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February 9, 2026Emergency Radiology0 citationsOpen Access

Computed tomography derived analytic morphomics as predictors of clinical outcomes in trauma: a systematic narrative review

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LKLudolf G A De KockRLRonan J. LeeDADavid O Adebayo

Key Points

  • This review aims to evaluate the effectiveness of analytic morphomics as predictors of clinical outcomes in trauma patients.
  • Conducted a systematic narrative review following PRISMA guidelines.
  • Search utilized databases including PubMed, Embase, and Scopus.
  • Assessed studies examining the relationship between CT-based AM parameters and clinical outcomes.
  • Analytic morphomics metrics like lumbar muscle quality, adiposity, and bone mineral density were linked to adverse outcomes.
  • Findings included associations with mortality, length of hospital stay, complications, and functional recovery.

Abstract

Abstract Medical imaging plays a central role in the management of trauma patients. Analytic morphomics (AM) through enabling measurement of specific biological markers of body composition from medical images is emerging as a potential tool to predict patient outcomes across multiple medical and surgical disciplines. We sought to provide a comprehensive review of the utility of AM in predicting outcomes in trauma patients. A systematic review with a narrative synthesis was conducted following the Preferred Reporting Items for Systematic Review and Meta-analyses (PRISMA) guidelines and checklists. PubMed, Embase, Scopus, The Cochrane Library as well as Web of Science and Trip database were searched for studies that assessed the relationship between computed tomography-based AM parameters and clinical outcomes in patients from a trauma cohort. Multiple AM domains, including lumbar muscle quantity and quality, adiposity, craniofacial measurements, and opportunistic bone mineral density (BMD), were consistently associated with adverse outcomes including mortality, length of stay, complications, and functional recovery. CT-derived AM metrics provide valuable prognostic information in trauma populations, extending beyond conventional measures such as chronological age and injury severity scores. Registration : PROSPERO Registration ID: CRD420251112652 Graphical abstract

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Cite This Study

Kock et al. (2026) studied this question.

synapsesocial.com/papers/698979e9f0ec2af6756e7f34https://doi.org/10.1007/s10140-026-02441-x
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