Age estimation by evaluation of osteophytes in thoracic and lumbar vertebrae using postmortem CT images in a modern Japanese population

Estimation of ancestry from cranial measurements based on MDCT data acquired in a Japanese and Western Australian population

The estimation of ancestry is important not only towards establishing identity but also as a required precursor to facilitating the accurate estimation of other attributes such as sex, age at death, and stature. The present study aims to analyze morphological variation in the crania of Japanese and Western Australian individuals and test predictive models based on machine learning for their potential forensic application. The Japanese and Western Australian samples comprise computed tomography (CT) scans of 230 (111 female; 119 male) and 225 adult individuals (112 female; 113 male), respectively. A total of 18 measurements were calculated, and machine learning methods (random forest modeling, RFM; support vector machine, SVM) were used to classify ancestry. The two-way unisex model achieved an overall accuracy of 93.2% for RFM and 97.1% for SVM, respectively. The four-way sex and ancestry model demonstrated an overall classification accuracy of 84.0% for RFM and 93.0% for SVM. The sex-specific models were most accurate in the female samples (♀ 95.1% for RFM and 100% for SVM; ♂91.4% for RFM and 97.4% for SVM). Our findings suggest that cranial measurements acquired in CT images can be used to accurately classify Japanese and Western Australian individuals into their respective population. This is the first study to assess the feasibility of ancestry estimation using three-dimensional CT images of the skull.

Age estimation by palatal suture using modified Kamijo's method

The present study aimed to investigate the correlation between palatal suture obliteration and age in modern Japanese and to develop an age estimation equation by modifying Kamijo's (1949) method. The subjects were 195 Japanese skeletal remains (155 males and 40 females) whose age and sex were known. First, obliteration score (OS) was obtained by measuring palatal suture obliteration from photographic images taken at the time of forensic autopsy, and the correlation with age was examined; no significant correlation was found in females. Second, the palatal sutures were divided into 14 sections, and each section was scored from 0 to 4 points according to the degree of the suture obliteration. Suture scores (SS) were then calculated for each of the four sutures, and the sum of the 14 scores (TSS: total suture score) was used to perform regression analysis for age. For male and all subjects (male and female), age significantly increased (p < 0.001) according to increment of SSs for all sutures. TSS has the highest regression coefficient (r = 0.540), and the lowest standard error of estimation (13.54 years) for all of the patients. The intra- and inter-observer agreement scoring showed high reliability. Validation study using the formulae showed a high percentage of correct responses (80 %). In conclusion, age estimation regression formula by palatal suture using modified Kamijo's method was established for Japanese population, and the study showed the formula might be valid for age estimation.

Age estimation by evaluating median palatine suture closure using postmortem CT

This study sought to develop an age-estimation formula to evaluate the extent of median palatine suture (MP) closure using postmortem computed tomographic (PMCT) images. The PMCT images of 634 Japanese subjects (mean age, 54.5 years; standard deviation [SD], 23.2 years) with known age and sex were examined. The degree of suture closure of the MP, anterior median palatine suture (AMP), and posterior median palatine suture (PMP) was measured and scored (suture closure score, SCS), and a single linear regression analysis was conducted with age at death. On the analysis, SCS of MP, AMP, and PMP showed a significant correlation with age (p < 0.001). The correlation coefficient of MP was higher (0.760, male; 0.803, female; and 0.779, total) than that of AMP (0.726, male; 0.745, female; and 0.735, total) or PMP (0.457, male; 0.630, female; and 0.549, total). The regression formula and standard error of estimation (SEE) of MP were calculated as Age = 100.95 × SCS + 20.51 (SEE 14.87 years) for male subjects, Age = 91.93 × SCS + 26.65 (SEE 14.12 years) for female subjects, and Age = 95.17 × SCS + 24.09 (SEE 14.59 years) for the total, respectively. In addition, another 50 Japanese subjects were randomly selected to validate the age-estimation formula. In this validation, the actual age of 36 subjects (72%) was within the estimated age ± SEE. This study showed that the age estimation formula using PMCT images of MPs was potentially useful for estimating the age of unidentified corpses.

Estimating age at death by Hausdorff distance analyses of the fourth lumbar vertebral bodies using 3D postmortem CT images

The existing methods for determining adult age from human skeletons are mostly qualitative. However, a shift in quantifying age-related skeletal morphology on a quantitative scale is emerging. This study describes an intuitive variable extraction technique and quantifies skeletal morphology in continuous data to understand their aging pattern. A total of 200 postmortem CT images from the deceased aged 25-99 years (130 males, 70 females) who underwent forensic death investigations were used in the study. The 3D volume of the fourth lumbar vertebral body was segmented, smoothed, and post-processed using the open-source software ITK-SNAP and MeshLab, respectively. To measure the extent of 3D shape deformity due to aging, the Hausdorff distance (HD) analysis was performed. In our context, the maximum Hausdorff distance (maxHD) was chosen as a metric, which was subsequently studied for its correlation with age at death. A strong statistically significant positive correlation (P < 0.001) between maxHD and age at death was observed in both sexes (Spearman's rho = 0.742, male; Spearman's rho = 0.729, female). In simple linear regression analyses, the regression equations obtained yielded the standard error of estimates of 12.5 years and 13.1 years for males and females, respectively. Our study demonstrated that age-related vertebral morphology could be described using the HD method. Moreover, it encourages further studies with larger sample sizes and on other population backgrounds to validate the methodology.

Deep Neural Networks-Based Age Estimation of Cadavers Using CT Imaging of Vertebrae

Although age estimation upon death is important in the identification of unknown cadavers for forensic scientists, to the best of our knowledge, no study has examined the utility of deep neural network (DNN) models for age estimation among cadavers. We performed a postmortem computed tomography (CT) examination of 1000 and 500 male and female cadavers, respectively. These CT slices were converted into 3-dimensional images, and only the thoracolumbar region was extracted. Eighty percent of them were categorized as training datasets and the others as test datasets for both sexes. We fine-tuned the ResNet152 models using the training datasets. We conducted 4-fold cross-validation, and the mean absolute error (MAE) of the test datasets was calculated using the ensemble learning of four ResNet152 models. Consequently, the MAE of the male and female models was 7.25 and 7.16, respectively. Our study shows that DNN models can be useful tools in the field of forensic medicine.

A novel method to estimate adult age from the lumbar vertebral body using 3D PMCT images in Japanese

This study evaluated the age-related changes in the vertebral body using 3D Postmortem CT (PMCT) images and proposed an alternative age estimation formula. The PMCT images of 200 deceased individuals aged 25 to 99 years (126 males, 74 females) were retrospectively reviewed and included in the study. Using the open-source software ITK-SNAP and MeshLab, a 3D surface mesh of the fourth lumbar vertebral body (L4) and its convex hull models were created from the PMCT data. Using their inbuilt tools, volumes (in mm3) of the L4 surface mesh and convex hull models were subsequently computed. We derived VD, defined as the difference in volumes between the convex hull and L4 surface mesh normalized by L4 mesh volume, and VR, defined as the ratio of L4 mesh volume to convex hull volume based on individual L4. Correlation and regression analyses were performed between VD, VR, and chronological age. A statistically significant positive correlation (P < 0.001) between chronological age and VD, (r_s = 0.764, males; r_s = 0.725, females), and a significant negative correlation between chronological age and VR (r_s = -0.764, males; r_s = -0.725, females) was obtained in both sexes. The lowest standard error of the estimate was demonstrated by the VR at 11.9 years and 12.5 years for males and females, respectively. As such, their regression models to estimate adult age were Age = 248.9-2.5VR years, males; Age = 258.1-2.5VR years, females. These regression equations may be useful for estimating age in Japanese adults in forensic settings.