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Introduction of a Simple Algorithm to Create Synthetic-computed Tomography of the Head from Magnetic Resonance Imaging

BACKGROUND: Recently, magnetic resonance imaging (MRI)-based radiotherapy has become a favorite science field for treatment planning purposes. In this study, a simple algorithm was introduced to create synthetic computed tomography (sCT) of the head from MRI. METHODS: A simple atlas-based method was...

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Autores principales: Chegeni, Nahid, Birgani, Mohamad Javad Tahmasebi, Birgani, Fariba Farhadi, Fatehi, Daryoush, Akbarizadeh, Gholamreza, Tahmasbi, Marziyeh
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Wolters Kluwer - Medknow 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6601231/
https://www.ncbi.nlm.nih.gov/pubmed/31316906
http://dx.doi.org/10.4103/jmss.JMSS_26_18
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author Chegeni, Nahid
Birgani, Mohamad Javad Tahmasebi
Birgani, Fariba Farhadi
Fatehi, Daryoush
Akbarizadeh, Gholamreza
Tahmasbi, Marziyeh
author_facet Chegeni, Nahid
Birgani, Mohamad Javad Tahmasebi
Birgani, Fariba Farhadi
Fatehi, Daryoush
Akbarizadeh, Gholamreza
Tahmasbi, Marziyeh
author_sort Chegeni, Nahid
collection PubMed
description BACKGROUND: Recently, magnetic resonance imaging (MRI)-based radiotherapy has become a favorite science field for treatment planning purposes. In this study, a simple algorithm was introduced to create synthetic computed tomography (sCT) of the head from MRI. METHODS: A simple atlas-based method was proposed to create sCT images based on the paired T1/T2-weighted MRI and bone/brain window CT. Dataset included 10 patients with glioblastoma multiforme and 10 patients with other brain tumors. To generate a sCT image, first each MR from dataset was registered to the target-MR, the resulting transformation was applied to the corresponding CT to create the set of deformed CTs. Then, deformed-CTs were fused to generate a single sCT image. The sCT images were compared with the real CT images using geometric measures (mean absolute error [MAE] and dice similarity coefficient of bone [DSC(bone)]) and Hounsfield unit gamma-index (Г(HU)) with criteria 100 HU/2 mm. RESULTS: The evaluations carried out by MAE, DSC(bone), and Г(HU) showed a good agreement between the synthetic and real CT images. The results represented the range of 78–93 HU and 0.80–0.89 for MAE and DSC(bone), respectively. The Г(HU) also showed that approximately 91%–93% of pixels fulfilled the criteria 100 HU/2 mm for brain tumors. CONCLUSION: This method showed that MR sequence (T1w or T2w) should be selected depending on the type of tumor. In addition, the brain window synthetic CTs are in better agreement with real CT relative to bone window sCT images.
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spelling pubmed-66012312019-07-17 Introduction of a Simple Algorithm to Create Synthetic-computed Tomography of the Head from Magnetic Resonance Imaging Chegeni, Nahid Birgani, Mohamad Javad Tahmasebi Birgani, Fariba Farhadi Fatehi, Daryoush Akbarizadeh, Gholamreza Tahmasbi, Marziyeh J Med Signals Sens Original Article BACKGROUND: Recently, magnetic resonance imaging (MRI)-based radiotherapy has become a favorite science field for treatment planning purposes. In this study, a simple algorithm was introduced to create synthetic computed tomography (sCT) of the head from MRI. METHODS: A simple atlas-based method was proposed to create sCT images based on the paired T1/T2-weighted MRI and bone/brain window CT. Dataset included 10 patients with glioblastoma multiforme and 10 patients with other brain tumors. To generate a sCT image, first each MR from dataset was registered to the target-MR, the resulting transformation was applied to the corresponding CT to create the set of deformed CTs. Then, deformed-CTs were fused to generate a single sCT image. The sCT images were compared with the real CT images using geometric measures (mean absolute error [MAE] and dice similarity coefficient of bone [DSC(bone)]) and Hounsfield unit gamma-index (Г(HU)) with criteria 100 HU/2 mm. RESULTS: The evaluations carried out by MAE, DSC(bone), and Г(HU) showed a good agreement between the synthetic and real CT images. The results represented the range of 78–93 HU and 0.80–0.89 for MAE and DSC(bone), respectively. The Г(HU) also showed that approximately 91%–93% of pixels fulfilled the criteria 100 HU/2 mm for brain tumors. CONCLUSION: This method showed that MR sequence (T1w or T2w) should be selected depending on the type of tumor. In addition, the brain window synthetic CTs are in better agreement with real CT relative to bone window sCT images. Wolters Kluwer - Medknow 2019 /pmc/articles/PMC6601231/ /pubmed/31316906 http://dx.doi.org/10.4103/jmss.JMSS_26_18 Text en Copyright: © 2019 Journal of Medical Signals & Sensors http://creativecommons.org/licenses/by-nc-sa/4.0 This is an open access journal, and articles are distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 License, which allows others to remix, tweak, and build upon the work non-commercially, as long as appropriate credit is given and the new creations are licensed under the identical terms.
spellingShingle Original Article
Chegeni, Nahid
Birgani, Mohamad Javad Tahmasebi
Birgani, Fariba Farhadi
Fatehi, Daryoush
Akbarizadeh, Gholamreza
Tahmasbi, Marziyeh
Introduction of a Simple Algorithm to Create Synthetic-computed Tomography of the Head from Magnetic Resonance Imaging
title Introduction of a Simple Algorithm to Create Synthetic-computed Tomography of the Head from Magnetic Resonance Imaging
title_full Introduction of a Simple Algorithm to Create Synthetic-computed Tomography of the Head from Magnetic Resonance Imaging
title_fullStr Introduction of a Simple Algorithm to Create Synthetic-computed Tomography of the Head from Magnetic Resonance Imaging
title_full_unstemmed Introduction of a Simple Algorithm to Create Synthetic-computed Tomography of the Head from Magnetic Resonance Imaging
title_short Introduction of a Simple Algorithm to Create Synthetic-computed Tomography of the Head from Magnetic Resonance Imaging
title_sort introduction of a simple algorithm to create synthetic-computed tomography of the head from magnetic resonance imaging
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6601231/
https://www.ncbi.nlm.nih.gov/pubmed/31316906
http://dx.doi.org/10.4103/jmss.JMSS_26_18
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