Literature DB >> 30858769

Validation of dose distribution computation on sCT images generated from MRI scans by Philips MRCAT.

Iva Bratova1, Petr Paluska1, Jakub Grepl1, Petra Sykorova1, Jan Jansa1, Miroslav Hodek1, Igor Sirak1, Milan Vosmik1, Jiri Petera1.   

Abstract

AIM: To evaluate calculation of treatment plans based on synthetic-CT (sCT) images generated from MRI.
BACKGROUND: Because of better soft tissue contrast, MR images are used in addition to CT images for radiotherapy planning. However, registration of CT and MR images or repositioning between scanning sessions introduce systematic errors, hence suggestions for MRI-only therapy. The lack of information on electron density necessary for dose calculation leads to sCT (synthetic CT) generation. This work presents a comparison of dose distribution calculated on standard CT and sCT.
MATERIALS AND METHODS: 10 prostate patients were included in this study. CT and MR images were collected for each patient and then water equivalent (WE) and MRCAT images were generated. The radiation plans were optimized on CT and then recalculated on MRCAT and WE data. 2D gamma analysis was also performed.
RESULTS: The mean differences in the majority of investigated DVH points were in order of 1% up to 10%, including both MRCAT and WE dose distributions. Mean gamma pass for acceptance criteria 1%/1 mm were greater than 82.5%. Prescribed doses for target volumes and acceptable doses for organs at risk were met in almost all cases.
CONCLUSIONS: The dose calculation accuracy on MRCAT was not significantly compromised in the majority of clinical relevant DVH points. The introduction of MRCAT into practise would eliminate systematic errors, increase patients' comfort and reduce treatment expenses. Institutions interested in MRCAT commissioning must, however, consider changes to established workflow.

Entities:  

Keywords:  MRCAT; Prostate cancer; Radiotherapy; sCT

Year:  2019        PMID: 30858769      PMCID: PMC6396091          DOI: 10.1016/j.rpor.2019.02.001

Source DB:  PubMed          Journal:  Rep Pract Oncol Radiother        ISSN: 1507-1367


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2.  MR-based synthetic CT generation using a deep convolutional neural network method.

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Review 3.  MRI simulation for radiotherapy treatment planning.

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4.  Quantification of confounding factors in MRI-based dose calculations as applied to prostate IMRT.

Authors:  Matteo Maspero; Peter R Seevinck; Gerald Schubert; Michaela A U Hoesl; Bram van Asselen; Max A Viergever; Jan J W Lagendijk; Gert J Meijer; Cornelis A T van den Berg
Journal:  Phys Med Biol       Date:  2017-01-11       Impact factor: 3.609

5.  Magnetic resonance-only simulation and dose calculation in external beam radiation therapy: a feasibility study for pelvic cancers.

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6.  Dosimetric and workflow evaluation of first commercial synthetic CT software for clinical use in pelvis.

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Journal:  Phys Med Biol       Date:  2016-12-16       Impact factor: 3.609

7.  Prostate gland motion assessed with cine-magnetic resonance imaging (cine-MRI).

Authors:  Michel J Ghilezan; David A Jaffray; Jeffrey H Siewerdsen; Marcel Van Herk; Anil Shetty; Michael B Sharpe; Syed Zafar Jafri; Frank A Vicini; Richard C Matter; Donald S Brabbins; Alvaro A Martinez
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8.  Automatic Substitute Computed Tomography Generation and Contouring for Magnetic Resonance Imaging (MRI)-Alone External Beam Radiation Therapy From Standard MRI Sequences.

Authors:  Jason A Dowling; Jidi Sun; Peter Pichler; David Rivest-Hénault; Soumya Ghose; Haylea Richardson; Chris Wratten; Jarad Martin; Jameen Arm; Leah Best; Shekhar S Chandra; Jurgen Fripp; Frederick W Menk; Peter B Greer
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9.  A criterion for the reliable use of MRI-only radiotherapy.

Authors:  Marie E Korsholm; Line W Waring; Jens M Edmund
Journal:  Radiat Oncol       Date:  2014-01-09       Impact factor: 3.481

Review 10.  A review of substitute CT generation for MRI-only radiation therapy.

Authors:  Jens M Edmund; Tufve Nyholm
Journal:  Radiat Oncol       Date:  2017-01-26       Impact factor: 3.481

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2.  Magnetic resonance image-based tomotherapy planning for prostate cancer.

Authors:  Sang Hoon Jung; Jinsung Kim; Yoonsun Chung; Bilgin Keserci; Hongryull Pyo; Hee Chul Park; Won Park
Journal:  Radiat Oncol J       Date:  2020-03-27
  2 in total

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