Skip to main content
Top
Published in: European Radiology 2/2022

Open Access 01-02-2022 | Computed Tomography | Computed Tomography

Comparison of low-contrast detectability between uniform and anatomically realistic phantoms—influences on CT image quality assessment

Authors: Juliane Conzelmann, Ulrich Genske, Arthur Emig, Michael Scheel, Bernd Hamm, Paul Jahnke

Published in: European Radiology | Issue 2/2022

Login to get access

Abstract

Objectives

To evaluate the effects of anatomical phantom structure on task-based image quality assessment compared with a uniform phantom background.

Methods

Two neck phantom types of identical shape were investigated: a uniform type containing 10-mm lesions with 4, 9, 18, 30, and 38 HU contrast to the surrounding area and an anatomically realistic type containing lesions of the same size and location with 10, 18, 30, and 38 HU contrast. Phantom images were acquired at two dose levels (CTDIvol of 1.4 and 5.6 mGy) and reconstructed using filtered back projection (FBP) and adaptive iterative dose reduction 3D (AIDR 3D). Detection accuracy was evaluated by seven radiologists in a 4-alternative forced choice experiment.

Results

Anatomical phantom structure impaired lesion detection at all lesion contrasts (p < 0.01). Detectability in the anatomical phantom at 30 HU contrast was similar to 9 HU contrast in uniform images (91.1% vs. 89.5%). Detection accuracy decreased from 83.6% at 5.6 mGy to 55.4% at 1.4 mGy in uniform FBP images (p < 0.001), whereas AIDR 3D preserved detectability at 1.4 mGy (80.7% vs. 85% at 5.6 mGy, p = 0.375) and was superior to FBP (p < 0.001). In the assessment of anatomical images, superiority of AIDR 3D was not confirmed and dose reduction moderately affected detectability (74.6% vs. 68.2%, p = 0.027 for FBP and 81.1% vs. 73%, p = 0.018 for AIDR 3D).

Conclusions

A lesion contrast increase from 9 to 30 HU is necessary for similar detectability in anatomical and uniform neck phantom images. Anatomical phantom structure influences task-based assessment of iterative reconstruction and dose effects.

Key Points

• A lesion contrast increase from 9 to 30 HU is necessary for similar low-contrast detectability in anatomical and uniform neck phantom images.
• Phantom background structure influences task-based assessment of iterative reconstruction and dose effects.
• Transferability of CT assessment to clinical imaging can be expected to improve as the realism of the test environment increases.
Appendix
Available only for authorised users
Literature
1.
go back to reference Racine D, Ryckx N, Ba A et al (2018) Task-based quantification of image quality using a model observer in abdominal CT: a multicentre study. Eur Radiol 28:5203–5210CrossRef Racine D, Ryckx N, Ba A et al (2018) Task-based quantification of image quality using a model observer in abdominal CT: a multicentre study. Eur Radiol 28:5203–5210CrossRef
2.
go back to reference Vaishnav JY, Jung WC, Popescu LM, Zeng R, Myers KJ (2014) Objective assessment of image quality and dose reduction in CT iterative reconstruction. Med Phys 41:071904CrossRef Vaishnav JY, Jung WC, Popescu LM, Zeng R, Myers KJ (2014) Objective assessment of image quality and dose reduction in CT iterative reconstruction. Med Phys 41:071904CrossRef
3.
go back to reference Barrett HH, Myers KJ, Hoeschen C, Kupinski MA, Little MP (2015) Task-based measures of image quality and their relation to radiation dose and patient risk. Phys Med Biol 60:R1-75CrossRef Barrett HH, Myers KJ, Hoeschen C, Kupinski MA, Little MP (2015) Task-based measures of image quality and their relation to radiation dose and patient risk. Phys Med Biol 60:R1-75CrossRef
4.
go back to reference Samei E, Bakalyar D, Boedeker KL et al (2019) Performance evaluation of computed tomography systems: summary of AAPM Task Group 233. Med Phys 46:e735–e756CrossRef Samei E, Bakalyar D, Boedeker KL et al (2019) Performance evaluation of computed tomography systems: summary of AAPM Task Group 233. Med Phys 46:e735–e756CrossRef
5.
go back to reference Samei E, Flynn MJ, Eyler WR (1999) Detection of subtle lung nodules: relative influence of quantum and anatomic noise on chest radiographs. Radiology 213:727–734CrossRef Samei E, Flynn MJ, Eyler WR (1999) Detection of subtle lung nodules: relative influence of quantum and anatomic noise on chest radiographs. Radiology 213:727–734CrossRef
6.
go back to reference Kotre CJ (1998) The effect of background structure on the detection of low contrast objects in mammography. Br J Radiol 71:1162–1167CrossRef Kotre CJ (1998) The effect of background structure on the detection of low contrast objects in mammography. Br J Radiol 71:1162–1167CrossRef
7.
go back to reference Bochud FO, Valley JF, Verdun FR, Hessler C, Schnyder P (1999) Estimation of the noisy component of anatomical backgrounds. Med Phys 26:1365–1370CrossRef Bochud FO, Valley JF, Verdun FR, Hessler C, Schnyder P (1999) Estimation of the noisy component of anatomical backgrounds. Med Phys 26:1365–1370CrossRef
8.
go back to reference Solomon J, Ba A, Bochud F, Samei E (2016) Comparison of low-contrast detectability between two CT reconstruction algorithms using voxel-based 3D printed textured phantoms. Med Phys 43:6497CrossRef Solomon J, Ba A, Bochud F, Samei E (2016) Comparison of low-contrast detectability between two CT reconstruction algorithms using voxel-based 3D printed textured phantoms. Med Phys 43:6497CrossRef
9.
go back to reference Dilger SKN, Yu L, Chen B et al (2019) Localization of liver lesions in abdominal CT imaging: I. Correlation of human observer performance between anatomical and uniform backgrounds. Phys Med Biol 64:105011CrossRef Dilger SKN, Yu L, Chen B et al (2019) Localization of liver lesions in abdominal CT imaging: I. Correlation of human observer performance between anatomical and uniform backgrounds. Phys Med Biol 64:105011CrossRef
10.
go back to reference Ardila Pardo GL, Conzelmann J, Genske U, Hamm B, Scheel M, Jahnke P (2020) 3D printing of anatomically realistic phantoms with detection tasks to assess the diagnostic performance of CT images. Eur Radiol 30:4557–4563CrossRef Ardila Pardo GL, Conzelmann J, Genske U, Hamm B, Scheel M, Jahnke P (2020) 3D printing of anatomically realistic phantoms with detection tasks to assess the diagnostic performance of CT images. Eur Radiol 30:4557–4563CrossRef
12.
go back to reference Dolly S, Chen HC, Anastasio M, Mutic S, Li H (2016) Practical considerations for noise power spectra estimation for clinical CT scanners. J Appl Clin Med Phys 17:392–407CrossRef Dolly S, Chen HC, Anastasio M, Mutic S, Li H (2016) Practical considerations for noise power spectra estimation for clinical CT scanners. J Appl Clin Med Phys 17:392–407CrossRef
13.
go back to reference Euler A, Stieltjes B, Szucs-Farkas Z et al (2017) Impact of model-based iterative reconstruction on low-contrast lesion detection and image quality in abdominal CT: a 12-reader-based comparative phantom study with filtered back projection at different tube voltages. Eur Radiol 27:5252–5259CrossRef Euler A, Stieltjes B, Szucs-Farkas Z et al (2017) Impact of model-based iterative reconstruction on low-contrast lesion detection and image quality in abdominal CT: a 12-reader-based comparative phantom study with filtered back projection at different tube voltages. Eur Radiol 27:5252–5259CrossRef
14.
go back to reference Schindera ST, Odedra D, Raza SA et al (2013) Iterative reconstruction algorithm for CT: can radiation dose be decreased while low-contrast detectability is preserved? Radiology 269:511–518CrossRef Schindera ST, Odedra D, Raza SA et al (2013) Iterative reconstruction algorithm for CT: can radiation dose be decreased while low-contrast detectability is preserved? Radiology 269:511–518CrossRef
15.
go back to reference Ba A, Abbey CK, Racine D et al (2019) Channelized Hotelling observer correlation with human observers for low-contrast detection in liver CT images. J Med Imaging (Bellingham) 6:025501 Ba A, Abbey CK, Racine D et al (2019) Channelized Hotelling observer correlation with human observers for low-contrast detection in liver CT images. J Med Imaging (Bellingham) 6:025501
16.
go back to reference Solomon J, Samei E (2014) Quantum noise properties of CT images with anatomical textured backgrounds across reconstruction algorithms: FBP and SAFIRE. Med Phys 41:091908CrossRef Solomon J, Samei E (2014) Quantum noise properties of CT images with anatomical textured backgrounds across reconstruction algorithms: FBP and SAFIRE. Med Phys 41:091908CrossRef
17.
go back to reference Richard S, Husarik DB, Yadava G, Murphy SN, Samei E (2012) Towards task-based assessment of CT performance: system and object MTF across different reconstruction algorithms. Med Phys 39:4115–4122CrossRef Richard S, Husarik DB, Yadava G, Murphy SN, Samei E (2012) Towards task-based assessment of CT performance: system and object MTF across different reconstruction algorithms. Med Phys 39:4115–4122CrossRef
18.
go back to reference Yu L, Vrieze TJ, Leng S, Fletcher JG, McCollough CH (2015) Technical note: measuring contrast- and noise-dependent spatial resolution of an iterative reconstruction method in CT using ensemble averaging. Med Phys 42:2261–2267CrossRef Yu L, Vrieze TJ, Leng S, Fletcher JG, McCollough CH (2015) Technical note: measuring contrast- and noise-dependent spatial resolution of an iterative reconstruction method in CT using ensemble averaging. Med Phys 42:2261–2267CrossRef
19.
go back to reference Joemai RM, Veldkamp WJ, Kroft LJ, Hernandez-Giron I, Geleijns J (2013) Adaptive iterative dose reduction 3D versus filtered back projection in CT: evaluation of image quality. AJR Am J Roentgenol 201:1291–1297CrossRef Joemai RM, Veldkamp WJ, Kroft LJ, Hernandez-Giron I, Geleijns J (2013) Adaptive iterative dose reduction 3D versus filtered back projection in CT: evaluation of image quality. AJR Am J Roentgenol 201:1291–1297CrossRef
20.
go back to reference Samei E, Flynn MJ, Peterson E, Eyler WR (2003) Subtle lung nodules: influence of local anatomic variations on detection. Radiology 228:76–84CrossRef Samei E, Flynn MJ, Peterson E, Eyler WR (2003) Subtle lung nodules: influence of local anatomic variations on detection. Radiology 228:76–84CrossRef
21.
go back to reference Smith TB, Rubin GD, Solomon J, Harrawood B, Choudhury KR, Samei E (2018) Local complexity metrics to quantify the effect of anatomical noise on detectability of lung nodules in chest CT imaging. J Med Imaging (Bellingham) 5:045502 Smith TB, Rubin GD, Solomon J, Harrawood B, Choudhury KR, Samei E (2018) Local complexity metrics to quantify the effect of anatomical noise on detectability of lung nodules in chest CT imaging. J Med Imaging (Bellingham) 5:045502
22.
go back to reference Jahnke P, Conzelmann J, Genske U et al (2021) Task-based assessment of neck CT protocols using patient-mimicking phantoms-effects of protocol parameters on dose and diagnostic performance. Eur Radiol 31:3177–3186CrossRef Jahnke P, Conzelmann J, Genske U et al (2021) Task-based assessment of neck CT protocols using patient-mimicking phantoms-effects of protocol parameters on dose and diagnostic performance. Eur Radiol 31:3177–3186CrossRef
Metadata
Title
Comparison of low-contrast detectability between uniform and anatomically realistic phantoms—influences on CT image quality assessment
Authors
Juliane Conzelmann
Ulrich Genske
Arthur Emig
Michael Scheel
Bernd Hamm
Paul Jahnke
Publication date
01-02-2022
Publisher
Springer Berlin Heidelberg
Published in
European Radiology / Issue 2/2022
Print ISSN: 0938-7994
Electronic ISSN: 1432-1084
DOI
https://doi.org/10.1007/s00330-021-08248-3

Other articles of this Issue 2/2022

European Radiology 2/2022 Go to the issue