Leiden University Scholarly Publications

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Cao, Q.; Broersen, A.; Kitslaar, P.H.; Yuan, M.Y.; Lelieveldt, B.P.F.; Dijkstra, J. (2020)

Automatic coronary artery plaque thickness comparison between baseline and follow-up CCTA images

Article / Letter to editor
Purpose Currently, coronary plaque changes are manually compared between a baseline and follow-up coronary computed tomography angiography (CCTA) images for long-term coronary plaque development investigation. We propose an automatic method to measure the plaque thickness change over time. Methods We model the lumen and vessel wall for both the baseline coronary artery tree (CAT-BL) and follow-up coronary artery tree (CAT-FU) as smooth three-dimensional (3D) surfaces using a subdivision fitting scheme with the same coarse meshes by which the correspondence among these surface points is generated. Specifically, a rigid point set registration is used to transform the coarse mesh from the CAT-FU to CAT-BL. The plaque thickness and the thickness difference is calculated as the distance between corresponding surface points. To evaluate the registration accuracy, the average distance between manually defined markers on clinical scans is calculated. Artificial CAT-BL and CAT-FU pairs were...Show morePurpose Currently, coronary plaque changes are manually compared between a baseline and follow-up coronary computed tomography angiography (CCTA) images for long-term coronary plaque development investigation. We propose an automatic method to measure the plaque thickness change over time. Methods We model the lumen and vessel wall for both the baseline coronary artery tree (CAT-BL) and follow-up coronary artery tree (CAT-FU) as smooth three-dimensional (3D) surfaces using a subdivision fitting scheme with the same coarse meshes by which the correspondence among these surface points is generated. Specifically, a rigid point set registration is used to transform the coarse mesh from the CAT-FU to CAT-BL. The plaque thickness and the thickness difference is calculated as the distance between corresponding surface points. To evaluate the registration accuracy, the average distance between manually defined markers on clinical scans is calculated. Artificial CAT-BL and CAT-FU pairs were created to simulate the plaque decrease and increase over time. Results For 116 pairs of markers from nine clinical scans, the average marker distance after registration was 0.95 +/- 0.98 mm (two times the voxel size). On the 10 artificial pairs of datasets, the proposed method successfully located the plaque changes. The average of the calculated plaque thickness difference is the same as the corresponding created value (standard deviation +/- 0.1 mm). Conclusions The proposed method automatically calculates local coronary plaque thickness differences over time and can be used for 3D visualization of plaque differences. The analysis and reporting of coronary plaque progression and regression will benefit from an automatic plaque thickness comparison.Show less
baseline and follow-up
coronary arteries
coronary computed tomography angiography
plaque thickness
visualization
All authors
Cao, Q.; Broersen, A.; Kitslaar, P.H.; Yuan, M.Y.; Lelieveldt, B.P.F.; Dijkstra, J.
Date
2020-01-20
Journal
Medical Physics
Volume
47
Issue
3
Pages
1083 - 1093
DOI
doi:10.1002/mp.13993
Link
https://aapm.onlinelibrary.wiley.com/doi/10.1002/mp.13993