radiol       Date:  2009-12-17       Impact factor: 3.039

7.  Automatic segmentation of whole breast using atlas approach and deformable image registration.

Authors:  Valerie K Reed; Wendy A Woodward; Lifei Zhang; Eric A Strom; George H Perkins; Welela Tereffe; Julia L Oh; T Kuan Yu; Isabelle Bedrosian; Gary J Whitman; Thomas A Buchholz; Lei Dong
Journal:  Int J Radiat Oncol Biol Phys       Date:  2008-09-17       Impact factor: 7.038

8.  Artificial intelligence in musculoskeletal oncological radiology.

Authors:  Matjaz Vogrin; Teodor Trojner; Robi Kelc
Journal:  Radiol Oncol       Date:  2020-11-10       Impact factor: 2.991

9.  Quantitative assessment of target delineation variability for thymic cancers: Agreement evaluation of a prospective segmentation challenge.

Authors:  Emma Holliday; Clifton D Fuller; Jayashree Kalpathy-Cramer; Daniel Gomez; Andreas Rimner; Ying Li; Suresh Senan; Lynn D Wilson; Jehee Choi; Ritsuko Komaki; Charles R Thomas
Journal:  J Radiat Oncol       Date:  2015-11-03

10.  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

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