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A Third-Generation Adaptive Statistical Iterative Reconstruction Technique: Phantom Study of Image Noise, Spatial Resolution, Lesion Detectability, and Dose Reduction Potential.

Publication ,  Journal Article
Euler, A; Solomon, J; Marin, D; Nelson, RC; Samei, E
Published in: AJR Am J Roentgenol
June 2018

OBJECTIVE: The purpose of this study was to assess image noise, spatial resolution, lesion detectability, and the dose reduction potential of a proprietary third-generation adaptive statistical iterative reconstruction (ASIR-V) technique. MATERIALS AND METHODS: A phantom representing five different body sizes (12-37 cm) and a contrast-detail phantom containing lesions of five low-contrast levels (5-20 HU) and three sizes (2-6 mm) were deployed. Both phantoms were scanned on a 256-MDCT scanner at six different radiation doses (1.25-10 mGy). Images were reconstructed with filtered back projection (FBP), ASIR-V with 50% blending with FBP (ASIR-V 50%), and ASIR-V without blending (ASIR-V 100%). In the first phantom, noise properties were assessed by noise power spectrum analysis. Spatial resolution properties were measured by use of task transfer functions for objects of different contrasts. Noise magnitude, noise texture, and resolution were compared between the three groups. In the second phantom, low-contrast detectability was assessed by nine human readers independently for each condition. The dose reduction potential of ASIR-V was estimated on the basis of a generalized linear statistical regression model. RESULTS: On average, image noise was reduced 37.3% with ASIR-V 50% and 71.5% with ASIR-V 100% compared with FBP. ASIR-V shifted the noise power spectrum toward lower frequencies compared with FBP. The spatial resolution of ASIR-V was equivalent or slightly superior to that of FBP, except for the low-contrast object, which had lower resolution. Lesion detection significantly increased with both ASIR-V levels (p = 0.001), with an estimated radiation dose reduction potential of 15% ± 5% (SD) for ASIR-V 50% and 31% ± 9% for ASIR-V 100%. CONCLUSION: ASIR-V reduced image noise and improved lesion detection compared with FBP and had potential for radiation dose reduction while preserving low-contrast detectability.

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Published In

AJR Am J Roentgenol

DOI

EISSN

1546-3141

Publication Date

June 2018

Volume

210

Issue

6

Start / End Page

1301 / 1308

Location

United States

Related Subject Headings

  • Tomography, X-Ray Computed
  • Radiographic Image Interpretation, Computer-Assisted
  • Radiation Dosage
  • Phantoms, Imaging
  • Nuclear Medicine & Medical Imaging
  • Models, Statistical
  • Humans
  • Data Interpretation, Statistical
  • Body Size
  • Algorithms
 

Citation

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Euler, A., Solomon, J., Marin, D., Nelson, R. C., & Samei, E. (2018). A Third-Generation Adaptive Statistical Iterative Reconstruction Technique: Phantom Study of Image Noise, Spatial Resolution, Lesion Detectability, and Dose Reduction Potential. AJR Am J Roentgenol, 210(6), 1301–1308. https://doi.org/10.2214/AJR.17.19102
Euler, André, Justin Solomon, Daniele Marin, Rendon C. Nelson, and Ehsan Samei. “A Third-Generation Adaptive Statistical Iterative Reconstruction Technique: Phantom Study of Image Noise, Spatial Resolution, Lesion Detectability, and Dose Reduction Potential.AJR Am J Roentgenol 210, no. 6 (June 2018): 1301–8. https://doi.org/10.2214/AJR.17.19102.
Euler, André, et al. “A Third-Generation Adaptive Statistical Iterative Reconstruction Technique: Phantom Study of Image Noise, Spatial Resolution, Lesion Detectability, and Dose Reduction Potential.AJR Am J Roentgenol, vol. 210, no. 6, June 2018, pp. 1301–08. Pubmed, doi:10.2214/AJR.17.19102.

Published In

AJR Am J Roentgenol

DOI

EISSN

1546-3141

Publication Date

June 2018

Volume

210

Issue

6

Start / End Page

1301 / 1308

Location

United States

Related Subject Headings

  • Tomography, X-Ray Computed
  • Radiographic Image Interpretation, Computer-Assisted
  • Radiation Dosage
  • Phantoms, Imaging
  • Nuclear Medicine & Medical Imaging
  • Models, Statistical
  • Humans
  • Data Interpretation, Statistical
  • Body Size
  • Algorithms