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Peri-aortic fat to assess cardiovascular aging using an AI-driven radiomic biomarker.

Journal articles  - Journal Article
Lebowitz, M; Modanwal, G; Singh, A; Dhamdhere, R; Diwan, S; Suleiman, TA; Al-Shakhshir, H; Gilkey, M; Shofer, S; Sirasapalli, SK; Shoemaker, MB ...
Published in: Eur Heart J
July 9, 2026

BACKGROUND AND AIMS: Chronological age is central to cardiovascular disease (CVD) risk estimation but poorly reflects interindividual heterogeneity in cardiovascular aging. This study developed a peri-aortic adipose tissue (PAAT) radiomic cardiovascular age (CV-Age) biomarker from routine chest CT and tested whether the PAAT age gap (ΔAge = CV-Age - chronological age) stratifies major adverse cardiovascular events (MACE) and improves risk classification. METHODS: Four chest CT cohorts with different protocols were utilized to train (n = 4451) and externally validate (n = 44 214) a CV-Age model. Associations between ΔAge decile groups (resilient ≤10th; accelerated ≥90th) and incident 5-point MACE (myocardial infarction, stroke, revascularization, heart failure, and death) were assessed using survival models. Clinical utility was evaluated by substituting CV-Age for chronological age in PREVENT to quantify risk reclassification. RESULTS: A 31-feature radiomic signature capturing PAAT volume, attenuation, and texture heterogeneity predicted age with good accuracy (training MAE 2.2 years; primary external validation MAE 2.7 years). In a separate higher-risk cohort, predictions showed a positive ΔAge (median +5.4 years), reflecting elevated baseline cardiovascular burden. ΔAge-stratified event-free survival differed across groups (log-rank P < .001); compared with normative agers, accelerated agers had higher MACE risk (HR 1.51, 95% CI 1.37-1.66), and resilient agers had lower risk (HR 0.70, 0.63-0.77). Substituting CV-Age into PREVENT improved risk reclassification (categorical NRI +0.03, P < .01, continuous NRI +0.04, P < .05). CONCLUSIONS: Radiomic profiling of PAAT on routine chest CT yields a scalable imaging biomarker of cardiovascular aging. CV-Age can help improve identification of higher-risk individuals missed by age-driven risk estimation, supporting its role as a risk-enrichment tool.

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Published In

Eur Heart J

DOI

EISSN

1522-9645

Publication Date

July 9, 2026

Location

England

Related Subject Headings

  • Cardiovascular System & Hematology
  • 3202 Clinical sciences
  • 3201 Cardiovascular medicine and haematology
 

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Lebowitz, M., Modanwal, G., Singh, A., Dhamdhere, R., Diwan, S., Suleiman, T. A., … Madabhushi, A. (2026). Peri-aortic fat to assess cardiovascular aging using an AI-driven radiomic biomarker. Eur Heart J. https://doi.org/10.1093/eurheartj/ehag498
Lebowitz, Mendel, Gourav Modanwal, Amritpal Singh, Rohan Dhamdhere, Saumya Diwan, Taofik Ahmed Suleiman, Hilmi Al-Shakhshir, et al. “Peri-aortic fat to assess cardiovascular aging using an AI-driven radiomic biomarker.” Eur Heart J, July 9, 2026. https://doi.org/10.1093/eurheartj/ehag498.
Lebowitz M, Modanwal G, Singh A, Dhamdhere R, Diwan S, Suleiman TA, et al. Peri-aortic fat to assess cardiovascular aging using an AI-driven radiomic biomarker. Eur Heart J. 2026 Jul 9;
Lebowitz, Mendel, et al. “Peri-aortic fat to assess cardiovascular aging using an AI-driven radiomic biomarker.” Eur Heart J, July 2026. Pubmed, doi:10.1093/eurheartj/ehag498.
Lebowitz M, Modanwal G, Singh A, Dhamdhere R, Diwan S, Suleiman TA, Al-Shakhshir H, Gilkey M, Shofer S, Sirasapalli SK, Shoemaker MB, Al-Kindi S, Rajagopalan S, Madabhushi A. Peri-aortic fat to assess cardiovascular aging using an AI-driven radiomic biomarker. Eur Heart J. 2026 Jul 9;
Journal cover image

Published In

Eur Heart J

DOI

EISSN

1522-9645

Publication Date

July 9, 2026

Location

England

Related Subject Headings

  • Cardiovascular System & Hematology
  • 3202 Clinical sciences
  • 3201 Cardiovascular medicine and haematology