Literature DB >> 28076338

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

Matteo Maspero1, 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.   

Abstract

Magnetic resonance (MR)-only radiotherapy treatment planning requires pseudo-CT (pCT) images to enable MR-based dose calculations. To verify the accuracy of MR-based dose calculations, institutions interested in introducing MR-only planning will have to compare pCT-based and computer tomography (CT)-based dose calculations. However, interpreting such comparison studies may be challenging, since potential differences arise from a range of confounding factors which are not necessarily specific to MR-only planning. Therefore, the aim of this study is to identify and quantify the contribution of factors confounding dosimetric accuracy estimation in comparison studies between CT and pCT. The following factors were distinguished: set-up and positioning differences between imaging sessions, MR-related geometric inaccuracy, pCT generation, use of specific calibration curves to convert pCT into electron density information, and registration errors. The study comprised fourteen prostate cancer patients who underwent CT/MRI-based treatment planning. To enable pCT generation, a commercial solution (MRCAT, Philips Healthcare, Vantaa, Finland) was adopted. IMRT plans were calculated on CT (gold standard) and pCTs. Dose difference maps in a high dose region (CTV) and in the body volume were evaluated, and the contribution to dose errors of possible confounding factors was individually quantified. We found that the largest confounding factor leading to dose difference was the use of different calibration curves to convert pCT and CT into electron density (0.7%). The second largest factor was the pCT generation which resulted in pCT stratified into a fixed number of tissue classes (0.16%). Inter-scan differences due to patient repositioning, MR-related geometric inaccuracy, and registration errors did not significantly contribute to dose differences (0.01%). The proposed approach successfully identified and quantified the factors confounding accurate MRI-based dose calculation in the prostate. This study will be valuable for institutions interested in introducing MR-only dose planning in their clinical practice.

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Year:  2017        PMID: 28076338     DOI: 10.1088/1361-6560/aa4fe7

Source DB:  PubMed          Journal:  Phys Med Biol        ISSN: 0031-9155            Impact factor:   3.609


  14 in total

1.  Dose evaluation of MRI-based synthetic CT generated using a machine learning method for prostate cancer radiotherapy.

Authors:  Ghazal Shafai-Erfani; Tonghe Wang; Yang Lei; Sibo Tian; Pretesh Patel; Ashesh B Jani; Walter J Curran; Tian Liu; Xiaofeng Yang
Journal:  Med Dosim       Date:  2019-02-01       Impact factor: 1.482

2.  Effect of region extraction and assigned mass-density values on the accuracy of dose calculation with magnetic resonance-based volumetric arc therapy planning.

Authors:  Keisuke Usui; Keisuke Sasai; Koichi Ogawa
Journal:  Radiol Phys Technol       Date:  2018-03-14

3.  On the accuracy of bulk synthetic CT for MR-guided online adaptive radiotherapy.

Authors:  Davide Cusumano; Lorenzo Placidi; Stefania Teodoli; Luca Boldrini; Francesca Greco; Silvia Longo; Francesco Cellini; Nicola Dinapoli; Vincenzo Valentini; Marco De Spirito; Luigi Azario
Journal:  Radiol Med       Date:  2019-10-08       Impact factor: 3.469

4.  Clinical experience and workflow challenges with magnetic resonance-only radiation therapy simulation and planning for prostate cancer.

Authors:  Neelam Tyagi; Michael J Zelefsky; Andreas Wibmer; Kristen Zakian; Sarah Burleson; Laura Happersett; Aleksi Halkola; Mo Kadbi; Margie Hunt
Journal:  Phys Imaging Radiat Oncol       Date:  2020-10-13

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

Authors:  Iva Bratova; Petr Paluska; Jakub Grepl; Petra Sykorova; Jan Jansa; Miroslav Hodek; Igor Sirak; Milan Vosmik; Jiri Petera
Journal:  Rep Pract Oncol Radiother       Date:  2019-02-28

6.  Assessment of dosimetric and positioning accuracy of a magnetic resonance imaging-only solution for external beam radiotherapy of pelvic anatomy.

Authors:  Reko Kemppainen; Sami Suilamo; Iiro Ranta; Marko Pesola; Aleksi Halkola; Alvin Eufemio; Heikki Minn; Jani Keyriläinen
Journal:  Phys Imaging Radiat Oncol       Date:  2019-06-22

7.  A single neural network for cone-beam computed tomography-based radiotherapy of head-and-neck, lung and breast cancer.

Authors:  Matteo Maspero; Antonetta C Houweling; Mark H F Savenije; Tristan C F van Heijst; Joost J C Verhoeff; Alexis N T J Kotte; Cornelis A T van den Berg
Journal:  Phys Imaging Radiat Oncol       Date:  2020-05-25

8.  Feasibility of magnetic resonance imaging-only rectum radiotherapy with a commercial synthetic computed tomography generation solution.

Authors:  Matteo Maspero; Marcus D Tyyger; Rob H N Tijssen; Peter R Seevinck; Martijn P W Intven; Cornelis A T van den Berg
Journal:  Phys Imaging Radiat Oncol       Date:  2018-10-02

9.  Cone beam CT for QA of synthetic CT in MRI only for prostate patients.

Authors:  Emilia Palmér; Emilia Persson; Petra Ambolt; Christian Gustafsson; Adalsteinn Gunnlaugsson; Lars E Olsson
Journal:  J Appl Clin Med Phys       Date:  2018-09-04       Impact factor: 2.102

10.  Clinical implementation of MRI-based organs-at-risk auto-segmentation with convolutional networks for prostate radiotherapy.

Authors:  Mark H F Savenije; Matteo Maspero; Gonda G Sikkes; Jochem R N van der Voort van Zyp; Alexis N T J Kotte; Gijsbert H Bol; Cornelis A T van den Berg
Journal:  Radiat Oncol       Date:  2020-05-11       Impact factor: 3.481

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