Literature DB >> 22349041

Impact of computed tomography image quality on image-guided radiation therapy based on soft tissue registration.

Natalya V Morrow1, Colleen A Lawton, X Sharon Qi, X Allen Li.   

Abstract

PURPOSE: In image-guided radiation therapy (IGRT), different computed tomography (CT) modalities with varying image quality are being used to correct for interfractional variations in patient set-up and anatomy changes, thereby reducing clinical target volume to the planning target volume (CTV-to-PTV) margins. We explore how CT image quality affects patient repositioning and CTV-to-PTV margins in soft tissue registration-based IGRT for prostate cancer patients. METHODS AND MATERIALS: Four CT-based IGRT modalities used for prostate RT were considered in this study: MV fan beam CT (MVFBCT) (Tomotherapy), MV cone beam CT (MVCBCT) (MVision; Siemens), kV fan beam CT (kVFBCT) (CTVision, Siemens), and kV cone beam CT (kVCBCT) (Synergy; Elekta). Daily shifts were determined by manual registration to achieve the best soft tissue agreement. Effect of image quality on patient repositioning was determined by statistical analysis of daily shifts for 136 patients (34 per modality). Inter- and intraobserver variability of soft tissue registration was evaluated based on the registration of a representative scan for each CT modality with its corresponding planning scan.
RESULTS: Superior image quality with the kVFBCT resulted in reduced uncertainty in soft tissue registration during IGRT compared with other image modalities for IGRT. The largest interobserver variations of soft tissue registration were 1.1 mm, 2.5 mm, 2.6 mm, and 3.2 mm for kVFBCT, kVCBCT, MVFBCT, and MVCBCT, respectively.
CONCLUSIONS: Image quality adversely affects the reproducibility of soft tissue-based registration for IGRT and necessitates a careful consideration of residual uncertainties in determining different CTV-to-PTV margins for IGRT using different image modalities. Copyright Â
© 2012 Elsevier Inc. All rights reserved.

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Year:  2012        PMID: 22349041     DOI: 10.1016/j.ijrobp.2011.11.043

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


  22 in total

1.  Prostate positioning using cone-beam computer tomography based on manual soft-tissue registration: interobserver agreement between radiation oncologists and therapists.

Authors:  B A Jereczek-Fossa; C Pobbiati; L Santoro; C Fodor; P Fanti; S Vigorito; G Baroni; D Zerini; O De Cobelli; R Orecchia
Journal:  Strahlenther Onkol       Date:  2013-08-17       Impact factor: 3.621

2.  Effect of dose reduction on image registration and image quality for cone-beam CT in radiotherapy.

Authors:  B Loutfi-Krauss; J Köhn; N Blümer; K Freundl; T Koch; E Kara; C Scherf; C Rödel; U Ramm; J Licher
Journal:  Strahlenther Onkol       Date:  2014-09-20       Impact factor: 3.621

3.  Semi-automated prediction approach of target shifts using machine learning with anatomical features between planning and pretreatment CT images in prostate radiotherapy.

Authors:  Yudai Kai; Hidetaka Arimura; Kenta Ninomiya; Tetsuo Saito; Yoshinobu Shimohigashi; Akiko Kuraoka; Masato Maruyama; Ryo Toya; Natsuo Oya
Journal:  J Radiat Res       Date:  2020-03-23       Impact factor: 2.724

4.  Comparative analysis of image guidance in two institutions for prostate cancer patients.

Authors:  Tomasz Piotrowski; Slav Yartsev; George Rodrigues; Tomasz Bajon
Journal:  Rep Pract Oncol Radiother       Date:  2014-01-02

5.  Magnetic resonance image (MRI) synthesis from brain computed tomography (CT) images based on deep learning methods for magnetic resonance (MR)-guided radiotherapy.

Authors:  Wen Li; Yafen Li; Wenjian Qin; Xiaokun Liang; Jianyang Xu; Jing Xiong; Yaoqin Xie
Journal:  Quant Imaging Med Surg       Date:  2020-06

6.  The potential failure risk of the cone-beam computed tomography-based planning target volume margin definition for prostate image-guided radiotherapy based on a prospective single-institutional hybrid analysis.

Authors:  Katsumi Hirose; Mariko Sato; Yoshiomi Hatayama; Hideo Kawaguchi; Fumio Komai; Makoto Sohma; Hideki Obara; Masashi Suzuki; Mitsuki Tanaka; Ichitaro Fujioka; Koji Ichise; Yoshihiro Takai; Masahiko Aoki
Journal:  Radiat Oncol       Date:  2018-06-07       Impact factor: 3.481

7.  Assessment of positional reproducibility in the head and neck on a 1.5-T MR simulator for an offline MR-guided radiotherapy solution.

Authors:  Yihang Zhou; Jing Yuan; Oi Lei Wong; Winky Wing Ki Fung; Ka Fai Cheng; Kin Yin Cheung; Siu Ki Yu
Journal:  Quant Imaging Med Surg       Date:  2018-10

8.  Commissioning of and preliminary experience with a new fully integrated computed tomography linac.

Authors:  Lei Yu; Jun Zhao; Zhen Zhang; Jiazhou Wang; Weigang Hu
Journal:  J Appl Clin Med Phys       Date:  2021-06-20       Impact factor: 2.102

9.  Correlation between patients' anatomical characteristics and interfractional internal prostate motion during intensity modulated radiation therapy for prostate cancer.

Authors:  Shintaroh Maruoka; Yasuo Yoshioka; Fumiaki Isohashi; Osamu Suzuki; Yuji Seo; Yuki Otani; Yuichi Akino; Yutaka Takahashi; Iori Sumida; Kazuhiko Ogawa
Journal:  Springerplus       Date:  2015-10-06

10.  Magnitude of observer error using cone beam CT for prostate interfraction motion estimation: effect of reducing scan length or increasing exposure.

Authors:  Helen A McNair; Emma J Harris; Vibeke N Hansen; Karen Thomas; Christopher South; Shaista Hafeez; Robert Huddart; David P Dearnaley
Journal:  Br J Radiol       Date:  2015-08-06       Impact factor: 3.039

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