Low contrast detectability and spatial resolution with model-based Iterative reconstructions of MDCT images: a phantom and cadaveric study.

Millon, Domitille;Vlassenbroek, Alain;Van Maanen, Aline G;Cambier, Samantha;Coche, Emmanuel
(2017) European Radiology : journal of the European Congress of Radiology — Vol. 27, n° 3, p. 927-937 (2017)

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Authors
  • Millon, DomitilleUCLouvain
    Author
  • Vlassenbroek, Alain
    Author
  • Van Maanen, Aline GUCLouvain
    Author
  • Cambier, SamanthaUCLouvain
    Author
  • Author
Abstract
OBJECTIVES: To compare image quality [low contrast (LC) detectability, noise, contrast-to-noise (CNR) and spatial resolution (SR)] of MDCT images reconstructed with an iterative reconstruction (IR) algorithm and a filtered back projection (FBP) algorithm. METHODS: The experimental study was performed on a 256-slice MDCT. LC detectability, noise, CNR and SR were measured on a Catphan phantom scanned with decreasing doses (48.8 down to 0.7 mGy) and parameters typical of a chest CT examination. Images were reconstructed with FBP and a model-based IR algorithm. Additionally, human chest cadavers were scanned and reconstructed using the same technical parameters. Images were analyzed to illustrate the phantom results. RESULTS: LC detectability and noise were statistically significantly different between the techniques, supporting model-based IR algorithm (p < 0.0001). At low doses, the noise in FBP images only enabled SR measurements of high contrast objects. The superior CNR of model-based IR algorithm enabled lower dose measurements, which showed that SR was dose and contrast dependent. Cadaver images reconstructed with model-based IR illustrated that visibility and delineation of anatomical structure edges could be deteriorated at low doses. CONCLUSION: Model-based IR improved LC detectability and enabled dose reduction. At low dose, SR became dose and contrast dependent. KEY POINTS: • Model- based Iterative Reconstruction improves detectability of low contrast object. • With model- based Iterative Reconstruction, spatial resolution is dose and contrast dependent. • Model-based Iterative Reconstruction algorithms enable improved IQ combined with dose-reduction possibilities. • Improvement of SR and LC detectability on the same IMR data set would reduce reconstructions.
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Citations

Millon, D., Vlassenbroek, A., Van Maanen, A. G., Cambier, S., & Coche, E. (2017). Low contrast detectability and spatial resolution with model-based Iterative reconstructions of MDCT images: a phantom and cadaveric study. European Radiology : journal of the European Congress of Radiology, 27(3), 927-937. https://doi.org/10.1007/s00330-016-4444-x (Original work published 2017)