ArticleTomography (Ann Arbor, Mich.)2026
Integrated Radiology-Biochemistry Diagnostic Flow Framework for Emergency Clinical Decision Support: A Simulation-Based Educational Model.
Article in Tomography (Ann Arbor, Mich.), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundEmergency radiology often demands rapid integration of clinical cues, biochemical markers, and imaging findings to support time-critical diagnostic reasoning. However, educational resources that explicitly structure this interdisciplinary integration particularly between radiology and laboratory medicine remain limited.
objectiveOur objective was to develop an Integrated Radiology-Biochemistry Diagnostic Flow Framework as a simulation-based methodological proof-of-concept and to document its structure, logic pathways, and internal consistency across common emergency presentations.
methodsWe designed an algorithmic framework combining (i) clinical triggers, (ii) targeted biochemical markers with predefined threshold and trajectory rules, (iii) imaging indication and modality selection (US/CTA/MRI/NCCT), and (iv) key radiologic patterns linked to escalation pathways. No patient data or human participants were included. Instead, forty fully synthetic emergency scenarios were generated to populate the framework and to examine logical completeness, branching coherence, and red-flag escalation routes.
resultsThe framework yielded scenario-specific diagnostic flowcharts that systematically connect biochemical escalation cues with imaging selection and expected imaging findings. The synthetic scenario library demonstrated consistent branching logic across conditions and enabled transparent visualization of imaging-centered decision pathways suitable for simulation-based teaching and structured case discussion.
conclusionsThis study reports a reproducible methodological proof-of-concept framework and a synthetic emergency scenario library. Further learner-based studies are required to evaluate usability, perceived realism, and educational effectiveness in authentic training settings.
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