Open-Source Framework for the Visualization, Quantification, and Analysis of 4D Flow and High-Dimensional Magnetic Resonance Images

Andras Lasso; Julia Iacovell; Csaba Pinter; Kevin K. Whitehead; Sehdev Pressley; Danish Vaiyani; Matthew Daemer; Katherine Hurm; Analise M. Sulentic; Christian Herz; Ryan T. Black; Seda Aslan; Christopher W. Roy; Mark A. Fogel; Jing Huang; Matthew A. Jolley

arXiv · 2610.38948

Open-Source Framework for the Visualization, Quantification, and Analysis of 4D Flow and High-Dimensional Magnetic Resonance Images

Andras Lasso·Julia Iacovell·Csaba Pinter·Kevin K. Whitehead·Sehdev Pressley·Danish Vaiyani·Matthew Daemer·Katherine Hurm·Analise M. Sulentic·Christian Herz·Ryan T. Black·Seda Aslan·Christopher W. Roy·Mark A. Fogel·Jing Huang·Matthew A. Jolley

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Abstract

Background: Four-dimensional (4D) flow cardiovascular magnetic resonance (CMR) captures 3D anatomy and blood velocity across the cardiac cycle, but current post-processing software is closed, varies across platforms, and sits outside open-source image-computing frameworks. We developed an open-source framework for the import, visualization, and quantification of 4D flow and other high-dimensional CMR within SlicerHeart, an extension for 3D Slicer. Methods: Import 4D Flow reads vendor DICOM, applies preprocessing, and stores velocities as a time-resolved vector field; Analyze 4D Flow provides measurement planes, streamline and Doppler-like visualization, segmentation propagation, and quantification. Underlying both, we extended the Insight Toolkit to store five- and higher-dimensional arrays. Flow quantification was compared with a commercial package (cvi42) and 2D phase contrast in 13 patients with congenital heart disease across 108 paired regions of interest (Bland-Altman analysis and intraclass correlation coefficients, ICCs). Consensus-recommended processing methods were also implemented as an open-source library with an automated test suite of analytic and CFD phantoms and clinical acquisitions. Results: The modules integrate with 3D Slicer's segmentation, registration, and rendering tools and export velocity fields and geometry for computational modeling. Agreement with cvi42 was close: forward volume bias -0.1 mL (95% limits of agreement 2.2 to -2.3; ICC 0.997), effective volume per minute bias -0.015 L/min (0.21 to -0.24; ICC 0.994). Against 2D phase contrast, forward volume bias (-2.2 mL) and mean absolute percentage error (21.8%) matched cvi42 (-2.1 mL; 21.3%). Conclusions: This open, extensible framework brings 4D flow CMR into an established image-computing ecosystem and agrees closely with a commercial reference; every step can be inspected, reproduced, and improved.

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Andras Lasso, Julia Iacovell, Csaba Pinter, Kevin K. Whitehead, Sehdev Pressley, Danish Vaiyani, Matthew Daemer, Katherine Hurm, Analise M. Sulentic, Christian Herz, Ryan T. Black, Seda Aslan, Christopher W. Roy, Mark A. Fogel, Jing Huang, Matthew A. Jolley. 2026-10-28. Open-Source Framework for the Visualization, Quantification, and Analysis of 4D Flow and High-Dimensional Magnetic Resonance Images. https://arxiv.org/abs/2610.38948

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