Quantitative analysis of 3D T1‐weighted gadolinium (Gd) DCE‐MRI with different repetition times

Elijah D. Rockers, Maria B. Pascual, Sahil Bajaj, Joseph C. Masdeu, Zhong Xue

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


Dynamic contrast-enhanced MRI (DCE-MRI) acquires T1-weighted MRI scans before and after injection of an MRI contrast agent such as gadolinium (Gd). Gadolinium causes the relaxation time to decrease, resulting in higher MR image intensities after injection followed by a gradual decrease in image intensities during wash out. Gd does not pass the intact blood–brain barrier (BBB), thus its dynamics can be used to quantify pathology associated with BBB leaks. In current clinical practice, it is suggested to use the same pulse sequence for pre-injection T1 calibration and Gd concentration calculation in the DCE image sequence based on the spoiled gradient recalled echo (SPGR) signal equation. A common method for T1 estimation is using variable flip angle (VFA). However, when the parameters such as the repetition time (TR) for image acquisition could be tuned differently for T1 estimation and DCE acquisition, the popular dcemriS4 software package that handles only a fixed TR often results in discrepancies in Gd concentration estimation. This paper reports a quick solution for calculating Gd concentrations when different TRs are used. First, the pre-injection T1 map is calculated by using the Levenberg-Marquardt algorithm with VFA acquisition, then, because the TR used for DCE acquisition is different from the VFA TR, the equilibrium magnetization is updated with the TR for DCE, and the Gd concentration is calculated thereafter. In the experiments, we first simulated Gd concentration curves for different tissue types and generated the corresponding VFA and DCE image sequences and then used the proposed method to reconstruct the concentration. Comparing with the original simulated data allows us to validate the accuracy of the proposed computation. Further, we tested performance of the method by simulating different amounts of Ktrans changes in a manually selected region of interest (ROI). The results showed that the new method can estimate Gd dynamics more accurately in the case where different TRs are used and be sensitive enough to detect slight Ktrans changes in DCE-MRI.

Original languageEnglish (US)
Title of host publicationMedical Imaging and Augmented Reality - 7th International Conference, MIAR 2016, Proceedings
EditorsHongen Liao, Guoyan Zheng, Su-Lin Lee, Philippe Cattin, Pierre Jannin
Number of pages10
ISBN (Print)9783319437743
StatePublished - 2016
Event7th International Conference on Medical Imaging and Augmented Reality, MIAR 2016 - Bern, Switzerland
Duration: Aug 24 2016Aug 26 2016

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9805 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Other7th International Conference on Medical Imaging and Augmented Reality, MIAR 2016


  • Gd concentration
  • Pharmacokinetics
  • T relaxation

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)


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