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The Effect of Contrast Material on Radiation Dose at CT: Part I. Incorporation of Contrast Material Dynamics in Anthropomorphic Phantoms.

Publication ,  Journal Article
Sahbaee, P; Segars, WP; Marin, D; Nelson, RC; Samei, E
Published in: Radiology
June 2017

Purpose To develop a method to incorporate the propagation of contrast material into computational anthropomorphic phantoms for estimation of organ dose at computed tomography (CT). Materials and Methods A patient-specific physiologically based pharmacokinetic (PBPK) model of the human cardiovascular system was incorporated into 58 extended cardiac-torso (XCAT) patient phantoms. The PBPK model comprised compartmental models of vessels and organs unique to each XCAT model. For typical injection protocols, the dynamics of the contrast material in the body were described according to a series of patient-specific iodine mass-balance differential equations, the solutions to which provided the contrast material concentration time curves for each compartment. Each organ was assigned to a corresponding time-varying iodinated contrast agent to create the contrast material-enhanced five-dimensional XCAT models, in which the fifth dimension represents the dynamics of contrast material. To validate the accuracy of the models, simulated aortic and hepatic contrast-enhancement results throughout the models were compared with previously published clinical data by using the percentage of discrepancy in the mean, time to 90% peak, peak value, and slope of enhancement in a paired t test at the 95% significance level. Results The PBPK model allowed effective prediction of the time-varying concentration curves of various contrast material administrations in each organ for different patient models. The contrast-enhancement results were in agreement with results of previously published clinical data, with mean percentage, time to 90% peak, peak value, and slope of less than 10% (P > .74), 4%, 7%, and 14% for uniphasic and 12% (P > .56), 4%, 12%, and 14% for biphasic injection protocols, respectively. The exception was hepatic enhancement results calculated for a uniphasic injection protocol for which the discrepancy was less than 25%. Conclusion A technique to model the propagation of contrast material in XCAT human models was developed. The models with added contrast material propagation can be applied to simulate contrast-enhanced CT examinations. © RSNA, 2017 Online supplemental material is available for this article.

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Published In

Radiology

DOI

EISSN

1527-1315

Publication Date

June 2017

Volume

283

Issue

3

Start / End Page

739 / 748

Location

United States

Related Subject Headings

  • Tomography, X-Ray Computed
  • Radiation Dosage
  • Phantoms, Imaging
  • Nuclear Medicine & Medical Imaging
  • Models, Biological
  • Contrast Media
  • 3202 Clinical sciences
  • 11 Medical and Health Sciences
 

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Sahbaee, P., Segars, W. P., Marin, D., Nelson, R. C., & Samei, E. (2017). The Effect of Contrast Material on Radiation Dose at CT: Part I. Incorporation of Contrast Material Dynamics in Anthropomorphic Phantoms. Radiology, 283(3), 739–748. https://doi.org/10.1148/radiol.2016152851
Sahbaee, Pooyan, W Paul Segars, Daniele Marin, Rendon C. Nelson, and Ehsan Samei. “The Effect of Contrast Material on Radiation Dose at CT: Part I. Incorporation of Contrast Material Dynamics in Anthropomorphic Phantoms.Radiology 283, no. 3 (June 2017): 739–48. https://doi.org/10.1148/radiol.2016152851.
Sahbaee, Pooyan, et al. “The Effect of Contrast Material on Radiation Dose at CT: Part I. Incorporation of Contrast Material Dynamics in Anthropomorphic Phantoms.Radiology, vol. 283, no. 3, June 2017, pp. 739–48. Pubmed, doi:10.1148/radiol.2016152851.

Published In

Radiology

DOI

EISSN

1527-1315

Publication Date

June 2017

Volume

283

Issue

3

Start / End Page

739 / 748

Location

United States

Related Subject Headings

  • Tomography, X-Ray Computed
  • Radiation Dosage
  • Phantoms, Imaging
  • Nuclear Medicine & Medical Imaging
  • Models, Biological
  • Contrast Media
  • 3202 Clinical sciences
  • 11 Medical and Health Sciences