Title
Personalized pulmonary trunk modeling for intervention planning and valve assessment estimated from CT data.
Abstract
Pulmonary valve disease affects a significant portion of the global population and often occurs in conjunction with other heart dysfunctions. Emerging interventional methods enable percutaneous pulmonary valve implantation, which constitute an alternative to open heart surgery. As minimal invasive procedures become common practice, imaging and non-invasive assessment techniques turn into key clinical tools. In this paper, we propose a novel approach for intervention planning as well as morphological and functional quantification of the pulmonary trunk and valve. An abstraction of the anatomic structures is represented through a four-dimensional, physiological model able to capture large pathological variation. A hierarchical estimation, based on robust learning methods, is applied to identify the patient-specific model parameters from volumetric CT scans. The algorithm involves detection of piecewise affine parameters, fast centre-line computation and local surface delineation. The estimated personalized model enables for efficient and precise quantification of function and morphology. This ability may have impact on the assessment and surgical interventions of the pulmonary valve and trunk. Experiments performed on 50 cardiac computer tomography sequences demonstrated the average speed of 202 seconds and accuracy of 2.2mm for the proposed approach. An initial clinical validation yielded a significant correlation between model-based and expert measurements. To the best of our knowledge this is the first dynamic model of the pulmonary trunk and right ventricle outflow track estimated from CT data.
Year
DOI
Venue
2009
10.1007/978-3-642-04268-3_3
MICCAI
Keywords
Field
DocType
percutaneous pulmonary valve implantation,pulmonary valve disease,ct data,pulmonary trunk,personalized pulmonary trunk modeling,patient-specific model parameter,dynamic model,intervention planning,physiological model,estimated personalized model,functional quantification,valve assessment,pulmonary valve,ct scan
Affine transformation,Population,Pulmonary valve,Ventricular outflow tract,Pattern recognition,Computer science,Tomography,Artificial intelligence,Ventricle,Radiology,Trunk,Pulmonary Valve Replacement
Conference
Volume
Issue
ISSN
12
Pt 1
0302-9743
Citations 
PageRank 
References 
5
0.57
4
Authors
7
Name
Order
Citations
PageRank
Dime Vitanovski1346.64
Razvan Ioan Ionasec221326.71
Bogdan Georgescu31638138.49
Martin Huber4425.85
Andrew Taylor5142.77
Joachim Hornegger61734190.62
Dorin Comaniciu78389601.83