Patient-Specific Characterization of Breast Cancer Hemodynamics Using Image-Guided Computational Fluid Dynamics
| العنوان: | Patient-Specific Characterization of Breast Cancer Hemodynamics Using Image-Guided Computational Fluid Dynamics |
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| المؤلفون: | David A. Hormuth, Todd Oliver, Guillermo Lorenzo, Robert D. Moser, Federico Pineda, Chengyue Wu, Gregory S. Karczmar, Thomas E. Yankeelov |
| المصدر: | IEEE Trans Med Imaging |
| بيانات النشر: | Institute of Electrical and Electronics Engineers (IEEE), 2020. |
| سنة النشر: | 2020 |
| مصطلحات موضوعية: | Contrast Media, Hemodynamics, Breast Neoplasms, Sensitivity and Specificity, Article, 030218 nuclear medicine & medical imaging, 03 medical and health sciences, 0302 clinical medicine, Breast cancer, medicine, Humans, Breast, Electrical and Electronic Engineering, Retrospective Studies, Radiological and Ultrasound Technology, medicine.diagnostic_test, Receiver operating characteristic, business.industry, Magnetic resonance imaging, Fluid mechanics, Blood flow, medicine.disease, Magnetic Resonance Imaging, Computer Science Applications, Diffusion Magnetic Resonance Imaging, ROC Curve, Dynamic contrast-enhanced MRI, Hydrodynamics, Female, business, Software, Biomedical engineering, Diffusion MRI |
| الوصف: | 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. |
| تدمد: | 1558-254X 0278-0062 |
| DOI: | 10.1109/tmi.2020.2975375 |
| URL الوصول: | https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1bd9b10c4264838f78a0ef65d0ad2715 https://doi.org/10.1109/tmi.2020.2975375 |
| Rights: | OPEN |
| رقم الانضمام: | edsair.doi.dedup.....1bd9b10c4264838f78a0ef65d0ad2715 |
| قاعدة البيانات: | OpenAIRE |
| تدمد: | 1558254X 02780062 |
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| DOI: | 10.1109/tmi.2020.2975375 |