Evidence map›Paper›PMID 40668630›Full record

ReviewAJR. American journal of roentgenology2026

Opportunistic Screening on Chest CT, From the

Konstantin L Thuere, Lea Mantz, Sadia Sultana, Louise M Henderson, Lori C Sakoda, Ella Kazerooni, Raúl San José Estépar, Mary L Bouxsein, Florian J Fintelmann

Abstract readReview
In one paragraph

Review in AJR. American journal of roentgenology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Observational
  2. Article
  3. Article
  4. Article
  5. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

9 authors.

Konstantin L ThuereDepartment of Radiology, Division of Thoracic Imaging and Intervention, Massachusetts General Hospital, 55 Fruit St, Boston, MA 02114.
Lea MantzDepartment of Radiology, Division of Thoracic Imaging and Intervention, Massachusetts General Hospital, 55 Fruit St, Boston, MA 02114.
Sadia SultanaDepartment of Radiology, Division of Cardiovascular Imaging, Massachusetts General Hospital, Boston, MA.
Louise M HendersonDepartment of Radiology, University of North Carolina, Chapel Hill, NC.
Lori C SakodaDivision of Research, Kaiser Permanente Northern California, Pleasanton, CA.
Ella KazerooniDepartments of Radiology and Internal Medicine, Michigan Medicine/University of Michigan Medical School, Ann Arbor, MI.
Raúl San José EstéparApplied Chest Imaging Laboratory at Brigham and Women's Hospital, Harvard Medical School, Boston, MA.
Mary L BouxseinThe Center for Advanced Orthopedic Studies, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA.
Florian J FintelmannDepartment of Radiology, Division of Thoracic Imaging and Intervention, Massachusetts General Hospital, 55 Fruit St, Boston, MA 02114.

Funding

OPTimizing surveillance in lung cancer survivors with novel IMAging biomarkers and deep-Learning (OPTIMAL)R01CA298002 · NCI · UNIV OF NORTH CAROLINA CHAPEL HILL · PI Florian J. Fintelmann, Louise Henderson · 2025 to 2026
$1.9M
NCI NIH HHS R01 CA298002
6 · The paper itself

Abstract

The increase in chest CT volumes affords radiologists the opportunity to systematically assess imaging biomarkers, including coronary and thoracic arterial calcification, emphysema, airway dysanapsis, adipose tissue in various compartments, skeletal muscle (in terms of both quantity and quality), and vertebral body bone attenuation (as a measure of bone mineral density), extending from the T1 through T12 vertebral body levels. These biomarkers represent a spectrum of disease-induced changes or increases in the risk of developing disease. This Special Series Review provides an overview of these established and emerging imaging biomarkers on chest CT scans, aiming to serve as a reference for practicing radiologists. We discuss the importance of imaging biomarkers for patient care; highlight recent developments; present approaches for interpretation and integration into clinical workflows, with attention given to the role of reference values; consider challenges in serial assessment resulting from variations in technical parameters; describe the incorporation of the biomarkers into societal guidelines; and summarize FDA-approved artificial intelligence tools to aid evaluation.

Indexed as

Lung DiseasesMass ScreeningRadiography, ThoracicTomography, X-Ray ComputedBiomarkersHumansBiomarkersartificial intelligencebody compositionclinical workflowCTimaging biomarkers

Identifiers

PMID40668630
PMCPMC12288959

What OpenQuestion holds

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Registered trials

None linked

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.