Abstract 4366856: Phase Matters: Diastolic versus Systolic Chamber Volumetry from CAC CT Scans in Heart Failure Risk Stratification

J Jaret Barr (Emory University, Atlanta, Georgia) G Gabrielle Gershon (Emory University, Atlanta, Georgia, United States) E Eshan Momin (Emory University, Atlanta, Georgia, United States) S Saikiran Rapaka A Athira Jacob (Siemens, Newark, Connecticut, United States) A Austin Rim (Emory University, Atlanta, Georgia, United States) C Carlo De Cecco (Emory University, Atlanta, Georgia, United States) M Marly van Assen

Abstract

Background: While non-contrast CT scans are routinely used to assess the risk of major adverse cardiac events by quantifying coronary artery calcium (CAC), there is growing interest in leveraging cardiac chamber volumetry derived from these scans to improve the prediction of heart failure (HF). However, it is unknown whether cardiac chamber volumes from varying phases of the cardiac cycle differ in ability to predict HF risk. Research Question: Does the phase of cardiac cycle during CT acquisition affect the predictive value of chamber volumes for heart failure risk? Methods: This is a retrospective cohort of 5,325 asymptomatic patients aged 45-75 years, without known cardiac disease, who underwent CT imaging for CAC scoring between 2010-2023. CT images were analyzed using a previously validated convolutional neural network-based autoencoder model to derive chamber volumes. Patients were divided into groups based on cardiac phase during CT acquisition (diastolic or systolic). Cox proportional hazard regression was used to assess the association between chamber volumes and heart failure. Hazard ratios (HR) were adjusted for clinical risk factors. Results: Patients were imaged during diastole (n=3,172, 58±9 years old, 44% women, 81% White) and during systole (n=2,153, 58±10 years old, 46% women, 84% White). Over a mean follow-up period of 4.7±2.6 years, 7.2% (n=384) developed HF within 10 years. There were 215 HF diagnoses in the diastolic group (6.8%) and 169 in the systolic group (7.8%). The strongest predictors of HF were left atrium (LA) and myocardial volumes. Optimal cutoffs for risk stratification were higher for diastolic chamber volumes (LA: >90.4 mL vs >82.1 mL; myocardium: >136.4 mL vs >102.2 mL). Greater LA and myocardial diastolic chamber volumes were independently associated with higher risk of HF than systolic volumes (LA: HR 1.379 [95% CI, 1.233-1.542] vs HR 1.223 [95% CI, 1.084-1.380], P<0.0001; myocardium: HR 1.513 [95% CI, 1.329-1.764] vs HR 1.426 [95% CI, 1.169-1.740], P<0.0001). Diastolic volumes had significant predictive improvement over systolic volumes (LA: AUC 0.712 [0.669-0.753) vs 0.703 [0.659-0.745]; myocardium: AUC 0.717 [0.674-0.757] vs 0.705 [0.662-0.745]). Conclusion: AI-derived diastolic chamber volumes from CAC CT scans outperformed systolic volumes in prediction of HF risk. These findings highlight the need for consideration of cardiac cycle phase during CT acquisition in the use of chamber volumetry for HF risk stratification.

Article Details

Journal Circulation
Volume / Issue Vol. 152, Issue Suppl_3
Published November 04, 2025
ISSN 0009-7322
Publisher Lippincott Williams & Wilkins

Journal Info

Circulation

Lippincott Williams & Wilkins

ISSN: 0009-7322 Health Sciences

Authors (8)

J

Jaret Barr

Emory University, Atlanta, Georgia

G

Gabrielle Gershon

Emory University, Atlanta, Georgia, United States

E

Eshan Momin

Emory University, Atlanta, Georgia, United States

S

Saikiran Rapaka

A

Athira Jacob

Siemens, Newark, Connecticut, United States

A

Austin Rim

Emory University, Atlanta, Georgia, United States

C

Carlo De Cecco

Emory University, Atlanta, Georgia, United States

M

Marly van Assen