Literature DB >> 28668420

Quantitative in vivo imaging of tissue factor expression in glioma using dynamic contrast-enhanced MRI derived parameters.

Xiao Chen1, Tian Xie1, Jingqin Fang1, Wei Xue1, Haipeng Tong1, Houyi Kang1, Sumei Wang2, Yizeng Yang3, Minhui Xu4, Weiguo Zhang5.   

Abstract

OBJECTIVE: Tissue Factor (TF) has been well established in angiogenesis, invasion, metastasis, and prognosis in glioma. A noninvasive assessment of TF expression status in glioma is therefore of obvious clinical relevance. Dynamic contrast-enhanced (DCE) MRI parameters have been used to evaluate microvascular characteristics and predict molecular expression status in tumors. Our aim is to investigate whether quantitative DCE-MRI parameters could assess TF expression in glioma.
MATERIALS AND METHODS: Thirty-two patients with histopathologically diagnosed supratentorial glioma who underwent DCE-MRI were retrospectively recruited. Extended Tofts linear model was used for DCE-MRI post-processing. Hot-spot, whole tumor cross-sectional approaches, and histogram were used for analysis of model based parameters. Four serial paraffin sections of each case were stained with TF, CD105, CD34 and α-Sooth Muscle Actin, respectively for evaluating the association of TF and microvascular properties. Pearson correlation was performed between percentage of TF expression area and DCE-MRI parameters, multiple microvascular indexes.
RESULTS: Volume transfer constant (Ktrans) hot-spot value best correlated with TF (r=0.886, p<0.001), followed by 90th percentile Ktrans value (r=0.801, p<0.001). Moreover, histogram analysis of Ktrans value demonstrated that weak TF expression was associated with less heterogeneous and positively skewed distribution. Finally, pathology analysis revealed TF was associated with glioma grade and significantly correlated with these two dynamic angiogenic indexes which could be used to explain the strong correlation between Ktrans and TF expression.
CONCLUSION: Our results indicate that Ktrans may serve as a potential clinical imaging biomarker to predict TF expression status preoperatively in gliomas.
Copyright © 2017 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Glioma; In vivo; K(trans); Magnetic resonance imaging; Tissue factor

Mesh:

Substances:

Year:  2017        PMID: 28668420     DOI: 10.1016/j.ejrad.2017.06.006

Source DB:  PubMed          Journal:  Eur J Radiol        ISSN: 0720-048X            Impact factor:   3.528


  2 in total

1.  Robust and efficient pharmacokinetic parameter non-linear least squares estimation for dynamic contrast enhanced MRI of the prostate.

Authors:  Soudabeh Kargar; Eric A Borisch; Adam T Froemming; Akira Kawashima; Lance A Mynderse; Eric G Stinson; Joshua D Trzasko; Stephen J Riederer
Journal:  Magn Reson Imaging       Date:  2017-12-24       Impact factor: 2.546

2.  Do coagulation or fibrinolysis reflect the disease condition in patients with soft tissue sarcoma?

Authors:  Kunihiro Asanuma; Tomoki Nakamura; Takayuki Okamoto; Tomohito Hagi; Kouji Kita; Koichi Nakamura; Yumi Matsuyama; Keisuke Yoshida; Yumiko Asanuma; Akihiro Sudo
Journal:  BMC Cancer       Date:  2022-10-18       Impact factor: 4.638

  2 in total

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