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Proceedings Paper

Evaluation of accuracy and workflow between different alignment techniques for correction of CTAC and PET misalignment in cardiac PET-CT imaging
Author(s): Elizabeth B. Philps; Sarah J. Aivano
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Paper Abstract

Small errors in the alignment between CT Attenuation Correction (CTAC) images and Positron Emission Tomography (PET) acquisitions can result in significant changes in PET attenuation corrected images. Misalignment due to respiratory or cardiac motion can produce mismatch between the PET and CTAC acquisitions. This contributes to artifactual hypoperfusion defects that are interpretable as myocardial ischemia or infarct. Correction for the misalignment between the PET and CTAC images can eliminate these false positive artifacts. Two methods for correcting for this respiratory and cardiac misalignment were compared. The first was an existing procedure, the manual-shift method, using point-to-point, in-plane, two-dimensional (2D) measurements of the shifts in axial, sagittal, and coronal planes. A new PET image reconstruction using the corrected attenuation map shifted by the 2D measurements was then performed. In the second method, the Interactive ACQC method, visual alignment was performed between the left ventricle boundaries on fused images and automated calculation of necessary rigid three-dimensional (3D) alignment parameters was performed. A new PET image reconstruction was then performed with an attenuation map shifted by the prescribed alignment parameters. The two methods were compared for accuracy and workflow efficiency using five cardiac PET/CT cases, scanned on GE Discovery VCT and Discovery ST systems. Alignment measurements using the visual alignment process (the interactive ACQC method) improved productivity by over five minutes, on average. The results show that the interactive ACQC procedure yields similar results to those of the point-to-point procedure while providing improved workflow for cardiac PET attenuation correction quality control.

Paper Details

Date Published: 3 March 2007
PDF: 9 pages
Proc. SPIE 6512, Medical Imaging 2007: Image Processing, 65124J (3 March 2007); doi: 10.1117/12.713599
Show Author Affiliations
Elizabeth B. Philps, GE Healthcare (United States)
Sarah J. Aivano, GE Healthcare (United States)


Published in SPIE Proceedings Vol. 6512:
Medical Imaging 2007: Image Processing
Josien P. W. Pluim; Joseph M. Reinhardt, Editor(s)

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