1D Thermoembolization Model Using CT Imaging Data for Porcine Liver

TL;DR

This study develops a 1D blood flow model using CT imaging data to predict embolization sites in porcine liver during thermoembolization, aiding understanding of complex biophysical processes.

Contribution

Introduces a simplified 1D flow model to predict embolization locations in thermoembolization, validated with in vivo porcine data.

Findings

66.8% accuracy in embolization site prediction

Model helps understand vascular transport during thermoembolization

Optimized hydrolysis time constants for each subject

Abstract

Objective: Innovative therapies such as thermoembolization are expected to play an important role in improvising care for patients with diseases such as hepatocellular carcinoma. Thermoembolization is a minimally invasive strategy that combines thermal ablation and embolization in a single procedure. This approach exploits an exothermic chemical reaction that occurs when an acid chloride is delivered via an endovascular route. However, comprehension of the complexities of the biophysics of thermoembolization is challenging. Mathematical models can aid in understanding such complex processes and assisting clinicians in making informed decisions. In this study, we used a Hagen Poiseuille 1D blood flow model to predict the mass transport and possible embolization locations in a porcine hepatic artery. Method: The 1D flow model was used on in vivo embolization imaging data of three pigs. The hydrolysis time constant of acid chloride chemical reaction was optimized for each pig, and LOOCV method was used to test the model's predictive ability. Conclusion: This basic model provided a balanced accuracy rate of 66.8% for identifying the possible locations of embolization in the hepatic artery. Use of the model provides an initial understanding of the vascular transport phenomena that are predicted to occur as a result of thermoembolization.