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Development of a method to create uniform phantoms for task‐based assessment of CT image quality
PURPOSE: To develop a customized method to produce uniform phantoms for task‐based assessment of CT image quality. METHODS: Contrasts between polymethyl methacrylate (PMMA) and fructose solutions of different concentrations (240, 250, 260, 280, 290, 300, 310, 320, 330, and 340 mg/mL) were calculated...
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/PMC7497917/ https://www.ncbi.nlm.nih.gov/pubmed/32721106 http://dx.doi.org/10.1002/acm2.12974 |
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author | Conzelmann, Juliane Schwarz, Felix Benjamin Hamm, Bernd Scheel, Michael Jahnke, Paul |
author_facet | Conzelmann, Juliane Schwarz, Felix Benjamin Hamm, Bernd Scheel, Michael Jahnke, Paul |
author_sort | Conzelmann, Juliane |
collection | PubMed |
description | PURPOSE: To develop a customized method to produce uniform phantoms for task‐based assessment of CT image quality. METHODS: Contrasts between polymethyl methacrylate (PMMA) and fructose solutions of different concentrations (240, 250, 260, 280, 290, 300, 310, 320, 330, and 340 mg/mL) were calculated. A phantom was produced by laser cutting PMMA slabs to the shape of a patient’s neck. An opening of 10 mm diameter was cut into the left parapharyngeal space. An angioplasty balloon was inserted and filled with the fructose solutions to simulate low‐contrast lesions. The phantom was scanned with six tube currents. Images were reconstructed with filtered back projection (FBP) and adaptive iterative dose reduction 3D (AIDR 3D). Calculated and measured contrasts were compared. The phantom was evaluated in a detectability experiment using images with 4 and 20 HU lesion contrast. RESULTS: Low‐contrast lesions of 4, 9, 11, 13, 18, 20, 24, 30, 35, and 37 HU contrast were simulated. Calculated and measured contrasts correlated excellently (r = 0.998; 95% confidence interval: 0.991 to 1). The mean ± SD difference was 0.41 ± 2.32 HU (P < 0.0001). Detection accuracy and reader confidence were 62.9 ± 18.2% and 1.58 ± 0.68 for 4 HU lesion contrast and 99.6 ± 1.3% and 4.27 ± 0.92 for 20 HU lesion contrast (P < 0.0001), confirming that the method produced lesions at the threshold of detectability. CONCLUSION: A cost‐effective and flexible approach was developed to create uniform phantoms with low‐contrast signals. The method should facilitate access to customized phantoms for task‐based image quality assessment. |
format | Online Article Text |
id | pubmed-7497917 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-74979172020-09-25 Development of a method to create uniform phantoms for task‐based assessment of CT image quality Conzelmann, Juliane Schwarz, Felix Benjamin Hamm, Bernd Scheel, Michael Jahnke, Paul J Appl Clin Med Phys Medical Imaging PURPOSE: To develop a customized method to produce uniform phantoms for task‐based assessment of CT image quality. METHODS: Contrasts between polymethyl methacrylate (PMMA) and fructose solutions of different concentrations (240, 250, 260, 280, 290, 300, 310, 320, 330, and 340 mg/mL) were calculated. A phantom was produced by laser cutting PMMA slabs to the shape of a patient’s neck. An opening of 10 mm diameter was cut into the left parapharyngeal space. An angioplasty balloon was inserted and filled with the fructose solutions to simulate low‐contrast lesions. The phantom was scanned with six tube currents. Images were reconstructed with filtered back projection (FBP) and adaptive iterative dose reduction 3D (AIDR 3D). Calculated and measured contrasts were compared. The phantom was evaluated in a detectability experiment using images with 4 and 20 HU lesion contrast. RESULTS: Low‐contrast lesions of 4, 9, 11, 13, 18, 20, 24, 30, 35, and 37 HU contrast were simulated. Calculated and measured contrasts correlated excellently (r = 0.998; 95% confidence interval: 0.991 to 1). The mean ± SD difference was 0.41 ± 2.32 HU (P < 0.0001). Detection accuracy and reader confidence were 62.9 ± 18.2% and 1.58 ± 0.68 for 4 HU lesion contrast and 99.6 ± 1.3% and 4.27 ± 0.92 for 20 HU lesion contrast (P < 0.0001), confirming that the method produced lesions at the threshold of detectability. CONCLUSION: A cost‐effective and flexible approach was developed to create uniform phantoms with low‐contrast signals. The method should facilitate access to customized phantoms for task‐based image quality assessment. John Wiley and Sons Inc. 2020-07-28 /pmc/articles/PMC7497917/ /pubmed/32721106 http://dx.doi.org/10.1002/acm2.12974 Text en © 2020 The Authors. Journal of Applied Clinical Medical Physics published by Wiley Periodicals, Inc. 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 | Medical Imaging Conzelmann, Juliane Schwarz, Felix Benjamin Hamm, Bernd Scheel, Michael Jahnke, Paul Development of a method to create uniform phantoms for task‐based assessment of CT image quality |
title | Development of a method to create uniform phantoms for task‐based assessment of CT image quality |
title_full | Development of a method to create uniform phantoms for task‐based assessment of CT image quality |
title_fullStr | Development of a method to create uniform phantoms for task‐based assessment of CT image quality |
title_full_unstemmed | Development of a method to create uniform phantoms for task‐based assessment of CT image quality |
title_short | Development of a method to create uniform phantoms for task‐based assessment of CT image quality |
title_sort | development of a method to create uniform phantoms for task‐based assessment of ct image quality |
topic | Medical Imaging |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7497917/ https://www.ncbi.nlm.nih.gov/pubmed/32721106 http://dx.doi.org/10.1002/acm2.12974 |
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