Clinical Reference Percentiles for AI-derived Epicardial Adipose Tissue: A Multicenter Study
- 1Cedars-Sinai Medical Center
Abstract
Background and AimsEpicardial adipose tissue (EAT) has emerged as an important cardiovascular biomarker that reflects both inflammatory and cardiometabolic risk. EAT volume and density vary significantly across populations, yet there is a lack of multicenter studies investigating the predictive value of population-specific EAT percentiles.
MethodsIn this multicenter study, we retrospectively analyzed low-dose computed tomography correction scans from 42,842 patients undergoing myocardial perfusion imaging. A derivation cohort of 15,082 patients was used to establish sex- and age-specific nomograms for EAT density and EAT volume indexed to body surface area. Percentile-based thresholds were tested for outcome prediction in a validation cohort of 27,760 patients. For clinical implementation, we developed an online EAT percentile calculator.
ResultsPercentile curves demonstrated increased BSA-indexed EAT volume and decreasing EAT density with age. Over a median follow-up of 3.6 years (IQR: 1.83 - 5.14), 4,956 patients experienced a nonfatal myocardial infarction or death. In multivariable Cox models, patients above the 95th sex- and age-specific percentile had significantly worse outcomes for BSA-indexed EAT volume [adjusted hazard ratio 1.30, 95% CI: 1.14 - 1.49, p < 0.001] and EAT density [adjusted hazard ratio 1.7, 95% CI: 1.51 - 1.92, p<0.001] when compared to patients below the 50th percentile (p<0.001).
ConclusionAge- and sex-specific EAT percentiles provide a clinically interpretable framework for contextualizing automated EAT measurements and identifying patients at increased cardiovascular risk. EAT density was a stronger prognostic marker and identified elevated risk even among patients with normal BMI, supporting its potential to provide information beyond conventional anthropometric assessment.
Graphical Abstract
O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=110 SRC="FIGDIR/small/26360111v1_ufig1.gif" ALT="Figure 1"> View larger version (38K): [email protected]@1711479org.highwire.dtl.DTLVardef@f73893org.highwire.dtl.DTLVardef@a3646c_HPS_FORMAT_FIGEXP M_FIG C_FIG
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BibTeX
@misc{kamagate2026clinical,
title = {{Clinical Reference Percentiles for AI-derived Epicardial Adipose Tissue: A Multicenter Study}},
author = {A. Kamagate and A. Shanbhag and M. Buchwald and R. J. H. Miller and S. Khanna and T. Zuhair Kassem and J. Kwiecinski and R. Bullock-Palmer and W. Zhang and A. M. Marcinkiewicz and J. Yi and G. Ramirez and M. Lemley and A. Killekar and P. B. Kavanagh and J. X. Liang and L. Slipczuk and M. I. Travin and E. Alexanderson and I. Carvajal-Juarez and R. R. Packard and M. Al-Mallah and T. D. Ruddy and R. A. deKemp and R. R. Buechel and A. J. Einstein and W. Acampa and S. Knight and V. T. Le and S. Mason and T. L. Rosamond and E. J. Miller and P. Chareonthaitawee and D. S. Berman and D. Dey and M. F. Di Carli and P. Slomka},
howpublished = {medRxiv},
year = {2026},
month = aug,
doi = {10.64898/2026.08.28.26360111},
url = {https://www.medrxiv.org/content/10.64898/2026.08.28.26360111v1},
note = {CC BY-NC},
}
RIS
TY - UNPB
TI - Clinical Reference Percentiles for AI-derived Epicardial Adipose Tissue: A Multicenter Study
AU - A. Kamagate
AU - A. Shanbhag
AU - M. Buchwald
AU - R. J. H. Miller
AU - S. Khanna
AU - T. Zuhair Kassem
AU - J. Kwiecinski
AU - R. Bullock-Palmer
AU - W. Zhang
AU - A. M. Marcinkiewicz
AU - J. Yi
AU - G. Ramirez
AU - M. Lemley
AU - A. Killekar
AU - P. B. Kavanagh
AU - J. X. Liang
AU - L. Slipczuk
AU - M. I. Travin
AU - E. Alexanderson
AU - I. Carvajal-Juarez
AU - R. R. Packard
AU - M. Al-Mallah
AU - T. D. Ruddy
AU - R. A. deKemp
AU - R. R. Buechel
AU - A. J. Einstein
AU - W. Acampa
AU - S. Knight
AU - V. T. Le
AU - S. Mason
AU - T. L. Rosamond
AU - E. J. Miller
AU - P. Chareonthaitawee
AU - D. S. Berman
AU - D. Dey
AU - M. F. Di Carli
AU - P. Slomka
PY - 2026
DA - 2026/08/28
PB - medRxiv
DO - 10.64898/2026.08.28.26360111
UR - https://www.medrxiv.org/content/10.64898/2026.08.28.26360111v1
AB - Background and AimsEpicardial adipose tissue (EAT) has emerged as an important cardiovascular biomarker that reflects both inflammatory and cardiometabolic risk. EAT volume and density vary significantly across populations, yet there is a lack of multicenter studies investigating the predictive value of population-specific EAT percentiles. MethodsIn this multicenter study, we retrospectively analyzed low-dose computed tomography correction scans from 42,842 patients undergoing myocardial perfusion imaging. A derivation cohort of 15,082 patients was used to establish sex- and age-specific nomograms for EAT density and EAT volume indexed to body surface area. Percentile-based thresholds were tested for outcome prediction in a validation cohort of 27,760 patients. For clinical implementation, we developed an online EAT percentile calculator. ResultsPercentile curves demonstrated increased BSA-indexed EAT volume and decreasing EAT density with age. Over a median follow-up of 3.6 years (IQR: 1.83 - 5.14), 4,956 patients experienced a nonfatal myocardial infarction or death. In multivariable Cox models, patients above the 95th sex- and age-specific percentile had significantly worse outcomes for BSA-indexed EAT volume [adjusted hazard ratio 1.30, 95% CI: 1.14 - 1.49, p < 0.001] and EAT density [adjusted hazard ratio 1.7, 95% CI: 1.51 - 1.92, p<0.001] when compared to patients below the 50th percentile (p<0.001). ConclusionAge- and sex-specific EAT percentiles provide a clinically interpretable framework for contextualizing automated EAT measurements and identifying patients at increased cardiovascular risk. EAT density was a stronger prognostic marker and identified elevated risk even among patients with normal BMI, supporting its potential to provide information beyond conventional anthropometric assessment. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=110 SRC="FIGDIR/small/26360111v1_ufig1.gif" ALT="Figure 1"> View larger version (38K): [email protected]@1711479org.highwire.dtl.DTLVardef@f73893org.highwire.dtl.DTLVardef@a3646c_HPS_FORMAT_FIGEXP M_FIG C_FIG
ER -