Estimation of four-dimensional CT-based imaging biomarker of liver fibrosis using finite element method

Koya Fujimoto; Takehiro Shiinoki; Yuki Yuasa

doi:10.1117/12.2548280

10 March 2020 Estimation of four-dimensional CT-based imaging biomarker of liver fibrosis using finite element method

Koya Fujimoto, Takehiro Shiinoki, Yuki Yuasa

Proceedings Volume 11313, Medical Imaging 2020: Image Processing; 113130J (2020) https://doi.org/10.1117/12.2548280
Event: SPIE Medical Imaging, 2020, Houston, Texas, United States

Abstract

This study developed the estimation method of the liver elasticity using the finite element method (FEM) based on the four-dimensional computed tomography (4DCT) images acquired for radiotherapy planning, and to evaluate the feasibility of estimated elasticity as a biomarker for diagnose liver fibrosis. Fifteen patients who underwent 4DCT images and gadoxetate-acid (Gd-EOB-DTPA)-enhanced magnetic resonance imaging (MRI) were enrolled in this study. The displacement vector fields were calculated between 4DCT images at the end-inspiration and at the end-exhalation using deformable image registration (actual respiratory-induced displacement). Further, we simulated the displacement during respiration by using the FEM (simulated respiratory-induced displacement). The elasticity in each element of liver model was optimized minimalizing the error between actual and simulated respiratory-induced displacement. In Gd-EOB-DTPAenhanced MRI, liver-to-spleen signal intensity ratio (LSR) was calculated using the mean signal intensity for whole liver and spleen. The correlations with two serum biomarkers (APRI: aspartate-aminotransferase to platelet ratio index, FIB-4: Fibrosis-4 index) for elasticity and for LSR were evaluated. The elasticity were strong correlation with APRI-score (r= 0.82), and with FIB-4-score (r= 0.86). On the other hand, LSR were modelate correlation with APRI-score (r= 0.32), and with FIB-4-score (r= 0.30). The mean ± standard deviation of errors between actual and simulated respiratory-induced displacement in the liver model was 0.63 ± 0.41 mm. In this study, liver elasticity was estimated using the FEM and respiratory-induced liver motion obtained from 4DCT images. Furthermore, the estimated elasticity could be a feasible imaging biomarker for diagnose the various degrees of liver fibrosis.

Citation Download Citation

Koya Fujimoto, Takehiro Shiinoki, and Yuki Yuasa "Estimation of four-dimensional CT-based imaging biomarker of liver fibrosis using finite element method", Proc. SPIE 11313, Medical Imaging 2020: Image Processing, 113130J (10 March 2020); https://doi.org/10.1117/12.2548280

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