The healthy blood flow dynamics is altered in presence of cardiovascular disease and therefore anomaly in the flow dynamics can offer a wealth of information. Similarly, the blood flow and vascular network connect are essential contributors to cancer metastasis by providing the connecting path for cell migration that includes the entire body. Blood flow dynamics is both a main contributor and a diagnostic indicator of progression of cardiovascular disease and cancer metastasis mediated by the vascular network connecting organs in the body. Computational analysis of hemodynamics can provide a means for investigating the disease state and detecting anomalies to provide diagnostic information, predict the next steps of disease progression and staging and guide personalized treatment planning.
Novel advanced computational hemodynamic analysis tools may enable the next generation of diagnosis, predictive, and treatment planning tools for cardiovascular disease and metastasis. Such methods should consider the wide inter-subject variability in the circulatory anatomy and pathophysiology, to provide personalized diagnosis, prediction, and treatment plans. The goal of this Research Topic is to document recent advances in developing such much-needed computational hemodynamic methods for diagnosis, prediction, and personalized treatment planning for cardiovascular diseases and cancer metastasis.
This Research Topic covers the novel tools, methods, and studies that exploit the power of novel advanced computational hemodynamic tools to provide quantitative information about blood flow and its interactions with cells and tissues beyond the current clinical conventional possibilities. The following themes are included in the scope:
• Advances in computational tools and models to quantify blood flow dynamics of cardiovascular disease.
• Advances in computational tools and models to simulate the intravasation, circulation, arrest, and extravasation of circulating tumour cells
• Advances in computational methods for cancer cell adhesion and vascular occlusion
• Advances computationally-augmented image and signal processing for diagnosis, monitoring, and prediction of cardiovascular disease and metastasis
• Advances in computationally-augmented personalized and precision treatment
• Advances in computational-aided interventions
The healthy blood flow dynamics is altered in presence of cardiovascular disease and therefore anomaly in the flow dynamics can offer a wealth of information. Similarly, the blood flow and vascular network connect are essential contributors to cancer metastasis by providing the connecting path for cell migration that includes the entire body. Blood flow dynamics is both a main contributor and a diagnostic indicator of progression of cardiovascular disease and cancer metastasis mediated by the vascular network connecting organs in the body. Computational analysis of hemodynamics can provide a means for investigating the disease state and detecting anomalies to provide diagnostic information, predict the next steps of disease progression and staging and guide personalized treatment planning.
Novel advanced computational hemodynamic analysis tools may enable the next generation of diagnosis, predictive, and treatment planning tools for cardiovascular disease and metastasis. Such methods should consider the wide inter-subject variability in the circulatory anatomy and pathophysiology, to provide personalized diagnosis, prediction, and treatment plans. The goal of this Research Topic is to document recent advances in developing such much-needed computational hemodynamic methods for diagnosis, prediction, and personalized treatment planning for cardiovascular diseases and cancer metastasis.
This Research Topic covers the novel tools, methods, and studies that exploit the power of novel advanced computational hemodynamic tools to provide quantitative information about blood flow and its interactions with cells and tissues beyond the current clinical conventional possibilities. The following themes are included in the scope:
• Advances in computational tools and models to quantify blood flow dynamics of cardiovascular disease.
• Advances in computational tools and models to simulate the intravasation, circulation, arrest, and extravasation of circulating tumour cells
• Advances in computational methods for cancer cell adhesion and vascular occlusion
• Advances computationally-augmented image and signal processing for diagnosis, monitoring, and prediction of cardiovascular disease and metastasis
• Advances in computationally-augmented personalized and precision treatment
• Advances in computational-aided interventions