Pulmonary transit time of cardiovascular magnetic resonance perfusion scans for quantification of cardiopulmonary haemodynamics

• Published in: European heart journal cardiovascular imaging Vol. 24; no. 8; pp. 1062 - 1071
• Main Authors: Segeroth, Martin, Winkel, David Jean, Strebel, Ivo, Yang, Shan, van der Stouwe, Jan Gerrit, Formambuh, Jude, Badertscher, Patrick, Cyriac, Joshy, Wasserthal, Jakob, Caobelli, Federico, Madaffari, Antonio, Lopez-Ayala, Pedro, Zellweger, Michael, Sauter, Alexander, Mueller, Christian, Bremerich, Jens, Haaf, Philip
• Format: Journal Article
• Language: English
• Published: US Oxford University Press 24.07.2023
• Subjects: Artificial Intelligence; Biomarkers; Dyspnea; Heart Failure; Hemodynamics; Humans; Magnetic Resonance Spectroscopy; Natriuretic Peptide, Brain; Peptide Fragments; Stroke Volume; Ventricular Function, Left; Ventricular Function, Right; cardiovascular magnetic resonance imaging; heart failure; haemodynamic biomarker; pulmonary transit time; artificial intelligence; N-terminal pro-brain natriuretic peptide
• ISSN: 2047-2404; 2047-2412
• DOI: 10.1093/ehjci/jead001

Abstract Aims Pulmonary transit time (PTT) is the time blood takes to pass from the right ventricle to the left ventricle via pulmonary circulation. We aimed to quantify PTT in routine cardiovascular magnetic resonance imaging perfusion sequences. PTT may help in the diagnostic assessment and characterization of patients with unclear dyspnoea or heart failure (HF). Methods and results We evaluated routine stress perfusion cardiovascular magnetic resonance scans in 352 patients, including an assessment of PTT. Eighty-six of these patients also had simultaneous quantification of N-terminal pro-brain natriuretic peptide (NTproBNP). NT-proBNP is an established blood biomarker for quantifying ventricular filling pressure in patients with presumed HF. Manually assessed PTT demonstrated low inter-rater variability with a correlation between raters >0.98. PTT was obtained automatically and correctly in 266 patients using artificial intelligence. The median PTT of 182 patients with both left and right ventricular ejection fraction >50% amounted to 6.8 s (Pulmonary transit time: 5.9–7.9 s). PTT was significantly higher in patients with reduced left ventricular ejection fraction (<40%; P < 0.001) and right ventricular ejection fraction (<40%; P < 0.0001). The area under the receiver operating characteristics curve (AUC) of PTT for exclusion of HF (NT-proBNP <125 ng/L) was 0.73 (P < 0.001) with a specificity of 77% and sensitivity of 70%. The AUC of PTT for the inclusion of HF (NT-proBNP >600 ng/L) was 0.70 (P < 0.001) with a specificity of 78% and sensitivity of 61%. Conclusion PTT as an easily, even automatically obtainable and robust non-invasive biomarker of haemodynamics might help in the evaluation of patients with dyspnoea and HF. Graphical Abstract Graphical Abstract