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Quantitative Features of Liver Lesions, Lung Nodules, and Renal Stones at Multi-Detector Row CT Examinations: Dependency on Radiation Dose and Reconstruction Algorithm.

Publication ,  Journal Article
Solomon, J; Mileto, A; Nelson, RC; Roy Choudhury, K; Samei, E
Published in: Radiology
April 2016

PURPOSE: To determine if radiation dose and reconstruction algorithm affect the computer-based extraction and analysis of quantitative imaging features in lung nodules, liver lesions, and renal stones at multi-detector row computed tomography (CT). MATERIALS AND METHODS: Retrospective analysis of data from a prospective, multicenter, HIPAA-compliant, institutional review board-approved clinical trial was performed by extracting 23 quantitative imaging features (size, shape, attenuation, edge sharpness, pixel value distribution, and texture) of lesions on multi-detector row CT images of 20 adult patients (14 men, six women; mean age, 63 years; range, 38-72 years) referred for known or suspected focal liver lesions, lung nodules, or kidney stones. Data were acquired between September 2011 and April 2012. All multi-detector row CT scans were performed at two different radiation dose levels; images were reconstructed with filtered back projection, adaptive statistical iterative reconstruction, and model-based iterative reconstruction (MBIR) algorithms. A linear mixed-effects model was used to assess the effect of radiation dose and reconstruction algorithm on extracted features. RESULTS: Among the 23 imaging features assessed, radiation dose had a significant effect on five, three, and four of the features for liver lesions, lung nodules, and renal stones, respectively (P < .002 for all comparisons). Adaptive statistical iterative reconstruction had a significant effect on three, one, and one of the features for liver lesions, lung nodules, and renal stones, respectively (P < .002 for all comparisons). MBIR reconstruction had a significant effect on nine, 11, and 15 of the features for liver lesions, lung nodules, and renal stones, respectively (P < .002 for all comparisons). Of note, the measured size of lung nodules and renal stones with MBIR was significantly different than those for the other two algorithms (P < .002 for all comparisons). Although lesion texture was significantly affected by the reconstruction algorithm used (average of 3.33 features affected by MBIR throughout lesion types; P < .002, for all comparisons), no significant effect of the radiation dose setting was observed for all but one of the texture features (P = .002-.998). CONCLUSION: Radiation dose settings and reconstruction algorithms affect the extraction and analysis of quantitative imaging features in lesions at multi-detector row CT.

Duke Scholars

Published In

Radiology

DOI

EISSN

1527-1315

Publication Date

April 2016

Volume

279

Issue

1

Start / End Page

185 / 194

Location

United States

Related Subject Headings

  • Retrospective Studies
  • Radiographic Image Interpretation, Computer-Assisted
  • Radiation Dosage
  • Nuclear Medicine & Medical Imaging
  • Multidetector Computed Tomography
  • Middle Aged
  • Male
  • Lung Diseases
  • Liver Diseases
  • Kidney Calculi
 

Citation

APA
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ICMJE
MLA
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Solomon, J., Mileto, A., Nelson, R. C., Roy Choudhury, K., & Samei, E. (2016). Quantitative Features of Liver Lesions, Lung Nodules, and Renal Stones at Multi-Detector Row CT Examinations: Dependency on Radiation Dose and Reconstruction Algorithm. Radiology, 279(1), 185–194. https://doi.org/10.1148/radiol.2015150892
Solomon, Justin, Achille Mileto, Rendon C. Nelson, Kingshuk Roy Choudhury, and Ehsan Samei. “Quantitative Features of Liver Lesions, Lung Nodules, and Renal Stones at Multi-Detector Row CT Examinations: Dependency on Radiation Dose and Reconstruction Algorithm.Radiology 279, no. 1 (April 2016): 185–94. https://doi.org/10.1148/radiol.2015150892.
Solomon, Justin, et al. “Quantitative Features of Liver Lesions, Lung Nodules, and Renal Stones at Multi-Detector Row CT Examinations: Dependency on Radiation Dose and Reconstruction Algorithm.Radiology, vol. 279, no. 1, Apr. 2016, pp. 185–94. Pubmed, doi:10.1148/radiol.2015150892.

Published In

Radiology

DOI

EISSN

1527-1315

Publication Date

April 2016

Volume

279

Issue

1

Start / End Page

185 / 194

Location

United States

Related Subject Headings

  • Retrospective Studies
  • Radiographic Image Interpretation, Computer-Assisted
  • Radiation Dosage
  • Nuclear Medicine & Medical Imaging
  • Multidetector Computed Tomography
  • Middle Aged
  • Male
  • Lung Diseases
  • Liver Diseases
  • Kidney Calculi