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Small whole heart volume predicts cardiovascular events in patients with stable chest pain: insights from the PROMISE trial

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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.

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Abbreviations

ASCVD:

Atherosclerosis cardiovascular disease

AUC:

Area under the curve

BSA:

Body surface area

CAC:

Coronary artery calcium

CAD:

Coronary artery disease

CI:

Confidence interval

CT:

Computed tomography

CTA:

Computed tomography angiography

CV:

Cardiovascular

DL:

Deep learning

HR:

Hazard ratio

HRPF:

High-risk plaque features

IQR:

Interquartile range

MACE:

Major adverse cardiac events

MI:

Myocardial infarction

ROC:

Receiver operator characteristic

SD:

Standard deviation

UA:

Unstable angina

WHV:

Whole heart volume

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Acknowledgements

Dr. Hoffmann received Research Grants from the National Institutes of Health (U01HL092040, U01HL092022), and Siemens Medical Solutions, Heart Flow Inc., and served as a consultant for Heart Flow. Dr. Lu reports consulting fees with PQBypass and a research grant from the Nvidia Corporation Academic Program. Dr. Lu is supported by grants from the American Heart Association Precision Medicine Institute 18UNPG34030172 and the Harvard University Center For AIDS Research NIH/NIAID 5P30AI060354-14. Dr. Ferencik reports receiving a grant from the American Heart Association 13FTF16450001. The other authors have nothing to disclose.

Funding

The PROMISE trial was supported by grants from the National Heart, Lung, and Blood Institute (R01HL098237, R01HL098236, R01HL098305, and R01HL098235).

Author information

Authors and Affiliations

  1. Cardiovascular Imaging Research Center, Massachusetts General Hospital – Harvard Medical School, 165 Cambridge Street, Suite 400, Boston, MA, 02114, USA

    Borek Foldyna, Parastou Eslami, Thomas Mayrhofer, Jan-Erik Scholtz, Maros Ferencik, Daniel O. Bittner, Nandini M. Meyersohn, Stefan B. Puchner, Hamed Emami, Hugo J. W. L. Aerts, Michael T. Lu & Udo Hoffmann

  2. Department of Radiology, Rhön Klinikum - Campus Bad Neustadt, Bad Neustadt an der Saale, Germany

    Borek Foldyna

  3. Artificial Intelligence in Medicine (AIM) Program, Brigham and Women’s Hospital - Harvard Medical School, Boston, MA, USA

    Roman Zeleznik & Hugo J. W. L. Aerts

  4. Department of Radiation Oncology, Brigham and Women’s Hospital, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA

    Roman Zeleznik & Hugo J. W. L. Aerts

  5. School of Business Studies, Stralsund University of Applied Sciences, Stralsund, Germany

    Thomas Mayrhofer

  6. Department of Diagnostic and Interventional Radiology, University Hospital Frankfurt, Frankfurt am Main, Germany

    Jan-Erik Scholtz

  7. Knight Cardiovascular Institute, Oregon Health & Science University, Portland, OR, USA

    Maros Ferencik

  8. Department of Cardiology, Friedrich-Alexander University Erlangen-Neurnberg (FAU), University Hospital Erlangen, Erlangen, Germany

    Daniel O. Bittner

  9. SBP Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria

    Stefan B. Puchner

  10. Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN, USA

    Patricia A. Pellikka

  11. Department of Radiology and Nuclear Medicine, Maastricht University Medical Center+, Maastricht, The Netherlands

    Hugo J. W. L. Aerts

  12. Duke Clinical Research Institute, Duke University School of Medicine, Durham, NC, USA

    Pamela S. Douglas

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  1. Borek Foldyna
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  14. Michael T. Lu
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  15. Udo Hoffmann
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Corresponding author

Correspondence to Borek Foldyna.

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Guarantor

The scientific guarantor of this publication is Dr. Borek Foldyna.

Conflict of interest

The authors of this manuscript declare no relationships with any companies whose products or services may be related to the subject matter of the article.

Statistics and biometry

One of the authors (Prof. Thomas Mayrhofer) has significant statistical expertise and no complex statistical methods were necessary for this paper.

Informed consent

Local and central institutional review boards approved the study, and all patients provided written informed consent.

Ethical approval

Local and central institutional review boards approved the study.

Study subjects or cohorts overlap

This investigation is a sub-study of the Prospective Multicenter Imaging Study for Evaluation of Chest Pain (PROMISE) trial.

Methodology

• Secondary analysis

• Multicenter randomized controlled trial

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Foldyna, B., Zeleznik, R., Eslami, P. et al. Small whole heart volume predicts cardiovascular events in patients with stable chest pain: insights from the PROMISE trial. Eur Radiol 31, 6200–6210 (2021). https://doi.org/10.1007/s00330-021-07695-2

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