PLoS ONE (Jan 2015)

Towards Personalized Cardiology: Multi-Scale Modeling of the Failing Heart.

  • Elham Kayvanpour,
  • Tommaso Mansi,
  • Farbod Sedaghat-Hamedani,
  • Ali Amr,
  • Dominik Neumann,
  • Bogdan Georgescu,
  • Philipp Seegerer,
  • Ali Kamen,
  • Jan Haas,
  • Karen S Frese,
  • Maria Irawati,
  • Emil Wirsz,
  • Vanessa King,
  • Sebastian Buss,
  • Derliz Mereles,
  • Edgar Zitron,
  • Andreas Keller,
  • Hugo A Katus,
  • Dorin Comaniciu,
  • Benjamin Meder

DOI
https://doi.org/10.1371/journal.pone.0134869
Journal volume & issue
Vol. 10, no. 7
p. e0134869

Abstract

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BackgroundDespite modern pharmacotherapy and advanced implantable cardiac devices, overall prognosis and quality of life of HF patients remain poor. This is in part due to insufficient patient stratification and lack of individualized therapy planning, resulting in less effective treatments and a significant number of non-responders.Methods and resultsState-of-the-art clinical phenotyping was acquired, including magnetic resonance imaging (MRI) and biomarker assessment. An individualized, multi-scale model of heart function covering cardiac anatomy, electrophysiology, biomechanics and hemodynamics was estimated using a robust framework. The model was computed on n=46 HF patients, showing for the first time that advanced multi-scale models can be fitted consistently on large cohorts. Novel multi-scale parameters derived from the model of all cases were analyzed and compared against clinical parameters, cardiac imaging, lab tests and survival scores to evaluate the explicative power of the model and its potential for better patient stratification. Model validation was pursued by comparing clinical parameters that were not used in the fitting process against model parameters.ConclusionThis paper illustrates how advanced multi-scale models can complement cardiovascular imaging and how they could be applied in patient care. Based on obtained results, it becomes conceivable that, after thorough validation, such heart failure models could be applied for patient management and therapy planning in the future, as we illustrate in one patient of our cohort who received CRT-D implantation.