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Patient-Specific Characterization of Breast Cancer Hemodynamics Using Image-Guided Computational Fluid Dynamics.

ABSTRACT: The overall goal of this study is to employ quantitative magnetic resonance imaging (MRI) data to constrain a patient-specific, computational fluid dynamics (CFD) model of blood flow and interstitial transport in breast cancer. We develop image processing methodologies to generate tumor-related vasculature-interstitium geometry and realistic material properties, using dynamic contrast enhanced MRI (DCE-MRI) and diffusion weighted MRI (DW-MRI) data. These data are used to constrain CFD simulations for determining the tumor-associated blood supply and interstitial transport characteristics unique to each patient. We then perform a proof-of-principle statistical comparison between these hemodynamic characteristics in 11 malignant and 5 benign lesions from 12 patients. Significant differences between groups (i.e., malignant versus benign) were observed for the median of tumor-associated interstitial flow velocity ( P = 0.028 ), and the ranges of tumor-associated blood pressure (P = 0.016) and vascular extraction rate (P = 0.040). The implication is that malignant lesions tend to have larger magnitude of interstitial flow velocity, and higher heterogeneity in blood pressure and vascular extraction rate. Multivariable logistic models based on combinations of these hemodynamic data achieved excellent differentiation between malignant and benign lesions with an area under the receiver operator characteristic curve of 1.0, sensitivity of 1.0, and specificity of 1.0. This image-based model system is a fundamentally new way to map flow and pressure fields related to breast tumors using only non-invasive, clinically available imaging data and established laws of fluid mechanics. Furthermore, the results provide preliminary evidence for this methodology's utility for the quantitative characterization of breast cancer.

SUBMITTER: Wu C

PROVIDER: S-EPMC7438313 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Accumulating studies on computational fluid dynamics (CFD) support the involvement of hemodynamic factors in artery stenosis. Based on a patient-specific CFD model, the present study aimed to investigate the hemodynamic characteristics of transplant renal artery stenosis (TRAS) and its alteration after stent treatment.Computed tomography angiography (CTA) data of kidney transplant recipients in a single transplant center from April 2013 to November 2014 were reviewed. The three-dimensional geometry of transplant renal artery (TRA) was reconstructed from the qualified CTA images and categorized into three groups: the normal, stenotic, and stented groups. Hemodynamic parameters including pressure distribution, velocity, wall shear stress (WSS), and mass flow rate (MFR) were extracted. The data of hemodynamic parameters were expressed as median (interquartile range), and Mann-Whitney U-test was used for analysis.Totally, 6 normal, 12 stenotic, and 6 stented TRAs were included in the analysis. TRAS presented nonuniform pressure distribution, adverse pressure gradient across stenosis throat, flow vortex, and a separation zone at downstream stenosis. Stenotic arteries had higher maximal velocity and maximal WSS (2.94 [2.14, 3.30] vs. 1.06 [0.89, 1.15] m/s, 256.5 [149.8, 349.4] vs. 41.7 [37.8, 45.3] Pa at end diastole, P= 0.001; 3.25 [2.67, 3.56] vs. 1.65 [1.18, 1.72] m/s, 281.3 [184.3, 364.7] vs. 65.8 [61.2, 71.9] Pa at peak systole, P= 0.001) and lower minimal WSS and MFRs (0.07 [0.03, 0.13] vs. 0.52 [0.45, 0.67] Pa, 1.5 [1.0, 3.0] vs. 11.0 [8.0, 11.3] g/s at end diastole, P= 0.001; 0.08 [0.03, 0.19] vs. 0.70 [0.60, 0.81] Pa, 2.0 [1.3, 3.3] vs. 16.5 [13.0, 20.3] g/s at peak systole, P= 0.001) as compared to normal arteries. Stent implantation ameliorated all the alterations of the above hemodynamic factors except low WSS.Hemodynamic factors were significantly changed in severe TRAS. Stent implantation can restore or ameliorate deleterious change of hemodynamic factors except low WSS at stent regions.

Project description:Complex hemodynamics assessments, as those related to carotid stenosis, are not always easily straightforward due to multifaceted challenges presented by the collateral flow in the Circle of Willis (CoW) and brain flow autoregulation. Advanced computational and benchtop methods to investigate hemodynamics aspects related to such complex flows are often used, however both have limitations and could lead to results which may diverge. In this study we investigated these aspects by performing correlated computational fluid dynamics (CFD) simulations and benchtop experiments in patient specific 3D printed phantoms. To investigate the flow in patients with carotid stenosis, we built two patient specific phantoms which contained the arterial lesion of interest, all main arteries leading to the brain, the CoW and main arteries branching from it. Each phantom was connected to a generic aortic arch. A programmable pump was connected and flow parameters were measured proximal and distal to the lesion and the contralateral arteries. The patient 3D geometry was used to perform a set of CFD simulations where inflow boundary conditions matched the experimental ones. Flow conditions were recorded at the same locations as the experimental setup. Further exploration into the translation from experimental to CFD was also performed by customizing vascular segmentation and physically manipulating arterial compliance properties. We initially observed significant differences between the CFD recordings and the experimental setup. Most of the differences were due to changes in phantom geometry when subjected to physiological pressures and simplistic outflow boundary conditions in the CFD simulations which do not account for pulsatility and nonlinear phenomena. Further work confirms the need for dynamic mesh behavior within CFD simulations attempting to computationally mimic 3D-printed benchtop experiments. Additionally, CFD simulation may benefit from considering geometry specific to a 3D-printed vascular phantom.

Project description:To assess whether in-silico models can be used to predict the risk of thrombus formation in pulmonary artery pressure sensors (PAPS), a chronic animal study using pigs was conducted. Computed tomography (CT) data was acquired before and immediately after implantation, as well as one and three months after the implantation. Devices were implanted into 10 pigs, each one in the left and right pulmonary artery (PA), to reduce the required number of animal experiments. The implantation procedure aimed at facilitating optimal and non-optimal positioning of the devices to increase chances of thrombus formation. Eight devices were positioned non-optimally. Three devices were positioned in the main PA instead of the left and right PA. Pre-interventional PA geometries were reconstructed from the respective CT images, and the devices were virtually implanted at the exact sites and orientations indicated by the follow-up CT after one month. Transient intra-arterial hemodynamics were calculated using computational fluid dynamics. Volume flow rates were modelled specifically matching the animals body weights. Wall shear stresses (WSS) and oscillatory shear indices (OSI) before and after device implantation were compared. Simulations revealed no relevant changes in any investigated hemodynamic parameters due to device implantation. Even in cases, where devices were implanted in a non-optimal manner, no marked differences in hemodynamic parameters compared to devices implanted in an optimal position were found. Before implantation time and surface-averaged WSS was 2.35±0.47 Pa, whereas OSI was 0.08±0.17, respectively. Areas affected by low WSS magnitudes were 2.5±2.7 cm2, whereas the areas affected by high OSI were 18.1±6.3 cm2. After device implantation, WSS and OSI were 2.45±0.49 Pa and 0.08±0.16, respectively. Surface areas affected by low WSS and high OSI were 2.9±2.7 cm2, and 18.4±6.1 cm2, respectively. This in-silico study indicates that no clinically relevant differences in intra-arterial hemodynamics are occurring after device implantation, even at non-optimal positioning of the sensor. Simultaneously, no embolic events were observed, suggesting that the risk for thrombus formation after device implantation is low and independent of the sensor position.

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Patient-Specific Characterization of Breast Cancer Hemodynamics Using Image-Guided Computational Fluid Dynamics.

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