OBJECTIVES: To use virtual anatomy technique in the analysis of post-mortem characteristic changes of CT images in the experimental drowning rabbit model and the related parameters in 3D virtual model, so as to explore its application value in the diagnosis of drowning in forensic pathology. METHODS: A model of drowning rabbits was established, with animal models of hemorrhagic shock and mechanical asphyxia as the controls. CT scan was performed on the experimental animals, and the differences in imaging features between the groups were compared by morphological reading of the tomographic images. CT data were imported into Mimics 14.0 software for 3D modeling. The CT values and lung volumes were calculated by the software, and the differences on CT values and lung volumes brought by different causes of death were analyzed. RESULTS: The CT images of lungs in the drowning group showed characteristic ground-glass opacity （diffuse and uniform density increase）. There were no obvious abnormalities in hemorrhagic shock group, and only a few similar changes were found in the mechanical asphyxia group. Compared with the controls, the CT values and the lung volumes in the drowning group were significantly increased P<0.05. CONCLUSIONS Based on post-mortem lung imaging, the combination of CT value and lung volume changes can effectively reflect the virtual anatomical features in drowning, and provide a diagnostic basis for the forensic identification of drowning.
Animals ; Drowning ; Lung/diagnostic imaging* ; Rabbits ; Tomography, X-Ray Computed

OBJECTIVES: To construct a YOLOv3-based model for diatom identification in scanning electron microscope images, explore the application performance in practical cases and discuss the advantages of this model. METHODS: A total of 25 000 scanning electron microscopy images were collected at 1 500× as an initial image set, and input into the YOLOv3 network to train the identification model after experts' annotation and image processing. Diatom scanning electron microscopy images of lung, liver and kidney tissues taken from 8 drowning cases were identified by this model under the threshold of 0.4, 0.6 and 0.8 respectively, and were also identified by experts manually. The application performance of this model was evaluated through the recognition speed, recall rate and precision rate. RESULTS: The mean average precision of the model in the validation set and test set was 94.8% and 94.3%, respectively, and the average recall rate was 81.2% and 81.5%, respectively. The recognition speed of the model is more than 9 times faster than that of manual recognition. Under the threshold of 0.4, the mean recall rate and precision rate of diatoms in lung tissues were 89.6% and 87.8%, respectively. The overall recall rate in liver and kidney tissues was 100% and the precision rate was less than 5%. As the threshold increased, the recall rate in all tissues decreased and the precision rate increased. The F1 score of the model in lung tissues decreased with the increase of threshold, while the F1 score in liver and kidney tissues with the increase of threshold. CONCLUSIONS The YOLOv3-based diatom electron microscope images automatic identification model works at a rapid speed and shows high recall rates in all tissues and high precision rates in lung tissues under an appropriate threshold. The identification model greatly reduces the workload of manual recognition, and has a good application prospect.
Diatoms ; Drowning/diagnosis* ; Humans ; Liver/diagnostic imaging* ; Lung/diagnostic imaging* ; Microscopy, Electron, Scanning

Objective To study the imaging characteristics of maxillary sinus effusion in drowned bodies, to explore its morphological characteristics and value in the diagnosis of the cause of death, and to provide objective evidence to support the study of virtual anatomy of drowning. Methods The 154 postmortem CT examination cases （31 cases of drowning, 123 cases of non-drowning） of Beijing Public Security Bureau Forensic Center in 2019 were collected. The bodies of all cases were scanned by multi-layer spiral CT before double-blind reading by clinical imaging experts. Maxillary sinus of corpses with maxillary sinus effusion in imaging findings was punctured. The detection rate of maxillary sinus effusion was calculated. The CT value and volume of maxillary sinus effusion were measured on 3D DICOM workstation. Results The detection rate of maxillary sinus effusion in the drowning was 100%, the shape was horizontal liquid level, the volume was 1.2-11.2 mL, the CT value was 6.08-19.02 Hu, with an average value of 12.85 Hu. The detection rate of maxillary sinus effusion in non-drowning was 19.51% （24/123）, the shape was wavy or irregular, and there were bubbles inside, the volume was 0.4-13.4 mL, the CT value was 23.68-77.75 Hu, with an average value of 42.08 Hu. The differences in CT value between the two groups had statistical significance. Conclusion The postmortem CT examination method can be used to observe the shape and measure the CT value of the maxillary sinus effusion in the bodies in water, which can be an auxiliary examination method for identification of drowning.
Autopsy ; Beijing ; Drowning/diagnostic imaging* ; Humans ; Maxillary Sinus/diagnostic imaging* ; Tomography, X-Ray Computed

Adult ; Extracorporeal Membrane Oxygenation ; methods ; Female ; Humans ; Near Drowning ; complications ; diagnostic imaging ; therapy ; Neuroimaging ; Treatment Outcome

OBJECTIVES: To explore the application value of virtual autopsy to obtain key evidence information on drowned corpses and its application value of virtual autopsy in the diagnosis of drowning. METHODS: In this study, 7 corpses were selected as the research objects. The image data of corpses were collected by computed tomography (CT) before conventional autopsy. The characteristics of corpses were observed through image reading, combined with virtual measurement indexes, and compared with 15 non-drowned corpses. RESULTS: The postmortem CT of drowning showed the more fluid in respiratory tract than the non-drowning, and ground-glass opacities in the lung. The statistical volume of fluid in the sinus (maxillary sinus and sphenoid sinus) was (10.24±4.70) mL in drowning cases and (2.02±2.45) mL in non-drowning cases. The average CT value of fluid in the sinus, left atrial blood and gastric contents in drowning cases were (15.91±17.20), (52.57±9.24) and (10.33±12.81) HU, respectively, which were lower than those in non-drowning cases (P<0.05). CONCLUSIONS The comprehensive consideration of multiple characteristic image manifestations and the virtual measurement indexes are helpful to the forensic pathological diagnosis of drowning. Virtual autopsy can be used as an auxiliary method in the forensic diagnosis of drowning.
Autopsy/methods* ; Cadaver ; Drowning/diagnostic imaging* ; Forensic Pathology/methods* ; Humans ; Tomography, X-Ray Computed/methods*