Maxime Gérard1, François Michaud2,3, Alexandre Bigot3, An Tang4,3, Gilles Soulez4,3,5, Samuel Kadoury6,7,8. 1. Institute of Biomedical Engineering, Polytechnique Montréal, 2900 Edouard-Montpetit Bld, Montreal, QC, H3T 1J4, Canada. 2. Department of Physics, Université de Montréal, 2900 Edouard-Montpetit Bld, Montreal, QC, H3T 1J4, Canada. 3. Centre de recherche du Centre hospitalier de l'Université de Montréal (CRCHUM), 900 Saint-Denis St, Montreal, QC, H2X 0A9, Canada. 4. Department of Radiology, Radio-Oncology and Nuclear Medicine, Université de Montréal, 2900 Edouard-Montpetit Bld, Montreal, QC, H3T 1J4, Canada. 5. Departement of Radiology, Centre Hospitalier de l'Université de Montréal, 1560 Shrebrooke East, Montreal, H2L 4M1, Canada. 6. Institute of Biomedical Engineering, Polytechnique Montréal, 2900 Edouard-Montpetit Bld, Montreal, QC, H3T 1J4, Canada. samuel.kadoury@polymtl.ca. 7. Centre de recherche du Centre hospitalier de l'Université de Montréal (CRCHUM), 900 Saint-Denis St, Montreal, QC, H2X 0A9, Canada. samuel.kadoury@polymtl.ca. 8. Department of Computer Engineering, Polytechnique Montréal, 2900 Edouard-Montpetit Bld, Montreal, QC, H3T 1J4, Canada. samuel.kadoury@polymtl.ca.
Abstract
PURPOSE: Modulating the chemotherapy injection rate with regard to blood flow velocities in the tumor-feeding arteries during intra-arterial therapies may help improve liver tumor targeting while decreasing systemic exposure. These velocities can be obtained noninvasively using Doppler ultrasound (US). However, small vessels situated in the liver are difficult to identify and follow in US. We propose a multimodal fusion approach that non-rigidly registers a 3D geometric mesh model of the hepatic arteries obtained from preoperative MR angiography (MRA) acquisitions with intra-operative 3D US imaging. METHODS: The proposed fusion tool integrates 3 imaging modalities: an arterial MRA, a portal phase MRA and an intra-operative 3D US. Preoperatively, the arterial phase MRA is used to generate a 3D model of the hepatic arteries, which is then non-rigidly co-registered with the portal phase MRA. Once the intra-operative 3D US is acquired, we register it with the portal MRA using a vessel-based rigid initialization followed by a non-rigid registration using an image-based metric based on linear correlation of linear combination. Using the combined non-rigid transformation matrices, the 3D mesh model is fused with the 3D US. RESULTS: 3D US and multi-phase MRA images acquired from 10 porcine models were used to test the performance of the proposed fusion tool. Unimodal registration of the MRA phases yielded a target registration error (TRE) of [Formula: see text] mm. Initial rigid alignment of the portal MRA and 3D US yielded a mean TRE of [Formula: see text] mm, which was significantly reduced to [Formula: see text] mm ([Formula: see text]) after affine image-based registration. The following deformable registration step allowed for further decrease of the mean TRE to [Formula: see text] mm. CONCLUSION: The proposed tool could facilitate visualization and localization of these vessels when using 3D US intra-operatively for either intravascular or percutaneous interventions to avoid vessel perforation.
PURPOSE: Modulating the chemotherapy injection rate with regard to blood flow velocities in the tumor-feeding arteries during intra-arterial therapies may help improve liver tumor targeting while decreasing systemic exposure. These velocities can be obtained noninvasively using Doppler ultrasound (US). However, small vessels situated in the liver are difficult to identify and follow in US. We propose a multimodal fusion approach that non-rigidly registers a 3D geometric mesh model of the hepatic arteries obtained from preoperative MR angiography (MRA) acquisitions with intra-operative 3D US imaging. METHODS: The proposed fusion tool integrates 3 imaging modalities: an arterial MRA, a portal phase MRA and an intra-operative 3D US. Preoperatively, the arterial phase MRA is used to generate a 3D model of the hepatic arteries, which is then non-rigidly co-registered with the portal phase MRA. Once the intra-operative 3D US is acquired, we register it with the portal MRA using a vessel-based rigid initialization followed by a non-rigid registration using an image-based metric based on linear correlation of linear combination. Using the combined non-rigid transformation matrices, the 3D mesh model is fused with the 3D US. RESULTS: 3D US and multi-phase MRA images acquired from 10 porcine models were used to test the performance of the proposed fusion tool. Unimodal registration of the MRA phases yielded a target registration error (TRE) of [Formula: see text] mm. Initial rigid alignment of the portal MRA and 3D US yielded a mean TRE of [Formula: see text] mm, which was significantly reduced to [Formula: see text] mm ([Formula: see text]) after affine image-based registration. The following deformable registration step allowed for further decrease of the mean TRE to [Formula: see text] mm. CONCLUSION: The proposed tool could facilitate visualization and localization of these vessels when using 3D US intra-operatively for either intravascular or percutaneous interventions to avoid vessel perforation.
Entities:
Keywords:
Fusion; Image registration; Magnetic resonance angiography; Ultrasound; Vessel segmentation
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