Literature DB >> 31834577

Comparison of rigid and deformable image registration for nasopharyngeal carcinoma radiotherapy planning with diagnostic position PET/CT.

Yudai Kai1,2, Hidetaka Arimura3, Ryo Toya4, Tetsuo Saito5, Tomohiko Matsuyama5, Yoshiyuki Fukugawa6, Shinya Shiraishi7, Yoshinobu Shimohigashi2, Masato Maruyama2, Natsuo Oya5.   

Abstract

PURPOSE: This observer study aimed to compare rigid image registration (RIR) with deformable image registration (DIR) for diagnostic position (DP) positron emission tomography/computed tomography (PET/CT) images in the delineation of gross tumor volumes (GTVs) in nasopharyngeal carcinoma (NPC) radiotherapy planning.
MATERIALS AND METHODS: Four radiation oncologists individually delineated the GTVs, GTVRIR, and GTVDIR, on planning CT (pCT) images registered with DP-PET/CT images using RIR and B-spline-based DIR, respectively. Reference GTVs were independently delineated by all radiation oncologists using radiotherapy position (RP)-PET/CT images. DP- and RP-PET/CT images for 14 patients with NPC were acquired using early and delayed scans, respectively. Dice's similarity coefficient (DSC), mean distance to agreement, and volume agreement with reference GTVs were compared by considering the interobserver variability in reference contours.
RESULTS: The average DSCs for GTVRIR and GTVDIR were 0.77 and 0.77, which were acceptable for GTV delineation. There were no statistically significant differences between GTVRIR and GTVDIR in all evaluation indexes (p > 0.05). Furthermore, the correlation between neck flexion angle differences and GTV accuracy was not statistically significant (p > 0.05).
CONCLUSION: RIR was a feasible choice compared with the B-spline-based DIR in GTV delineation for NPC under variations of neck flexion angle.

Entities:  

Keywords:  Deformable image registration; Delineation of gross tumor volume; Diagnostic position PET/CT; Nasopharyngeal carcinoma; Rigid image registration

Year:  2019        PMID: 31834577     DOI: 10.1007/s11604-019-00911-6

Source DB:  PubMed          Journal:  Jpn J Radiol        ISSN: 1867-1071            Impact factor:   2.374


  25 in total

1.  Can positron emission tomography (PET) or PET/Computed Tomography (CT) acquired in a nontreatment position be accurately registered to a head-and-neck radiotherapy planning CT?

Authors:  Andrew B Hwang; Stephen L Bacharach; Sue S Yom; Vivian K Weinberg; Jeanne M Quivey; Benjamin L Franc; Ping Xia
Journal:  Int J Radiat Oncol Biol Phys       Date:  2008-12-10       Impact factor: 7.038

2.  Use of image registration and fusion algorithms and techniques in radiotherapy: Report of the AAPM Radiation Therapy Committee Task Group No. 132.

Authors:  Kristy K Brock; Sasa Mutic; Todd R McNutt; Hua Li; Marc L Kessler
Journal:  Med Phys       Date:  2017-05-23       Impact factor: 4.071

3.  An evaluation of an automated 4D-CT contour propagation tool to define an internal gross tumour volume for lung cancer radiotherapy.

Authors:  Stewart Gaede; Jason Olsthoorn; Alexander V Louie; David Palma; Edward Yu; Brian Yaremko; Belal Ahmad; Jeff Chen; Karl Bzdusek; George Rodrigues
Journal:  Radiother Oncol       Date:  2011-10-06       Impact factor: 6.280

4.  Multi-institutional Validation Study of Commercially Available Deformable Image Registration Software for Thoracic Images.

Authors:  Noriyuki Kadoya; Yujiro Nakajima; Masahide Saito; Yuki Miyabe; Masahiko Kurooka; Satoshi Kito; Yukio Fujita; Motoharu Sasaki; Kazuhiro Arai; Kensuke Tani; Masashi Yagi; Akihisa Wakita; Naoki Tohyama; Keiichi Jingu
Journal:  Int J Radiat Oncol Biol Phys       Date:  2016-05-19       Impact factor: 7.038

Review 5.  Practical integration of [18F]-FDG-PET and PET-CT in the planning of radiotherapy for non-small cell lung cancer (NSCLC): the technical basis, ICRU-target volumes, problems, perspectives.

Authors:  Ursula Nestle; Stephanie Kremp; Anca-Ligia Grosu
Journal:  Radiother Oncol       Date:  2006-10-24       Impact factor: 6.280

6.  F-18 FDG PET-CT fusion in radiotherapy treatment planning for head and neck cancer.

Authors:  Mary Koshy; Arnold C Paulino; Rebecca Howell; David Schuster; Raghuveer Halkar; Lawrence W Davis
Journal:  Head Neck       Date:  2005-06       Impact factor: 3.147

7.  Deformable registration of preoperative PET/CT with postoperative radiation therapy planning CT in head and neck cancer.

Authors:  Nataliya Kovalchuk; Scharukh Jalisi; Rathan M Subramaniam; Minh T Truong
Journal:  Radiographics       Date:  2012 Sep-Oct       Impact factor: 5.333

Review 8.  Deformable image registration in radiation therapy.

Authors:  Seungjong Oh; Siyong Kim
Journal:  Radiat Oncol J       Date:  2017-06-30

9.  Benchmarking of five commercial deformable image registration algorithms for head and neck patients.

Authors:  Jason Pukala; Perry B Johnson; Amish P Shah; Katja M Langen; Frank J Bova; Robert J Staton; Rafael R Mañon; Patrick Kelly; Sanford L Meeks
Journal:  J Appl Clin Med Phys       Date:  2016-05-08       Impact factor: 2.102

10.  Deep Deconvolutional Neural Network for Target Segmentation of Nasopharyngeal Cancer in Planning Computed Tomography Images.

Authors:  Kuo Men; Xinyuan Chen; Ye Zhang; Tao Zhang; Jianrong Dai; Junlin Yi; Yexiong Li
Journal:  Front Oncol       Date:  2017-12-20       Impact factor: 6.244

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  2 in total

1.  Prevalence and risk factors of retro-styloid lymph node metastasis in oropharyngeal carcinoma.

Authors:  Ryo Toya; Tetsuo Saito; Yoshiyuki Fukugawa; Tomohiko Matsuyama; Tadashi Matsumoto; Shinya Shiraishi; Daizo Murakami; Yorihisa Orita; Toshinori Hirai; Natsuo Oya
Journal:  Ann Med       Date:  2022-12       Impact factor: 4.709

2.  Impact of metal artifact reduction algorithm on gross tumor volume delineation in tonsillar cancer: reducing the interobserver variation.

Authors:  Yoshiyuki Fukugawa; Ryo Toya; Tomohiko Matsuyama; Takahiro Watakabe; Yoshinobu Shimohigashi; Yudai Kai; Tadashi Matsumoto; Natsuo Oya
Journal:  BMC Med Imaging       Date:  2022-09-06       Impact factor: 2.795

  2 in total

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