Anatomical DCE-MRI phantoms generated from glioma patient data

Andrew Beers, Ken Chang, James Brown, Xia Zhu, Dipanjan Sengupta, Theodore L. Willke, Elizabeth Gerstner, Bruce Rosen, Jayashree Kalpathy-Cramer

Research output: Chapter in Book/Report/Conference proceedingConference contribution


Several digital reference objects (DROs) for DCE-MRI have been created to test the accuracy of pharmacokinetic modeling software under a variety of different noise conditions. However, there are few DROs that mimic the anatomical distribution of voxels found in real data, and similarly few DROs that are based on both malignant and normal tissue. We propose a series of DROs for modeling Ktrans and Ve derived from a publically-available RIDER DCEMRI dataset of 19 patients with gliomas. For each patient's DCE-MRI data, we generate Ktrans and Ve parameter maps using an algorithm validated on the QIBA Tofts model phantoms. These parameter maps are denoised, and then used to generate noiseless time-intensity curves for each of the original voxels. This is accomplished by reversing the Tofts model to generate concentration-times curves from Ktrans and Ve inputs, and subsequently converting those curves into intensity values by normalizing to each patient's average pre-bolus image intensity. The result is a noiseless DRO in the shape of the original patient data with known ground-truth Ktrans and Ve values. We make this dataset publically available for download for all 19 patients of the original RIDER dataset.

Original languageEnglish (US)
Title of host publicationMedical Imaging 2018
Subtitle of host publicationPhysics of Medical Imaging
ISBN (Electronic)9781510616356
Publication statusPublished - Jan 1 2018
Externally publishedYes
EventMedical Imaging 2018: Physics of Medical Imaging - Houston, United States
Duration: Feb 12 2018Feb 15 2018


OtherMedical Imaging 2018: Physics of Medical Imaging
CountryUnited States



  • DCE
  • DRO
  • Ktrans
  • Parametric
  • Phantom
  • Tofts
  • Ve

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Biomaterials
  • Atomic and Molecular Physics, and Optics
  • Radiology Nuclear Medicine and imaging

Cite this

Beers, A., Chang, K., Brown, J., Zhu, X., Sengupta, D., Willke, T. L., ... Kalpathy-Cramer, J. (2018). Anatomical DCE-MRI phantoms generated from glioma patient data. In Medical Imaging 2018: Physics of Medical Imaging (Vol. 10573). [105732V] SPIE.