Improving treatment strategies for heart failure using patient-specific computer models

Improving treatment strategies for heart failure using patient-specific computer models

Research Area
Cardiac Modeling

Computer model derived indices for optimal patient-specific treatment selection and planning in Heart Failure (VP2HF)

Heart failure (HF) is one of the major health issues in Europe, affecting 6 million patients and growing substantially because of the ageing population and improving survival following myocardial infarction. The poor short to medium term prognosis of these patients means that treatments such as cardiac re-synchronisation therapy and mitral valve repair can have substantial impact. However, these therapies are ineffective in up to 50% of the treated patients and involve significant morbidity and substantial cost.

The primary aim of VP2HF is to bring together image and data processing tools with statistical and integrated biophysical models mainly developed in previous VPH projects, into a single clinical workflow to improve therapy selection and treatment optimisation in HF. The tools will be tested and validated in 200 patients (including 50 historical datasets) across 3 clinical sites, including a prospective clinical study in 50 patients in the last year of the project. The key innovations in VP2HF that make it likely that the project results will be commercially exploited and have major clinical impact, are:

  1. all tools to process images and signals, and obtain the statistical and biophysical models will be integrated into one clinical software platform that can be easily and intuitively used by clinicians and tried out in the prospective clinical study
  2. by utilising a decision tree stratification approach, only the appropriate parts of the tool chain, that will add maximum value to the predictions will be used in individual patients, so that the more resource intensive parts will be used when they will add real value. 

Final goal:

We expect that the study results in substantial improved efficacy of decision making over current guidelines, and an integrated package that is used as part of clinical workflow will ensure the industrial project partners, in particular Philips, will develop project outputs into dedicated products that will have significant clinical impact.

Funding source: 

  • European Commission (EC),
  • FP7


ICT-2013.5.2 - Virtual Physiological Human

All partners:

  • King's College London (Coordinator), United Kingdom
  • Université Catholique de Louvain, Belgium
  • Philips Technologie GMBH, Germany
  • Universitat Pompeu Fabra, Spain
  • Institut National de Recherche en Informatique et en Automatique, France
  • Chu Cote de Nacre - Caen, France
  • Philips France, France
  • Simula Research Laboratory AS, Norway