Jonathan Lessick1, Oliver Klass2, Sabine Wuchenauer2, Matthew J Walker3, Holger Schmitt4, Jochen Peters4, Juergen Weese4, Horst Brunner2, Mani Vembar3, Michael Grass4, Doron Aronson5, Martin H K Hoffmann2. 1. Cardiology Department, Rambam Health Care Campus and Technion, Israel Institute of Technology, Haalita Street, Haifa 3109601, Israel. Electronic address: j_lessick@rambam.health.gov.il. 2. Klinik für Diagnostische und Interventionelle Radiologie, Ulm, Germany. 3. Philips Healthcare, Cleveland, Ohio. 4. Philips Research Laboratories, Hamburg, Germany. 5. Cardiology Department, Rambam Health Care Campus and Technion, Israel Institute of Technology, Haalita Street, Haifa 3109601, Israel.
Abstract
RATIONALE AND OBJECTIVES: Selecting the optimal phase for coronary artery evaluation can be challenging, especially at higher heart rates, given that the optimal phase may differ for each of the coronary arteries. This study aimed to evaluate a novel vessel-specific algorithm which automatically outputs the minimum motion phase per coronary artery. MATERIALS AND METHODS: The study included 44 patients who underwent 256-slice cardiac computed tomography for evaluation of chest pain. End-systolic and mid-diastolic minimal motion phases were automatically calculated by a previously validated global motion algorithm and by a new vessel-specific algorithm which calculates the minimum motion for each of the three main coronary arteries, separately. Two readers blindly evaluated all coronary segments for image quality. Median scores per coronary artery were compared by the Wilcoxon signed rank test. RESULTS: The variation, per patient, between the optimal phases of the three coronary arteries was 5.0 ± 4.5% (1%-22%) for end systole and 4.8 ± 4.1% (0%-19%) for mid diastole. The mean image quality scores per coronary artery were 4.0 ± 0.61 for the vessel-specific approach and 3.80 ± 0.69 for the global phase selection (P < .001). Overall, 46 of 122 arteries had a better score with the vessel-specific approach and five with the standard global approach. Interreader agreement was substantial (k = 0.72). CONCLUSIONS: This study has shown that multiple phases are required to ensure optimal image quality for all three coronary arteries and that a vessel-specific phase selection algorithm achieves superior results to the standard global approach.
RATIONALE AND OBJECTIVES: Selecting the optimal phase for coronary artery evaluation can be challenging, especially at higher heart rates, given that the optimal phase may differ for each of the coronary arteries. This study aimed to evaluate a novel vessel-specific algorithm which automatically outputs the minimum motion phase per coronary artery. MATERIALS AND METHODS: The study included 44 patients who underwent 256-slice cardiac computed tomography for evaluation of chest pain. End-systolic and mid-diastolic minimal motion phases were automatically calculated by a previously validated global motion algorithm and by a new vessel-specific algorithm which calculates the minimum motion for each of the three main coronary arteries, separately. Two readers blindly evaluated all coronary segments for image quality. Median scores per coronary artery were compared by the Wilcoxon signed rank test. RESULTS: The variation, per patient, between the optimal phases of the three coronary arteries was 5.0 ± 4.5% (1%-22%) for end systole and 4.8 ± 4.1% (0%-19%) for mid diastole. The mean image quality scores per coronary artery were 4.0 ± 0.61 for the vessel-specific approach and 3.80 ± 0.69 for the global phase selection (P < .001). Overall, 46 of 122 arteries had a better score with the vessel-specific approach and five with the standard global approach. Interreader agreement was substantial (k = 0.72). CONCLUSIONS: This study has shown that multiple phases are required to ensure optimal image quality for all three coronary arteries and that a vessel-specific phase selection algorithm achieves superior results to the standard global approach.
Authors: Bhavna Balaney; Mani Vembar; Michael Grass; Amita Singh; Keigo Kawaji; Luis Landeras; Jonathan Chung; Victor Mor-Avi; Amit R Patel Journal: Eur J Radiol Date: 2019-03-02 Impact factor: 3.528
Authors: Lubomir Hadjiiski; Jordan Liu; Heang-Ping Chan; Chuan Zhou; Jun Wei; Aamer Chughtai; Jean Kuriakose; Prachi Agarwal; Ella Kazerooni Journal: Comput Math Methods Med Date: 2016-09-19 Impact factor: 2.238