Impact of individualized segmentation on diagnostic performance of quantitative positron emission tomography for haemodynamically significant coronary artery disease.

Aims: Despite high variability in coronary anatomy, quantitative positron emission tomography (PET) perfusion in coronary territories is traditionally calculated according to the American Heart Association (AHA) 17-segments model. This study aimed to assess the impact of individualized segmentation of myocardial segments on the diagnostic accuracy of hyperaemic myocardial blood flow (MBF) values for haemodynamically significant coronary artery disease (CAD).

Methods and results: Patients with suspected CAD (n = 204) underwent coronary computed tomography angiography (CCTA) and [15O]H2O PET followed by invasive coronary angiography with fractional flow reserve assessment of all major coronary arteries. Hyperaemic MBF per vascular territory was calculated using both standard segmentation according to the AHA model and individualized segmentation, in which CCTA was used to assign coronary arteries to PET perfusion territories. In 122 (59.8%) patients, one or more segments were redistributed after individualized segmentation. No differences in mean MBF values were seen between segmentation methods, except for a minor difference in hyperaemic MBF in the LCX territory (P = 0.001). These minor changes resulted in discordant PET-defined haemodynamically significant CAD between the two methods in only 5 (0.8%) vessels. The diagnostic value for detecting haemodynamically significant CAD did not differ between individualized and standard segmentation, with area under the curves of 0.79 and 0.78, respectively (P = 0.34).

Conclusions: Individualized segmentation using CCTA-derived coronary anatomy led to redistribution of standard myocardial segments in 60% of patients. However, this had little impact on [15O]H2O PET MBF values and diagnostic value for detecting haemodynamically significant CAD did not change. Therefore, clinical impact of individualized segmentation seems limited.