Browsing by Author "Pleouras, Dimitrios S. (57213604972)"
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Publication A Machine Learning Model for the prediction of the progression of carotid arterial stenoses(2023) ;Siogkas, Panagiotis K. (36976596100) ;Pleouras, Dimitrios S. (57213604972) ;Tsakanikas, Vasilis D. (36718299600) ;Potsika, Vassiliki T. (55826618900) ;Tsiouris, Kostas M. (56252054300) ;Sakellarios, Antonis (36476633700) ;Karamouzi, Evdokia (58761408700) ;Lagiou, Foteini (58761633000) ;Charalampopoulos, George (17343466700) ;Galyfos, George (55658700300) ;Sigala, Fragiska (55393308900) ;Koncar, Igor (19337386500)Fotiadis, Dimitrios I. (55938920100)Atherosclerotic carotid plaque development results in a steady narrowing of the artery lumen, which may eventually trigger catastrophic plaque rupture leading to thromboembolism and stroke. The primary cause of ischemic stroke in the EU is carotid artery disease, which increases the demand for tools for risk stratification and patient management in carotid artery disease. Additionally, advancements in cardiovascular modeling over the past few years have made it possible to build accurate three-dimensional models of patient-specific primary carotid arteries. Computational models then incorporate the aforementioned 3D models to estimate either the development of atherosclerotic plaque or a number of flow-related parameters that are linked to risk assessment. This work presents an attempt to provide a carotid artery stenosis prognostic model, utilizing non-imaging and imaging data, as well as simulated hemodynamic data. The overall methodology was trained and tested on a dataset of 41 cases with 23 carotid arteries with stable stenosis and 18 carotids with increasing stenosis degree. The highest accuracy of 71% was achieved using a neural network classifier. The novel aspect of our work is the definition of the problem that is solved, as well as the amount of simulated data that are used as input for the prognostic model.Clinical Relevance - A prognostic model for the prediction of the trajectory of carotid artery atherosclerosis is proposed, which can support physicians in critical treatment decisions. © 2023 IEEE. - Some of the metrics are blocked by yourconsent settings
Publication A Machine Learning Model for the prediction of the progression of carotid arterial stenoses(2023) ;Siogkas, Panagiotis K. (36976596100) ;Pleouras, Dimitrios S. (57213604972) ;Tsakanikas, Vasilis D. (36718299600) ;Potsika, Vassiliki T. (55826618900) ;Tsiouris, Kostas M. (56252054300) ;Sakellarios, Antonis (36476633700) ;Karamouzi, Evdokia (58761408700) ;Lagiou, Foteini (58761633000) ;Charalampopoulos, George (17343466700) ;Galyfos, George (55658700300) ;Sigala, Fragiska (55393308900) ;Koncar, Igor (19337386500)Fotiadis, Dimitrios I. (55938920100)Atherosclerotic carotid plaque development results in a steady narrowing of the artery lumen, which may eventually trigger catastrophic plaque rupture leading to thromboembolism and stroke. The primary cause of ischemic stroke in the EU is carotid artery disease, which increases the demand for tools for risk stratification and patient management in carotid artery disease. Additionally, advancements in cardiovascular modeling over the past few years have made it possible to build accurate three-dimensional models of patient-specific primary carotid arteries. Computational models then incorporate the aforementioned 3D models to estimate either the development of atherosclerotic plaque or a number of flow-related parameters that are linked to risk assessment. This work presents an attempt to provide a carotid artery stenosis prognostic model, utilizing non-imaging and imaging data, as well as simulated hemodynamic data. The overall methodology was trained and tested on a dataset of 41 cases with 23 carotid arteries with stable stenosis and 18 carotids with increasing stenosis degree. The highest accuracy of 71% was achieved using a neural network classifier. The novel aspect of our work is the definition of the problem that is solved, as well as the amount of simulated data that are used as input for the prognostic model.Clinical Relevance - A prognostic model for the prediction of the trajectory of carotid artery atherosclerosis is proposed, which can support physicians in critical treatment decisions. © 2023 IEEE. - Some of the metrics are blocked by yourconsent settings
Publication Computational modeling of atherosclerotic plaque progression in carotid lesions with moderate degree of stenosis(2021) ;Mantzaris, Michalis D. (24478053800) ;Siogkas, Panagiotis K. (36976596100) ;Tsakanikas, Vassilis D. (36718299600) ;Potsika, Vassiliki T. (55826618900) ;Pleouras, Dimitrios S. (57213604972) ;Sakellarios, Antonis I. (36476633700) ;Karagiannis, Georgios (57509364400) ;Galyfos, George (55658700300) ;Sigala, Fragiska (55393308900) ;Liasis, Nikolaos (10440375500) ;Jovanovic, Marija (57194767566) ;Koncar, Igor B. (19337386500) ;Kallmayer, Michael (41861588900)Fotiadis, Dimitrios I. (55938920100)Carotid atherosclerotic plaque growth leads to the progressive luminal stenosis of the vessel, which may erode or rupture causing thromboembolism and cerebral infarction, manifested as stroke. Carotid atherosclerosis is considered the major cause of ischemic stroke in Europe and thus new imaging-based computational tools that can improve risk stratification and management of carotid artery disease patients are needed. In this work, we present a new computational approach for modeling atherosclerotic plaque progression in real patient-carotid lesions, with moderate to severe degree of stenosis (>50%). The model incorporates for the first time, the baseline 3D geometry of the plaque tissue components (e.g. Lipid Core) identified by MR imaging, in which the major biological processes of atherosclerosis are simulated in time. The simulated plaque tissue production results in the inward remodeling of the vessel wall promoting luminal stenosis which in turn predicts the region of the actual stenosis progression observed at the follow-up visit. The model aims to support clinical decision making, by identifying regions prone to plaque formation, predict carotid stenosis and plaque burden progression, and provide advice on the optimal time for patient follow-up screening. © 2021 IEEE. - Some of the metrics are blocked by yourconsent settings
Publication Computational modeling of atherosclerotic plaque progression in carotid lesions with moderate degree of stenosis(2021) ;Mantzaris, Michalis D. (24478053800) ;Siogkas, Panagiotis K. (36976596100) ;Tsakanikas, Vassilis D. (36718299600) ;Potsika, Vassiliki T. (55826618900) ;Pleouras, Dimitrios S. (57213604972) ;Sakellarios, Antonis I. (36476633700) ;Karagiannis, Georgios (57509364400) ;Galyfos, George (55658700300) ;Sigala, Fragiska (55393308900) ;Liasis, Nikolaos (10440375500) ;Jovanovic, Marija (57194767566) ;Koncar, Igor B. (19337386500) ;Kallmayer, Michael (41861588900)Fotiadis, Dimitrios I. (55938920100)Carotid atherosclerotic plaque growth leads to the progressive luminal stenosis of the vessel, which may erode or rupture causing thromboembolism and cerebral infarction, manifested as stroke. Carotid atherosclerosis is considered the major cause of ischemic stroke in Europe and thus new imaging-based computational tools that can improve risk stratification and management of carotid artery disease patients are needed. In this work, we present a new computational approach for modeling atherosclerotic plaque progression in real patient-carotid lesions, with moderate to severe degree of stenosis (>50%). The model incorporates for the first time, the baseline 3D geometry of the plaque tissue components (e.g. Lipid Core) identified by MR imaging, in which the major biological processes of atherosclerosis are simulated in time. The simulated plaque tissue production results in the inward remodeling of the vessel wall promoting luminal stenosis which in turn predicts the region of the actual stenosis progression observed at the follow-up visit. The model aims to support clinical decision making, by identifying regions prone to plaque formation, predict carotid stenosis and plaque burden progression, and provide advice on the optimal time for patient follow-up screening. © 2021 IEEE. - Some of the metrics are blocked by yourconsent settings
Publication Investigation of the significance of the plaque morphology evolution in plaque rupture events using computational biomechanics(2024) ;Pleouras, Dimitrios S. (57213604972) ;Siogkas, Panagiotis K. (36976596100) ;Potsika, Vassiliki T. (55826618900) ;Tsakanikas, Vasilis D. (36718299600) ;Dimos, Sokratis S. (59513716600) ;Mantzaris, Michalis D. (24478053800) ;Koncar, Igor (19337386500)Fotiadis, Dimitrios I. (55938920100)Forwarded by the technological urge of this era, several computational methods are implemented to give further insights into possible outcomes of diseases. In this context, atherosclerosis, which is one of the most fatal diseases nowadays, is treated alike, where several computational models are proposed annually allowing for the evaluation of several outcomes for patient specific cases. Among them, one of the most significant models is able to predict the atherosclerotic evolution over time. In this proof-of-concept study, we aim to investigate the effect of plaque morphology on plaque rupture in a two-case scenario - a longitudinal and a bulk plaque evolution in 3D-reconstructed patient-specific carotids arteries. Our approach is based on a three-step process: i) the implementation of a state-of-the-art plaque growth model that predicts evolving and new plaques in real patient specific carotid arteries, ii) the selection of 2 patient cases, one with longitudinal plaque evolution and one with bulk plaque evolution and, finally, iii) the evaluation the maximum principal stress over the plaques and the endothelium layers to assess the plaque rupture risk. The results indicate that the evolving plaques towards the lumen, not only cause stenoses but also are more prone to rupture. Clinical relevance- This proof-of-concept work establishes that the plaques that grow towards the luminal border present with a higher risk of potential rupture compared to plaques that grow longitudinally, thus giving valuable insights to clinicians for important decision making regarding potential endarterectomy procedures. © 2024 IEEE. - Some of the metrics are blocked by yourconsent settings
Publication Investigation of the significance of the plaque morphology evolution in plaque rupture events using computational biomechanics(2024) ;Pleouras, Dimitrios S. (57213604972) ;Siogkas, Panagiotis K. (36976596100) ;Potsika, Vassiliki T. (55826618900) ;Tsakanikas, Vasilis D. (36718299600) ;Dimos, Sokratis S. (59513716600) ;Mantzaris, Michalis D. (24478053800) ;Koncar, Igor (19337386500)Fotiadis, Dimitrios I. (55938920100)Forwarded by the technological urge of this era, several computational methods are implemented to give further insights into possible outcomes of diseases. In this context, atherosclerosis, which is one of the most fatal diseases nowadays, is treated alike, where several computational models are proposed annually allowing for the evaluation of several outcomes for patient specific cases. Among them, one of the most significant models is able to predict the atherosclerotic evolution over time. In this proof-of-concept study, we aim to investigate the effect of plaque morphology on plaque rupture in a two-case scenario - a longitudinal and a bulk plaque evolution in 3D-reconstructed patient-specific carotids arteries. Our approach is based on a three-step process: i) the implementation of a state-of-the-art plaque growth model that predicts evolving and new plaques in real patient specific carotid arteries, ii) the selection of 2 patient cases, one with longitudinal plaque evolution and one with bulk plaque evolution and, finally, iii) the evaluation the maximum principal stress over the plaques and the endothelium layers to assess the plaque rupture risk. The results indicate that the evolving plaques towards the lumen, not only cause stenoses but also are more prone to rupture. Clinical relevance- This proof-of-concept work establishes that the plaques that grow towards the luminal border present with a higher risk of potential rupture compared to plaques that grow longitudinally, thus giving valuable insights to clinicians for important decision making regarding potential endarterectomy procedures. © 2024 IEEE.
