A Quantitative Study of the Dimensional Change of Inferior Vena Cava on Computed Tomography During Acute Hemorrhage Shock in Swine

Abstract

Background: The purpose of this study was to examine the dimensional change of IVC during acute hemorrhage through a volume-controlled acute hemorrhagic shock model in swine. Methods: Volume-controlled hemorrhage was performed in 10 adult Bama mini pigs. Enhanced CT scan and hemodynamic monitoring were performed when the cumulative blood loss volume reached 0%, 10%, 20%, 30%, and 40%. The transverse diameter (T) and anteroposterior diameter (AP) of IVC were measured in axial images. Hemodynamic parameters were obtained with Pulse Contour Cardiac Output (PiCCO) hemodynamic monitor device. Arterial blood samples were also collected for artery blood gas analysis at each time point. Results: As the blood loss volume increased, the collapsibility (T/AP) and cross section area (CSA) of IVC significantly changed first in hepatic level and pre-renal level. The significant decrease of the CSA of IVC (shrink) occurred early when the blood loss volume reached only 10%, but the collapse of IVC occurred until the blood loss volume reached 30%. Conclusions: IVC shrank early but collapsed late during the acute hemorrhage in swine. The finding of collapsed IVC on CT scans suggested severe hypovolemic shock. Evaluation of the IVC at the CT scans can be an adjunctive test of the hemodynamic status in trauma patients.

Keywords:

• hemorrhagic shock
• computed tomography
• inferior vena cava
• swine model

Acknowledgments

Thanks are due to Dr. Dao-cheng Liu, Mr. Liang-chao Zhang, and Mr. Chong Dong for assistance with the animal experiments.

Declaration of interest

The authors report no conflicts of interest. The authors alone are responsible for the content and writing of the paper.

Additional information

Funding

The study was supported by the Chongqing science and technology innovation program for people's livelihood [grant Number: cstc2016shmszx130022] and PLA medical research program [grant Number: AWS15J004].