Reference number : GC-2017-Q1-02598, amendment number : , agreement type : G, recipient legal name : Keshavarz Motamed, Zahra (McMaster University), recipient country : CA, recipient province : nan, recipient city : Ontario, recipient postal code : nan, program name english : Discovery Grants Program - Individual, program name french : Programme de subventions à la découverte - individuelles, program purpose english : The main functions of the cardiovascular system are to transport, control and maintain blood flow in the entire body. Abnormal hemodynamics greatly alters this tranquil picture, leading to initiation and progression of disease. Cardiovascular disease is the leading cause of death globally. In Canada, one in every four deaths is from cardiovascular disease. Flow quantification can be greatly useful for accurate and early diagnosis but we still lack proper diagnostic methods for many cardiovascular diseases. Furthermore, as most interventions intend to recover the healthy condition, the ability to predict hemodynamics and biomechanics following a particular intervention can have significant impacts on saving lives. Despite remarkable advances in medical imaging, predictive methods remain rare. 
 
The main objective of this proposal is developing computational-mechanics frameworks for diagnosis and prediction for the most fundamentally challenging condition: complex ventricular-valvular interactions (CVVI). CVVI represent conditions in which multiple valvular and ventricular pathologies have mechanical interactions with one another wherein physical phenomena associated with each pathology amplify effects of others on the cardiovascular system. Transcatheter valve replacement (TVR) is a minimally invasive and growing alternative intervention in patients with severe valvular pathologies. It was shown that many patients experience a significant improvement after TVR but in many others CVVI worsens or changes to other forms of CVVI. As pathologies in CVVI are essentially of fluid-dynamic nature, they are best quantified using mechanics. Indeed, even the emerging innovations in therapeutics such as TVR are themselves mechanical. Yet, few to date have used basic mechanics for diagnosis of these pathologies and for prediction of response to interventions. The heart resides in a sophisticated vascular network whose loads impose boundary conditions on the heart function. Effective diagnosis and prediction hinge on quantifications of the heart workload (global effect) and of hemodynamics of CVVI and TVR (local effect). 
 
This proposal tackles profound scientific and engineering challenges to develop the following innovative computational-mechanics methods for diagnosis and prediction: 
 
(1) Computational-mechanics and imaging-based diagnostic methods: 
 (a) Local: to noninvasively quantify vortex dynamics, fluid transport, and mixing in CVVI and TVR using Lagrangian coherent structures (LCS); 
 (b) Global: to noninvasively quantify global hemodynamics to diagnose pathologies present in CVVI in terms of heart workload. 
 
 (2) A multiscale predictive computational-mechanics framework that dynamically couples the local hemodynamics with the global circulatory cardiovascular system in pre-intervention condition to predict local and global hemodynamics post-TVR., program purpose french : The main functions of the cardiovascular system are to transport, control and maintain blood flow in the entire body. Abnormal hemodynamics greatly alters this tranquil picture, leading to initiation and progression of disease. Cardiovascular disease is the leading cause of death globally. In Canada, one in every four deaths is from cardiovascular disease. Flow quantification can be greatly useful for accurate and early diagnosis but we still lack proper diagnostic methods for many cardiovascular diseases. Furthermore, as most interventions intend to recover the healthy condition, the ability to predict hemodynamics and biomechanics following a particular intervention can have significant impacts on saving lives. Despite remarkable advances in medical imaging, predictive methods remain rare. 
 
The main objective of this proposal is developing computational-mechanics frameworks for diagnosis and prediction for the most fundamentally challenging condition: complex ventricular-valvular interactions (CVVI). CVVI represent conditions in which multiple valvular and ventricular pathologies have mechanical interactions with one another wherein physical phenomena associated with each pathology amplify effects of others on the cardiovascular system. Transcatheter valve replacement (TVR) is a minimally invasive and growing alternative intervention in patients with severe valvular pathologies. It was shown that many patients experience a significant improvement after TVR but in many others CVVI worsens or changes to other forms of CVVI. As pathologies in CVVI are essentially of fluid-dynamic nature, they are best quantified using mechanics. Indeed, even the emerging innovations in therapeutics such as TVR are themselves mechanical. Yet, few to date have used basic mechanics for diagnosis of these pathologies and for prediction of response to interventions. The heart resides in a sophisticated vascular network whose loads impose boundary conditions on the heart function. Effective diagnosis and prediction hinge on quantifications of the heart workload (global effect) and of hemodynamics of CVVI and TVR (local effect). 
 
This proposal tackles profound scientific and engineering challenges to develop the following innovative computational-mechanics methods for diagnosis and prediction: 
 
(1) Computational-mechanics and imaging-based diagnostic methods: 
 (a) Local: to noninvasively quantify vortex dynamics, fluid transport, and mixing in CVVI and TVR using Lagrangian coherent structures (LCS); 
 (b) Global: to noninvasively quantify global hemodynamics to diagnose pathologies present in CVVI in terms of heart workload. 
 
 (2) A multiscale predictive computational-mechanics framework that dynamically couples the local hemodynamics with the global circulatory cardiovascular system in pre-intervention condition to predict local and global hemodynamics post-TVR., agreement title english : Development of diagnostic and predictive computational mechanics methods for cardiovascular system, agreement title french : Development of diagnostic and predictive computational mechanics methods for cardiovascular system, agreement number : RGPIN, agreement value : 150000.0, agreement start date : 2017-05-10, agreement end date : nan, description english : nan, description french : nan, expected results english : nan, expected results french : nan, additional information english : Grant or Award spanning more than one fiscal year. (2017-2018 to 2022-2023), additional information french : Subvention ou bourse octroyée s'appliquant à plus d'un exercice financier. (2017-2018 à 2022-2023), owner organization : nserc-crsng, owner organization title : Natural Sciences and Engineering Research Council of Canada | Conseil de recherches en sciences naturelles et en génie du Canada