A Mesoscale Computational Model for Microvascular Oxygen Transfer

Possenti, Luca; Cicchetti, A.; Rosati, Riccardo; Cerroni, Daniele; Costantino, Maria Laura; Rancati, T.; Zunino, Paolo

doi:10.1007/s10439-021-02807-x

Cited by 20 publications

(29 citation statements)

References 74 publications

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“…Both altered scenarios decrease the average oxygen content in the tissue with respect to the reference state. Among the two, increased consumption induces a stronger reduction, according to previous work on oxygenation [20, 66, 67]. An important difference between the two scenarios is how they act in the two domains.…”

Section: Resultsmentioning

confidence: 84%

“…Among the two, increased consumption induces a stronger reduction, according to previous work on oxygenation [20,66,67]. An important difference between the two scenarios is how they act in the two domains.…”

Section: Influence Of Acute Hypoxia and Tumor Oxygen Consumptionmentioning

confidence: 83%

“…All of these studies focus mainly on oxygen diffusion within tissue, with simplified models of oxygen transport within the microvascular network. A more complex model of oxygen transport within the microvascular network (that is, including blood flow and the presence of red blood cells [20, 52, 71, 72]) can describe the heterogeneous distribution of oxygen within vessels and its consequence on oxygen delivery, modifying the influence of microvascular morphology on radiation results.…”

Section: Discussionmentioning

confidence: 99%

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Microvascular morphology affects radiotherapy outcomes: a computational study

Possenti,

Vitullo,

Cicchetti

et al. 2023

Preprint

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Radiotherapy (RT) is the most common cancer treatment, and hypoxia is one of the main causes of resistance to RT. We investigate how microvascular morphology affects radiation therapy results, exploring the role of the microvasculature. Several computational models have been developed to analyze microvascular oxygen delivery. However, few of these models have been applied to study RT and the microenvironment. We generated 27 different networks, covering 9 scenarios defined by the vascular density and the network regularity. Leveraging these networks, we solved a computational mixed-dimensional model for fluid flow, red blood cell distribution, and oxygen delivery in the microenvironment. Then, we simulated a fractionated RT treatment (30 × 2GyRBE) using the Linear Quadratic model, accounting for oxygen-related (OER) modifications by two different models from the literature. First, the analysis of the hypoxic volume fraction and its distribution reveals a correlation between hypoxia and treatment outcome. The study also shows how vascular density and regularity are essential in determining the success of treatment. Indeed, in our computational dataset, an insufficient vascular density or regularity is sufficient to decrease the success probability for photon-based RT. We also applied our quantitative analysis to hadron therapy and different oxygenation states to assess the consistency of the microvasculature’s role in various treatments and conditions. While proton RT provides a Tumor Control Probability similar to photons, carbon ions mark a clear difference, especially with bad vascular scenarios, i.e., where strong hypoxia is present. These data also suggest a scenario where carbon-based hadron therapy can help overcome hypoxia-mediated resistance to RT. As a final remark, we discuss the significance of these data with reference to clinical data and the possible identification of subvoxel hypoxia, given the size similarity between the computational domain and the imaging voxel.

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Section: Resultsmentioning

confidence: 84%

Section: Influence Of Acute Hypoxia and Tumor Oxygen Consumptionmentioning

confidence: 83%

Section: Discussionmentioning

confidence: 99%

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Microvascular morphology affects radiotherapy outcomes: a computational study

Possenti,

Vitullo,

Cicchetti

et al. 2023

Preprint

Self Cite

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“…After considering the classical Dirichlet-Neumann interface conditions, we also address Robin type transmission conditions. This variant of the problem formulation is particularly significant for multiscale mass transport and fluid mechanics problems [14,12,24,23,32]. Here, we show how a prototype of these applications can be formulated and analyzed in the framework of perturbed saddle point problems.…”

Section: Introductionmentioning

confidence: 99%

Reduced Lagrange multiplier approach for non-matching coupling of mixed-dimensional domains

Heltai¹,

Zunino²

2023

Preprint

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Many physical problems involving heterogeneous spatial scales, such as the flow through fractured porous media, the study of fiber-reinforced materials or the modeling of the small circulation in living tissues -just to mention a few examples -can be described as coupled partial differential equations defined in domains of heterogeneous dimensions that are embedded into each other. This formulation is a consequence of geometric model reduction techniques that transform the original problems defined in complex three-dimensional domains into more tractable ones. The definition and the approximation of coupling operators suitable for this class of problems is still a challenge. The main objective of this work is to develop a general mathematical framework for the analysis and the approximation of partial differential equations coupled by nonmatching constraints across different dimensions. Considering the non standard formulation of the coupling conditions, we focus on their enforcement using Lagrange multipliers. In this context we address in abstract and general terms the well posedness, the stability, the robustness of the problem with respect to the smallest characteristic length of the embedded domain. We also address the the numerical approximation of the problem and we discuss the inf-sup stability of the proposed numerical scheme for some representative configuration of the embedded domain. The main message of this work is twofold: from the standpoint of the theory of mixed-dimensional problems, we provide general and abstract mathematical tools to formulate coupled problems across dimensions. From the practical standpoint of the numerical approximation, we show the interplay between the mesh characteristic size, the dimension of the Lagrange multiplier space and the size of the inclusion in representative configurations interesting for applications. The latter analysis is complemented with illustrative numerical examples.

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“…Multiscale model strategies are derived to account for the effect of blood flow pressure on the surrounding elastic tissue 7 or to investigate oxygen transport. 12 In order for in silico medicine to become a reality, the methods developed to solve the model equations need to be efficient. For example, Pfaller et al 11 proposed a methodology to monitor and achieve faster blood flow periodicity of the solution using a coarser scale initial solution.…”

mentioning

confidence: 99%