CONTACT US: Contact info
|
Citation |
Jian J, Wan L, Shao Y, Zou D, Huang P, Wang Z, Liu N, Chen Y. Forensic Sci. Res. 2021; 6(2): 152-158. |
|
Copyright |
(Copyright © 2021, Informa - Taylor and Francis Group) |
|
DOI |
|
PMID |
34377573 |
|
Abstract |
It may be difficult to distinguish the cause of death in drowning cases without specific findings. The aim of this study was to explore the forensic value of thoracic postmortem computed tomography (PMCT) using routine images and three-dimensional (3D) image reconstructions. The imaging data of PMCT examinations of six drowning cadavers, aged 21-54 years, were analyzed. Twelve victims of sudden death from coronary artery disease (CAD) were chosen as a control group. After 3D bilateral lung images were reconstructed using image processing software, an interactive medical image control system was used to measure and analyze parameters including lung volume, lung volume ratio, mean CT value of the whole lung, and lung CT value distribution curves. Lung volume and lung volume ratio were used to assess the shape changes of the lung. Lung CT value distribution curves showed the corresponding number of pixels of the different CT values in the lung image. Lung volume was not significantly larger in drowning cases (mean 2 958 cm(3)) than in controls (mean 2 342 cm(3)). Lung volume ratio values in the drowning group (mean 0.3156) were greater than those in the control group (mean 0.2763); (P = 0.02). There was no significant difference between the drowning and control group in the mean CT value of the whole lung. There were differences between lung CT value distribution curves in drowning victims and controls, with drowning victims showing a single peak and CAD cases showing a bimodal distribution. Thoracic PMCT is helpful for the forensic medical diagnosis of drowning. Lung volume ratio and lung CT value distribution are potential indicators to distinguish between drowning and CAD. Language: en |
|
Keywords |
drowning; CT data; Forensic sciences; forensic pathology; postmortem CT; lung 3D reconstruction |