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A comprehensive workflow for CCTA and OCT data fusion with 3D printing validation: advancing patient-specific testing environments for percutaneous coronary intervention devices
A comprehensive workflow for CCTA and OCT data fusion with 3D printing validation: advancing patient-specific testing environments for percutaneous coronary intervention devices
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A comprehensive workflow for CCTA and OCT data fusion with 3D printing validation: advancing patient-specific testing environments for percutaneous coronary intervention devices
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A comprehensive workflow for CCTA and OCT data fusion with 3D printing validation: advancing patient-specific testing environments for percutaneous coronary intervention devices
A comprehensive workflow for CCTA and OCT data fusion with 3D printing validation: advancing patient-specific testing environments for percutaneous coronary intervention devices

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A comprehensive workflow for CCTA and OCT data fusion with 3D printing validation: advancing patient-specific testing environments for percutaneous coronary intervention devices
A comprehensive workflow for CCTA and OCT data fusion with 3D printing validation: advancing patient-specific testing environments for percutaneous coronary intervention devices
Journal Article

A comprehensive workflow for CCTA and OCT data fusion with 3D printing validation: advancing patient-specific testing environments for percutaneous coronary intervention devices

2025
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Overview
Objective To create high-resolution, patient-specific 3D coronary artery models aimed at developing digital models and functional phantoms for the testing of cardiac catheterization devices. Methods Using coronary computed tomography angiography (CCTA) and optical coherence tomography (OCT), coronary artery lesions were identified and quantified. Imaging data were fused using a custom-made workflow to create highly accurate digital 3D models. For validation of the workflow, coronary artery phantoms were fabricated using additive manufacturing. An OCT was then conducted on the 3D printed phantom, and the developed workflow was applied to generate a derivative model, which was subsequently compared to the original. Results CCTA and OCT datasets from 15 patients were successfully collected and used to develop patient-specific 3D coronary artery models, including detailed inner shells, calcifications, outer wall structures, and side branches. Of these, 13 out of 15 3D printed phantoms were successfully validated and compared to their corresponding original model. The median vertex deviation of the derivative model was 0.15 (0.14 - 0.17) mm. The median absolute stenosis difference between the derivative model and the original model was 3 (1–5)%AS. Conclusion We present a novel workflow to produce high-resolution patient-specific phantoms of coronary arteries.