Cargando…

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Conzelmann, Juliane, Schwarz, Felix Benjamin, Hamm, Bernd, Scheel, Michael, Jahnke, Paul
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2020
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
_version_ 1783583406476492800
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
work_keys_str_mv AT conzelmannjuliane developmentofamethodtocreateuniformphantomsfortaskbasedassessmentofctimagequality
AT schwarzfelixbenjamin developmentofamethodtocreateuniformphantomsfortaskbasedassessmentofctimagequality
AT hammbernd developmentofamethodtocreateuniformphantomsfortaskbasedassessmentofctimagequality
AT scheelmichael developmentofamethodtocreateuniformphantomsfortaskbasedassessmentofctimagequality
AT jahnkepaul developmentofamethodtocreateuniformphantomsfortaskbasedassessmentofctimagequality