{
  "abstract": "Opportunistic CT screening for osteoporosis is moving toward clinical implementation, but progress is constrained by the absence of a standardized, machine learning compatible ground truth for vertebral fractures. Traditional semi-quantitative grading systems show only moderate inter-observer agreement, with ambiguity concentrated at mild deformities, introducing label noise that degrades AI triage performance. This invited review synthesizes the current evidence and proposes a hypothesis-generating framework; the Skeletal Failure paradigm is a proposal requiring prospective validation, not an established standard. Against this background, we outline the current landscape of AI-driven opportunistic CT tools and identify label inconsistency as a central barrier to reliable deployment. Drawing on this synthesis and the author’s clinical and research experience, we propose a binary, action-oriented classification—“Skeletal Failure”—defined by unequivocal endplate disruption or >20% vertebral height loss, providing a potentially reproducible structural endpoint. When combined with phantomless CT trabecular Hounsfield unit measurements, this framework is proposed as a candidate ML-ready substrate for automated triage and structured reporting. The Skeletal Failure paradigm is designed to support efficient human-in-the-loop triage, reduce radiologist cognitive load, and facilitate population-level fracture prevention. It may be particularly useful in resource-constrained settings, including the Middle East and North Africa, where DXA availability is limited and WHO T-score thresholds underperform in non-Caucasian populations. By converting incidental CT findings into consistent, machine-readable risk profiles, this approach aims to better align algorithmic detection with clinically actionable pathways, especially in older adults at risk of vertebral fragility and underdiagnosis.",
  "abstract_shown": true,
  "affiliations": [
    "Diagnostic and Interventional Radiology Department, Faculty of Medicine, Alexandria University"
  ],
  "article_type": null,
  "arxiv": null,
  "author_total": 1,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "Mohamed Ragab Nouh"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/9390gc6s6vzy3.bib",
  "cited_by": 0,
  "doi": "10.1186/s43055-026-01895-w",
  "fulltext_url": "https://doi.org/10.1186/s43055-026-01895-w",
  "id": "9390gc6s6vzy3",
  "issns": [
    "2090-4762",
    "0378-603X"
  ],
  "landing_url": "https://doi.org/10.1186/s43055-026-01895-w",
  "language": "en",
  "licence": "CC-BY",
  "licence_label": "CC BY",
  "licence_source": "journal",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "lcc",
      "R895-920"
    ],
    [
      "openalex",
      "2204|Medical Imaging and Analysis"
    ]
  ],
  "openalex": "W7223566956",
  "pdf_url": "https://link.springer.com/content/pdf/10.1186/s43055-026-01895-w.pdf",
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-25",
  "publisher": "SpringerOpen",
  "ris": "https://research.draconitic.com/paper/9390gc6s6vzy3.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T13:45:44Z",
      "native_id": "51465ab6d12a45f680eb52976711c7f4",
      "source": "doaj",
      "url": "https://doi.org/10.1186/s43055-026-01895-w"
    }
  ],
  "subjects": [
    {
      "field": "medicine",
      "origin": "journal-openalex:2741|MRI in cancer diagnosis",
      "subfield": "imaging"
    }
  ],
  "title": "AI-Driven opportunistic osteoporosis screening: the skeletal failure paradigm for trustworthy vertebral fracture triage",
  "title_text": "AI-Driven opportunistic osteoporosis screening: the skeletal failure paradigm for trustworthy vertebral fracture triage",
  "type": "peer-reviewed",
  "updated_at": "2026-10-30T13:45:44Z",
  "url": "https://research.draconitic.com/paper/9390gc6s6vzy3",
  "venue": "The Egyptian Journal of Radiology and Nuclear Medicine",
  "versions": []
}