Literature DB >> 25079610

Coronary CT angiography (cCTA): automated registration of coronary arterial trees from multiple phases.

Lubomir Hadjiiski1, Chuan Zhou, Heang-Ping Chan, Aamer Chughtai, Prachi Agarwal, Jean Kuriakose, Ella Kazerooni, Jun Wei, Smita Patel.   

Abstract

Coronary computed tomography angiography (cCTA) is a commonly used imaging modality for the evaluation of coronary artery disease. cCTA is generally reconstructed in multiple cardiac phases because different coronary arteries may be better visualized in some phases than in others due to the periodic cardiac motion. We are developing an automated registration method for coronary arterial trees from multiple-phase cCTA that has potential application in building a 'best-quality' tree to facilitate image analysis and detection of stenotic plaques. Given the segmented left or right coronary arterial (LCA or RCA) trees from the multiple phases as input, the adjacent phase pairs, where displacements are relatively small, are registered by a specifically designed method based on a cubic B-spline with fast localized optimization (CBSO). For the phase pairs with large displacements, a global registration using an affine transform with quadratic terms and nonlinear simplex optimization (AQSO) is followed by a local registration using CBSO to refine the AQSO registered volumes. 26 LCA and 26 RCA trees with six cCTA phases from 26 patients were used for registration evaluation. The average distances for the tree pairs between the adjacent phases with small displacements before and after CBSO registration were 0.96  ±  0.79 and 0.76  ±  0.61 mm respectively for LCA, and 0.93  ±  0.97 and 0.64  ±  0.43 mm, respectively for RCA. The average distance differences before and after registration were statistically significant (p < 0.001) for both LCA and RCA trees. The average distances for the distant phases with large displacements before registration, after AQSO registration, and finally after the CBSO registration were 2.85  ±  1.46, 1.62  ±  0.76, and 0.97  ±  0.43 mm, respectively for LCA, and 4.03  ±  2.36, 2.18  ±  1.11, and 0.97  ±  0.44 mm, respectively for RCA. The average distance differences between every two consecutive stages of registration were statistically significant. The corresponding phases of LCA and RCA trees were aligned to an average of less than 1 mm, providing a basis for a best-quality tree construction.

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Year:  2014        PMID: 25079610      PMCID: PMC4277697          DOI: 10.1088/0031-9155/59/16/4661

Source DB:  PubMed          Journal:  Phys Med Biol        ISSN: 0031-9155            Impact factor:   3.609


  10 in total

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5.  Statistical coronary motion models for 2D+t/3D registration of X-ray coronary angiography and CTA.

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7.  Coronary CT angiography (cCTA): automated registration of coronary arterial trees from multiple phases.

Authors:  Lubomir Hadjiiski; Chuan Zhou; Heang-Ping Chan; Aamer Chughtai; Prachi Agarwal; Jean Kuriakose; Ella Kazerooni; Jun Wei; Smita Patel
Journal:  Phys Med Biol       Date:  2014-07-31       Impact factor: 3.609

8.  Automated cardiac phase selection with 64-MDCT coronary angiography.

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  10 in total
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Authors:  Jun Wei; Chuan Zhou; Heang-Ping Chan; Aamer Chughtai; Prachi Agarwal; Jean Kuriakose; Lubomir Hadjiiski; Smita Patel; Ella Kazerooni
Journal:  Med Phys       Date:  2014-08       Impact factor: 4.071

2.  Coronary artery analysis: Computer-assisted selection of best-quality segments in multiple-phase coronary CT angiography.

Authors:  Chuan Zhou; Heang-Ping Chan; Lubomir M Hadjiiski; Aamer Chughtai; Jun Wei; Ella A Kazerooni
Journal:  Med Phys       Date:  2016-10       Impact factor: 4.071

3.  Coronary CT angiography (cCTA): automated registration of coronary arterial trees from multiple phases.

Authors:  Lubomir Hadjiiski; Chuan Zhou; Heang-Ping Chan; Aamer Chughtai; Prachi Agarwal; Jean Kuriakose; Ella Kazerooni; Jun Wei; Smita Patel
Journal:  Phys Med Biol       Date:  2014-07-31       Impact factor: 3.609

4.  Best-Quality Vessel Identification Using Vessel Quality Measure in Multiple-Phase Coronary CT Angiography.

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5.  A Patient-Specific 3Dt Coronary Artery Motion Modeling Method Using Hierarchical Deformation with Electrocardiogram.

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  5 in total

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