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Development and characterization of a rat brain metastatic tumor model by multiparametric magnetic resonance imaging and histomorphology

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Abstract

To facilitate the development of new brain metastasis (BM) treatment, an easy-to-use and clinically relevant animal model with imaging platform is needed. Rhabdomyosarcoma BM was induced in WAG/Rij rats. Post-implantation surveillance and characterizations were systematically performed with multiparametric MRI including 3D T1 and T2 weighted imaging, diffusion-weighted imaging (DWI), T1 and T2 mapping, and perfusion-weighted imaging (PWI), which were validated by postmortem digital radiography (DR), µCT angiography and histopathology. The translational potential was exemplified by the application of a vascular disrupting agent (VDA). BM was successfully induced in most rats of both genders (18/20). Multiparametric MRI revealed significantly higher T2 value, pre-contrast-enhanced (preCE) T1 value, DWI-derived apparent diffusion coefficient (ADC) and CE ratio, but a lower post-contrast-enhanced (postCE) T1 value in BM lesions than in adjacent brain (p < 0.01). PWI showed the dynamic and higher contrast agent uptake in the BM compared with the adjacent brain. DR, µCT and histopathology characterized the BM as hypervascular tumors. After VDA treatment, the BM showed drug-related perfusion changes and partial necrosis as evidenced by anatomical, functional MRI parameters and postmortem findings. The present BM model and imaging modalities represent a feasible and translational platform for developing BM-targeting therapeutics.

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Data availability

All data in this study is available under reasonable request.

Code availability

Python codes are available under reasonable request.

Abbreviations

ADC:

Apparent diffusion coefficient

BBB:

Blood–brain barrier

BBTB:

Blood–brain-tumor-barrier

BM:

Brain metastasis

CA:

Contrast agent

CA4P:

Combretastatin A4 phosphate

CE:

Contrast-enhanced

DKI:

Diffusion kurtosis imaging

DR:

Digital radiography

DWI:

Diffusion-weighted imaging

IHC:

Immunohistochemistry

µCT:

Micro computed tomography

MRI:

Magnetic resonance imaging

postCE:

Post-contrast-enhanced

preCE:

Pre-contrast-enhanced

PDX:

Patient-derived xenograft

PWI:

Dynamic contrast enhanced perfusion weighted imaging

R1:

Rhabdomyosarcoma

SPACE:

Sampling perfection with application optimized contrasts using different flip angle evolution

SI:

Signal intensity

TSE:

Turbo spin echo

VDA:

Vascular-disrupting agent

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Acknowledgements

We thank Prof. Stefaan Soenen from Nanohealth and Optical Imaging Group in KU Leuven for providing rhabdomyosarcoma cell line. We also appreciate the Center for Artificial Intelligence in Medicine & Imaging at Stanford University for making the clinical brain MRI images publicly available with special thanks to Prof. Dr. Greg Zaharchuk from department of radiology, Stanford University for approving the use of clinical brain metastasis images in figure 2. We sincerely thank Ahmed Radwan from department of imaging and pathology, KU Leuven and Sjoerd Nooijens from department of cardiovascular sciences, KU Leuven, Belgium, who actively participated in the discussion of imaging analyses. We acknowledge Oncocidia Limited, London, UK and Mr. Jean-Pierre Peters with his firm P&R Medical, Hasselt, Belgium for their partial financial supports to our ongoing research.

Funding

The authors received no specific funding for this work.

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Authors and Affiliations

  1. KU Leuven, Biomedical Group, Campus Gasthuisberg, 3000, Leuven, Belgium

    Shuncong Wang, Lei Chen, Yuanbo Feng, Ting Yin, Jie Yu, Guy Bormans, Johan Swinnen, Yue Li & Yicheng Ni

  2. MR Collaborations, Siemens Healthineers Ltd, Shanghai, China

    Ting Yin

  3. Department of Radiology, University Hospitals Leuven, KU Leuven, Herestraat 49, 3000, Leuven, Belgium

    Frederik De Keyzer, Ronald Peeters, Chantal Van Ongeval & Yicheng Ni

  4. KU Leuven, Department of Materials Engineering, Kasteelpark Arenberg 44, 3001, Leuven, Belgium

    Jeroen Soete & Martine Wevers

  5. Shanghai Key Laboratory of Molecular Imaging, Shanghai University of Medicine and Health Sciences, Shanghai, 201318, China

    Yue Li

Authors
  1. Shuncong Wang
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  2. Lei Chen
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Contributions

SW Performing experiment, statistical analyses and drafting manuscript; LC Performing experiment, and statistical analyses; YF MRI image segementation, drafting manuscript and discussion; TY MRI image analyses, and discussion; JY Pathological analyses, and discussion; FDK MRI image analyses, and discussion; RP MRI image analyses, and discussion; CVO MRI image analyses, and discussion; GB Supervision, and discussion; JS Supervision, and discussion; JS Performing experiments, uCT image analyses, discussion; MW Performing experiments, uCT image analyses, discussion; YL Study design, reviewing manuscript; YN Supervision of study, study design, reviewing manuscript, MRI image segementation.

Corresponding authors

Correspondence to Yue Li or Yicheng Ni.

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All authors declare no conflict of interest.

Ethical approval

This study was approved by the ethical committee of KU Leuven with a registry No. P046/2019 and executed with laboratory animal care.

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Wang, S., Chen, L., Feng, Y. et al. Development and characterization of a rat brain metastatic tumor model by multiparametric magnetic resonance imaging and histomorphology. Clin Exp Metastasis 39, 479–493 (2022). https://doi.org/10.1007/s10585-022-10155-w

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  • DOI: https://doi.org/10.1007/s10585-022-10155-w

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