Geometric feature-based multimodal image registration of contrast-enhanced cardiac CT with gated myocardial perfusion

Jonghye Woo1, Piotr J Slomka, Damini Dey

  • 1Department of Imaging/AIM program, Cedars-Sinai Medical Center, Los Angeles, California 90048, USA.

Medical Physics
|January 26, 2010
PubMed

Insights

A new automated method accurately registers cardiac CT and myocardial perfusion SPECT scans for diagnosing coronary artery disease. This fusion of imaging data improves diagnostic accuracy for specific coronary vessels.

Area of Science:

  • Medical Imaging
  • Cardiovascular Disease Diagnosis
  • Image Registration

Background:

  • Cardiac computed tomography (CT) and single photon emission computed tomography (SPECT) offer complementary diagnostic information for coronary artery disease (CAD).
  • Sequential acquisition of fused anatomical and physiological data on separate scanners necessitates accurate coregistration for precise CAD diagnosis in specific coronary vessels.

Purpose of the Study:

  • To present a fully automated method for registering contrast cardiac CT with gated myocardial perfusion SPECT (MPS).
  • To achieve accurate fusion of cardiac CT and MPS data for improved CAD diagnosis.

Main Methods:

  • Utilized geometric features from segmented gated MPS volumes as an anatomical mask to mitigate intensity variations.
  • Employed a multiresolution approach with a piecewise constant image model and gradient descent for alignment.
  • Incorporated nonlinear registration using thin-plate-spline warping for automatic cardiac phase matching between CT and MPS.

Main Results:

  • The automated method achieved registration accuracy comparable to manual alignment, with mean errors typically below 5 mm and 2 degrees.
  • Demonstrated robustness across different sites and CT perfusion datasets, with errors generally less than 1 voxel.
  • Validation confirmed that the automated phase matching aligned closely with expert visual assessment.

Conclusions:

  • Developed a fast, fully automated registration method for cardiac CT and gated MPS, including nonlinear cardiac phase matching.
  • The method demonstrates capability in registering these modalities with accuracy <10 mm in 87% of cases.
  • This automated approach facilitates accurate CAD diagnosis through fused imaging data.
Abstract

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