Jeong-Hwa Kwon

Estimation of body parameters, height and body weight, is important for biological profiling in forensic investigations. This study aimed to develop a deep learning model for automated height and weight estimation using postmortem computed tomography (PMCT) scout view images acquired in forensic practice. A retrospective analysis was conducted in 3,124 cases that underwent autopsy and PMCT. Scout view images were preprocessed with geometric correction based on PMCT table height. Three CT window settings were fused into RGB channels, enhancing anatomical and environmental information. A convolutional neural network based on a pre-trained VGG16 architecture was trained to simultaneously estimate height and weight. Model performance was evaluated on a test dataset (n = 624) using mean absolute error (MAE), mean absolute percentage error (MAPE), correlation analysis, and Bland-Altman analysis. The multi-window RGB fusion model achieved MAE values of 2.39 cm for height and 1.83 kg for weight, outperforming the single-window model. Predicted and reference values were strongly correlated. Bland-Altman analysis demonstrated narrow limits of agreement. Deep learning applied to PMCT scout view images enables automatic estimation of height and weight with high accuracy. The proposed multi-window RGB fusion with geometric correction offers a practical tool for body parameter estimation in forensic investigations.

New psychoactive substances (NPS) have rapidly emerged in illicit drug markets worldwide and are increasingly encountered in postmortem examinations. However, postmortem data on NPS-related deaths remain limited worldwide. This study describes postmortem findings from forensic autopsy cases in which NPS were detected and explores the characteristics of these deaths through a retrospective review. Six postmortem cases were identified between 2023 and 2024. The cases predominantly involved young adults. Toxicological analysis identified synthetic cannabinoids, dissociatives, and a stimulant, either alone or in combination with alcohol or conventional illicit drugs such as methamphetamine and 3,4-methylenedioxymethamphetamine (MDMA). Drug paraphernalia or a documented history of drug use was identified in only some cases. The causes of death included acute intoxication and traumatic deaths in which drug intoxication may have contributed to abnormal behavior and fatal outcomes. These findings provide preliminary forensic evidence of the emergence of NPS in South Korea. They underscore the importance of postmortem examination with comprehensive toxicological screening and continued surveillance of emerging psychoactive substances in forensic practice. They also suggest the value of reviewing a history of prior substance use even in unexpected sudden deaths not initially suspected to be drugrelated.

Sphenoid sinus fluid is considered a supportive indicator of drowning in forensic medicine, but traditional manual assessment on postmortem computed tomography (PMCT) is labor-intensive and observer-dependent. Efficient, reproducible methods for quantitative evaluation are needed in forensic practice. This study developed deep learning-based approaches for the automated segmentation and volumetric estimation of sphenoid sinus fluid using PMCT images from 165 autopsy-confirmed drowning cases. Three U-Net-based models (2D, 2.5D, and 3D) were developed and evaluated against manually annotated reference standards. In the test dataset, mean Dice coefficients were 0.866 (2D), 0.869 (2.5D), and 0.798 (3D). Volumetric estimates showed no statistically significant differences from the reference standard, with strong correlations (Spearman's ρ = 0.976-0.988). Mean absolute errors were 0.218 (2D), 0.206 (2.5D), and 0.310 ml (3D). The 2.5D approach provided the most balanced performance between segmentation accuracy and volumetric estimation. These findings demonstrate the feasibility of automated PMCT-based segmentation and volumetric quantification of sphenoid sinus fluid, enabling quantitative assessment on PMCT images prior to autopsy.

Aesthetic procedures are widely performed in Korea, reflecting strong societal demand and accessibility. However, their exact numbers are not systematically recorded, and reliable mortality data remain unavailable. The absence of comprehensive statistics limits our understanding of the risks and hinders evidence-based safety policies. In this context, death investigation and forensic autopsy provide valuable insights into the circumstances and causes of such deaths. This study analyzed 50 forensic autopsy cases of aesthetic procedurerelated fatalities referred to the National Forensic Service between 2016 and 2024. Clinical information and postmortem findings, including histopathological examination and ancillary testing, were reviewed. Demographics, procedural and anesthesia types, and facility characteristics were also examined. The causes of death were classified as anesthesia–related, procedural complications, diseases, or others. Most decedents were women in their 20s-40s (30/50), and 64% of cases occurred in Seoul Metropolitan area. Most cases involved face and neck procedures (52%), followed by liposuction (22%) and vaginal rejuvenation (12%). Anesthesia–related deaths predominated in face and neck procedures and other groups, whereas liposuction fatalities were mainly due to procedural complications. Vaginal rejuvenation was most often associated with fatal pulmonary embolism from filler materials. Overall, anesthesia–related deaths constituted the largest single category across all procedural types. These findings emphasize anesthesia–related mortality as the key cause of death in aesthetic medicine and highlight the essential role of forensic autopsy in accurate death certification and prevention of premature. Strengthened management, adherence to safety guidelines, and improved awareness of procedural safety, efficacy, and necessity are crucial for preventing fatal outcomes.

Patients with mental disorders have higher mortality rates than the general population, particularly from unnatural causes. However, research on psychiatric patient deaths is limited. In this study, we examined the incidence of sudden deaths in psychiatric hospitals from 2015 to 2024. An average of 6.5 deaths annually occurred in psychiatric settings, with a male-to-female ratio of 2.82:1. Most deaths were observed in patients in their 50s, with a body mass index of 20.1-25. Cardiovascular disease was the most common comorbidity, followed by gastrointestinal disorders. Schizophrenia was the most frequently diagnosed psychiatric condition, and most patients had been hospitalized for <1 year. Trauma was the leading cause of death, although 12 cases had undetermined causes. Among cases with undetermined causes of death, intellectual disability and schizophrenia were diagnosed in four males cases each, whereas both female cases had schizophrenia. This study highlights the frequent occurrence of unnatural or undetermined causes of death in psychiatric hospitals and emphasizes the need for greater attention to preventable fatalities.

Myositis ossificans (MO) is defined as a lesion where abnormal ossification forms in soft tissues, such as muscle, fascia, and ligament, usually as a result of trauma. It commonly appears in areas such as the thigh, hip, and elbow, though it can affect any part of the body. In the forensic field, MO resulting from trauma is reported to be valuable evidence of repeated physical abuse. This case report describes a deceased adult male with an intellectual disability, whose cause of death was multiple injuries from assault. Postmortem computed tomography (PMCT) and autopsy findings revealed MO of both thighs associated with repeated physical abuse. This case also showed typical findings of MO on PMCT imaging, characterized by well-defined, high-density lesions within the quadriceps. Adults with intellectual disabilities are at high risk of abuse and assault. Therefore, autopsy findings of MO can serve as important evidence in forensic practice, considering the possibility of repeated abuse.

The cause and manner of death in the Busan and Gyeongnam regions were analyzed using autopsy data performed by the National Forensic Service Busan Institute (NFS BI) for 10 years—from 2014 to 2023. In addition, changes in the number of autopsy cases of elderly individuals aged 65 and older, were analyzed in the Busan and Gyeongnam regions. A total of 6,374 cases were classified, excluding autopsies from the Ulsan area and the Coast Guard, from the NFS BI data. Analysis of the manner of death revealed that 3,203 cases (50.3%) were unnatural deaths; 2,031 cases (31.9%) were natural deaths; and 1,140 cases (17.9%) were deaths of unknown cause. Among the unnatural deaths, accidents were the most common at 1,149 cases (18.0%), followed by suicide at 979 cases (15.4%); and homicide at 583 cases (9.1%). Among natural deaths, heart disease was the most common with 764 cases (37.6%), followed by vascular disease with 351 cases (17.3%). The proportion of the population aged 65 or older in Busan and Gyeongnam has been steadily increasing from 13.7% in 2014 to 21.6% in 2023. Accordingly, the number of autopsies on people aged 65 or older has increased from 72 in 2014 to 174 in 2023, and the number of autopsies on people aged 65 or older accounted for one-quarter of the total number of forensic autopsies commissioned by Busan/Gyeongnam, and performed by NFS BI in 2023. Therefore, we plan to introduce emerging issues relating to population aging and geriatric forensic medicine.

Postmortem computed tomography (PMCT) is used in forensic medicine worldwide due to its ability to non-invasively visualize injuries, hemorrhage, and estimate volume. In the autopsy of infants, assessing nutritional conditions such as weight is crucial for identifying neglect. This study aims to evaluate the usefulness of retrospectively estimating the weight of Korean infants using PMCT-based volume and multiplication factors, even when the body has been cremated. A total of 44 cases of infant death (under 12 months) were analyzed. PMCT images were obtained before autopsy. Autopsy records and documentation provided by the police at the time of autopsy were reviewed to determine the weight (g) of the infant. PMCT-based infant volumes (mL) were estimated using a three-dimensional semi-automatic segmentation method. Multiplication factors (g/mL) were calculated by dividing the weight recorded at autopsy by the PMCT-based volume, yielding a mean of 1.047 g/mL, ranging from 1.014 g/mL to 1.085 g/mL. The mean absolute error compared to weights recorded at autopsy was 95 g. Significant discrepancies were observed between weights recorded at the scene or medical center and those measured at autopsy. This study demonstrates that PMCT-based weight estimation for Korean infants is a reliable method and has the potential for retrospectively validating incorrect weight measurements and addressing inconsistencies in recorded weight data.

Lymphocytic hypophysitis is a rare condition characterized by lymphocyte and plasma cell infiltration, leading to fibrosis and functional impairment of the pituitary gland. Although lymphocytic hypophysitis is associated with pregnancy, its diagnosis may be challenging in pregnant women owing to unclear symptoms of pituitary dysfunction. Lymphocytic hypophysitis can lead to serious complications, including a sudden death; however, no case of maternal death has been reported in Korea. This study presents a case of maternal death after childbirth. The deceased had a history of hypertension, obesity, hypothyroidism, and gestational diabetes and died suddenly the day after the emergency cesarean section. Notably, no other pregnancy-related complications were observed. Histopathological examination of the pituitary gland confirmed lymphocytic hypophysitis. This case report emphasizes the requirement of clinical awareness and underscores the significance of examining the pituitary gland during autopsy investigations of maternal deaths.

Detecting sphenoid sinus fluid (SSF) is an additional finding in autopsies for diagnosing drowning. SSF can provide additional forensic evidence through laboratory tests such as diatom and electrolyte analyses. If drowning is suspected, accurately assessing the presence and volume of SSF during an autopsy is crucial. Utilizing postmortem computed tomography (PMCT) images could aid in accurately sampling SSF. Accurately segmenting the region of interest is essential for volume analysis using computed tomography images. However, manual segmentation techniques are labor-intensive and time-consuming, and their success depends on the experience of the observer. Therefore, this study aimed to develop a U-Net–based deep learning model for the automatic segmentation of SSF in drowning cases using PMCT images and to evaluate the performance of the model. We retrospectively reviewed 34 drowning cases in which both PMCT scans and forensic autopsies were performed at our institution. The U-Net architecture of deep learning was used for automatic segmentation. The proposed model achieved the Dice similarity coefficient (DSC) and Intersection over Union (IoU) of a maximum of 95.85% and 92.03%, a minimum of 0% and 0%, and an average of 77.15% and 67.18%, respectively. Although the average DSC and IoU did not show high similarity, this study showed that PMCT images can be used for automatic segmentation of SSF in drowning cases, which could improve the performance with sufficient dataset acquisition and further model training.