Patient specific reconstruction of vascular network for hemodynamic modeling Yury Ivanov (INM RAS), Roman Pryamonosov (MSU), 2014, Moscow

3D reconstruction of vascular structure for patient- specific simulation CT, MRT diagnostic data in DICOM files Image preprocessing Performing vessels segmentation Extraction of vascular structure Geometric analysis and building topology of a vascular segment Simulation with network blood circulation model

3D vessel segmentation Amira 3D Visualization and Analysis Software for Life Sciences and bio-medical data Volume of interest extraction Arithmetic operation on images Noise reduction with digital image filters Segmentation

Extraction of vascular structure VMTK (The Vascular Modeling Toolkit) - open source library, Computing centerlines – convenient way of representation of tube-like structure as sets of center points and corresponding radiuses. Centerlines defined as centers of maximal inscribed spheres, calculated with Voronoi diagram method.

Patient specific reconstruction of vascular network for haemodynamic modeling. 3D vascular domain: polygonal surface mesh and computed centerlines

Export data into GUI and building of topology Export centerlines in VTK format Converting to the internal format of vessel representation. Visualize 3D objects Perform hierarchical connectivity analysis: determination of intersection with consecutive building of node and branch tables. Every branch entry has information about pair of nodes, average radius and actual length (along the vessel axis)

Patient specific reconstruction of vascular network for hemodynamic modeling The vascular network of arterial part of systemic circulation based on virtual 3D model. (Realistic, detailed model of Circulatory System -

Patient specific reconstruction of vascular network for hemodynamic modeling: Aorta and coronary arteries segmentation Stack of DICOM files of size 512x512x248 (CT data) Slices of middle mediastinum: heart and lungs Input data:

Patient specific reconstruction of vascular network for hemodynamic modeling: Result of aorta and coronary arteries segmentation Aorta is segmented with isoperimetric graph partitioning algorithm* (Leo Grady). Ostia points are detected as 2 aorta points of maximal Frangi Vesselness filter values. Arteries is segmented using Frangi Filter as connectivity components of ostia points. * Isoperimetric distance tree

Patient specific reconstruction of vascular network for hemodynamic modeling: Result of skeletonization Result of distance-ordered homotopic thinning. Skeleton allows to build 1d tree or graph. 1-dimentional centerline tree contains information about lengths and average radiuses.

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