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Semmineh NB, Stokes AM, Bell LC, et al. A Population-Based Digital Reference Object (DRO) for Optimizing Dynamic Susceptibility Contrast (DSC)-MRI Methods for Clinical Trials. Tomography. 2017;3(1):41-49doi: 10.18383/j.tom.2016.00286.
Semmineh, N. B., Stokes, A. M., Bell, L. C., Boxerman, J. L., & Quarles, C. C. (2017). A Population-Based Digital Reference Object (DRO) for Optimizing Dynamic Susceptibility Contrast (DSC)-MRI Methods for Clinical Trials. Tomography (Ann Arbor, Mich.), 3(1), 41-49. https://doi.org/10.18383/j.tom.2016.00286
Semmineh, Natenael B, et al. "A Population-Based Digital Reference Object (DRO) for Optimizing Dynamic Susceptibility Contrast (DSC)-MRI Methods for Clinical Trials." Tomography (Ann Arbor, Mich.) vol. 3,1 (2017): 41-49. doi: https://doi.org/10.18383/j.tom.2016.00286
Semmineh NB, Stokes AM, Bell LC, Boxerman JL, Quarles CC. A Population-Based Digital Reference Object (DRO) for Optimizing Dynamic Susceptibility Contrast (DSC)-MRI Methods for Clinical Trials. Tomography. 2017 Mar;3(1):41-49. doi: 10.18383/j.tom.2016.00286. PMID: 28584878; PMCID: PMC5454781.
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Tomography. 2017 Mar;3(1):41-49. doi: 10.18383/j.tom.2016.00286.

A Population-Based Digital Reference Object (DRO) for Optimizing Dynamic Susceptibility Contrast (DSC)-MRI Methods for Clinical Trials.

Tomography (Ann Arbor, Mich.)

Natenael B Semmineh, Ashley M Stokes, Laura C Bell, Jerrold L Boxerman, C Chad Quarles

Affiliations

  1. Department of Imaging Research, Barrow Neurological Institute, Phoenix, Arizona.
  2. Department of Diagnostic Imaging, RI Hospital and Alpert Medical School of Brown University, Providence, Rhode Island.

PMID: 28584878 PMCID: PMC5454781 DOI: 10.18383/j.tom.2016.00286

Abstract

The standardization and broad-scale integration of dynamic susceptibility contrast (DSC)-magnetic resonance imaging (MRI) have been confounded by a lack of consensus on DSC-MRI methodology for preventing potential relative cerebral blood volume inaccuracies, including the choice of acquisition protocols and postprocessing algorithms. Therefore, we developed a digital reference object (DRO), using physiological and kinetic parameters derived from in vivo data, unique voxel-wise 3-dimensional tissue structures, and a validated MRI signal computational approach, aimed at validating image acquisition and analysis methods for accurately measuring relative cerebral blood volume in glioblastomas. To achieve DSC-MRI signals representative of the temporal characteristics, magnitude, and distribution of contrast agent-induced T

Keywords: brain tumor perfusion; digital reference object; dynamic susceptibility contrast MRI

Conflict of interest statement

Conflict of Interest: None reported.

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