Key result
biv-me pipeline generates accurate biventricular meshes from cine CMR with ~99% success rate.
Why the study?
Most methods for cardiac mesh reconstruction from CMR are not open-source, are single-centre, and lack deployability across heterogeneous scanning protocols and patient groups.
The biv-me pipeline provides a rapid, highly feasible, and open-source method for generating time-varying biventricular meshes from CMR images, enabling personalized cardiac assessment and computational modeling.
May support digital twin modeling from routine CMR; leaves open prospective clinical validation.
The generation of geometric representations of the heart is essential for personalised approaches to cardiac assessment. Structured biventricular meshes customised to imaging data have demonstrated utility in a number of model-based applications that can provide more sensitive insights into patient health than routine cardiac indices alone. Cardiovascular magnetic resonance (CMR) imaging is a common starting point for the creation of digital twin geometries, with numerous published methods for mesh reconstruction. However, the majority of these methods are not open-source, are typically developed and validated using data from a single-centre, and lack deployability across heterogeneous scanning protocols and patient groups. We present an open-source, end-to-end pipeline (biv-me), to automatically generate time-varying biventricular meshes from cine CMR DICOM images, and perform external validation against a clinical reference software tool on 1313 CMR imaging studies across five publicly available datasets. We report excellent agreement in left and right ventricular indices and high scan-rescan reproducibility. Mesh generation was rapid, with a mean processing time of 2.5 min, and highly feasible, with 99% of meshes successfully generated to a high standard with median error of <1.5 mm. The biv-me pipeline - including code, models, and documentation - is available at https://github.com/UOA-Heart-Mechanics-Research/biv-me.
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Dillon et al. (2026) studied Cardiovascular magnetic resonance (CMR) imaging studies (n=1,313). biv-me pipeline vs. suiteHEART clinical reference software was evaluated on Mesh generation success rate. The biv-me pipeline successfully generated time-varying biventricular meshes from cine CMR images with a 99% success rate and a median error of <1.5 mm.
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