Multimodality quantitative assessments of myocardial perfusion using dynamic contrast enhanced magnetic resonance and (15)O-labelled water positron emission tomography imaging

利用动态对比增强磁共振成像和(15)O标记水正电子发射断层扫描成像技术对心肌灌注进行多模态定量评估

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Abstract

Kinetic modelling of myocardial perfusion imaging data allows the absolute quantification of myocardial blood flow (MBF) and can improve the diagnosis and clinical assessment of coronary artery disease (CAD). Positron emission tomography (PET) imaging is considered the reference standard technique for absolute quantification, whilst oxygen-15 ((15)O)-water has been extensively implemented for MBF quantification. Dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) has also been used for MBF quantification and showed comparable diagnostic performance against ((15)O)-water PET studies. We investigated for the first time the diagnostic performance of two different PET MBF analysis softwares PMOD and Carimas, for obstructive CAD detection against invasive clinical standard methods in 20 patients with known or suspected CAD. Fermi and distributed parameter modelling-derived MBF quantification from DCE-MRI was also compared against ((15)O)-water PET, in a subgroup of 6 patients. The sensitivity and specificity for PMOD was significantly superior for obstructive CAD detection in both per vessel (0.83, 0.90) and per patient (0.86, 0.75) analysis, against Carimas (0.75, 0.65), (0.81, 0.70), respectively. We showed strong, significant correlations between MR and PET MBF quantifications (r=0.83-0.92). However, DP and PMOD analysis demonstrated comparable and higher haemodynamic differences between obstructive versus (no, minor or non)-obstructive CAD, against Fermi and Carimas analysis. Our MR method assessments against the optimum PET reference standard technique for perfusion analysis showed promising results in per segment level and can support further multi-modality assessments in larger patient cohorts. Further MR against PET assessments may help to determine their comparative diagnostic performance for obstructive CAD detection.

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