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Integration with true coronary anatomy changes the standard assignment of vascular territories on perfusion images: A hybrid PET-CT analysis

¹ Johns Hopkins University, Baltimore, Maryland

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Objectives: For interpretation of myocardial perfusion studies, tissue segments are usually assigned to vascular territories based on a general assumption about the most frequent vascular distribution pattern. This may be inaccurate due to interindividual anatomic variability. Hybrid imaging may allow for overcoming this limitation by integrating coronary anatomy with myocardial tissue regions individually.

Methods: We studied 35 consecutive pts who underwent concurrent Rb-82 perfusion PET-CT with CT angiography for biomorphologic work up of coronary disease on a 64-row GE Discovery Rx VCT PET-CT scanner. Using 2D and 3D fusion images, coronary vessels as defined by CT were assigned to each of 17 myocardial segments for PET analysis. These reassigned maps were compared to standard segments as proposed in the AHA segmental model.

Results: 80% of pts (28/35) demonstrated differences from the standard vascular territory assignment in at least one segment. The average number of remapped segments was 2.4 per pt. Of the 28 pts, standard LAD segments were reassigned to true RCA territories in 68%, standard RCA segments were reassigned to LCX in 29% and standard LCX segments were reassigned to LAD or RCA in 21%. Overall, integration with CTA resulted in vascular territory reassignment of 14.4% of the LV area used for PET perfusion analysis.

Conclusions: Standard assumptions about vascular territory distribution in myocardial perfusion analysis are frequently inaccurate due to morphologic variability of the coronary tree. PET-CT can integrate coronary anatomy and myocardial tissue in a single imaging session. This may help for a more accurate assignment of perfusion abnormalities to culprit vessels and thus for improved guidance of targeted therapy.

This Article Services Email this article to a friend Similar articles in this journal Alert me to new issues of the journal Download to citation manager Google Scholar Articles by Javadi, M. Articles by Bengel, F. PubMed Articles by Javadi, M. Articles by Bengel, F.