About this Research Topic
Thrombosis and haemostasis are two complex pathophysiological processes which may affect both,
arteries and veins, subsequently leading to morphological and functional changes in the tributary territories. The clinical picture can sometimes, suggests the location and severity of embolism/thrombosis, while often the clinical features are unspecific requiring multiple investigations to establish the diagnosis.
An important dilemma encountered by the physicians who needs to treat patients with arterial embolism or venous thrombosis is when to initiate and stop the anticoagulant treatment considering the frail balance between the increased thrombotic risk versus the hazard of bleeding which frequently represents a serious concern. Thus, the management of this category of patients raises multiple problems, as the physician must choose the correct drug and dose, intensity and duration of the anticoagulant/antithrombotic therapy. The risk or recurrence is often difficult to appreciate and frequently requires elaborated laboratory examinations, sometimes even genetic testing. The development of new diagnostic, therapeutic methods and protocols is needed to facilitate a precocious diagnosis, which allows an easier and more accurate quantification of the risk of recurrent thrombosis, while also decreasing the bleeding hazard. This new insight into the process of haemostasis and thrombosis requires clinical, imagistic, and genetical assessments and therapeutic approaches.
Machine learning may prove its utility in helping the physicians to establish suitable protocols. Along with data analysis, these algorithms may assist the physicians in the diagnosis and treatment of patients with cardiovascular pathology, especially of those with coagulopathies. Hemodynamic analysis facilitates a personalised diagnosis and individualised treatment of thrombosis. The patient specific hemodynamic modelling is enabled by 3D reconstruction of the blood vessels from the medical imagistic along with invasive and non-invasive measurements of flow patterns.
This Research Topic focuses on original articles, reviews, meta-analysis and case reports referring to groundbreaking research regarding thrombosis and haemostasis.
arteries and veins, subsequently leading to morphological and functional changes in the tributary territories. The clinical picture can sometimes, suggests the location and severity of embolism/thrombosis, while often the clinical features are unspecific requiring multiple investigations to establish the diagnosis.
An important dilemma encountered by the physicians who needs to treat patients with arterial embolism or venous thrombosis is when to initiate and stop the anticoagulant treatment considering the frail balance between the increased thrombotic risk versus the hazard of bleeding which frequently represents a serious concern. Thus, the management of this category of patients raises multiple problems, as the physician must choose the correct drug and dose, intensity and duration of the anticoagulant/antithrombotic therapy. The risk or recurrence is often difficult to appreciate and frequently requires elaborated laboratory examinations, sometimes even genetic testing. The development of new diagnostic, therapeutic methods and protocols is needed to facilitate a precocious diagnosis, which allows an easier and more accurate quantification of the risk of recurrent thrombosis, while also decreasing the bleeding hazard. This new insight into the process of haemostasis and thrombosis requires clinical, imagistic, and genetical assessments and therapeutic approaches.
Machine learning may prove its utility in helping the physicians to establish suitable protocols. Along with data analysis, these algorithms may assist the physicians in the diagnosis and treatment of patients with cardiovascular pathology, especially of those with coagulopathies. Hemodynamic analysis facilitates a personalised diagnosis and individualised treatment of thrombosis. The patient specific hemodynamic modelling is enabled by 3D reconstruction of the blood vessels from the medical imagistic along with invasive and non-invasive measurements of flow patterns.
This Research Topic focuses on original articles, reviews, meta-analysis and case reports referring to groundbreaking research regarding thrombosis and haemostasis.
Keywords: haemostasis, thrombosis, embolism, haemorrhagic risk, laboratory tests, clinical presentation, antithrombotic/anticoagulant therapy, medical image processing, data mining, machine learning, deep learning, computational fluid dynamics
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