Shutter-Speed DCE-MRI Analyses of Human Glioblastoma Multiforme (GBM) Data

Ruiliang Bai, Bao Wang, Yinhang Jia, Zejun Wang, Charles S. Springer, Zhaoqing Li, Chuanjin Lan, Yi Zhang, Peng Zhao, Yingchao Liu

Research output: Contribution to journalArticlepeer-review

16 Scopus citations


Background: The shutter-speed model dynamic contrast-enhanced (SSM-DCE) MRI pharmacokinetic analysis adds a metabolic dimension to DCE-MRI. This is of particular interest in cancers, since abnormal metabolic activity might happen. Purpose: To develop a DCE-MRI SSM analysis framework for glioblastoma multiforme (GBM) cases considering the heterogeneous tissue found in GBM. Study Type: Prospective. Subjects: Ten GBM patients. Field Strength/Sequence: 3T MRI with DCE-MRI. Assessments: The corrected Akaike information criterion (AICc) was used to automatically separate DCE-MRI data into proper SSM versions based on the contrast agent (CA) extravasation in each pixel. The supra-intensive parameters, including the vascular water efflux rate constant (kbo), the cellular efflux rate constant (kio), and the CA vascular efflux rate constant (kpe), together with intravascular and extravascular–extracellular water mole fractions (pb and po, respectively) were determined. Further error analyses were also performed to eliminate unreliable estimations on kio and kbo. Statistical Tests: Student's t-test. Results: For tumor pixels of all subjects, 88% show lower AICc with SSM than with the Tofts model. Compared to normal-appearing white matter (NAWM), tumor tissue showed significantly larger pb (0.045 vs. 0.011, P < 0.001) and higher kpe (3.0 × 10−2 s−1 vs. 6.1 × 10−4 s−1, P < 0.001). In the contrast, significant kbo reduction was observed from NAWM to GBM tumor tissue (2.8 s−1 vs. 1.0 s−1, P < 0.001). In addition, kbo is four orders and two orders of magnitude greater than kpe in the NAWM and GBM tumor, respectively. These results indicate that CA and water molecule have different transmembrane pathways. The mean tumor kio of all subjects was 0.57 s−1. Data Conclusion: We demonstrate the feasibility of applying SSM models in GBM cases. Within the proposed SSM analysis framework, kio and kbo could be estimated, which might be useful biomarkers for GBM diagnosis and survival prediction in future. Level of Evidence: 4. Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2020;52:850–863.

Original languageEnglish (US)
Pages (from-to)850-863
Number of pages14
JournalJournal of Magnetic Resonance Imaging
Issue number3
StatePublished - Sep 1 2020


  • glioblastoma
  • metabolism
  • shutter speed
  • tumor heterogeneity

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging


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