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2 nd Case: Statistical/Numerical Investigations of Cerebral Aneurysm Risk Development

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cynara
27 diapositives · 373 Views · Oct 12, 2014

The ANEURISK project aims to explore the relationship between vascular morphology and aneurysm development risks through 3D reconstruction, numerical simulations, and statistical analysis. The project includes segmentation, geometric analysis, and landmark characterization of cerebral vasculature. Preliminary numerical results also investigate the blood flow behavior in aneurysms. This multidisciplinary project integrates mathematics, statistics, and medical validation for deep insights into cerebrovascular pathologies.

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2 nd Case: Statistical/Numerical Investigations of Cerebral Aneurysm Risk Development
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  1. 2nd Case: Statistical/Numerical Investigations of Cerebral Aneurysm Risk Development THE “ANEURISK” PROJECT (2005-2007) www2.mate.polimi.it:8080/aneurisk S.Bacigaluppi, E. Boccardi, L. Antiga, B. Ene-Iordache, M. Piccinelli, A. Remuzzi, G. Dubini, F. Migliavacca, L. Socci, P. Secchi, S. Vantini, L. Formaggia, T. Passerini, M.R. De Luca, A. V. (Coordinator)

  2. CEREBRAL ANEUSYSMS are lesions arising on cerebral vessels characterized by a bulge of the vessel wall. They quite often they are subject to rupture. This event means cerebral haemorrhage. ANEURISK GOAL: To highlight the possible relationships linking vascular morphology and development/rupture risks in Aneurysms

  3. STRUCTURE OF THE PROJECT 3D reconstruction and semi-automatic detection of relevant morphological features Clinical Data (DICOM) GEOMETRICAL ANALYSIS DATA-BASE NUMERICAL SIMULATIONS STATISTICAL ANALYSIS Correlation Analysis, Decision Tree Definition 3D Simulations WSS Computation,…

  4. 3D RECONSTRUCTION* Level set is a numerical method for tracking the evolution of contours and surfaces. The contour is embedded as the zero-level of a function evolving under the control of a differential equation. Gradient Image The initial conditions (initial contour) are given by the user and then it evolves until it will locate on the regions corresponding to the steepest change of image intensity across the vessel wall, which is a robust and objective criterion. *L. Antiga, M. Piccinelli

  5. Definition of the region of interest Initialization Level Set surface VTK/ITK based C++ Code

  6. PROBLEMS IN 3D RECONSTRUCTION 1) Segmentation and Filtering can be Operator/Code Dependent Mimics (Materialize) Amira (Mercury Inc.) Level Sets method seem to be more robust and accurate

  7. Home Amira

  8. 2) Variability of Cerebral Vasculature Internal Carotid Arteries

  9. Basilar Arteries

  10. (SEMI-)AUTOMATIC GEOMETRY CHARACTERIZATION • Decomposition of the vascular structure into subdomains on the basis of centerlines computation • Computation of Landmarks parameters on • Segments, Bifurcations, Aneurysms • (detected at the previous step)

  11. Centerline computation and Vascular Structure Subdivision

  12. LANDMARKS SEGMENTS • Length L • Min/max/mean Radius R • Mean curvature • Torsion • Toruosity (L/d) • Stenosis (Boolean)

  13. LANDMARKS BIFURCATIONS • Angles • Radii

  14. LANDMARKS ANEURYSMS • Presence (Boolean) • Rupture (Boolean) • Position • Inlet Section Area • Angiographic Volume • Shape

  15. PRELIMINAR NUMERICAL RESULTS* Is the blood Newtonian in Aneurysms? Steady/Unsteady Computation Newton vs. Casson Rheologies Boundary Conditions: *F. Migliavacca, L. Socci FLUENT

  16. PRESSURE FIELDS Casson Newton

  17. WALL SHEAR STRESSES Casson Newton

  18. UNSTEADY COMPUTATION

  19. Is this flow division realistic?

  20. ANSWER: Integration of 1D/3D/0D Models

  21. 1D REPRESENTATIONS OF THE WILLIS CIRCLE *T. Passerini, M.R. De Luca, A.V.

  22. 1D MATHEMATICAL MODEL OF THE WILLIS CIRCLE Starting point: Euler equations for an arterial segment: Bi-Trifurcation Modeling: Conservation of flow rates and (total) pressures

  23. THE SYMMETRIC CASE

  24. RIGHT CAROTID COMPRESSION TEST

  25. PCA MISSING (16% PATIENTS)

  26. CAROTID COMPRESSION ON A PATIENT WITH NO PCA

  27. A lot of work to do…(Un)fortunately… Conclusions and Perspectives 1 - Deep understanding of relevant cerebrovascular pathologies is quite far: mathematical/numerical models can support investigations and hypotheses validations 2 - Cerebral circulation has specific features to be considered: Biochemics/Haemodynamics interaction Willis Circle robustness 3 – Integration of different competences is mandatory: Numerics+Statistics+Medical Validation+Geometry Analysis…