euHeart: personalized and integrated cardiac care using patient-specific cardiovascular modelling

Abstract

The loss of cardiac pump function accounts for a significant increase in both mortality and morbidity in Western society, where there is currently a one in four lifetime risk, and costs associated with acute and long-term hospital treatments are accelerating. The significance of cardiac disease has motivated the application of state-of-the-art clinical imaging techniques and functional signal analysis to aid diagnosis and clinical planning. Measurements of cardiac function currently provide high-resolution datasets for characterizing cardiac patients. However, the clinical practice of using population-based metrics derived from separate image or signal-based datasets often indicates contradictory treatments plans owing to inter-individual variability in pathophysiology. To address this issue, the goal of our work, demonstrated in this study through four specific clinical applications, is to integrate multiple types of functional data into a consistent framework using multi-scale computational modelling.

Image-based large-eddy simulation in a realistic left heart

“…In this approach, patient-specific data are needed [33,34]. What is the exact rheology of the myocardial muscle?…”

Patient-specific image-based computer simulation for theprediction of valve morphology and calcium displacement after TAVI with the Medtronic CoreValve and the Edwards SAPIEN valve

“…The present study is a proof of concept and is indicative of the clinical utility of preprocedural computer simulation. Patientspecific preprocedural planning or personalised medicine is requested by many healthcare authorities confronted by increasing healthcare costs as a result of an ageing population and also increasing treatment modalities for older patients 27,28 . The methods proposed in this study may serve this goal since and -at variance with surgical valve replacement -there is no direct vision of the target zone and no excision of calcium that is intrinsically associated with a higher degree of unpredictability of valve geometry and function.…”

The Virtual Physiological Human: Ten Years After

“…Another VPH initiative that facilitates the development of computational models for the clinic is VPH-Share 25 . This major project, led by the University of Sheffield, has created a cloud-320 based IT infrastructure and universal clinical workflow development system capable of supporting the construction and operation of complete software systems to extract novel and possibly complex biomarkers from raw clinical information, and so to provide clinicians with decision support for diagnosis, stratification, therapy selection and treatment planning (20).…”