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Title: Post-procedure micro-CT analyses of coronary artery stenting in left main vessels of reanimated and perfusion-fixed human hearts
Abstract BackgroundPercutaneous coronary interventions (PCIs) within left main coronary arteries are high-risk procedures that require optimization of interactions between stent(s) and diseased vessels. Optical Coherence Tomography (OCT) is a widely accepted tool that enhances physicians’ ability to assess proper stent appositions during clinical procedures. The primary aim of this study was to develop complementary post-procedure imaging methodologies to better assess and interpret outcomes of left main PCI procedures, utilizing both reanimated and perfusion-fixed human hearts. MethodsPCIs were performed while obtaining OCT scans within the left main anatomies of six human hearts. Subsequently, each heart was scanned with a micro-CT scanner with optimized parameters to achieve resolutions up to 20 µm. Scans were reconstructed and imported into a DICOM segmentation software to generate computational models of implanted stents and associated coronary vessels. 2D images from OCT that were obtained during PCIs were compared to the 3D models generated from micro-CT reconstructions. In addition, the 3D models were utilized to create virtual reality scenes and enlarged 3D prints for development of “mixed reality” tools relative to bifurcation stenting within human left main coronary arteries. ResultsWe developed reproducible methodologies for post-implant analyses of coronary artery stenting procedures. In addition, we generated high-resolution 3D computational models, with ~ 20-micron resolutions, of PCIs performed within reanimated and perfusion-fixed heart specimens. ConclusionsGenerated computational models of left main PCIs performed in isolated human hearts can be used to obtain detailed measurements that provide further clinical insights on procedural outcomes. The 3D models from these procedures are useful for generating virtual reality scenes and 3D prints for physician training and education.  more » « less
Award ID(s):
1941543
PAR ID:
10471551
Author(s) / Creator(s):
;
Publisher / Repository:
NSF
Date Published:
Journal Name:
BioMedical Engineering OnLine
Volume:
22
Issue:
1
ISSN:
1475-925X
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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