4.5 Article

Integrating computational fluid dynamics data into medical image visualization workflows via DICOM

Journal

Publisher

SPRINGER HEIDELBERG
DOI: 10.1007/s11548-022-02613-3

Keywords

CFD; Hemodynamics; DICOM; Visualization; Interaction; Cross-disciplinary

Funding

  1. Natural Sciences and Engineering Research Council of Canada [RGPIN-201804649]
  2. Barbara and Frank Milligan Fellowship

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Translating CFD data to DICOM series enables interactive visualization in standard radiological software. Our approach allows real-time modifications of transfer functions for representations of scalar isosurfaces, volumetric rendering, and tubular pathlines.
Purpose Communicating complex blood flow patterns generated from computational fluid dynamics (CFD) simulations to clinical audiences for the purposes of risk assessment or treatment planning is an ongoing challenge. While attempts have been made to develop new software tools for such clinical visualization of CFD data, these often overlook established medical imaging/visualization practice and data infrastructures. Here, leveraging the clinical ubiquity of the DICOM file format, we present techniques for the translation of CFD data to DICOM series, facilitating interactive visualization in standard radiological software. Methods Unstructured CFD data (volumetric fields of velocity magnitude, Q-criterion, and pathlines) are resampled to structured grids. Novel raster-based techniques that simulate experimental optical blurring are presented for bringing simulated pathlines into structured image volumes. DICOM series are created by strategically encoding these data into the file's PixelArray tag. Lumen surface information is also strategically encoded into a different range of pixel intensities, allowing hemodynamics and morphology to be co-visualized in a single volume using opacity-based rendering transfer functions. Results We show that 3D temporal CFD data represented as structured DICOM series can be rendered interactively in Horos, a widely-used medical imaging/radiology software. Our transfer function-based approach allows for representations of scalar isosurfaces, volumetric rendering, and tubular pathlines to be modified in real-time, resembling conventional unstructured visualizations. Careful selection of voxelization ROIs helps to ensure that data are kept lightweight for real-time rendering and minimal storage. Conclusion While our approach inherently sacrifices some of the advanced visualization capabilities of specialized software tools, we believe our closer consideration of standardization can help to facilitate meaningful clinical interaction. This work opens up possibilities for the complete integration of measured and simulated data in established radiological software environments and workflows from PACS storage to 3D/4D visualization.

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