Impact of Contour Boundary Offsets on 4D Flow CMR-Derived Intracardiac Haemodynamic Parameters
Alexander Gall, Rui Li, Ciaran Grafton-Clarke, Zia Mehmood, Kurian Thampi, Amanda Noyes, David Hewson, Victoria Underwood, Rebekah Girling, David Marlevi, Peter P Swoboda, Rob J. van der Geest, Gareth Matthews, Pankaj GargFour-dimensional (4D) flow cardiovascular magnetic resonance assesses advanced haemodynamic parameters like kinetic energy (KE), vorticity, and viscous energy loss (vEL). However, gradient-based metrics (vorticity, vEL) are highly sensitive to partial volume effects near the fluid–tissue boundary. This study investigated the impact of systematic contour boundary offsets on these parameters to standardise analysis. Five cases underwent 4D flow imaging. Deep learning-derived automated segmentations of the cardiac chambers were generated. Haemodynamics were analysed using three contouring methods: the baseline mask, a one-voxel inward offset, and a two-voxel inward offset. KE, vorticity, and vEL decreased progressively with larger offsets. KE declined modestly with erosion (by approximately 18% and 35% at one- and two-voxel offsets, respectively), a reduction commensurate with the loss of integration volume rather than the removal of boundary artefacts. By contrast, the gradient-based metrics were disproportionately sensitive to boundary proximity. In the left ventricle, mean full-cycle vorticity decreased from 249.6 ± 79.9 s−1 (baseline) to 157.0 ± 60.4 s−1 (two-voxel offset; Hedges’ g 2.11), whilst vEL decreased from 549.4 ± 303.0 µW to 351.3 ± 230.0 µW (Hedges’ g 2.00). A one-voxel inward offset optimally reduces boundary noise for sensitive gradient-based parameters. While KE analysis remains satisfactory using unmodified baseline contours, we recommend the uniform application of a one-voxel offset across all parameters to ensure methodological simplicity and pipeline standardisation.