Borek Foldyna1,2, Roman Zeleznik3,4, Parastou Eslami5, Thomas Mayrhofer5,6, Jan-Erik Scholtz5,7, Maros Ferencik5,8, Daniel O Bittner5,9, Nandini M Meyersohn5, Stefan B Puchner5,10, Hamed Emami5, Patricia A Pellikka11, Hugo J W L Aerts5,3,4,12, Pamela S Douglas13, Michael T Lu5, Udo Hoffmann5. 1. Cardiovascular Imaging Research Center, Massachusetts General Hospital - Harvard Medical School, 165 Cambridge Street, Suite 400, Boston, MA, 02114, USA. bfoldyna@mgh.harvard.edu. 2. Department of Radiology, Rhön Klinikum - Campus Bad Neustadt, Bad Neustadt an der Saale, Germany. bfoldyna@mgh.harvard.edu. 3. Artificial Intelligence in Medicine (AIM) Program, Brigham and Women's Hospital - Harvard Medical School, Boston, MA, USA. 4. Department of Radiation Oncology, Brigham and Women's Hospital, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA. 5. Cardiovascular Imaging Research Center, Massachusetts General Hospital - Harvard Medical School, 165 Cambridge Street, Suite 400, Boston, MA, 02114, USA. 6. School of Business Studies, Stralsund University of Applied Sciences, Stralsund, Germany. 7. Department of Diagnostic and Interventional Radiology, University Hospital Frankfurt, Frankfurt am Main, Germany. 8. Knight Cardiovascular Institute, Oregon Health & Science University, Portland, OR, USA. 9. Department of Cardiology, Friedrich-Alexander University Erlangen-Neurnberg (FAU), University Hospital Erlangen, Erlangen, Germany. 10. SBP Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria. 11. Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN, USA. 12. Department of Radiology and Nuclear Medicine, Maastricht University Medical Center+, Maastricht, The Netherlands. 13. Duke Clinical Research Institute, Duke University School of Medicine, Durham, NC, USA.
Abstract
OBJECTIVES: The size of the heart may predict major cardiovascular events (MACE) in patients with stable chest pain. We aimed to evaluate the prognostic value of 3D whole heart volume (WHV) derived from non-contrast cardiac computed tomography (CT). METHODS: Among participants randomized to the CT arm of the Prospective Multicenter Imaging Study for Evaluation of Chest Pain (PROMISE), we used deep learning to extract WHV, defined as the volume of the pericardial sac. We compared the WHV across categories of cardiovascular risk factors and coronary artery disease (CAD) characteristics and determined the association of WHV with MACE (all-cause death, myocardial infarction, unstable angina; median follow-up: 26 months). RESULTS: In the 3798 included patients (60.5 ± 8.2 years; 51.5% women), the WHV was 351.9 ± 57.6 cm3/m2. We found smaller WHV in no- or non-obstructive CAD, women, people with diabetes, sedentary lifestyle, and metabolic syndrome. Larger WHV was found in obstructive CAD, men, and increased atherosclerosis cardiovascular disease (ASCVD) risk score (p < 0.05). In a time-to-event analysis, small WHV was associated with over 4.4-fold risk of MACE (HR (per one standard deviation) = 0.221; 95% CI: 0.068-0.721; p = 0.012) independent of ASCVD risk score and CT-derived CAD characteristics. In patients with non-obstructive CAD, but not in those with no- or obstructive CAD, WHV increased the discriminatory capacity of ASCVD and CT-derived CAD characteristics significantly. CONCLUSIONS: Small WHV may represent a novel imaging marker of MACE in stable chest pain. In particular, WHV may improve risk stratification in patients with non-obstructive CAD, a cohort with an unmet need for better risk stratification. KEY POINTS: • Heart volume is easily assessable from non-contrast cardiac computed tomography. • Small heart volume may be an imaging marker of major adverse cardiac events independent and incremental to traditional cardiovascular risk factors and established CT measures of CAD. • Heart volume may improve cardiovascular risk stratification in patients with non-obstructive CAD.
OBJECTIVES: The size of the heart may predict major cardiovascular events (MACE) in patients with stable chest pain. We aimed to evaluate the prognostic value of 3D whole heart volume (WHV) derived from non-contrast cardiac computed tomography (CT). METHODS: Among participants randomized to the CT arm of the Prospective Multicenter Imaging Study for Evaluation of Chest Pain (PROMISE), we used deep learning to extract WHV, defined as the volume of the pericardial sac. We compared the WHV across categories of cardiovascular risk factors and coronary artery disease (CAD) characteristics and determined the association of WHV with MACE (all-cause death, myocardial infarction, unstable angina; median follow-up: 26 months). RESULTS: In the 3798 included patients (60.5 ± 8.2 years; 51.5% women), the WHV was 351.9 ± 57.6 cm3/m2. We found smaller WHV in no- or non-obstructive CAD, women, people with diabetes, sedentary lifestyle, and metabolic syndrome. Larger WHV was found in obstructive CAD, men, and increased atherosclerosis cardiovascular disease (ASCVD) risk score (p < 0.05). In a time-to-event analysis, small WHV was associated with over 4.4-fold risk of MACE (HR (per one standard deviation) = 0.221; 95% CI: 0.068-0.721; p = 0.012) independent of ASCVD risk score and CT-derived CAD characteristics. In patients with non-obstructive CAD, but not in those with no- or obstructive CAD, WHV increased the discriminatory capacity of ASCVD and CT-derived CAD characteristics significantly. CONCLUSIONS: Small WHV may represent a novel imaging marker of MACE in stable chest pain. In particular, WHV may improve risk stratification in patients with non-obstructive CAD, a cohort with an unmet need for better risk stratification. KEY POINTS: • Heart volume is easily assessable from non-contrast cardiac computed tomography. • Small heart volume may be an imaging marker of major adverse cardiac events independent and incremental to traditional cardiovascular risk factors and established CT measures of CAD. • Heart volume may improve cardiovascular risk stratification in patients with non-obstructive CAD.
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