3D modelling of drug-coated balloons for the treatment of calcified superficial femoral arteries

Abstract

Background/Objectives Drug-coated balloon therapy for diseased superficial femoral arteries remains controversial. Despite its clinical relevance, only a few computational studies based on simplistic two-dimensional models have been proposed to investigate this endovascular therapy to date. This work addresses the aforementioned limitation by analyzing the drug transport and kinetics occurring during drug-coated balloon deployment in a three-dimensional geometry. Methods An idealized three-dimensional model of a superficial femoral artery presenting with a calcific plaque and treated with a drug-coated balloon was created to perform transient mass transport simulations. To account for the transport of drug (i.e. paclitaxel) released by the device, a diffusion-reaction equation was implemented by describing the drug bound to specific intracellular receptors through a non-linear, reversible reaction. The following features concerning procedural aspects, pathologies and modelling assumptions were investigated: (i) balloon application time (60–180 seconds); (ii) vessel wall composition (healthy vs. calcified wall); (iii) sequential balloon application; and (iv) drug wash-out by the blood stream vs. coating retention, modeled as exponential decay. Results The balloon inflation time impacted both the free and specifically-bound drug concentrations in the vessel wall. The vessel wall composition highly affected the drug concentrations. In particular, the specifically-bound drug concentration was four orders of magnitude lower in the calcific compared with healthy vessel wall portions, primarily as a result of reduced drug diffusion. The sequential application of two drug-coated balloons led to modest differences (~15%) in drug concentration immediately after inflation, which became negligible within 10 minutes. The retention of the balloon coating increased the drug concentration in the vessel wall fourfold. Conclusions The overall findings suggest that paclitaxel kinetics may be affected not only by the geometrical and compositional features of the vessel treated with the drug-coated balloon, but also by balloon design characteristics and procedural aspects that should be carefully considered.

Understudied factors in drug‐coated balloon design and evaluation: A biophysical perspective

“… 21 Additionally, Kolandaivelu et al presented a supervised machine learning framework, using drug coated balloons as an exemplary scenario (Figure 6 ), to process data generated from coarse meshes to predict results derived from highly‐refined meshes – thereby drastically increasing the efficiency in the computational modeling workflow. 69 However, it must be noted that all the studies to‐date, except one, 70 are inherently limited by the fact that the geometric domain is simplified down to a one‐ or two‐dimensional representation. While it has been shown that lower‐dimensional models can adequately predict the numerical results that would be derived from three‐dimensional models when the device‐vessel interface is spatially uniform, the assumption begins to break down as heterogeneity in both the vessel tissue and balloon surface are incorporated into the computational model.…”

Theoretical modeling of endovascular drug delivery into a multilayer arterial wall from a drug-coated balloon

“…Consider the process of endovascular drug delivery by a drug-coated balloon adhered to the luminal wall of an artery for a short duration, typically 60-120 seconds in practice [9,11].…”

“…Numerical studies are typically computationally expensive and make a number of (different) assumptions to enable solutions to be obtained in a reasonable time frame. Drug delivery from the DCB is typically modeled as either a constant concentration for a finite time [11] or a timedependent flux [6][7][8][9][10]. All of the aforementioned numerical models assume that drug is transported through the arterial wall due to diffusion: only two models [8,9] account for advective transport due to the known pressure gradient across the arterial wall.…”

“…Drug binding is dependent on the physio-chemical properties of the particular drug and is handled in different ways in these models, ranging from linear reversible binding kinetics through to multiple phases of nonlinear reversible binding [12]. While most of these models assume a healthy artery, two of these models account for the presence of a homogeneous atherosclerotic plaque within 3D [11] and 2D [9] geometries: however, the healthy portion of the arterial wall is assumed to be a homogeneous material with the same properties. A major limitation of each of these numerical models is that they do not consider the multi-layer nature of the arterial wall.…”

DECODE cloud platform: A new cloud platform to combat the burden of peripheral artery disease

“…It has been reported that PAD affects people aged 25 years and over. Recent data indicated that about 202 million people have this disease, while the number increased to 230 million people infected in 2015 [1]. As a result, powerful computational tools have been developed as a result of the PAD study's widespread interest.…”