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Creation of an anthropomorphic CT head phantom for verification of image segmentation
PURPOSE: Many methods are available to segment structural magnetic resonance (MR) images of the brain into different tissue types. These have generally been developed for research purposes but there is some clinical use in the diagnosis of neurodegenerative diseases such as dementia. The potential e...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7383927/ https://www.ncbi.nlm.nih.gov/pubmed/32160322 http://dx.doi.org/10.1002/mp.14127 |
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author | Holmes, Robin B. Negus, Ian S. Wiltshire, Sophie J. Thorne, Gareth C. Young, Peter |
author_facet | Holmes, Robin B. Negus, Ian S. Wiltshire, Sophie J. Thorne, Gareth C. Young, Peter |
author_sort | Holmes, Robin B. |
collection | PubMed |
description | PURPOSE: Many methods are available to segment structural magnetic resonance (MR) images of the brain into different tissue types. These have generally been developed for research purposes but there is some clinical use in the diagnosis of neurodegenerative diseases such as dementia. The potential exists for computed tomography (CT) segmentation to be used in place of MRI segmentation, but this will require a method to verify the accuracy of CT processing, particularly if algorithms developed for MR are used, as MR has notably greater tissue contrast. METHODS: To investigate these issues we have created a three‐dimensional (3D) printed brain with realistic Hounsfield unit (HU) values based on tissue maps segmented directly from an individual T1 MRI scan of a normal subject. Several T1 MRI scans of normal subjects from the ADNI database were segmented using SPM12 and used to create stereolithography files of different tissues for 3D printing. The attenuation properties of several material blends were investigated, and three suitable formulations were used to print an object expected to have realistic geometry and attenuation properties. A skull was simulated by coating the object with plaster of Paris impregnated bandages. Using two CT scanners, the realism of the phantom was assessed by the measurement of HU values, SPM12 segmentation and comparison with the source data used to create the phantom. RESULTS: Realistic relative HU values were measured although a subtraction of 60 was required to obtain equivalence with the expected values (gray matter 32.9–35.8 phantom, 29.9–34.2 literature). Segmentation of images acquired at different kVps/mAs showed excellent agreement with the source data (Dice Similarity Coefficient 0.79 for gray matter). The performance of two scanners with two segmentation methods was compared, with the scanners found to have similar performance and with one segmentation method clearly superior to the other. CONCLUSION: The ability to use 3D printing to create a realistic (in terms of geometry and attenuation properties) head phantom has been demonstrated and used in an initial assessment of CT segmentation accuracy using freely available software developed for MRI. |
format | Online Article Text |
id | pubmed-7383927 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-73839272020-07-27 Creation of an anthropomorphic CT head phantom for verification of image segmentation Holmes, Robin B. Negus, Ian S. Wiltshire, Sophie J. Thorne, Gareth C. Young, Peter Med Phys DIAGNOSTIC IMAGING (IONIZING AND NON‐IONIZING) PURPOSE: Many methods are available to segment structural magnetic resonance (MR) images of the brain into different tissue types. These have generally been developed for research purposes but there is some clinical use in the diagnosis of neurodegenerative diseases such as dementia. The potential exists for computed tomography (CT) segmentation to be used in place of MRI segmentation, but this will require a method to verify the accuracy of CT processing, particularly if algorithms developed for MR are used, as MR has notably greater tissue contrast. METHODS: To investigate these issues we have created a three‐dimensional (3D) printed brain with realistic Hounsfield unit (HU) values based on tissue maps segmented directly from an individual T1 MRI scan of a normal subject. Several T1 MRI scans of normal subjects from the ADNI database were segmented using SPM12 and used to create stereolithography files of different tissues for 3D printing. The attenuation properties of several material blends were investigated, and three suitable formulations were used to print an object expected to have realistic geometry and attenuation properties. A skull was simulated by coating the object with plaster of Paris impregnated bandages. Using two CT scanners, the realism of the phantom was assessed by the measurement of HU values, SPM12 segmentation and comparison with the source data used to create the phantom. RESULTS: Realistic relative HU values were measured although a subtraction of 60 was required to obtain equivalence with the expected values (gray matter 32.9–35.8 phantom, 29.9–34.2 literature). Segmentation of images acquired at different kVps/mAs showed excellent agreement with the source data (Dice Similarity Coefficient 0.79 for gray matter). The performance of two scanners with two segmentation methods was compared, with the scanners found to have similar performance and with one segmentation method clearly superior to the other. CONCLUSION: The ability to use 3D printing to create a realistic (in terms of geometry and attenuation properties) head phantom has been demonstrated and used in an initial assessment of CT segmentation accuracy using freely available software developed for MRI. John Wiley and Sons Inc. 2020-03-31 2020-06 /pmc/articles/PMC7383927/ /pubmed/32160322 http://dx.doi.org/10.1002/mp.14127 Text en © 2020 The Authors. Medical Physics published by Wiley Periodicals LLC on behalf of American Association of Physicists in Medicine This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | DIAGNOSTIC IMAGING (IONIZING AND NON‐IONIZING) Holmes, Robin B. Negus, Ian S. Wiltshire, Sophie J. Thorne, Gareth C. Young, Peter Creation of an anthropomorphic CT head phantom for verification of image segmentation |
title | Creation of an anthropomorphic CT head phantom for verification of image segmentation |
title_full | Creation of an anthropomorphic CT head phantom for verification of image segmentation |
title_fullStr | Creation of an anthropomorphic CT head phantom for verification of image segmentation |
title_full_unstemmed | Creation of an anthropomorphic CT head phantom for verification of image segmentation |
title_short | Creation of an anthropomorphic CT head phantom for verification of image segmentation |
title_sort | creation of an anthropomorphic ct head phantom for verification of image segmentation |
topic | DIAGNOSTIC IMAGING (IONIZING AND NON‐IONIZING) |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7383927/ https://www.ncbi.nlm.nih.gov/pubmed/32160322 http://dx.doi.org/10.1002/mp.14127 |
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