Creation of an anthropomorphic CT head phantom for verification of image segmentation.


Journal

Medical physics
ISSN: 2473-4209
Titre abrégé: Med Phys
Pays: United States
ID NLM: 0425746

Informations de publication

Date de publication:
Jun 2020
Historique:
received: 10 01 2019
revised: 21 02 2020
accepted: 21 02 2020
pubmed: 12 3 2020
medline: 15 5 2021
entrez: 12 3 2020
Statut: ppublish

Résumé

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. 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. 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. 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.

Identifiants

pubmed: 32160322
doi: 10.1002/mp.14127
pmc: PMC7383927
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

2380-2391

Subventions

Organisme : Alzheimer's Disease Neuroimaging Initiative
Organisme : Alzheimer's Drug Discovery Foundation
Organisme : Takeda Pharmaceutical Company
Organisme : GE Healthcare
Organisme : Transition Therapeutics
Organisme : F. Hoffmann-La Roche Ltd
Organisme : Eli Lilly and Company
Organisme : Merck & Co., Inc.
Organisme : Eisai Inc.
Organisme : Department of Defense
ID : W81XWH-12-2-0012
Organisme : EuroImmun
Organisme : Biogen
Organisme : Johnson & Johnson Pharmaceutical Research & Development LLC.
Organisme : Lumosity
Organisme : Bristol-Myers Squibb Company
Organisme : NIA NIH HHS
ID : U01 AG024904
Pays : United States
Organisme : Genentech, Inc.
Organisme : UK National Institute for Health Research
Organisme : Araclon Biotech
Organisme : NIH HHS
ID : U01 AG024904
Pays : United States
Organisme : Novartis Pharmaceuticals Corporation
Organisme : Meso Scale Diagnostics, LLC.
Organisme : CereSpir, Inc.
Organisme : Northern California Institute for Research and Education
Organisme : University of Liverpool
Organisme : BioClinica, Inc.
Organisme : Janssen Alzheimer Immunotherapy Research & Development, LLC.
Organisme : AbbVie
Organisme : Cogstate
Organisme : University of Southern California
Organisme : NIBIB NIH HHS
Pays : United States
Organisme : The Canadian Institutes of Health Research
Organisme : Piramal Imaging; Servier
Organisme : NIH HHS
Pays : United States
Organisme : Pfizer Inc.
Organisme : Elan Pharmaceuticals, Inc.
Organisme : IXICO Ltd.
Organisme : NeuroRx Research
Organisme : Alzheimer's Association
Organisme : Neurotrack Technologies
Organisme : Fujirebio
Organisme : Lundbeck

Informations de copyright

© 2020 The Authors. Medical Physics published by Wiley Periodicals LLC on behalf of American Association of Physicists in Medicine.

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Auteurs

Robin B Holmes (RB)

Department of Medical Physics and Bioengineering, University Hospitals Bristol NHS Foundation Trust, Bristol, BS28HW, UK.

Ian S Negus (IS)

Department of Medical Physics and Bioengineering, University Hospitals Bristol NHS Foundation Trust, Bristol, BS28HW, UK.

Sophie J Wiltshire (SJ)

Department of Medical Physics and Bioengineering, University Hospitals Bristol NHS Foundation Trust, Bristol, BS28HW, UK.

Gareth C Thorne (GC)

Department of Medical Physics and Bioengineering, University Hospitals Bristol NHS Foundation Trust, Bristol, BS28HW, UK.

Peter Young (P)

Umea Functional Brain Imaging Center, Umea University, 901 87, Umea, Sweden.

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