Optimizing registration of complex vascular geometries

Advances in imaging, such as coronary angiography, intravascular ultrasound, and optical coherence tomography, can improve procedural success and outcomes for endovascular catheter intervention, such as stent implantation. Yet, these imaging modalities are not universally embraced; and thus, optimization of stent implantation and management of the adverse outcomes remain challenging. This is partially because full adoption of complex imaging awaits methods to reconstruct precise 3D structure of lumen and implanted stent, and to track vascular responses to stent implantation over time in 3D. This thesis creates new methods for reconstruction and registration in 3D by melding disparate imaging modalities, coronary angiography and optical coherence tomography (OCT), that provide different 2D-plane information (longitudinal and cross-sectional) using widely-varied experimental models (static phantom models, preclinical swine model with controlled scenarios of stent implantation in coronary arteries, and clinical unbiased model of stent implantation). A 3D vessel centerline from coronary angiography serves as a fusion path for OCT to reconstruct 3D structures and as a registration path for the reconstructed 3D structures across time. The developed vessel centerline reconstruction method overcame current spatial and temporal alignment challenges, and demonstrated high reproducibility across imaging angles and throughout the cardiac cycle. Structural reconstruction by angiography-OCT fusion was established and improved to account for the cardiac motion, reducing error in estimation of the stent length from 5.5% ± 4.5% with standard fusion to 2.4% ± 2.0%. Time-point registration was accomplished by detecting landmarks that are least affected by the vascular responses - its error, i.e., stent-strut shift from post-implantation to follow-up, was 1.6 mm ± 0.5 mm (9.2% ± 3.0% of the stent length). These methods were validated in a clinical setting and the errors of all methods were within those in the preclinical setting, suggesting potential for clinical applicability.

Department dc:contributor.department

Harvard--MIT Program in Health Sciences and Technology.

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2016

Author dc:creator

• Kunio, Mie

Advisor dc:contributor.advisor

• Elazer R. Edelman.

• Harvard--MIT Program in Health Sciences and Technology.

Statement dc:rights

• M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

eng

Handle dc:identifier.uri

http://hdl.handle.net/1721.1/104613

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/104613