Purpose: A model for calculating the three-dimensional volume of arteriovenous malformations from biplane angiography. Methods and Material: Three-dimensional (3D) volume reconstruction is easily feasible with axial, coronal, or sagittal computer tomography (CT) and nuclear magnetic resonance (NMR) scans. On the other hand, radiosurgical treatment of arteriovenous malformations (AVM) is exclusively based on two orthogonal stereotactic projections, obtained with angiographic procedures. Most commonly, AVM volumes have been calculated by assimilating the nidus volume to a prolate ellipsoid. We present an algorithm dedicated to 3D structure reconstruction starting from two orthogonal stereotactic projections. This has been achieved using a heuristic approach, which has been widely adopted in the artificial intelligence domain. Results: Tests on phantom of different complexity have shown excellent results. Conclusion: The importance of the algorithm is considerable. As a matter of fact: (a) it allows calculations of complex structures far away from regular ellipsoid; (b) it permits shape recovery; (c) it provides AVM visualization on axial planes.
Shape recovery and volume calculation from biplane angiography in the stereotactic radiosurgical treatment of arteriovenous malformations
FORONI, Roberto;GEROSA, Massimo;
1996-01-01
Abstract
Purpose: A model for calculating the three-dimensional volume of arteriovenous malformations from biplane angiography. Methods and Material: Three-dimensional (3D) volume reconstruction is easily feasible with axial, coronal, or sagittal computer tomography (CT) and nuclear magnetic resonance (NMR) scans. On the other hand, radiosurgical treatment of arteriovenous malformations (AVM) is exclusively based on two orthogonal stereotactic projections, obtained with angiographic procedures. Most commonly, AVM volumes have been calculated by assimilating the nidus volume to a prolate ellipsoid. We present an algorithm dedicated to 3D structure reconstruction starting from two orthogonal stereotactic projections. This has been achieved using a heuristic approach, which has been widely adopted in the artificial intelligence domain. Results: Tests on phantom of different complexity have shown excellent results. Conclusion: The importance of the algorithm is considerable. As a matter of fact: (a) it allows calculations of complex structures far away from regular ellipsoid; (b) it permits shape recovery; (c) it provides AVM visualization on axial planes.
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