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Alejandro F. Frangi

Alejandro F. Frangi

Alejandro F. Frangi

Day 1, Thursday, Nov 26, 2020
Image-based cerebrovascular modelling for advanced diagnosis and interventional planning

Abstract

Current technological progress in the multidimensional and multimodal acquisition of biomedical data enables a detailed investigation of the individual health status that should underpin improved patient diagnosis and treatment outcome. However, the abundance of biomedical information has not always been translated directly in improved healthcare. It instead increases the current information deluge and desperately calls for more holistic ways to analyse and assimilate patient data effectively.

The Virtual Physiological Human aims at developing the framework and tools that ultimately enable such integrated investigation of the human body and rendering methods for personalised and predictive medicine.

This lecture will focus on and illustrate two specific aspects: a) how the integration of biomedical imaging and sensing, signal and image computing and computational physiology are essential components in addressing this personalised, predictive and integrative healthcare challenge, and b) how such principles could be put at work to address specific clinical questions in the cardiovascular domain.

Finally, this lecture will also underline the critical role of model validation as a key to translational success and how such validations span from technical validation of specific modelling components to clinical assessment of the effectiveness of the proposed tools. To conclude, the talk will outline some areas where current research efforts fall short in the VPH domain, and that will possibly receive further investigation in the upcoming years.

References

Geers AJ, Morales HG, Larrabide I, Frangi AF (2014) Approximating hemodynamics of cerebral aneurysms with steady flow simulations, J Biomech, 2014;47(1):178-85.

Morales HG, Larrabide I, Geers AJ, Dai D, Kallmes DF, Frangi AF. (2013) Analysis and Quantification of Endovascular Coils Distribution inside Saccular Aneurysms Using Histological Images, J Neuro Intervent Surg, J Neurointerv Surg. 2013 Nov;5 Suppl 3:iii33-7.

Morales HG, Larrabide I, Geers AJ, Aguilar ML, Frangi AF (2013) Newtonian and Non-Newtonian Blood Flow in Coiled Cerebral Aneurysms, J Biomech, Sep 3;46(13):2158-64.

Larrabide I, Aguilar ML, Morales HG, Geers AJ, Kulczar S, R¸fenacht D, Frangi AF. Intra-aneurysmal pressure and flow changes induced by flow diverters: relation to aneurysm size and shape. AJNR Am J Neuroradiol, 2013 Apr;34(4):816- 22.

Pozo JM, Villa-Uriol, MC, Frangi AF. Efficient 3D geometric and Zernike moments computation from unstructured surface meshes. IEEE Trans Pattern Anal Mach Intell. 2011;33:471-484

Morales HG, Kim M, Villa-Uriol MC, Larrabide I, Vivas EE, Sola T, Guimaraens L, Frangi AF. How do coil configuration and packing density influence intra-aneurysmal hemodynamics? AJNR Am J Neuroradiol. 2011;32:1935-1941

Larrabide I, Villa-Uriol MC, Cardenes R, Pozo JM, Macho J, San Roman L, Blasco J, Vivas E, Marzo A, Hose DR, Frangi AF. Three-dimensional morphological analysis of intracranial aneurysms: A fully automated method for aneurysm sac isolation and quantification. Med Phys. 2011;38:2439-2449

Bernardini A, Larrabide I, Morales HG, Cito S, Pennati G, Petrini L, Frangi AF. Influence of different computational approaches for stent deployment on cerebral aneurysm haemodynamics. Interface Focus. 2011;1:338-348