3D reconstruction of coronary arteries from 2D angiographic projections using non-uniform rational basis splines (NURBS) for accurate modelling of coronary stenoses

Journal article

Objective
Assessment of coronary stenosis severity is crucial in clinical practice. This study proposes a novel method to generate 3D models of stenotic coronary arteries, directly from 2D coronary images, and suitable for immediate assessment of the stenosis severity.

Methods
From multiple 2D X-ray coronary arteriogram projections, 2D vessels were extracted. A 3D centreline was reconstructed as intersection of surfaces from corresponding branches. Next, 3D luminal contours were generated in a two-step process: first, a Non-Uniform Rational B-Spline (NURBS) circular contour was designed and, second, its control points were adjusted to interpolate computed 3D boundary points. Finally, a 3D surface was generated as an interpolation across the control points of the contours and used in the analysis of the severity of a lesion. To evaluate the method, we compared 3D reconstructed lesions with Optical Coherence Tomography (OCT), an invasive imaging modality that enables high-resolution endoluminal visualization of lesion anatomy.

Results
Validation was performed on routine clinical data. Analysis of paired cross-sectional area discrepancies indicated that the proposed method more closely represented OCT contours than conventional approaches in luminal surface reconstruction, with overall root-mean-square errors ranging from 0.213mm2 to 1.013mm2, and maximum error of 1.837mm2. Comparison of volume reduction due to a lesion with corresponding FFR measurement suggests that the method may help in estimating the physiological significance of a lesion.

Conclusion
The algorithm accurately reconstructed 3D models of lesioned arteries and enabled quantitative assessment of stenoses. The proposed method has the potential to allow immediate analysis of the stenoses in clinical practice, thereby providing incremental diagnostic and prognostic information to guide treatments in real time and without the need for invasive techniques.

Authors: Galassi, F; Alkhalil, M; Lee, R; Martindale, P; Kharbanda, R

• Publication status: Published
• Peer review status: Peer reviewed
• Publisher: Public Library of Science
• Journal: PLoS One
• Volume: 13
• Issue: 1
• Article number: e0190650
• Publication date: 2018-01-03
• Acceptance date: 2017-12-18
• DOI: 10.1371/journal.pone.0190650
• EISSN: 1932-6203
• ISSN: 1932-6203
• Pmid: 29298341
• Language: English
• Keywords: coronary stenosis; coronary angiography; algorithms; models, biological; humans; coronary vessels; imaging, three-dimensional