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

被引:23
作者
Bai, Ruiliang [1 ,2 ]
Wang, Bao [3 ]
Jia, Yinhang [1 ]
Wang, Zejun [2 ]
Springer, Charles S., Jr. [4 ]
Li, Zhaoqing [2 ]
Lan, Chuanjin [3 ]
Zhang, Yi [5 ]
Zhao, Peng [6 ]
Liu, Yingchao [6 ]
机构
[1] Zhejiang Univ, Interdisciplinary Inst Neurosci & Technol, Affiliated Sir Run Run Shaw Hosp, Dept Phys Med & Rehabil,Sch Med, Hangzhou, Peoples R China
[2] Zhejiang Univ, Coll Biomed Engn & Instrument Sci, Minist Educ, Key Lab Biomed Engn, Hangzhou, Peoples R China
[3] Shandong Univ, Qilu Hosp, Dept Radiol, Jinan, Peoples R China
[4] Oregon Hlth & Sci Univ, Adv Imaging Res Ctr, Portland, OR 97201 USA
[5] Shandong Univ, Shandong Med Imaging Res Inst, Jinan, Peoples R China
[6] Shandong First Med Univ, Shandong Prov Hosp, Dept Neurosurg, Jinan, Peoples R China
基金
中国国家自然科学基金;
关键词
DCE MRI; metabolism; shutter speed; glioblastoma; tumor heterogeneity; INTRACELLULAR WATER LIFETIME; PERFUSION MRI; BLOOD-VOLUME; EXCHANGE; TUMOR; PERMEABILITY; PARAMETERS; EVOLUTION; BIOMARKER; ARTERIAL;
D O I
10.1002/jmri.27118
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
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)andp(o), respectively) were determined. Further error analyses were also performed to eliminate unreliable estimations onk(io)andk(bo). Statistical Tests Student'st-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 largerp(b)(0.045 vs. 0.011,P < 0.001) and higherk(pe)(3.0 x 10(-2)s(-1)vs. 6.1 x 10(-4)s(-1),P < 0.001). In the contrast, significantk(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 thank(pe)in the NAWM and GBM tumor, respectively. These results indicate that CA and water molecule have different transmembrane pathways. The mean tumork(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)andk(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 J. Magn. Reson. Imaging 2020;52:850-863.
引用
收藏
页码:850 / 863
页数:14
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