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Development and validation of an automated methodology to assess perceptual in vivo noise texture in liver CT.

Publication ,  Journal Article
Smith, TB; Abadi, E; Sauer, TJ; Fu, W; Solomon, J; Samei, E
Published in: J Med Imaging (Bellingham)
September 2021

Purpose: Developing, validating, and evaluating a method for measuring noise texture directly from patient liver CT images (i.e., in vivo). Approach: The method identifies target regions within patient scans that are least likely to have major contribution of patient anatomy, detrends them locally, and measures noise power spectrum (NPS) there using a previously phantom-validated technique targeting perceptual noise-non-anatomical fluctuations in the image that may interfere with the detection of focal lesions. Method development and validation used scanner-specific CT simulations of computational, anthropomorphic phantom (XCAT phantom, three phases of contrast-enhancement) with known ground truth of the NPS. Simulations were based on a clinical scanner (Definition Flash, Siemens) and clinically relevant settings (tube voltage of 120 kV at three dose levels). Images were reconstructed with filtered backprojection (kernel: B31, B41, and B50) and Sinogram Affirmed Iterative Reconstruction (kernel: I31, I41, and I50) using a manufacturer-specific reconstruction software (ReconCT, Siemens). All NPS measurements were made in the liver. Ground-truth NPS were taken as the sum of (1) a measurement in parenchymal regions of anatomy-subtracted (i.e., noise only) scans, and (2) a measurement in the same region of noise-free (pre-noise-insertion) images. To assess in vivo NPS performance, correlation of NPS average frequency ( f avg ), was reported. Sensitivity of accuracy [root-mean-square-error (RMSE)] to number of pixels included in measurement was conducted via bootstrapped pixel-dropout. Sensitivity of NPS to dose and reconstruction kernel was assessed to confirm that ground truth NPS similarities were maintained in patient-specific measurements. Results: Pearson and Spearman correlation coefficients 0.97 and 0.96 for f avg indicated good correlation. Results suggested accurate NPS measurements (within 5% total RMSE) could be acquired with ∼ 10 6    pixels . Conclusions: Relationships of similar NPS due to reconstruction kernel and dose were preserved between gold standard and observed in vivo estimations. The NPS estimation method was further deployed on clinical cases to demonstrate the feasibility of clinical analysis.

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Published In

J Med Imaging (Bellingham)

DOI

ISSN

2329-4302

Publication Date

September 2021

Volume

8

Issue

5

Start / End Page

052113

Location

United States

Related Subject Headings

  • 4003 Biomedical engineering
  • 3202 Clinical sciences
 

Citation

APA
Chicago
ICMJE
MLA
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Smith, T. B., Abadi, E., Sauer, T. J., Fu, W., Solomon, J., & Samei, E. (2021). Development and validation of an automated methodology to assess perceptual in vivo noise texture in liver CT. J Med Imaging (Bellingham), 8(5), 052113. https://doi.org/10.1117/1.JMI.8.5.052113
Smith, Taylor Brunton, Ehsan Abadi, Thomas J. Sauer, Wanyi Fu, Justin Solomon, and Ehsan Samei. “Development and validation of an automated methodology to assess perceptual in vivo noise texture in liver CT.J Med Imaging (Bellingham) 8, no. 5 (September 2021): 052113. https://doi.org/10.1117/1.JMI.8.5.052113.
Smith TB, Abadi E, Sauer TJ, Fu W, Solomon J, Samei E. Development and validation of an automated methodology to assess perceptual in vivo noise texture in liver CT. J Med Imaging (Bellingham). 2021 Sep;8(5):052113.
Smith, Taylor Brunton, et al. “Development and validation of an automated methodology to assess perceptual in vivo noise texture in liver CT.J Med Imaging (Bellingham), vol. 8, no. 5, Sept. 2021, p. 052113. Pubmed, doi:10.1117/1.JMI.8.5.052113.
Smith TB, Abadi E, Sauer TJ, Fu W, Solomon J, Samei E. Development and validation of an automated methodology to assess perceptual in vivo noise texture in liver CT. J Med Imaging (Bellingham). 2021 Sep;8(5):052113.

Published In

J Med Imaging (Bellingham)

DOI

ISSN

2329-4302

Publication Date

September 2021

Volume

8

Issue

5

Start / End Page

052113

Location

United States

Related Subject Headings

  • 4003 Biomedical engineering
  • 3202 Clinical sciences