Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2021 Sep 10;5(1):39.
doi: 10.1186/s41747-021-00237-x.

Improved precision of noise estimation in CT with a volume-based approach

Hendrik Joost Wisselink  1 , Gert Jan Pelgrim  1 , Mieneke Rook  1   2 , Ivan Dudurych  1 , Maarten van den Berge  3 , Geertruida H de Bock  4 , Rozemarijn Vliegenthart  5
Affiliations

Improved precision of noise estimation in CT with a volume-based approach

Hendrik Joost Wisselink et al. Eur Radiol Exp. .

Abstract

Assessment of image noise is a relevant issue in computed tomography (CT). Noise is routinely measured by the standard deviation of density values (Hounsfield units, HU) within a circular region of interest (ROI). We explored the effect of a spherical volume of interest (VOI) on noise measurements. Forty-nine chronic obstructive pulmonary disease patients underwent CT with clinical protocol (regular dose [RD], volumetric CT dose index [CTDIvol] 3.04 mGy, 64-slice unit), and ultra-low dose (ULD) protocol (median CTDIvol 0.38 mGy, dual-source unit). Noise was measured in 27 1-cm2 ROIs and 27 0.75-cm3 VOIs inside the trachea. Median true noise was 21 HU (range 17-29) for RD-CT and 33 HU (26-39) for ULD-CT. The VOI approach resulted in a lower mean distance between limits of agreement compared to ROI: 5.9 versus 10.0 HU for RD-CT (-40%); 4.7 versus 9.9 HU for ULD-CT (-53%). Mean systematic bias barely changed: -1.6 versus -0.9HU for RD-CT; 0.0 to 0.4HU for ULD-CT. The average measurement time was 6.8 s (ROI) versus 9.7 (VOI), independent of dose level. For chest CT, measuring noise with a VOI-based instead of a ROI-based approach reduces variability by 40-53%, without a relevant effect on systematic bias and measurement time.

Trial registration: ClinicalTrials.gov NCT02477397.

Keywords: Data accuracy; Noise; Pulmonary disease (chronic obstructive); Thorax; Tomography (x-ray computed).

PubMed Disclaimer

Conflict of interest statement

RV is supported by an institutional grant from Siemens Healthineers. The other authors have no competing interests to be declared.

Figures

Fig. 1
Fig. 1
Flow chart of the steps to determine the ground truth noise and the isocenter for the measurements. ROI, region of interest; VOI, volume of interest
Fig. 2
Fig. 2
Subsection of the CT images around the carina (window width 1600 HU, window level −700 HU). The red part is the position of the region of interest, the blue is the volume of interest, the yellow is used to measure the ground truth, and the green area was removed from the segmentation to prevent edge artifacts like the partial volume effect. This image shows the measurement with the isocenter 1.0 cm above the carina ridge. a Axial images. b Coronal images, interpolated to account for the anisotropic dimensions of the voxels. c Volume render of the yellow segmentation
Fig. 3
Fig. 3
Results of the Bland-Altman analyses. Each plot shows the difference between the noise measured with either ROI or VOI and ground truth noise on the y-axis, versus ground truth on the x-axis. Regular radiation dose computed tomography protocol measured with an ROI (a) or a VOI (b), same data for ultra-low dose protocol (c and d, respectively). ROI, region of interest; VOI, volume of interest; LoA, limits of agreement; HU, Hounsfield units
See this image and copyright information in PMC

References

    1. European Commission (2000) European guidelines on quality criteria for CT, available at https://op.europa.eu/s/n8PM, archived at http://web.archive.org/web/20210225144451/https://op.europa.eu/o/opporta.... Office for Official Publications of the European Communities
    1. Messerli M, Ottilinger T, Warschkow R, Leschka S, Alkadhi H, Wildermuth S, Bauer RW. Emphysema quantification and lung volumetry in chest X-ray equivalent ultralow dose CT–intra-individual comparison with standard dose CT. Eur J Radiol. 2017;91:1–9. doi: 10.1016/j.ejrad.2017.03.003. - DOI - PubMed
    1. den Harder AM, de Boer E, Lagerweij SJ, Boomsma MF, Schilham AMR, Willemink MJ, Milles J, Leiner T, Budde RPJ, de Jong PA. Emphysema quantification using chest CT: influence of radiation dose reduction and reconstruction technique. Eur Radiol Exp. 2018;2:30. doi: 10.1186/s41747-018-0064-3. - DOI - PMC - PubMed
    1. Martin SP, Gariani J, Feutry G, Adler D, Karenovics W, Becker CD, Montet X. Emphysema quantification using hybrid versus model-based generations of iterative reconstruction: SAFIRE versus ADMIRE. Medicine. 2019;98:e14450. doi: 10.1097/MD.0000000000014450. - DOI - PMC - PubMed
    1. Wisselink HJ, Pelgrim GJ, Rook M, van den Berge M, Slump K, Nagaraj Y, van Ooijen P, Oudkerk M, Vliegenthart R. Potential for dose reduction in CT emphysema densitometry with post-scan noise reduction: a phantom study. Br J Radiol. 2019;93:20181019. doi: 10.1259/bjr.20181019. - DOI - PMC - PubMed

Publication types

Associated data