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Using postmortem computed tomography (CT) images, we achieved personal identification of a body using transposed teeth and dental treatment marks. Transposition of teeth is a rare malpositioning anomaly. CT images can clarify the malpositioning of the teeth's roots, which is difficult to discern from gross observation of the dentition. Because dental hygiene has reduced the incidence of caries in recent years, it might be difficult to use treatment marks for personal identification in the future. Transposed teeth, although rare, provide an important clue to personal identification.

IntroductionBrain positron emission tomography/computed tomography (PET/CT) scans are useful for identifying the cause of dementia by evaluating glucose metabolism in the brain with F-18-fluorodeoxyglucose or Aβ deposition with F-18-florbetaben. However, since imaging time ranges from 10 to 30 minutes, movements during the examination might result in image artifacts, which interfere with diagnosis. To solve this problem, data-driven brain motion correction (DDBMC) techniques are capable of performing motion corrected reconstruction using highly accurate motion estimates with high temporal resolution. In this study, we investigated the effectiveness of DDBMC techniques on PET/CT images using a Hoffman phantom, involving continuous rotational and tilting motion, each expanded up to approximately 20 degrees.Materials and methodsListmode imaging was performed using a Hoffman phantom that reproduced rotational and tilting motions of the head. Brain motion correction processing was performed on the obtained data. Reconstructed images with and without brain motion correction processing were compared. Visual evaluations by a nuclear medicine specialist and quantitative parameters of images with correction and reference still images were compared.ResultsNormalized Mean Squared Error (NMSE) results demonstrated the effectiveness of DDBMC in compensating for rotational and tilting motions during PET imaging. In Cases 1 and 2 involving rotational motion, NMSE decreased from 0.15-0.2 to approximately 0.01 with DDBMC, indicating a substantial reduction in differences from the reference image across various brain regions. In the Structural Similarity Index (SSIM), DDBMC improved it to above 0.96 Contrast assessment revealed notable improvements with DDBMC. In continuous rotational motion, % contrast increased from 42.4% to 73.5%, In tilting motion, % contrast increased from 52.3% to 64.5%, eliminating significant differences from the static reference image. These findings underscore the efficacy of DDBMC in enhancing image contrast and minimizing motion induced variations across different motion scenarios.ConclusionsDDBMC processing can effectively compensate for continuous rotational and tilting motion of the head during PET, with motion angles of approximately 20 degrees. However, a significant limitation of this study is the exclusive validation of the proposed method using a Hoffman phantom; its applicability to the human brain has not been investigated. Further research involving human subjects is necessary to assess the generalizability and reliability of the presented motion correction technique in real clinical scenarios.

The utility of convolutional neural networks (CNNs) for sex estimation of the pelvis was evaluated using depth images generated from reconstructed three-dimensional (3D) computed tomography images. The 3D volume data were normalized by a homologous modeling technique to create polygon data with identical topology, then captured images for learning and testing. The neural networks were trained via transfer learning. As a result, a correct assignment rate >90% was obtained in most trials. The frontal view of the pelvis with 60-degree inclination achieved the best results. Selecting samples close to the average images of the sex was effective for training.

Gallbladder injuries are extremely rare in blunt trauma, with a reported incidence of

In forensic medicine, fatal hypothermia diagnosis is not always easy because findings are not specific, especially if traumatized. Post-mortem computed tomography (PMCT) is a useful adjunct to the cause-ofdeath diagnosis and some qualitative image character analysis, such as diffuse hyperaeration with decreased vascularity or pulmonary emphysema, have also been utilized for fatal hypothermia. However, it is challenging for inexperienced forensic pathologists to recognize the subtle differences of fatal hypothermia in PMCT images. In this study, we developed a deep learning-based diagnosis system for fatal hypothermia and explored the possibility of being an alternative diagnostic for forensic pathologists. An in-house dataset of forensic autopsy proven samples was used for the development and performance evaluation of the deep learning system. We used the area under the receiver operating characteristic curve (AUC) of the system for evaluation, and a human-expert comparable AUC value of 0.905, sensitivity of 0.948, and specificity of 0.741 were achieved. The experimental results clearly demonstrated the usefulness and feasibility of the deep learning system for fatal hypothermia diagnosis. [ABSTRACT FROM AUTHOR]

Positron emission tomography (PET)/computed tomography (CT) has improved sensitivity and resolution using silicon photomultiplier as a photosensor. Previously, only a fixed setting was available for the shooting time of 1 bed, but now, the shooting time can be changed for each bed. Time can be shortened or extended depending on the target area. A few studies reported on image reconstruction conditions for head and neck cancer in whole-body PET/CT examinations. Thus, this study aimed to optimize the imaging conditions of the head and neck region during whole-body imaging. A cylindrical acrylic container with a 200 mm diameter was used to simulate the head and neck area using a PET/CT system equipped with a semiconductor detector. Spheres of 6-30 mm in diameter were enclosed in the 200 mm diameter cylindrical acrylic vessel. Radioactivity in 18F solution (Hot:BG ratio 4:1) was enclosed in a phantom following the Japanese Society of Nuclear Medicine (JSNM) guidelines. Background radioactivity concentration was 2.53 kBq/mL. List mode acquisition of 1,800 s was collected at 60-1,800 s with the field of view of 700 mm and 350 mm. The image was reconstructed by resizing the matrix to 128 128, 192 192, 256 256, and 384 384, respectively. The imaging time per bed in the head and neck should be at least 180 s, and the reconstruction conditions should be a field of view (FOV) of 350 mm, matrix sizes of ≥ 192, and a Bayesian penalized likelihood (BPL) reconstruction with a β-value of 200. This allows detection of > 70% of the 8-mm spheres in the images. [ABSTRACT FROM AUTHOR]

Imaging features of the lung in postmortem computed tomography (CT) scans have been reported in drowning cases. However, it is difficult for forensic pathologists with limited experience to distinguish subtle differences in CT images. In this study, artificial intelligence (AI) with deep learning capability was used to diagnose drowning in postmortem CT images, and its performance was evaluated. The samples consisted of high-resolution CT images of the chest of 153 drowned and 160 non-drowned bodies captured by an 8- or 64-row multislice CT system. The images were captured with an image slice thickness of 1.0 mm and spacing of 30 mm, and 28 images were typically captured. A modified AlexNet was used as the AI architecture. The output result was the drowning probability for each component image. To evaluate the performance of the proposed model, the area under the receiver operating characteristic curve (AUC) was analyzed, and the AUC value of 0.95 was obtained. This indicates that the proposed AI architecture is a useful and powerful complementary testing approach for diagnosing drowning in postmortem CT images. Notably, the accuracy was 81% (62/77) for cases in which resuscitation was performed, and 92% (216/236) for cases in which resuscitation was not attempted. Therefore, the proposed AI method should not be used to diagnose the cause of death when aggressive cardiopulmonary resuscitation was performed. Additionally, because honeycomb lungs are likely to exhibit different morphologies, emphysema cases should also be treated with caution when the proposed AI method is used to diagnose drowning. [ABSTRACT FROM AUTHOR]

The liver is an organ that is frequently injured by blunt trauma. In clinical medicine, contrast-enhanced computed tomography (CT) is useful for diagnosing liver damage. However, detection of liver injury is difficult with postmortem CT (PMCT) that does not use contrast media. This study aims to identify findings that are useful for diagnosing liver injury with PMCT. This study included 97 high-energy trauma cases that underwent both PMCT without contrast and forensic autopsy between July 2009 and November 2020. PMCT findings in and around the liver in cases of liver injury were collected. The diagnostic accuracy of each finding was calculated. Of 97 cases, 62 had liver injury on autopsy. PMCT detected hepatic surface gas in 31 cases, intrahepatic focal gas in 19 cases, high-density fluid accumulation around the liver in 12 cases, and fracture of a right lower (9th-12th) rib in 48 cases. Abnormal PMCT findings in and around the liver had insufficient diagnostic sensitivity, ranging from 19.4% to 38.7%. By contrast, the finding of a right lower rib fracture was more sensitive for suspected liver injury. Our results indicate that abdominal liver findings (hepatic surface gas, intrahepatic focal gas, and high-density fluid accumulation around the liver) are of limited utility for the diagnosis of liver injury, whereas a right lower rib fracture is a useful indirect finding. [ABSTRACT FROM AUTHOR]

The article focuses on a study regarding the use of interventional radiology (IVR) for delivering high radiation doses to the patient. It mentions that radiation-induced injuries that occur because of the effect of the high radiation doses. It also mentions that small synthetic rubies emit a tiny amount of light that is difficult to detect using common systems such as photodiodes.

Traditional autopsy has changed little in the past century. In Japan, the rate of forensic autopsy in cases of unusual death is very low. Therefore, multi-slice computed tomography (CT) has been used to obtain imaging data instead of or in addition to autopsy in suspicious forensic cases. In our institute, postmortem multi-slice CT has been performed since 2009, and by 2014 there were over 1,000 cases. Our extensive experience with postmortem CT shows that in many cases of death by drug overdose, stomach contents exhibit high X-ray absorption. This article reviews the relationship between CT findings of stomach contents and toxicological analysis results in 23 cases of death by drug overdose. All cases (12 females and 11 males, aged 44 ± 11 years) known to have orally ingested drugs were included in this study. We assessed the slices of all stomach areas on consecutive axial CT images. Twenty cases (87%) showed high X-ray absorption in the stomach, while the other three did not demonstrate radio-dense stomach contents even though drug analysis detected lethal concentrations of drugs in the blood. In conclusion, drugs were frequently, but not always, visualized as contents with high X-ray absorption in the stomach. Postmortem gastric CT images can provide useful information in cases of oral drug intoxication if there are empty drug packages or a suicide note at the death scene. However, precise determination of the cause of death requires full autopsy in cases where there is no indication of suicide at the death scene. [ABSTRACT FROM AUTHOR]

A middle-aged female patient with a depressive disorder presented to a mental hospital because of a 2-month worsening history of headache, dizziness, and nausea. The next morning, she was observed to be sleeping, but was then found dead 1h later. Postmortem computed tomography and autopsy revealed a large cyst in the right cerebellar hemisphere, hydrocephalus, and transforaminal herniation. Careful observation revealed an approximately 0.4cm×0.8cm slightly grayish discoloration in the cyst wall that was diagnosed as hemangioblastoma based on its histological features. Finally, we concluded that the cause of death in this case was attributable to the brain stem compression, which was caused by obstructive hydrocephalus secondary to the cystic hemangioblastoma in the cerebellum. The symptoms for 2 months before her death had most likely resulted from increased intracranial pressure. Hemangioblastomas usually appear as nodules in the wall of the cyst, but the tumor in our case looked like just a slightly grayish discoloration. Therefore, cystic lesions in the CNS need to be carefully examined. [ABSTRACT FROM AUTHOR]