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Dobrolinska MM, Jukema RA, van Velzen SGM, van Diemen PA, Greuter MJW, Prakken NHJ, van der Werf NR, Raijmakers PG, Slart RHJA, Knaapen P, Isgum I, Danad I. The prognostic value of visual and automatic coronary calcium -scoring from low dose CT-[15O]-water PET. Eur Heart J Cardiovasc Imaging 2024:jeae081. [PMID: 38525588 DOI: 10.1093/ehjci/jeae081] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/16/2023] [Revised: 02/28/2024] [Accepted: 03/06/2024] [Indexed: 03/26/2024] Open
Abstract
PURPOSE Firstly, to validate automatically and visually scored coronary artery calcium (CAC) on low dose CT (LDCT) scans with a dedicated calcium scoring CT (CSCT) scan. Secondly, to assess the added value of CAC scored from LDCT scans acquired during [15O]-water-PET myocardial perfusion imaging (MPI) on prediction of major adverse cardiac events (MACE). METHODS 572 consecutive patients with suspected coronary artery disease, who underwent [15O]-water-PET MPI with LDCT and a dedicated CSCT scan were included. In the reference CSCT scans, manual CAC scoring was performed, while LDCT scans were scored visually and automatically using deep learning approach. Subsequently, based on CAC score results from CSCT and LDCT scans, each patient's scan was assigned to one out of five cardiovascular risk groups (0; 1-100; 101-400; 401-1000; >1000) and the agreement in risk group classification between CSCT and LDCT scans was investigated. MACE was defined as a composite of all-cause death, nonfatal myocardial infarction, coronary revascularization, and unstable angina. RESULTS The agreement in risk group classification between reference CSCT manual scoring and visual/automatic LDCT scoring from LDCT was 0.66 (95% CI: 0.62-0.70) and 0.58 (95% CI: 0.53-0.62), respectively. Based on visual and automatic CAC scoring from LDCT scans, patients with CAC>100 and CAC>400, respectively, were at increased risk of MACE, independently of ischemic information from the [15O]-water-PET scan. CONCLUSIONS There is a moderate agreement in risk classification between visual and automatic CAC scoring from LDCT and reference CSCT scans. Visual and automatic CAC scoring from LDCT scans improve identification of patients at higher risk of MACE.
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Affiliation(s)
- M M Dobrolinska
- Medical Imaging Center, Departments of Radiology, Nuclear Medicine and Molecular Imaging, University of Groningen, University Medical Center Groningen, PO Box 30.001, 9700 RB Groningen, The Netherlands
| | - R A Jukema
- Department of Cardiology, Amsterdam UMC, Vrije Universiteit Amsterdam, De Boelelaan 1117, Amsterdam, the Netherlands
| | - S G M van Velzen
- Department of Biomedical Engineering and Physics, Amsterdam UMC location University of Amsterdam, the Netherlands
- Informatics Institute, University of Amsterdam, the Netherlands
- Amsterdam Cardiovascular Sciences, Amsterdam, The Netherlands
| | - P A van Diemen
- Department of Cardiology, Amsterdam UMC, Vrije Universiteit Amsterdam, De Boelelaan 1117, Amsterdam, the Netherlands
| | - M J W Greuter
- Medical Imaging Center, Departments of Radiology, Nuclear Medicine and Molecular Imaging, University of Groningen, University Medical Center Groningen, PO Box 30.001, 9700 RB Groningen, The Netherlands
- Department of Robotics and Mechatronics, Faculty of Electrical Engineering, Mathematics & Computer Science, University of Twente, P.O. Box 217, 7500 AE Enschede, Netherlands
| | - N H J Prakken
- Medical Imaging Center, Departments of Radiology, Nuclear Medicine and Molecular Imaging, University of Groningen, University Medical Center Groningen, PO Box 30.001, 9700 RB Groningen, The Netherlands
| | - N R van der Werf
- Department of Radiology, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX, Utrecht, The Netherlands
| | - P G Raijmakers
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, De Boelelaan 1117
| | - R H J A Slart
- Medical Imaging Center, Departments of Radiology, Nuclear Medicine and Molecular Imaging, University of Groningen, University Medical Center Groningen, PO Box 30.001, 9700 RB Groningen, The Netherlands
- Department of Biomedical Photonic Imaging, Faculty of Science and Technology, University of Twente, Drienerlolaan 5, 7522 NB Enschede, The Netherlands
| | - P Knaapen
- Department of Cardiology, Amsterdam UMC, Vrije Universiteit Amsterdam, De Boelelaan 1117, Amsterdam, the Netherlands
| | - I Isgum
- Department of Biomedical Engineering and Physics, Amsterdam UMC location University of Amsterdam, the Netherlands
- Informatics Institute, University of Amsterdam, the Netherlands
- Amsterdam Cardiovascular Sciences, Amsterdam, The Netherlands
- Department of Radiology and Nuclear Medicine, Amsterdam UMC location University of Amsterdam, the Netherlands
| | - I Danad
- Department of Cardiology, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX Utrecht, The Netherlands
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van Velzen SGM, Dobrolinska MM, Knaapen P, van Herten RLM, Jukema R, Danad I, Slart RHJA, Greuter MJW, Išgum I. Automated cardiovascular risk categorization through AI-driven coronary calcium quantification in cardiac PET acquired attenuation correction CT. J Nucl Cardiol 2023; 30:955-969. [PMID: 35851642 PMCID: PMC10261233 DOI: 10.1007/s12350-022-03047-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2022] [Accepted: 05/30/2022] [Indexed: 12/17/2022]
Abstract
BACKGROUND We present an automatic method for coronary artery calcium (CAC) quantification and cardiovascular risk categorization in CT attenuation correction (CTAC) scans acquired at rest and stress during cardiac PET/CT. The method segments CAC according to visual assessment rather than the commonly used CT-number threshold. METHODS The method decomposes an image containing CAC into a synthetic image without CAC and an image showing only CAC. Extensive evaluation was performed in a set of 98 patients, each having rest and stress CTAC scans and a dedicated calcium scoring CT (CSCT). Standard manual calcium scoring in CSCT provided the reference standard. RESULTS The interscan reproducibility of CAC quantification computed as average absolute relative differences between CTAC and CSCT scan pairs was 75% and 85% at rest and stress using the automatic method compared to 121% and 114% using clinical calcium scoring. Agreement between automatic risk assessment in CTAC and clinical risk categorization in CSCT resulted in linearly weighted kappa of 0.65 compared to 0.40 between CTAC and CSCT using clinically used calcium scoring. CONCLUSION The increased interscan reproducibility achieved by our method may allow routine cardiovascular risk assessment in CTAC, potentially relieving the need for dedicated CSCT.
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Affiliation(s)
- S G M van Velzen
- Department of Biomedical Engineering and Physics, Amsterdam UMC location University of Amsterdam, Meibergdreef 123, 1105 AZ, Amsterdam, the Netherlands.
- Informatics Institute, University of Amsterdam, Amsterdam, the Netherlands.
- Amsterdam Cardiovascular Sciences, Heart Failure & Arrhythmias, Amsterdam, the Netherlands.
| | - M M Dobrolinska
- Medical Imaging Center, Departments of Radiology, Nuclear Medicine and Molecular Imaging, University of Groningen, University Medical Center Groningen, PO Box 30.001, 9700 RB, Groningen, the Netherlands
| | - P Knaapen
- Department of Cardiology, VU University Medical Center, Amsterdam, the Netherlands
| | - R L M van Herten
- Department of Biomedical Engineering and Physics, Amsterdam UMC location University of Amsterdam, Meibergdreef 123, 1105 AZ, Amsterdam, the Netherlands
- Informatics Institute, University of Amsterdam, Amsterdam, the Netherlands
- Amsterdam Cardiovascular Sciences, Heart Failure & Arrhythmias, Amsterdam, the Netherlands
| | - R Jukema
- Department of Cardiology, VU University Medical Center, Amsterdam, the Netherlands
| | - I Danad
- Department of Cardiology, VU University Medical Center, Amsterdam, the Netherlands
| | - R H J A Slart
- Medical Imaging Center, Departments of Radiology, Nuclear Medicine and Molecular Imaging, University of Groningen, University Medical Center Groningen, PO Box 30.001, 9700 RB, Groningen, the Netherlands
- Department of Biomedical Photonic Imaging, Faculty of Science and Technology, University of Twente, Drienerlolaan 5, 7522 NB, Enschede, the Netherlands
| | - M J W Greuter
- Medical Imaging Center, Departments of Radiology, Nuclear Medicine and Molecular Imaging, University of Groningen, University Medical Center Groningen, PO Box 30.001, 9700 RB, Groningen, the Netherlands
- Department of Robotics and Mechatronics, Faculty of Electrical Engineering, Mathematics & Computer Science, University of Twente, P.O. Box 217, 7500 AE, Enschede, the Netherlands
| | - I Išgum
- Department of Biomedical Engineering and Physics, Amsterdam UMC location University of Amsterdam, Meibergdreef 123, 1105 AZ, Amsterdam, the Netherlands
- Informatics Institute, University of Amsterdam, Amsterdam, the Netherlands
- Amsterdam Cardiovascular Sciences, Heart Failure & Arrhythmias, Amsterdam, the Netherlands
- Department of Radiology and Nuclear Medicine, Amsterdam UMC location University of Amsterdam, Amsterdam, the Netherlands
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