Multiscale Model of Liver DCE-MRI Towards a Better Understanding of Tumor Complexity

Abstract

The use of quantitative imaging for the characterization of hepatic tumors in magnetic resonance imaging (MRI) can improve the diagnosis and therefore the treatment of these life-threatening tumors. However, image parameters remain difficult to interpret because they result from a mixture of complex processes related to pathophysiology and to acquisition. These processes occur at variable spatial and temporal scales. We propose a multiscale model of liver dynamic contrast-enhanced (DCE) MRI in order to better understand the tumor complexity in images. Our design couples a model of the organ (tissue and vasculature) with a model of the image acquisition. At the macroscopic scale, vascular trees take a prominent place. Regarding the formation of MRI images, we propose a distributed model of parenchymal biodistribution of extracellular contrast agents. Model parameters can be adapted to simulate the tumor development. The sensitivity of the multiscale model of liver DCE-MRI was studied through observations of the influence of two physiological parameters involved in carcinogenesis (arterial flow and capillary permeability) on its outputs (MRI images at arterial and portal phases). Finally, images were simulated for a set of parameters corresponding to the five stages of hepatocarcinogenesis (from regenerative nodules to poorly differentiated HepatoCellular Carcinoma).

Models and methods for analyzing DCE‐MRI: A review

“…As a generalization of the 2CXM model, multicompartment models with multiple tissue compartments have also been proposed. 135,[195][196][197][198][199] These models possess the ability to appropriately describe the observed CA dynamics. 135 However, the increased complexity of these models, sensitivity to the choice of initial values, and numerical instability have prevented the widespread use of these multicompartment models.…”

Contrast agents as a biological marker in magnetic resonance imaging of the liver: conventional and new approaches

“…This produces the same parameters, but affects the measured values. More advanced models have been proposed as well, allowing for tracer diffusion in the capillary bed and extracellular space [59], but the risk arises that such models have unmeasureable parameters.…”

In Silico Modeling of Magnetic Resonance Flow Imaging in Complex Vascular Networks

“…The vascular trees supply MFUs with blood. Moreover, in each MFU a micromodel is hidden [3]. It represents the microvascularization responsible for contrast agent propagation in the tissue.…”

“…In this paper, we focus on the vascular network model at the macroscopic level, since it is subsequently coupled with the flow and MRI models. For a detailed survey of the complete model, we refer the reader to our previous papers, e.g., [21], [3].…”

“…Such vessel perturbations can lead to many serious consequences, such as cerebral hemorrhage [6], liver ischemia with hepatic insufficiency [7], or thromboembolic pulmonary embolism [8]. Another example is the use of contrast agents transported by blood to enhance the MR signal in hypervascularized areas of tumoral lesions (contrast-enhanced MRA) [3].…”