Ying Li1, Guangming Zhu1, Victoria Ding2, Bin Jiang1, Derek Boothroyd2, Fatima Rodriguez3, Dominik Fleischmann4, Manisha Desai2, David Saloner5, Luca Saba6, Jason Hom7, Max Wintermark1. 1. From the Neuroradiology Section, Department of Radiology. 2. Quantitative Sciences Unit, Department of Medicine, Stanford University School of Medicine. 3. Division of Cardiovascular Medicine, Stanford University. 4. Cardiovascular Imaging Section, Department of Radiology, Stanford University School of Medicine, Palo Alto. 5. Department of Radiology, University of California San Francisco, San Francisco, California. 6. Dipartimento di Radiologia, Azienda Ospedaliero Universitaria di Cagliari, Cagliari, Italy. 7. Department of Medicine, Stanford University School of Medicine, Palo Alto, California.
Abstract
PURPOSE: The aim of this study was to compare coronary and carotid artery imaging and determine which one shows the strongest association with atherosclerotic cardiovascular disease (ASCVD) score. PATIENTS AND METHODS: Two separate series patients who underwent either coronary computed tomography angiography (CTA) or carotid CTA were included. We recorded the ASCVD scores and assessed the CTA imaging. Two thirds were used to build predictive models, and the remaining one third generated predicted ASCVD scores. The Bland-Altman analysis analyzed the concordance. RESULTS: A total of 110 patients were included in each group. There was no significant difference between clinical characteristics. Three imaging variables were included in the carotid model. Two coronary models (presence of calcium or Agatston score) were created. The bias between true and predicted ASCVD scores was 0.37 ± 5.72% on the carotid model, and 2.07 ± 7.18% and 2.47 ± 7.82% on coronary artery models, respectively. CONCLUSIONS: Both carotid and coronary artery imaging features can predict ASCVD score. The carotid artery was more associated to the ASCVD score than the coronary artery.
PURPOSE: The aim of this study was to compare coronary and carotid artery imaging and determine which one shows the strongest association with atherosclerotic cardiovascular disease (ASCVD) score. PATIENTS AND METHODS: Two separate series patients who underwent either coronary computed tomography angiography (CTA) or carotid CTA were included. We recorded the ASCVD scores and assessed the CTA imaging. Two thirds were used to build predictive models, and the remaining one third generated predicted ASCVD scores. The Bland-Altman analysis analyzed the concordance. RESULTS: A total of 110 patients were included in each group. There was no significant difference between clinical characteristics. Three imaging variables were included in the carotid model. Two coronary models (presence of calcium or Agatston score) were created. The bias between true and predicted ASCVD scores was 0.37 ± 5.72% on the carotid model, and 2.07 ± 7.18% and 2.47 ± 7.82% on coronary artery models, respectively. CONCLUSIONS: Both carotid and coronary artery imaging features can predict ASCVD score. The carotid artery was more associated to the ASCVD score than the coronary artery.
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