Age estimation equations using vertebral osteophyte formation in a Thai population: comparison and modified osteophyte scoring method

Development of a deep-learning algorithm for age estimation on CT images of the vertebral column

PURPOSE

The accurate age estimation of cadavers is essential for their identification. However, conventional methods fail to yield adequate age estimation especially in elderly cadavers. We developed a deep learning algorithm for age estimation on CT images of the vertebral column and checked its accuracy.

METHOD

For the development of our deep learning algorithm, we included 1,120 CT data of the vertebral column of 140 patients for each of 8 age decades. The deep learning model of regression analysis based on Visual Geometry Group-16 (VGG16) was improved in its estimation accuracy by bagging. To verify its accuracy, we applied our deep learning algorithm to estimate the age of 219 cadavers who had undergone postmortem CT (PMCT). The mean difference and the mean absolute error (MAE), the standard error of the estimate (SEE) between the known- and the estimated age, were calculated. Correlation analysis using the intraclass correlation coefficient (ICC) and Bland-Altman analysis were performed to assess differences between the known- and the estimated age.

RESULTS

For the 219 cadavers, the mean difference between the known- and the estimated age was 0.30 years; it was 4.36 years for the MAE, and 5.48 years for the SEE. The ICC (2,1) was 0.96 (95 % confidence interval: 0.95-0.97, p < 0.001). Bland-Altman analysis showed that there were no proportional or fixed errors (p = 0.08 and 0.41).

CONCLUSIONS

Our deep learning algorithm for estimating the age of 219 cadavers on CT images of the vertebral column was more accurate than conventional methods and highly useful.

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.

Testing the accuracy of the DRNNAGE software for age estimation in a modern Greek sample

Estimation of age-at-death from human skeletal remains is fundamental in forensic anthropology as part of the construction of the biological profile of the individual under study. At the same time, skeletal age-at-death estimation in adults is problematic due to the disparity between chronological and biological age, the important inter-individual variability at the rate of skeletal aging, and inherent biases in the available methodologies (e.g., age mimicry). A recent paper proposed a method for skeletal age-at-death estimation based on multiple anatomical traits and machine learning. A software was also created, DRNNAGE, for the easy implementation of this method. The authors of that study supported that their methods have very high repeatability and reproducibility, and the mean absolute error of the age estimation was ~6 years across the entire adult age span, which is particularly high and promising. This paper tests the proposed methodology on a modern documented Greek sample of 219 adult individuals from the Athens Collection, with age-at-death from 19 to 99 years old. The sample was split into males and females as well as into individuals under and over 50 years old. We also divided the sample in 10-year intervals. First, intra- and inter-observer error was estimated in order to assess repeatability and reproducibility of the variables employed for age-at-death estimation. Then, the validity (correct classification performance) of DRNNAGE for each anatomical region individually, as well as all combined, was evaluated on each demographic separately and on the pooled sample. According to the results, some of the variables showed very low repeatability and reproducibility, thus their use should be cautious. The DRNNAGE software showed overall highly accurate age-at-death estimates for individuals older than 50 years, but poor on younger adults, with only exception the cranial sutures, which performed surprisingly well for all age groups. Overall, these results support the importance of cross-validation and the use of population-specific methods in forensic anthropology.

Radiographic age estimation based on degenerative changes of vertebrae

Age estimation is an important component of decedent identification. When assessing adult remains, anthropologists frequently use gross examination of skeletal elements, such as clavicles, ribs, and pubic symphyses. For fleshed bodies, this requires the removal of these elements and maceration prior to analysis. A new method was developed using radiographic imaging to estimate age from degenerative changes of the lower thoracic and upper lumbar vertebrae. This technique will complement anthropological age estimation methods in young and middle-aged adults and may serve as a stand-alone method for older individuals. Digital radiographs from 240 medical examiner cases were evaluated. The sample included 120 females and 120 males between the ages of 18 and 101 years. A 3-phased scoring system was used for the target vertebrae. Transition analysis was conducted on binned average scores and a Bayesian approach was used to assign age intervals. At the 90% credible interval, individuals in Bin 1 were under 36 years of age while those in Bin 3 were over 47 years of age. Individuals in Bin 2 showed too much age variation to be informative. No significant differences were found between males and females. These findings will be especially useful in the age estimation of older adults and may eliminate the need for skeletal sampling in medicolegal cases where advanced degenerative changes are radiographically observed in the lower thoracic and/or upper lumbar vertebrae. This method was developed for use on fleshed individuals but may also be applicable to skeletonized remains.

Predicting chronological age based on age-related osteophyte development in the superior and inferior vertebral centrum margins of T12-L5

The purpose of this study was to determine the relationship between vertebral margins at individual vertebral levels between T12-L5 vertebra and chronological age and develop predictive models. Three hundred and nineteen CT scans from a medical imaging database in North America were randomly selected. Three superior and inferior vertebral margin sites were scored based on observable age-related changes. All individual vertebral margin site scores significantly correlated with age at death with Pearson r values ranging from 0.47 to 0.77. Totaling the individual vertebral margin site scores for L1-L5 improved Pearson r to 0.92. All resulting predictive models were significant, and the best models predicted age at death within 10 years 70%-76% of the time for males, females, and combined male and females. In conclusion, this study produced accurate and reliable models to predict age at death using age-related changes in the spine for a North American population.

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.

Morphometric analysis of dry atlas vertebrae in a northeastern Thai population and possible correlation with sex

PURPOSE

The uppermost segment of the cervical vertebra or atlas (C1) is a critically important anatomical structure, housing the medulla oblongata and containing the grooves for the C1 spinal nerve and the vertebral vessels. Variations of the C1 vertebra can affect upper spine stability, and morphometric parameters have been reported to differ by population. However, there are few data regarding these parameters in Thais. The use of this bone to predict sex and age has never been reported.

METHODS

This study aimed to examine C1 morphometry and determine its ability to predict sex. Twelve diameter parameters were taken from the C1 vertebrae of identified skeletons (n = 104, males [n, 54], females [n, 50]). Correlation analysis was also performed for sex and age, which were predicted using machine learning algorithms.

RESULTS

The results showed that 8 of the 12 measured parameters were significantly longer in the male atlas (p < 0.05), while the remaining 4 (distance between both medial-most edges of the transverse foramen, transverse dimension of the superior articular surface, frontal plane passing through the canal's midpoint, and anteroposterior dimension of the inferior articular surface) did not differ significantly by sex. There was no statistically significant difference in these parameters on the lateral side. The decision stump classifier was trained on C1 parameters, and the resulting model could predict sex with 82.6% accuracy (root mean square error = 0.38).

CONCLUSION

Assertation of the morphometric parameters of the atlas is important for preoperative assessment, especially for the treatment of atlas dislocation. Our findings also highlighted the potential use of atlas measurements for sex prediction.

The impact of age on the morphology of the 12th thoracic vertebral endplates

The current article explores the aging effects on the overall morphology of the endplates of the 12th thoracic vertebra (T12), while screening for sex differences. It further evaluates the suitability of T12 for estimating age-at-death in bioarcheaological contexts. We captured the morphology of the vertebral endplates, including the formation of osteophytes, in a novel continuous quantitative manner using digital photography. 168 Greek adults from the Athens Collection were used for modeling the aging effects and another 107 individuals from two Danish archaeological assemblages for evaluation. Regression analysis is based on generalized additive models for correlating age-at-death and morphological variation. Our proposed measurement method is highly reliable (R>0.98) and the main differences observed between sexes are size related. Aging has considerable effect on the endplate morphology of the T12 with the total area of the endplate, the area of the epiphyseal rim, and the shape irregularities of the endplate's external boundary being mostly affected. Multivariate regression shows that aging effects account up to 46% of the observed variation, although with differential expression between sexes. Correct age prediction on archaeological remains reached 33% with a prominent tendency for overestimation. The morphology of the T12 endplates is influenced by age and it can provide some insight with respect to the age-at-death of unidentified individuals, especially when other skeletal age markers are unavailable. Our proposed method provides an age-estimation framework for bioarchaeological settings, especially for estimating broader age ranges, such as discriminating between young and old adults.

Estimating age from digital radiographic images of lumbar vertebrae in a Thai population using an image analysis technique

Using the lumbar vertebra for age estimation is helpful in cases when skeletal remains are incomplete and typical skeletal age indicators are absent. This study aimed to apply an image analysis method in extracting black pixel variables for age estimation by using the radiographic images of lumbar vertebra in a Thai population. All lumbar vertebrae L1-L5 of 220 (110 males and 110 females) from Thai individuals of known sex and ages were studied. The variables of Total Percentage of black pixels (TP), Mean Percentage of black pixels (MP), and Ratio of black to white pixels (BW), were calculated to assess the relationship between black pixel variables and aging. Equations were formulated using linear regression analysis. The results of this study indicated three variables of the lumbar vertebrae had significantly positive correlations with age. The correlation between parameters with age in males ranged 0.211-0.419, while the range in females was 0.219-0.458. The appropriate linear regression equation with the total and mean percentages of black pixel variables shows Age = -1.348+0.871 (TP) +0.514 (MP) of L4 for males (SEE; 15.4 years), and Age = 5.338 +0.316 (TP) +0.952 (MP) of L1 for females (SEE; 13.8 years). Age estimation using an image analysis method is an alternative to investigating the trabecular structure. The black pixel variable is not the actual value of bone density. However, it is useful to study its relationship with aging.

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

Estimation of age at death is important in forensic investigations of unknown remains. There have been several reports on applying the degree of osteophyte formation-an age-related change in the vertebral body-for age estimation; however, this method is not yet established. This study investigated a method for age estimation of modern Japanese individuals using osteophytes measured on CT images. The sample included 250 cadavers (125 males) aged 20-95 years. The degree of osteophyte formation was evaluated as score O (0-5 points), and the degree of fusion of the osteophytes between the upper and lower vertebrae was evaluated as score B (0-2 points). Age estimation equations were developed using regression analyses with seven variables, determined by scores O and B, and the equation with the smallest standard error of estimate (SEE) was obtained when the number of vertebrae with score O ≥ 2 was used as the explanatory variable. Age estimation with SEE of about 10 years was possible even when partial vertebrae with a high degree of osteophyte formation were used, showing its potential for practical application. The cutoff value for age estimation was established using the receiver operating characteristic curve analysis, wherein good results were obtained for all variables (area under the curve ≥ 0.8). The combination of the estimation equation and the cutoff value can narrow the range of age estimates.

Imaging features of the aging spine

Among many degenerative abnormalities commonly found in spine imaging, not all are associated with the patient's symptoms. We aimed to assess features of the standard, asymptomatic aging process of the spine. In this narrative review, we emphasize studies that describe imaging features of the spine in asymptomatic populations of different age groups. Degeneration of the intervertebral discs, bulging, and facet joint arthropathy have been documented in almost 90% of asymptomatic patients over 60 years of age. After the age of 40 years, nearly all patients have anterior and lateral vertebral osteophytes, whereas posterior osteophytes are found in a minority of them. There is a gradual increase in vertebral bone marrow fat composition with age with the acceleration of this process in women after menopause. The prevalence of these findings is common in asymptomatic populations and varies depending on the patient's age. It is essential to differentiate likely natural and age-related findings from pathological abnormalities to make an accurate diagnosis.

Sex estimation using subpubic angle from reconstructed three-dimensional computed tomography pelvic model in a contemporary Malaysian population

Research in forensic anthropology is recent in Malaysia due to limited access to documented skeletal collections. However, advanced imaging techniques provide virtual bone samples for use in morphometric studies to establish population-specific standards by virtual anthropology. This study examined sexual dimorphism in the subpubic angle using a three-dimensional computed tomography model of the pelvis, in a contemporary Malaysian population. The sample comprised multidetector computed tomography (MDCT) scans of 50 male and 50 female adults. Segmentation of the MDCT scans was performed using 3D Slicer, and four landmarks were acquired using Stratovan Checkpoint for the subpubic angle measurement. The technical error of measurement (TEM), relative TEM, and coefficient of reliability (R) exhibited high reliability in measurements. Results showed that the subpubic angle in males was 68.6°±7.6° and in females 87.4°±6.5°. The subpubic angle in females was significantly larger than in males (P<0.001). Inverse correlation was found between the subpubic angle and age, in both males (r=−0.449, P<0.01) and females (r=−0.385, P<0.01). The overall accuracy of sex estimation using the subpubic angle was 94% (P<0.001). The subpubic angle, with a demarcating point of 78.6°, showed a sensitivity and specificity of 94% in the classification of female individuals. In conclusion, sex estimation using the subpu bic angle is highly accurate, with a high degree of expected sensitivity and specificity in the Malaysian population.