{
  "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.\n\nMethodsIn 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.\n\nResultsPercentile 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).\n\nConclusionAge- 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.\n\nGraphical Abstract\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=110 SRC=\"FIGDIR/small/26360111v1_ufig1.gif\" ALT=\"Figure 1\"> View larger version (38K): org.highwire.dtl.DTLVardef@1ef252aorg.highwire.dtl.DTLVardef@1711479org.highwire.dtl.DTLVardef@f73893org.highwire.dtl.DTLVardef@a3646c_HPS_FORMAT_FIGEXP M_FIG C_FIG",
  "abstract_shown": true,
  "affiliations": [
    "Cedars-Sinai Medical Center"
  ],
  "article_type": "PUBLISHAHEADOFPRINT",
  "arxiv": null,
  "author_total": 37,
  "authors": [
    {
      "name": "A. Kamagate"
    },
    {
      "name": "A. Shanbhag"
    },
    {
      "name": "M. Buchwald"
    },
    {
      "name": "R. J. H. Miller"
    },
    {
      "name": "S. Khanna"
    },
    {
      "name": "T. Zuhair Kassem"
    },
    {
      "name": "J. Kwiecinski"
    },
    {
      "name": "R. Bullock-Palmer"
    },
    {
      "name": "W. Zhang"
    },
    {
      "name": "A. M. Marcinkiewicz"
    },
    {
      "name": "J. Yi"
    },
    {
      "name": "G. Ramirez"
    },
    {
      "name": "M. Lemley"
    },
    {
      "name": "A. Killekar"
    },
    {
      "name": "P. B. Kavanagh"
    },
    {
      "name": "J. X. Liang"
    },
    {
      "name": "L. Slipczuk"
    },
    {
      "name": "M. I. Travin"
    },
    {
      "name": "E. Alexanderson"
    },
    {
      "name": "I. Carvajal-Juarez"
    },
    {
      "name": "R. R. Packard"
    },
    {
      "name": "M. Al-Mallah"
    },
    {
      "name": "T. D. Ruddy"
    },
    {
      "name": "R. A. deKemp"
    },
    {
      "name": "R. R. Buechel"
    },
    {
      "name": "A. J. Einstein"
    },
    {
      "name": "W. Acampa"
    },
    {
      "name": "S. Knight"
    },
    {
      "name": "V. T. Le"
    },
    {
      "name": "S. Mason"
    },
    {
      "name": "T. L. Rosamond"
    },
    {
      "name": "E. J. Miller"
    },
    {
      "name": "P. Chareonthaitawee"
    },
    {
      "name": "D. S. Berman"
    },
    {
      "name": "D. Dey"
    },
    {
      "name": "M. F. Di Carli"
    },
    {
      "affs": [
        0
      ],
      "name": "P. Slomka"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/a6sqcw18w272e.bib",
  "cited_by": 0,
  "doi": "10.64898/2026.08.28.26360111",
  "fulltext_url": "https://www.medrxiv.org/content/10.64898/2026.08.28.26360111v1.full",
  "id": "a6sqcw18w272e",
  "issns": [],
  "landing_url": "https://www.medrxiv.org/content/10.64898/2026.08.28.26360111v1",
  "language": null,
  "licence": "CC-BY-NC",
  "licence_label": "CC BY-NC",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by-nc/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "medrxiv",
      "cardiovascular medicine"
    ],
    [
      "openalex",
      "2705|Cardiovascular Disease and Adiposity"
    ]
  ],
  "openalex": "W7204944231",
  "pdf_url": "https://www.medrxiv.org/content/10.64898/2026.08.28.26360111v1.full.pdf",
  "pmcid": null,
  "pmid": null,
  "published": "2026-08-28",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/a6sqcw18w272e.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:17:27Z",
      "native_id": "10.64898/2026.08.28.26360111",
      "source": "medrxiv",
      "url": "https://www.medrxiv.org/content/10.64898/2026.08.28.26360111v1"
    }
  ],
  "subjects": [
    {
      "field": "medicine",
      "origin": "medrxiv:cardiovascular medicine",
      "subfield": "cardiovascular"
    }
  ],
  "title": "Clinical Reference Percentiles for AI-derived Epicardial Adipose Tissue: A Multicenter Study",
  "title_text": "Clinical Reference Percentiles for AI-derived Epicardial Adipose Tissue: A Multicenter Study",
  "type": "preprint",
  "updated_at": "2026-10-30T12:17:27Z",
  "url": "https://research.draconitic.com/paper/a6sqcw18w272e",
  "venue": "medRxiv",
  "versions": []
}