Early detection of cardiac allograft vasculopathy using highly automated 3-dimensional optical coherence tomography analysis.

Background: Optical coherence tomography (OCT)-based studies of cardiac allograft vasculopathy (CAV) published thus far have focused mainly on frame-based qualitative analysis of the vascular wall. Full capabilities of this inherently 3-dimensional (3D) imaging modality to quantify CAV have not been fully exploited.

Methods: Coronary OCT imaging was performed at 1 month and 12 months after heart transplant (HTx) during routine surveillance cardiac catheterization. Both baseline and follow-up OCT examinations were analyzed using proprietary, highly automated 3D graph-based optimal segmentation software. Automatically identified borders were efficiently adjudicated using our "just-enough-interaction" graph-based segmentation approach that allows to efficiently correct local and regional segmentation errors without slice-by-slice retracing of borders.

Results: A total of 50 patients with paired baseline and follow-up OCT studies were included. After registration of baseline and follow-up pullbacks, a total of 356 ± 89 frames were analyzed per patient. During the first post-transplant year, significant reduction in the mean luminal area (p = 0.028) and progression in mean intimal thickness (p = 0.001) were observed. Proximal parts of imaged coronary arteries were affected more than distal parts (p < 0.001). High levels of LDL cholesterol (p = 0.02) and total cholesterol (p = 0.031) in the first month after HTx were the main factors associated with early CAV development.

Conclusions: Our novel, highly automated 3D OCT image analysis method for analyzing intimal and medial thickness in HTx recipients provides fast, accurate, and highly detailed quantitative data on early CAV changes, which are characterized by significant luminal reduction and intimal thickness progression as early as within the first 12 months after HTx.