Literature DB >> 15885831

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.

Giovanni Mauro Cattaneo1, Michele Reni, Giovanna Rizzo, Pietro Castellone, Giovanni Luca Ceresoli, Cesare Cozzarini, Andrés José Maria Ferreri, Paolo Passoni, Riccardo Calandrino.   

Abstract

BACKGROUND AND
PURPOSE: To investigate the interobserver variability of intracranial tumour delineation on computed tomography (CT) scans using pre-operative MR hardcopies (CT+MR(conv)) or CT-MR (pre-operative) registered images (CT+MR(matched)). PATIENTS AND METHODS: Five physicians outlined the 'initial' clinical tumour volume (CTV0) of seven patients affected by HGG and candidates for radiotherapy (RT) after radical resection. The observers performed on screen-tumour delineation using post-operative CT images of the patients in the treatment position and pre-operative MR radiographs (CT+MR(conv)); they also outlined CTV0 with both CT and corresponding MR axial image on screen (CT+MR(matched)). The accuracy of the image fusion was quantitatively assessed. An analysis was conducted to assess the variability among the five observers in CT+MR(conv) and CT+MR(matched) modality.
RESULTS: The registration accuracy in 3D space is always less than 3.7 mm. The concordance index was significantly better in CT+MR(matched) (47.4+/-12.4%) than in CT+MR(conv) (14.1+/-12.7%) modality (P<0.02). The intersecting volumes represent 67+/-15 and 24+/-18% of the patient mean volume for CT+MR(matched) and CT+MR(conv), respectively (P<0.02).
CONCLUSIONS: The use of CT and MR registered imaging reduces interobserver variability in target volume delineation for post-operative irradiation of HGG; smaller margins around target volume could be adopted in defining irradiation technique.

Entities:  

Mesh:

Year:  2005        PMID: 15885831     DOI: 10.1016/j.radonc.2005.03.012

Source DB:  PubMed          Journal:  Radiother Oncol        ISSN: 0167-8140            Impact factor:   6.280


  19 in total

1.  Interobserver variability in target volume delineation in postoperative radiochemotherapy for gastric cancer. A pilot prospective study.

Authors:  Cristina Moretones; David León; Arturo Navarro; Olalla Santacruz; Ana María Boladeras; Miquel Macià; María Cambray; Valentí Navarro; Ignasi Modolell; Ferran Guedea
Journal:  Clin Transl Oncol       Date:  2012-02       Impact factor: 3.405

2.  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

3.  Results of a multi-institutional benchmark test for cranial CT/MR image registration.

Authors:  Kenneth Ulin; Marcia M Urie; Joel M Cherlow
Journal:  Int J Radiat Oncol Biol Phys       Date:  2010-04-08       Impact factor: 7.038

4.  CT- and MRI-based gross target volume comparison in vestibular schwannomas.

Authors:  Bhudevi Soubhagya N Kulkarni; Harjot Bajwa; Mukka Chandrashekhar; Sunil Dutt Sharma; Rohith Singareddy; Dileep Gudipudi; Shabbir Ahmad; Alok Kumar; N V N Madusudan Sresty; Alluri Krishnam Raju
Journal:  Rep Pract Oncol Radiother       Date:  2017-04-22

5.  Prospective randomized double-blind pilot study of site-specific consensus atlas implementation for rectal cancer target volume delineation in the cooperative group setting.

Authors:  Clifton D Fuller; Jasper Nijkamp; Joop C Duppen; Coen R N Rasch; Charles R Thomas; Samuel J Wang; Paul Okunieff; William E Jones; Daniel Baseman; Shilpen Patel; Carlo G N Demandante; Anna M Harris; Benjamin D Smith; Alan W Katz; Camille McGann; Jennifer L Harper; Daniel T Chang; Stephen Smalley; David T Marshall; Karyn A Goodman; Niko Papanikolaou; Lisa A Kachnic
Journal:  Int J Radiat Oncol Biol Phys       Date:  2010-04-18       Impact factor: 7.038

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

Authors:  Yunfeng Cui; Wenzhou Chen; Feng-Ming Spring Kong; Lindsey A Olsen; Ronald E Beatty; Peter G Maxim; Timothy Ritter; Jason W Sohn; Jane Higgins; James M Galvin; Ying Xiao
Journal:  Pract Radiat Oncol       Date:  2014-06-30

7.  Supervised machine learning-based classification scheme to segment the brainstem on MRI in multicenter brain tumor treatment context.

Authors:  Jose Dolz; Anne Laprie; Soléakhéna Ken; Henri-Arthur Leroy; Nicolas Reyns; Laurent Massoptier; Maximilien Vermandel
Journal:  Int J Comput Assist Radiol Surg       Date:  2015-07-24       Impact factor: 2.924

8.  Feasibility of synthetic computed tomography generated with an adversarial network for multi-sequence magnetic resonance-based brain radiotherapy.

Authors:  Yuhei Koike; Yuichi Akino; Iori Sumida; Hiroya Shiomi; Hirokazu Mizuno; Masashi Yagi; Fumiaki Isohashi; Yuji Seo; Osamu Suzuki; Kazuhiko Ogawa
Journal:  J Radiat Res       Date:  2020-01-23       Impact factor: 2.724

9.  MIRSIG position paper: the use of image registration and fusion algorithms in radiotherapy.

Authors:  Nicholas Lowther; Rob Louwe; Johnson Yuen; Nicholas Hardcastle; Adam Yeo; Michael Jameson
Journal:  Phys Eng Sci Med       Date:  2022-05-06

10.  Postoperative radiotherapy for glioma: improved delineation of the clinical target volume using the geodesic distance calculation.

Authors:  DanFang Yan; SenXiang Yan; ZhongJie Lu; Cong Xie; Wei Chen; Xing Xu; Xinke Li; Haogang Yu; Xinli Zhu; LingYan Zheng
Journal:  PLoS One       Date:  2014-06-04       Impact factor: 3.240

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