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

Abstract

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 (AIC_c) 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 (k_bo), the cellular efflux rate constant (k_io), and the CA vascular efflux rate constant (k_pe), together with intravascular and extravascular–extracellular water mole fractions (p_b and p_o, respectively) were determined. Further error analyses were also performed to eliminate unreliable estimations on k_io and k_bo. Statistical Tests Student's t‐test. Results For tumor pixels of all subjects, 88% show lower AIC_c with SSM than with the Tofts model. Compared to normal‐appearing white matter (NAWM), tumor tissue showed significantly larger p_b (0.045 vs. 0.011, P < 0.001) and higher k_pe (3.0 × 10⁻² s⁻¹ vs. 6.1 × 10⁻⁴ s⁻¹, P < 0.001). In the contrast, significant k_bo reduction was observed from NAWM to GBM tumor tissue (2.8 s⁻¹ vs. 1.0 s⁻¹, P < 0.001). In addition, k_bo is four orders and two orders of magnitude greater than k_pe in the NAWM and GBM tumor, respectively. These results indicate that CA and water molecule have different transmembrane pathways. The mean tumor k_io 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, k_io and k_bo could be estimated, which might be useful biomarkers for GBM diagnosis and survival prediction in future. Level of Evidence 4 Technical Efficacy Stage 1