title: Perfusion dyssynchrony analysis.
abstract: OBJECTIVE
  We sought to describe perfusion dyssynchrony analysis specifically to exploit the high temporal resolution of stress perfusion CMR. This novel approach detects differences in the temporal distribution of the wash-in of contrast agent across the left ventricular wall.
  
  
  RESULTS
  Ninety-eight patients with suspected coronary artery disease (CAD) were retrospectively identified. All patients had undergone perfusion CMR at 3T and invasive angiography with fractional flow reserve (FFR) of lesions visually judged >50% stenosis. Stress images were analysed using four different perfusion dyssynchrony indices: the variance and coefficient of variation of the time to maximum signal upslope (V-TTMU and C-TTMU) and the variance and coefficient of variation of the time to peak myocardial signal enhancement (V-TTP and C-TTP). Patients were classified according to the number of vessels with haemodynamically significant CAD indicated by FFR <0.8. All indices of perfusion dyssynchrony were capable of identifying the presence of significant CAD. C-TTP >10% identified CAD with sensitivity 0.889, specificity 0.857 (P < 0.0001). All indices correlated with the number of diseased vessels. C-TTP >12% identified multi-vessel disease with sensitivity 0.806, specificity 0.657 (P < 0.0001). C-TTP was also the dyssynchrony index with the best inter- and intra-observer reproducibility. Perfusion dyssynchrony indices showed weak correlation with other invasive and non-invasive measurements of the severity of ischaemia, including FFR, visual ischaemic burden, and MPR.
  
  
  CONCLUSIONS
  These findings suggest that perfusion dyssynchrony analysis is a robust novel approach to the analysis of first-pass perfusion and has the potential to add complementary information to aid assessment of CAD.
authors.affiliation: Division of Imaging Sciences and Biomedical Engineering, Department of Cardiovascular Imaging, King's College London, 4th Floor Lambeth Wing, St Thomas' Hospital, London SE1 7EH, UK amedeo.chiribiri@kcl.ac.uk.
authors.forename: Amedeo
authors.initials: A
authors.lastname: Chiribiri
authors.affiliation: Division of Imaging Sciences and Biomedical Engineering, Department of Cardiovascular Imaging, King's College London, 4th Floor Lambeth Wing, St Thomas' Hospital, London SE1 7EH, UK.
authors.forename: Adriana D M
authors.initials: AD
authors.lastname: Villa
authors.affiliation: Division of Imaging Sciences and Biomedical Engineering, Department of Cardiovascular Imaging, King's College London, 4th Floor Lambeth Wing, St Thomas' Hospital, London SE1 7EH, UK.
authors.forename: Eva
authors.initials: E
authors.lastname: Sammut
authors.affiliation: Philips Healthcare, Imaging Systems-MR Eindhoven, The Netherlands.|Eindhoven University of Technology, Biomedical Engineering, Biomedical Image Analysis, Eindhoven, The Netherlands.
authors.forename: Marcel
authors.initials: M
authors.lastname: Breeuwer
authors.affiliation: Division of Imaging Sciences and Biomedical Engineering, Department of Cardiovascular Imaging, King's College London, 4th Floor Lambeth Wing, St Thomas' Hospital, London SE1 7EH, UK.|DZHK Centre for Cardiovascular Imaging, University Hospital Frankfurt/Main, Frankfurt am Main, Germany.
authors.forename: Eike
authors.initials: E
authors.lastname: Nagel
mesh_terms: D000367:Age Factors; D000368:Aged; D000704:Analysis of Variance; D015331:Cohort Studies; D016001:Confidence Intervals; D017023:Coronary Angiography / Q000379:methods*; D023921:Coronary Stenosis / Q000000981:diagnostic imaging* / Q000503:physiopathology*; D005260:Female; D053805:Fractional Flow Reserve, Myocardial / Q000502:physiology; D006801:Humans; D018810:Magnetic Resonance Angiography / Q000379:methods; D019028:Magnetic Resonance Imaging, Cine / Q000379:methods*; D008297:Male; D008875:Middle Aged; D055414:Myocardial Perfusion Imaging / Q000379:methods*; D015588:Observer Variation; D012372:ROC Curve; D012189:Retrospective Studies; D018570:Risk Assessment; D012680:Sensitivity and Specificity; D012720:Severity of Illness Index; D012737:Sex Factors; D018709:Statistics, Nonparametric
keywords: adenosine; dyssynchrony analysis; gadolinium; perfusion