Evidence map›Paper›PMID 42245027›Full record

ArticlemedRxiv : the preprint server for health sciences2026

Hierarchical organ aging signatures from routine abdominal CT add incremental disease risk stratification beyond blood biomarkers.

Zengtian Deng, Yufeng Wang, Yu Shi, Lixia Wang, Touseef Ahmad Qureshi, Srinivas Gaddam, Sehrish Javed, Yin-Chen Hsu, Dante Rigo De Righi, Linda Azab and 22 more

Abstract readPreprint
PubMed Full text at PMC Publisher
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

32 authors.

Zengtian DengBiomedical Imaging Research Institute, Cedars-Sinai Medical Center, LA, CA, 90048, USA.
Yufeng WangBiomedical Imaging Research Institute, Cedars-Sinai Medical Center, LA, CA, 90048, USA.
Yu ShiBiomedical Imaging Research Institute, Cedars-Sinai Medical Center, LA, CA, 90048, USA.
Lixia WangBiomedical Imaging Research Institute, Cedars-Sinai Medical Center, LA, CA, 90048, USA.
Touseef Ahmad QureshiBiomedical Imaging Research Institute, Cedars-Sinai Medical Center, LA, CA, 90048, USA.
Srinivas GaddamDepartment of Medicine, Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA.
Sehrish JavedBiomedical Imaging Research Institute, Cedars-Sinai Medical Center, LA, CA, 90048, USA.
Yin-Chen HsuBiomedical Imaging Research Institute, Cedars-Sinai Medical Center, LA, CA, 90048, USA.
Dante Rigo De RighiBiomedical Imaging Research Institute, Cedars-Sinai Medical Center, LA, CA, 90048, USA.
Linda AzabBiomedical Imaging Research Institute, Cedars-Sinai Medical Center, LA, CA, 90048, USA.
Garima DiwanBiomedical Imaging Research Institute, Cedars-Sinai Medical Center, LA, CA, 90048, USA.
Ju Dong YangKarsh Division of Gastroenterology and Hepatology, Cedars-Sinai Medical Center, 8900 Beverly Blvd, Los Angeles, CA 90048, USA.
Yibin XieBiomedical Imaging Research Institute, Cedars-Sinai Medical Center, LA, CA, 90048, USA.
Chen YuanDepartment of Computational Biomedicine, Cedars-Sinai Medical Center, Los Angeles, CA, USA.
Camila Lopes VendramiDepartment of Radiology, Northwestern Memorial Hospital, Northwestern University Feinberg School of Medicine, IL 60611, USA.
Alex RodriguezDivision of Gastrointestinal and Liver Diseases, University of Southern California Keck School of Medicine, Los Angeles, CA 90033, USA.
Katherine SpechtDivision of Gastroenterology, Massachusetts General Hospital, Boston, MA 02114, USA.
Christie Y JeonBiomedical Science Department, Cedars-Sinai Medical Center, Los Angeles, CA, 90048, USA.
Humaira ChaudhryDepartment of Radiology, Rutgers New Jersey Medical School, NJ 07103, USA.
James BuxbaumDivision of Gastrointestinal and Liver Diseases, University of Southern California Keck School of Medicine, Los Angeles, CA 90033, USA.
Joseph R PisegnaDivision of Gastroenterology, Hepatology and Parenteral Nutrition, VA Greater Los Angeles Healthcare System, CA 90073, USA.
Vahid YaghmaiRadiological Sciences, University of California, Irvine CA 92868, USA.
Wolfram GoesslingRadiological Sciences, University of California, Irvine CA 92868, USA.
Yasmin G Hernandez-BarcoDivision of Gastroenterology, Massachusetts General Hospital, Boston, MA 02114, USA.
Frank H MillerDepartment of Radiology, Northwestern Memorial Hospital, Northwestern University Feinberg School of Medicine, IL 60611, USA.
Temel TirkesDepartment of Radiology and Imaging Sciences, Indiana University School of Medicine, IN 46202, USA.
Sara EspinozaCenter for Translational Geroscience, Department of Medicine, Cedars-Sinai Health Sciences Center, 8700 Beverly Boulevard, Los Angeles, CA 90048, USA.
Nicolas MusiCenter for Translational Geroscience, Department of Medicine, Cedars-Sinai Health Sciences Center, 8700 Beverly Boulevard, Los Angeles, CA 90048, USA.
Damini DeyBiomedical Imaging Research Institute, Cedars-Sinai Medical Center, LA, CA, 90048, USA.
Kyung Hyun SungDepartment of Bioengineering, University of California, Los Angeles, CA, 90048, USA.
Stephen J PandolDivision of Digestive and Liver Diseases, Cedars-Sinai Medical Center, Los Angeles, CA, 90048, USA.
Debiao LiBiomedical Imaging Research Institute, Cedars-Sinai Medical Center, LA, CA, 90048, USA.

Funding

Predicting Pancreatic Ductal Adenocarcinoma PDAC Through Artificial Intelligence Analysis of Pre Diagnostic CT Images in African AmericansR01CA260955 · NCI · CEDARS-SINAI MEDICAL CENTER · PI LI, DEBIAO, PANDOL, STEPHEN J. · 2021 to 2025
$4.8M
NCI NIH HHS R01 CA260955
6 · The paper itself

Abstract

Biological aging is heterogeneous across organ systems, yet whether CT-derived abdominal aging provides prognostic value beyond routine clinical data - and whether organ decomposition adds beyond a unified estimate - remains untested. We developed and evaluated organ-specific and ensemble biological age models from radiomic features across five abdominal organs in 68,682 CT scans from 32,882 subjects, evaluated on alignment with chronological age of healthy subjects (nested cross validation: MAE=3.68 years, R

Indexed as

abdominal CTbiological agedisease predictionradiomicssurvival analysis

Identifiers

PMID42245027
PMCPMC13232388

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.