Computational analysis of cardiac structure and function in congenital heart disease: Translating discoveries to clinical strategies

Nickolas Forsch*, Sachin Govil, James C. Perry, Sanjeet Hegde, Alistair A. Young, Jeffrey H. Omens, Andrew D. McCulloch

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)

Abstract

Increased availability and access to medical image data has enabled more quantitative approaches to clinical diagnosis, prognosis, and treatment planning for congenital heart disease. Here we present an overview of long-term clinical management of congenital heart disease and its intersection with novel computational and data science approaches to discovering biomarkers of functional and prognostic importance. Efforts in translational medicine that seek to address the clinical challenges associated with cardiovascular diseases using personalized and precision-based approaches are then discussed. The considerations and challenges of translational cardiovascular medicine are reviewed, and examples of digital platforms with collaborative, cloud-based, and scalable design are provided.

Original languageEnglish
Article number101211
JournalJournal of Computational Science
Volume52
Early online date19 Sept 2020
DOIs
Publication statusE-pub ahead of print - 19 Sept 2020

Keywords

  • Cardiac magnetic resonance
  • Cardiovascular medicine
  • Congenital heart disease
  • Statistical shape atlases
  • Translational medicine

Fingerprint

Dive into the research topics of 'Computational analysis of cardiac structure and function in congenital heart disease: Translating discoveries to clinical strategies'. Together they form a unique fingerprint.

Cite this