JoVE Video Dataset

Abstract

A modified silicone injection procedure was used for visualization of the hepatic vascular tree. This procedure consisted of in-vivo injection of the silicone compound, via a 26 G catheter, into the portal or hepatic vein. After silicone injection, organs were explanted and prepared for ex-vivo micro-CT (µCT) scanning. The silicone injection procedure is technically challenging. Achieving a successful outcome requires extensive microsurgical experience from the surgeon. One of the challenges of this procedure involves determining the adequate perfusion rate for the silicone compound. The perfusion rate for the silicone compound needs to be defined based on the hemodynamic of the vascular system of interest. Inappropriate perfusion rate can lead to an incomplete perfusion, artificial dilation and rupturing of vascular trees. The 3D reconstruction of the vascular system was based on CT scans and was achieved using preclinical software such as HepaVision. The quality of the reconstructed vascular tree was directly related to the quality of silicone perfusion. Subsequently computed vascular parameters indicative of vascular growth, such as total vascular volume, were calculated based on the vascular reconstructions. Contrasting the vascular tree with silicone allowed for subsequent histological work-up of the specimen after µCT scanning. The specimen can be subjected to serial sectioning, histological analysis and whole slide scanning, and thereafter to 3D reconstruction of the vascular trees based on histological images. This is the prerequisite for the detection of molecular events and their distribution with respect to the vascular tree. This modified silicone injection procedure can also be used to visualize and reconstruct the vascular systems of other organs. This technique has the potential to be extensively applied to studies concerning vascular anatomy and growth in various animal and disease models.

Authors 10

1. Chichi Xie

   Jena University Hospital

   Affiliation as printed

   Department of General, Visceral and Vascular Surgery, Jena University Hospital

2. Weiwei Wei

   Jena University Hospital

   Affiliation as printed

   Department of General, Visceral and Vascular Surgery, Jena University Hospital

3. Andrea Schenk

   Fraunhofer Institute for Digital Medicine

   Affiliation as printed

   Fraunhofer Institute for Medical Image Computing MEVIS

4. Lars Ole Schwen

   Fraunhofer Institute for Digital Medicine

   Affiliation as printed

   Fraunhofer Institute for Medical Image Computing MEVIS

5. Sara Zafarnia Aachen Experimental Molecular Imaging

   RWTH Aachen University

   Affiliation as printed

   Experimental Molecular Imaging, RWTH Aachen University

6. Michael Schwier

   Fraunhofer Institute for Digital Medicine

   Affiliation as printed

   Fraunhofer Institute for Medical Image Computing MEVIS

7. Felix Gremse Aachen Experimental Molecular Imaging

   RWTH Aachen University

   Affiliation as printed

   Experimental Molecular Imaging, RWTH Aachen University

8. Isabel Jank

   Jena University Hospital

   Affiliation as printed

   Department of General, Visceral and Vascular Surgery, Jena University Hospital

9. Olaf Dirsch

   Klinikum Chemnitz

   Affiliation as printed

   Institute of Pathology, Klinikum Chemnitz gGmbH

10. Uta Dahmen

    Jena University Hospital

    Affiliation as printed

    Department of General, Visceral and Vascular Surgery, Jena University Hospital