13N-ammonia positron emission tomography-derived left-ventricular strain in patients after heart transplantation validated using cardiovascular magnetic resonance feature tracking as reference

2021 
Heart transplant rejection leads to cardiac allograft vasculopathy (CAV). 13N-ammonia positron emission tomography (PET) can be useful in detecting CAV, as it can evaluate both epicardial vessels and microvasculature. In this study, we evaluated the regional wall motion in heart transplant patients using our PET-specific feature-tracking (FT) algorithm for myocardial strain calculation and validated it using a cardiovascular magnetic resonance (CMR) FT strain as a reference. A total of 15 heart transplant patients who underwent both 13N-ammonia PET and CMR within 3 months were retrospectively enrolled. The same slice position of short-axis cine images of the middle slice of left ventricle (LV) and the same slice position of horizontal long-axis cine images were selected for the two modalities to measure the circumferential strain (CS) and longitudinal strain (LS), respectively. Based on the FT technique, time–strain curves were calculated by semi-automatic tracking of the endocardial contour on cine images throughout a cardiac cycle. The peak value in the time-strain curve was defined as the representative value. Correlations of CS and LS between PET and CMR were analyzed using Pearson correlation coefficients. The inter-modality error of strain measurements was evaluated using intraclass correlation coefficients (ICCs) with two-way random single measures. Excellent correlations of CS and LS between PET and CMR were observed (CS: r = 0.80; p < 0.01; LS: r = 0.87; p < 0.01). Excellent ICCs were observed (0.89 and 0.85) in CS and LS derived from PET. We propose the first PET strain showing an excellent agreement with the CMR strain and high reproducibility in measurement.
    • Correction
    • Source
    • Cite
    • Save
    • Machine Reading By IdeaReader
    26
    References
    0
    Citations
    NaN
    KQI
    []