Interstitial hydraulic conductivity and interstitial fluid pressure for avascular or poorly vascularized tumors

Liu, Long Jian; Schlesinger, M.

doi:10.1016/j.jtbi.2015.05.012

Cited by 14 publications

(23 citation statements)

References 18 publications

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“…This may simplify the computation for estimating TIFP. If we choose a direction in which the velocity distribution curve is nonlinear, more parameters such as  (Baxter and Jain, 1989),  and/or  (Liu and Schlesinger, 2015) will be needed to describe the distribution. However, we might not be able to determine these parameters.…”

Section: Methodsmentioning

confidence: 99%

“…However, we might not be able to determine these parameters. Generally, a linear fluid velocity distribution can be expressed as (Hompland et al, 2012b;Liu and Schlesinger, 2015) 8…”

Section: Methodsmentioning

confidence: 99%

“…where R 0 represents the boundary of the central region (an iso-pressure and iso-velocity surface), R s the tumor surface, R m the maximum position that tumor interstitial fluid can spread to, which is the location where pressure becomes the same as that in normal tissue, d 0 =R s -R 0 and d m =R m -R s (Liu and Schlesinger, 2015;Liu et al, 2011). For an isolated tumor, d m =0, so the above formula for the region R 0 <r<R s can still be applied.…”

Section: Methodsmentioning

confidence: 99%

“…TIFP may be estimated through i) approximation of the velocity of tumor exudate at tumor surface, ii) measurement of the distance from tumor surface to where the tumor exudate is absorbed (or normalized), and iii) estimation of the interstitial hydraulic conductivity, which is referred to as the K-factor of the tissue through which the tumor exudate travels (Liu and Schlesinger, 2015;Liu et al, 2011). Hompland et al (Hompland et al, 2012b) showed the method for determining the fluid velocity and size of the tumor rim based on DCE-MRI images.…”

Section: Introductionmentioning

confidence: 99%

“…Typically, interstitial fluid velocity distribution is modeled as shown in Fig. 1 (Baxter and Jain, 1989;Liu and Schlesinger, 2015). Fig.1.…”

Section: Introductionmentioning

confidence: 99%

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MRI contrast agent concentration and tumor interstitial fluid pressure

Liu

Schlesinger

2016

Journal of Theoretical Biology

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Section: Methodsmentioning

confidence: 99%

“…However, we might not be able to determine these parameters. Generally, a linear fluid velocity distribution can be expressed as (Hompland et al, 2012b;Liu and Schlesinger, 2015) 8…”

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

“…Typically, interstitial fluid velocity distribution is modeled as shown in Fig. 1 (Baxter and Jain, 1989;Liu and Schlesinger, 2015). Fig.1.…”

Section: Introductionmentioning

confidence: 99%

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MRI contrast agent concentration and tumor interstitial fluid pressure

Liu

Schlesinger

2016

Journal of Theoretical Biology

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Hydraulic conductivity of human cancer tissue: A hybrid study

Salavati,

Pullens,

Debbaut

et al. 2023

Bioengineering & Transla Med

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BackgroundElevated tumor tissue interstitial fluid pressure (IFP) is an adverse biomechanical biomarker that predicts poor therapy response and an aggressive phenotype. Advances in functional imaging have opened the prospect of measuring IFP non‐invasively. Image‐based estimation of the IFP requires knowledge of the tissue hydraulic conductivity (K), a measure for the ease of bulk flow through the interstitium. However, data on the magnitude of K in human cancer tissue are not available.MethodsWe measured the hydraulic conductivity of tumor tissue using modified Ussing chambers in surgical resection specimens. The effect of the tumor microenvironment (TME) on K was investigated by quantifying the collagen content, cell density, and fibroblast density of the tested samples using quantitative immune histochemistry. Also, we developed a computational fluid dynamics (CFD) model to evaluate the role of K on interstitial fluid flow and drug transport in solid tumors.ResultsThe results show that the hydraulic conductivity of human tumor tissues is very limited, ranging from approximately 10−15 to 10−14 m2/Pa∙s. Moreover, K values varied significantly between tumor types and between different samples from the same tumor. A significant inverse correlation was found between collagen fiber density and hydraulic conductivity values. However, no correlation was detected between K and cancer cell or fibroblast densities. The computational model demonstrated the impact of K on the interstitial fluid flow and the drug concentration profile: higher K values led to a lower IFP and deeper drug penetration.ConclusionsHuman tumor tissue is characterized by a very limited hydraulic conductivity, representing a barrier to effective drug transport. The results of this study can inform the development of realistic computational models, facilitate non‐invasive IFP estimation, and contribute to stromal targeting anticancer therapies.

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Modeling In Vivo Interstitial Hydration-Pressure Relationships in Skin and Skeletal Muscle

Øien

Wiig

2018

Biophysical Journal

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A theoretical understanding of hydrostatic pressure-fluid volume relationships, or equations of state, of interstitial fluid in skin and skeletal muscle through mathematical/physical modeling is lacking. Here, we investigate at the microscopic level forces that seem to underlie and determine the movements of fluid and solid tissue elements on the microscopic as well as on the macroscopic level. Effects that occur during variation of hydration due to interaction between expanding glycosaminoglycans (GAGs) and the collagen interstitial matrix of tissue seem to be of major importance. We focus on these interactions that let effects from spherical GAGs expand and contract relative to collagen on the microscopic level as hydration changes and thereby generate a hydration-dependent electrostatic pressure on the extracellular matrix on the microscopic level. This pressure spreads to macroscopic levels and become a key factor for setting up equations of state for skin and skeletal muscle interstitia. The modeling for a combined skeletal muscle and skin tissue is one dimensional, i.e., a flat box that may mimic central transverse parts of tissue with more complex geometry. Incorporating values of GAG and collagen densities and fluid contents of skin and muscle tissues that are of an order of magnitude found in literature into the model gives interstitial hydrostatic pressure- fluid volume relationships for these tissues that agree well with experimental results.

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Interstitial hydraulic conductivity and interstitial fluid pressure for avascular or poorly vascularized tumors

Cited by 14 publications

References 18 publications

MRI contrast agent concentration and tumor interstitial fluid pressure

MRI contrast agent concentration and tumor interstitial fluid pressure

Hydraulic conductivity of human cancer tissue: A hybrid study

Modeling In Vivo Interstitial Hydration-Pressure Relationships in Skin and Skeletal Muscle

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