人类多形性胶质母细胞瘤（GBM）数据的快门速度动态对比增强磁共振成像（DCE-MRI）分析

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

作者信息

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

机构信息

Department of Physical Medicine and Rehabilitation, Interdisciplinary Institute of Neuroscience and Technology, The Affiliated Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, China.

Key Laboratory of Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China.

出版信息

J Magn Reson Imaging. 2020 Sep;52(3):850-863. doi: 10.1002/jmri.27118. Epub 2020 Mar 13.

DOI:10.1002/jmri.27118

PMID:32167637

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 ) 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 ), the cellular efflux rate constant (k ), and the CA vascular efflux rate constant (k ), together with intravascular and extravascular-extracellular water mole fractions (p and p , respectively) were determined. Further error analyses were also performed to eliminate unreliable estimations on k and k .

STATISTICAL TESTS

Student's t-test.

RESULTS

For tumor pixels of all subjects, 88% show lower AIC with SSM than with the Tofts model. Compared to normal-appearing white matter (NAWM), tumor tissue showed significantly larger p (0.045 vs. 0.011, P < 0.001) and higher k (3.0 × 10 s vs. 6.1 × 10 s , P < 0.001). In the contrast, significant k reduction was observed from NAWM to GBM tumor tissue (2.8 s vs. 1.0 s , P < 0.001). In addition, k is four orders and two orders of magnitude greater than k in the NAWM and GBM tumor, respectively. These results indicate that CA and water molecule have different transmembrane pathways. The mean tumor k of all subjects was 0.57 s .

DATA CONCLUSION

We demonstrate the feasibility of applying SSM models in GBM cases. Within the proposed SSM analysis framework, k and k 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.

摘要

背景

快门速度模型动态对比增强（SSM-DCE）MRI药代动力学分析为DCE-MRI增加了代谢维度。这在癌症中尤其令人感兴趣，因为可能会发生异常代谢活动。

目的

针对多形性胶质母细胞瘤（GBM）病例，考虑到GBM中发现的异质性组织，开发一种DCE-MRI SSM分析框架。

研究类型

前瞻性研究。

研究对象

10例GBM患者。

场强/序列：3T MRI及DCE-MRI。

评估

使用校正后的赤池信息准则（AIC）根据每个像素中的造影剂（CA）外渗情况自动将DCE-MRI数据分离为合适的SSM版本。确定了超强化参数，包括血管水流出速率常数（k）、细胞流出速率常数（k）和CA血管流出速率常数（k），以及血管内和血管外-细胞外水摩尔分数（分别为p和p）。还进行了进一步的误差分析，以消除对k和k的不可靠估计。

统计检验

学生t检验。

结果

对于所有受试者的肿瘤像素，88%显示SSM的AIC低于Tofts模型。与正常外观白质（NAWM）相比，肿瘤组织的p显著更大（0.045对0.011，P < 0.001）且k更高（3.0×10 s对6.1×10 s，P < 0.001）。相反，从NAWM到GBM肿瘤组织观察到k显著降低（2.8 s对1.0 s，P < 0.001）。此外，在NAWM和GBM肿瘤中，k分别比k大四个数量级和两个数量级。这些结果表明CA和水分子具有不同的跨膜途径。所有受试者的平均肿瘤k为0.57 s。