Just as radiography has been used in forensic medicine since shortly after the discovery of x-rays in 1895, CT was introduced to postmortem investigation not long after its introduction to medicine in the 1970s. In recent decades, forensic radiology has declared itself as a new subspecialty capable of revolutionizing death investigation and research. A variety of postmortem imaging techniques have emerged. Postmortem CT (PMCT) is widely accepted around the world as a supplementary tool and, in specific cases and settings, an alternative to full autopsy. As its popularity grows, however, it is important for radiologists and pathologists to expand their understanding of the applications, benefits, and limitations of these techniques, as well as the unique nuances of postmortem imaging interpretation. This will ensure high-quality interpretations and avoid potential pitfalls that could result in premature or erroneous conclusions. The authors introduce the reader, particularly the radiologist, to the growing subspecialty of forensic imaging (focusing on imaging of the deceased), specifically focusing on PMCT and its applications in death investigation in both clinical and forensic settings. The authors also discuss the benefits and limitations of PMCT as well as important nuances of PMCT interpretation, emphasizing the similarities and differences between clinical and postmortem studies, the necessity of conducting thorough death investigations, and the importance of pursuing specialized education or training in postmortem imaging interpretation. Applications of more specialized imaging techniques to postmortem and forensic investigations are described, including developing research in this area.
(Publisher abstract provided.)
Downloads
Similar Publications
- A Turning Point in Mass Incarceration? Local Imprisonment Trajectories and Decarceration under California's Realignment
- Emergency department-based testing for xylazine and other novel psychoactive substances in Central Alabama: a feasibility study
- Using Geographically Weighted Regression to Explore Local Crime Patterns