Abstract 4363429: Periaortic Fat Inflammation on Preprocedural CT Predicts Long-Term Mortality in Patients Undergoing Transcatheter Aortic Valve Replacement

J Jan Brendel (Massachusetts General Hospital, Boston, Massachusetts, United States) I Ibrahim Hadzic (Massachusetts General Hospital, Boston, Massachusetts, United States) T Thomas Mayrhofer L Lauren Cooke (Massachusetts General Hospital, Boston, Massachusetts, United States) I Isabel Langenbach (Massachusetts General Hospital, Boston, Massachusetts, United States) M Marcel Langenbach (Massachusetts General Hospital, Boston, Massachusetts, United States) N Nora Kerkovits (Massachusetts General Hospital, Boston, Massachusetts, United States) V Vencel Juhasz (Massachusetts General Hospital, Boston, Massachusetts, United States) M Matthias Jung (Medical Center - University of Freiburg, Freiburg, Germany) E Evin Yucel (Massachusetts General Hospital, Boston, Massachusetts, United States) V Vineet Raghu (Massachusetts General Hospital, Boston, Massachusetts, United States) M Michael Lu (Massachusetts General Hospital, Wellesley, Massachusetts, United States) H Hugo Aerts P Pamela Douglas (DUKE UNIVERSITY DUMC, Durham, North Carolina, United States) B Borek Foldyna

Abstract

Background: Chronic inflammation is a key driver of cardiovascular disease progression and may impact transcatheter aortic valve replacement (TAVR) outcomes. Higher periaortic adipose tissue (PAAT) attenuation reflects aortic wall inflammation and can be measured on routine preprocedural CT. Yet, its prognostic value in TAVR patients remains unclear. Aim: To explore whether PAAT attenuation predicts long-term mortality in TAVR patients beyond traditional risk factors. Methods: We retrospectively analyzed preprocedural CT scans from consecutive TAVR patients treated at a single tertiary center between 2013 and 2023. The aorta was automatically segmented using a deep learning-based segmentation tool (TotalSegmentator) from the sinotubular junction to the distal infrarenal segment. PAAT attenuation was defined as the mean attenuation (Hounsfield units, HU) of all voxels within a 10mm radial cylinder around the aortic wall and an attenuation range of -190 to -30 HU. PAAT attenuation was associated with 5-year all-cause mortality using Cox regression models, adjusting for technical parameters (tube voltage, signal-to-noise ratio, BSA-indexed PAAT volume) and clinical covariates (age, sex, BMI, and Society of Thoracic Surgeons [STS] risk score). Incremental predictive value of PAAT attenuation was evaluated using Harrell’s C-statistic, and a high-attenuation threshold was derived by Euclidean distance within a receiver operating characteristic framework. Results: The study included 1,003 patients (51.5 % male, mean age 80±8y, BMI 28.6±6.0 kg/m 2 , median STS score 4.3 [2.5–7.0]%), followed for a median 22 (14–37) months; 5-year mortality rate was 23.6% (n=237). Mean PAAT attenuation was -77.3±7.3 HU. Non-survivors had higher mean PAAT attenuation than survivors (-75.9 vs -77.8 HU, P<0.001), Figure 1 . Those with high PAAT attenuation (>-77 HU) were slightly older, and more often female (both P≤0.05). PAAT attenuation independently predicted mortality (aHR [per 10 HU] 1.71, 95%-CI: 1.29–2.26; P<0.001) after adjustment. Adding PAAT attenuation to the clinical model (age, sex, BMI, STS score) improved discrimination for 5-year death (Harrell’s C from 0.69 to 0.70; P<0.001). Conclusions: High periaortic fat attenuation on preprocedural CT independently predicts long-term mortality in patients undergoing TAVR. Quantifying PAAT inflammation may offer additional prognostic value beyond established clinical risk factors and refine preprocedural 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 (15)

J

Jan Brendel

Massachusetts General Hospital, Boston, Massachusetts, United States

I

Ibrahim Hadzic

Massachusetts General Hospital, Boston, Massachusetts, United States

T

Thomas Mayrhofer

L

Lauren Cooke

Massachusetts General Hospital, Boston, Massachusetts, United States

I

Isabel Langenbach

Massachusetts General Hospital, Boston, Massachusetts, United States

M

Marcel Langenbach

Massachusetts General Hospital, Boston, Massachusetts, United States

N

Nora Kerkovits

Massachusetts General Hospital, Boston, Massachusetts, United States

V

Vencel Juhasz

Massachusetts General Hospital, Boston, Massachusetts, United States

M

Matthias Jung

Medical Center - University of Freiburg, Freiburg, Germany

E

Evin Yucel

Massachusetts General Hospital, Boston, Massachusetts, United States

V

Vineet Raghu

Massachusetts General Hospital, Boston, Massachusetts, United States

M

Michael Lu

Massachusetts General Hospital, Wellesley, Massachusetts, United States

H

Hugo Aerts

P

Pamela Douglas

DUKE UNIVERSITY DUMC, Durham, North Carolina, United States

B

Borek Foldyna