Gadofosveset-enhanced MRI as simple surrogate parameter for real-time evaluation of the initial tumour vessel infarction by retargeted tissue factor tTF-NGR.

anti-vascular treatment gadofosveset real-time visualization truncated tissue factor tumour vessel infarction

Journal

Oncology letters
ISSN: 1792-1074
Titre abrégé: Oncol Lett
Pays: Greece
ID NLM: 101531236

Informations de publication

Date de publication:
Jan 2019
Historique:
received: 28 03 2018
accepted: 22 08 2018
entrez: 19 1 2019
pubmed: 19 1 2019
medline: 19 1 2019
Statut: ppublish

Résumé

Truncated tissue factor (tTF)-NGR consists of the extracellular domain of the human TF and the binding motif NGR. tTF-NGR activates blood coagulation within the tumour vasculature following binding to CD13, and is overexpressed in the endothelial cells of tumour vessels, resulting in tumour vessel infarction and subsequent retardation/regression of tumour growth. The aim of the present study was to investigate gadofosveset-based real-time dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in evaluating the initial therapeutic effects of the anti-vascular tTF-NGR approach. DCE-MRI (3.0 T) was performed in human U87-glioblastoma tumour-bearing nude mice. During a dynamic T1w GE-sequence, a gadolinium-based blood pool contrast agent (gadofosveset) was injected via a tail vein catheter. Following the maximum contrast intensity inside the tumour being obtained, tTF-NGR was injected (controls received NaCl) and the contrast behaviour of the tumour was monitored by ROI analysis. The slope difference of signal intensities between controls and the tTF-NGR group was investigated, as well as the differences between the average area under the curve (AUC) of the two groups. The association between intensity, group (control vs. tTF-NGR group) and time was analysed by fitting a linear mixed model. Following the injection of tTF-NGR, the signal intensity inside the tumours exhibited a statistically significantly stronger average slope decrease compared with the signal intensity of the tumours in the NaCl group. Furthermore, the initial average AUC values of mice treated with tTF-NGR were 5.7% lower than the average AUC of the control animals (P<0.05). Gadofosveset-enhanced MRI enables the visualization of the initial tumour response to anti-vascular treatment in real-time. Considering the clinical application of tTF-NGR, this method may provide a simple alternative parameter for monitoring the tumour response to vascular disrupting agents and certain vascular targeting agents in humans.

Identifiants

pubmed: 30655764
doi: 10.3892/ol.2018.9638
pii: OL-0-0-9638
pmc: PMC6313167
doi:

Types de publication

Journal Article

Langues

eng

Pagination

270-280

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Auteurs

Anna Höink (A)

Department of Clinical Radiology, University Hospital Münster, D-48149 Münster, Germany.
Department of Diagnostic and Interventional Radiology, University Hospital Cologne, D-50937 Cologne, Germany.

Thorsten Persigehl (T)

Department of Clinical Radiology, University Hospital Münster, D-48149 Münster, Germany.
Department of Diagnostic and Interventional Radiology, University Hospital Cologne, D-50937 Cologne, Germany.

Robert Kwiecien (R)

Institute of Biostatistics and Clinical Research, University of Münster, Germany.

Martin Balthasar (M)

Department of Diagnostic and Interventional Radiology, University Hospital Cologne, D-50937 Cologne, Germany.

Rolf Mesters (R)

Department of Medicine A - Haematology and Oncology, University Hospital Münster, D-48149 Münster, Germany.

Wolfgang Berdel (W)

Department of Medicine A - Haematology and Oncology, University Hospital Münster, D-48149 Münster, Germany.

Walter Heindel (W)

Department of Clinical Radiology, University Hospital Münster, D-48149 Münster, Germany.

Christoph Bremer (C)

Department of Clinical Radiology, University Hospital Münster, D-48149 Münster, Germany.
Department of Radiology, St. Franziskus-Hospital Münster, D-48145 Münster, Germany.

Christian Schwöppe (C)

Department of Radiology, St. Franziskus-Hospital Münster, D-48145 Münster, Germany.

Classifications MeSH