Computational high-resolution heart phantoms for medical imaging and dosimetry simulations

Songxiang Gu1, Rajiv Gupta, Iacovos Kyprianou

  • 1Center for Devices and Radiological Health, US Food and Drug Administration, Silver Spring, MD, USA. songxiang.gu@fda.hhs.gov

Insights

Researchers developed an open-source platform to create detailed, gender-specific heart phantoms from CT scans. These phantoms aid in optimizing medical imaging and radiation dose for cardiovascular disease diagnosis and treatment.

Area of Science:

  • Medical Imaging
  • Computational Anatomy
  • Radiation Dosimetry

Background:

  • Cardiovascular diseases, particularly coronary artery disease (CAD), are leading global causes of mortality.
  • Current diagnostic methods like coronary angiography and CT angiography (CTA) involve ionizing radiation, raising safety concerns.
  • Accurate, gender-specific anthropomorphic phantoms are needed for optimizing imaging quality and minimizing radiation dose, but are currently unavailable.

Purpose of the Study:

  • To develop an open-source platform for creating detailed, gender-specific cardiac and coronary artery phantoms.
  • To generate high-resolution phantoms from CTA datasets for imaging and dosimetry applications.
  • To enable the simulation of cardiovascular disease scenarios, including stenotic lesions.

Main Methods:

  • Development of a graphical user interface-based open-source heart phantom platform.
  • Utilizing histogram analysis, vesselness, connectivity criteria, and active contours for precise segmentation of CTA data.
  • Fitting triangular meshes to segmented data and developing a visualization tool for adding stenotic lesions.
  • Cross-registering male and female phantoms into the mesh-based Virtual Family for matched age/gender information.

Main Results:

  • Successfully developed seven high-resolution cardiac/coronary artery phantoms from CTA datasets.
  • Demonstrated the ability to identify up to 100 coronary artery branches in a female phantom.
  • Integrated generated phantoms into the Virtual Family, enabling realistic simulation with user-defined stenoses using Monte Carlo code penMesh.

Conclusions:

  • The developed platform provides a novel solution for creating detailed, anatomically accurate, gender-specific heart phantoms.
  • These phantoms are valuable tools for optimizing imaging protocols and radiation dosimetry in cardiovascular imaging.
  • The open-source nature and integration into the Virtual Family facilitate wider research and clinical application.