Global Advances in Postmortem Imaging and Virtual Autopsy for Disaster Victim Identification: Technical Innovations, Operational Models, and Future Applications with Focus on Saudi Arabia

Abstract Disaster victim identification (DVI) is a critical medicolegal process following mass fatality incidents, yet it is frequently challenged by severe body fragmentation, burning, and decomposition that limit the effectiveness of conventional identification methods. In recent years, postmortem imaging and virtual autopsy have emerged as transformative tools, shifting DVI practice toward noninvasive, digital, and workflow-driven approaches. This narrative review examines global advances in postmortem imaging modalities – including postmortem computed tomography (PMCT), postmortem magnetic resonance imaging (PMMRI), digital radiography, and three-dimensional (3D) surface scanning – and evaluates their technical and operational roles within contemporary DVI frameworks. By synthesizing international disaster case studies and current forensic guidelines, the review demonstrates how imaging has evolved from a supplementary technique to a core component of DVI operations. Integrated imaging enables rapid triage, improves examiner safety, provides standardized and auditable documentation, and accelerates reconciliation through early identification of dental, skeletal, and medical markers. Particular emphasis is placed on structured workflow integration, including standardized imaging protocols, interoperable forensic PACS systems, and harmonized radiology reporting, which collectively enhance scalability and interagency collaboration during mass fatality events. The review further contextualizes these developments within Saudi Arabia and the broader Middle East, where cultural and religious considerations often limit invasive autopsy practices. Virtual autopsy is highlighted as a culturally acceptable and strategically valuable solution for strengthening regional DVI preparedness. Emerging innovations, such as photon-counting CT and artificial intelligence-assisted image analysis, are discussed as future enablers of faster, more accurate, and resilient DVI systems.