Efficacy of three-dimensional cinematic rendering computed tomography images in visualizing features related to age estimation in pelvic bones

Applicability of the six-phase method for auricular age estimation in an Indian population: A CT-based study

Age estimation plays a crucial role in human identification. Amongst numerous age markers located throughout the skeletal framework, the auricular surface of the ilium presents as a resilient structure, with different methods for auricular age estimation currently in practice. Amongst these methods, the Osborne method is believed to permit accurate age estimation through its use of robust age categories and discrete phase descriptors. The present study aimed to assess the applicability of the Osborne method in an Indian population through a computed tomographic (CT) examination of the auricular surface, an aspect presently unreported. In order to do so, CT scans of 380 individuals were collected and evaluated using the Osborne method. A CT-based examination indicated that surface texture described by Osborne is difficult to appreciate through 3D CT images. Indistinct definitions associated with certain features, and the mosaic display of features within each phase further prevents applying the method effectively. Overall accuracy percentages of 99.47% and 98.90% were obtained using the method in males and females, respectively, with corresponding inaccuracy values of 10.10 years and 9.04 years. Significantly reduced accuracy percentages were obtained with alternate, more robust age brackets presented within the original study, demonstrating the limited reliability associated with the method. Inaccuracy and bias values computed for each decade indicate the relative utility of the method in aging 40-59-year-old individuals. Low accuracy percentages, high error rates and different methodological hindrances encountered within the present study illustrate the limited applicability of the Osborne method in aging an Indian population.

Age estimation from iliac auricular surface using Bayesian inference and principal component analysis: a CT-based study in an Indian population

Age estimation constitutes one of the pillars of human identification. The auricular surface of the ilium presents as a durable and robust structure within the human skeletal framework, capable of enabling accurate age estimation in older adults. Amongst different documented auricular age estimation methods, the Buckberry-Chamberlain method offers greater objectivity through its component-based approach. The present study aimed to test the applicability of the Buckberry-Chamberlain method in an Indian population through a CT-based examination of the auricular surface. CT scans of 435 participants undergoing CT examinations following the advice of their treating physicians were scrutinized for different age-related auricular changes. Three of the five morphological features described by Buckberry-Chamberlain could be appreciated on CT scans, and thus further statistical analysis was restricted to these features. Transition analysis coupled with Bayesian inference was undertaken individually for each feature to enable age estimation from individual features, while circumventing age mimicry. A Bayesian analysis of individual features yielded highest accuracy percentages (98.64%) and error rates (12.99 years) with macroporosity. Transverse organization and apical changes yielded accuracy percentages of 91.67% and 94.84%, respectively, with inaccuracy computations of 10.18 years and 11.74 years, respectively. Summary age models, i.e. multivariate age estimation models, derived by taking this differential accuracy and inaccuracy into consideration yielded a reduced inaccuracy value of 8.52 years. While Bayesian analysis undertaken within the present study enables age estimation from individual morphological features, summary age models appropriately weigh all appreciable features to yield more accurate and reliable estimates of age.

Applicability of the Suchey-Brooks method for age estimation in an Indian population: A computed tomography-based exploration using Bayesian analysis and machine learning

Age estimation occupies a prominent niche in the identification process. In cases where skeletal remains present for examination, age is often estimated from markers distributed throughout the skeletal framework. Within the pelvis, the pubic symphysis constitutes one of the more commonly utilized skeletal markers for age estimation, with the Suchey-Brooks method comprising one of the more commonly employed methods for pubic symphyseal age estimation. The present study was targeted towards assessing the applicability of the Suchey-Brooks method for pubic symphyseal age estimation, an aspect largely unreported for an Indian population. In order to do so, clinically undertaken pelvic computed tomography scans of individuals were evaluated using the Suchey-Brooks method, and the error associated with the method was established using Bayesian analysis and different machine learning regression models. Amongst different supervised machine learning models, support vector regression and random forest furnished lowest error computations in both sexes. Using both Bayesian analysis and machine learning, lower error computations were observed in females, suggesting that the method demonstrates greater applicability for this sex. Inaccuracy and root mean square error obtained with Bayesian analysis and machine learning illustrates that both statistical modalities furnish comparable error computations for pubic symphyseal age estimation using the Suchey-Brooks method. However, given the numerous advantages associated with machine learning, it is recommended to use the same within medicolegal settings. Error computations obtained with the Suchey-Brooks method, regardless of the statistical modality utilized, indicate that the method should be used in amalgamation with additional markers to garner accurate estimates of age.

Technical note: Interest of focused fields in post-mortem computed tomography using photorealistic images for age at death estimation from the pubic symphysis

INTRODUCTION

The morphological assessment of the pubic symphysis using the Suchey-Brooks method is considered a reliable age at death indicator. Age at death estimation methods can be adapted to the images obtained from post-mortem computed tomography (PMCT). The aim of this study is to evaluate the utility of pubic symphysis photorealistic images obtained through Global illumination rendering (GIR) for age at death estimation from whole-body PMCT and from focused PMCT on the pubic bone.

MATERIALS AND METHODS

We performed virtual age at death estimation using the Suchey Brooks method from both the whole-body field of view (Large Field of View: LFOV) and the pubis-focused field of view (Small and Field of View: SFOV) of 100 PMCT. The 3D photorealistic images were evaluated by three forensic anthropologists and the results were statistically evaluated for accuracy of the two applied PMCT methods and the intra- and inter-observer errors.

RESULTS

When comparing the two acquisitions of PMCT, the accuracy rate reaches 98.5% when using a pubic-focused window (SFOV) compared to 86% with a whole-body window (LFOV). Additionally, the intra- and inter-observer variability has demonstrated that the focused window provides better repeatability and reproducibility.

CONCLUSION

Adding a pubic-focused field of view to standard PMCT and processing it with GIR appears to be an applicable technique that increases the accuracy rate for age at death estimation from the pubic symphysis.

Forensic age estimation in adults by pubic bone mineral density using multidetector computed tomography

Radiology plays a crucial role in forensic anthropology for age estimation. However, most studies rely on morphological methods. This study aims to investigate the feasibility of using pubic bone mineral density (BMD) as a new age estimation method in the Chinese population. 468 pubic bone CT scans from living individuals in a Chinese hospital aged 18 to 87 years old were used to measure pubic BMD. The BMD of the bilateral pubic bone was measured using the Mimics software on cross-sectional CT images and the mean BMD of the bilateral pubic bone was also calculated. Regression analysis was performed to assess the correlation between pubic BMD and chronological age and to develop mathematical models for age estimation. We evaluated the accuracy of the best regression model using an independent validation sample by calculating the mean absolute error (MAE). Among all established models, the cubic regression model had the highest R2 value in both genders, with R2 = 0.550 for males and R2 = 0.634 for females. The results of the best model test showed that the MAE for predicting age using pubic BMD was 8.66 years in males and 7.69 years in females. This study highlights the potential of pubic BMD as a useful objective indicator for adult age estimation and could be used as an alternative in forensic practice when other better indicators are lacking.

An evaluation of the three-component pubic symphyseal human age estimation method: a CT-based exploration in an Indian population

Age estimation constitutes an important facet of human identification within forensic, bioarchaeological, repatriation, and humanitarian contexts. Within the human skeletal framework, the pubic symphysis comprises one of the more commonly utilized structures for age estimation. The present investigation was aimed at establishing the applicability of the McKern-Stewart pubic symphyseal age estimation method in males and females of an Indian population, an aspect previously unreported. Three hundred and eighty clinical CT scans of the pubic symphysis were collected and scored in accordance with the McKern-Stewart method. An overall accuracy of 68.90% was obtained on applying the method to males, demonstrating a limited applicability of the method in its primal form. Subsequently, Bayesian analysis was undertaken to enable accurate age estimation from individual components in both sexes. Bayesian parameters obtained with females suggest that McKern-Stewart's components fail to accommodate for age-related changes within the female pubic bone. Improved accuracy percentages and reduced inaccuracy values were obtained with Bayesian analysis in males. With females, the error computations were high. Weighted summary age models were utilized for multivariate age estimation, and furnished inaccuracy values of 11.51 years (males) and 17.92 years (females). Error computations obtained with descriptive analysis, Bayesian analysis, and principal component analysis demonstrate the limited applicability of McKern-Stewart's components in generating accurate age profiles for Indian males and females. The onset and progression of age-related changes within the male and female pubic bone may be of interest to biological anthropologists and anatomists involved in exploring the underlying basis for aging.

A machine-learning approach using pubic CT based on radiomics to estimate adult ages

PURPOSE

Adult skeletal age estimation is an active research field. To evaluate the performance of a pubic CT radiomics-based machine learning model for estimating age, we established a multiple linear regression model based on radiomics and machine learning methods.

METHODS

A total of 355 subjects were enrolled in this retrospective study from August 2016 to August 2021, and divided into a training cohort (N = 325) and a testing cohort (N = 30). Computerized texture analysis of the semi-automatically segmentation was performed and 107 texture features were extracted from the regions. Then we used univariate linear regression and multivariate stepwise regression to assess correlations of texture parameters with age. The most vital features were used to make the best predictive model. Eventually, the established radiomics model was tested with an additional 30 patients.

RESULTS

Clinical characteristics include age, sex, height, weight and BMI were not statistically significant different between training and testing cohort (p = 0.098-0.888). Through a multivariate regression analysis using stepwise regression, six texture parameters were found to have significant correlations with age. The regression formula estimating the age was constructed.

CONCLUSIONS

The radiomics model using machine learning is considered as a new approach forage estimation frompubic symphysis CT features.Digital osteology is obtained in a non-invasive way so that it can be an ideal collection for anthropological studies.

Computed tomographic evaluation of the acetabulum for age estimation in an Indian population using principal component analysis and regression models

The acetabulum presents as a well-preserved evidence, resistant to taphonomic degradation changes and can thus aid in the age estimation process. A CT-based examination of the acetabulum can further help simplify the process of age estimation by overcoming the time-consuming process of maceration and by doing away with the interference resulting from tissue remnants. The aim of the present study was to evaluate the role of the acetabulum for age estimation in an Indian population through a CT-based examination, using principal component analysis and regression models. CT images of 400 individuals aged 10 years and above were evaluated according to the features defined in the San-Millán-Rissech method of age estimation. Five of the seven morphological features defined by San-Millán-Rissech were appreciable on CT scans, and, to enable further statistical analysis, a cumulative score was computed using these five features. A significant correlation of 0.835 and 0.830 for the right and left acetabulum, respectively, was obtained between computed cumulative scores and chronological age of individuals. No significant sex differences were observed in the scoring of different age-related morphological changes. Regression models were generated using individual features and cumulative scores. Regression models derived using the cumulative score yielded inaccuracy values of 9.67 years for the right acetabulum and 9.15 years for the left acetabulum. Inaccuracy and bias values were computed for each individual feature, as well as for each decade, using mean point ages established within the original study. Amongst the various features, acetabular rim porosity was seen to have the lowest values of inaccuracy (11.50 years) and bias (2.32 years) and activity on outer edge of acetabular fossa the highest (inaccuracy and bias values of 22.36 years and 21.50 years, respectively). Taking into consideration this differential contribution towards age estimation, weighted coefficients and mean point ages for different morphological features were determined using principal component analysis. Subsequently, summary age models were generated from the obtained weighted coefficients and mean age values. Summary age models derived in the present study yield lower estimates of inaccuracy of 7.60 years for the right acetabulum and 7.82 years for the left acetabulum. While regression models derived in the present study allow for age estimation using even a single appreciable feature, summary age models take into account the contribution of each feature and generate more accurate estimates of age. Both statistical computations yield reduced error rates and thus can render greater applicability to the acetabulum in forensic age estimation.

CT-based evaluation of the acetabulum for age estimation in an Indian population

Age estimation constitutes an important aspect of forensic research, investigation and human identification. For the purpose of age estimation, various markers within the skeletal framework are employed. Degenerative morphological changes in the skeleton can be used for age estimation in adults. Amongst the various bones, age-progressive changes in the innominate bone are of particular significance in age estimation. Within the pelvis, the acetabulum presents as a durable and well-preserved evidence, characteristic manifestations of which can be employed for age estimation. The present study aimed at a CT-based evaluation of acetabular changes for the purpose of age estimation in an Indian population. CT images of 250 individuals aged 10-88 years were scrutinized according to the features defined in the Calce method of acetabular age estimation. Scores were allotted to the various features and a cumulative score was calculated. No significant bilateral and sex differences were observed. Significant correlation was obtained between the scores for these defined characteristics and the chronological age of individuals. Population-specific regression models were generated for age estimation. The scoring method devised in the present research requires further validation as it represents a new tool for age estimation in medico-legal cases.

Computed tomographic age estimation from the pubic symphysis using the Suchey-Brooks method: A Systematic Review and Meta-analysis

Forensic age estimation is routinely applied in investigations involving identification of individuals. Over the past century a myriad of methods have been devised for age estimation. One such method, proposed by Suchey and Brooks in 1990, groups the observed changes occurring in the pubic symphysis into six phases, each defined by a corresponding age range. The present study was piloted with the focussed question being to empirically determine the accuracy of the Suchey-Brooks method in computed tomographic age estimation by analysing morphological changes occurring in the pubic symphysis. Original articles pertaining to the use of the Suchey-Brooks method for CT based age estimation were extracted from four different databases- PubMed, CENTRAL, Google Scholar and ScienceDirect. Research papers which were answering the focussed question were selected for data analysis. After assessing the risk of bias of the selected articles, the data was subjected to Meta-analysis. Pooled analysis of correctly/accurately aged individuals/remains using the random and fixed effect models yielded a prediction percentage of 78% and 86%, respectively. Higher percentages were obtained for phase-wise and subgroup analysis, indicating that the Suchey-Brooks method is a reliable method for age estimation.

Age estimation based on the acetabulum using global illumination rendering with computed tomography

INTRODUCTION

The acetabulum has been reported as a reliable age estimation marker. However, analyzing its morphological changes can be challenging using computed tomography (CT) imaging. Newly introduced global illumination rendering (GIR) applied to CT can improve the visualization of the fine details and thus the method's performance. This study aimed to analyze age estimation using morphological features of the acetabulum using GIR applied to CT.

METHODS

We collected 200 postmortem CT scans. A segmentation of the acetabular joint was initially done. Then, three-dimensional (3D) reconstruction of the images was performed using GIR. These images were saved and then analyzed by two operators based on the three morphological criteria described in the Rougé-Maillart method. Reproducibility was assessed by intraclass correlation (ICC). Age estimation was assessed by multiple linear regression.

RESULTS

The sample was composed of 155 males and 45 females, with a mean age of 50 ± 18.3 years old. We observed high agreement in both the inter-observer and intra-observer reproducibility for the three variables (ICC of 75.6 to 90.8% and 89.3 to 95.8%, respectively) and the total score (ICC of 93.5% and 95%, respectively). The three variables, as well as the total score, were significantly correlated with age groups. The total score showed a prediction rate higher than 85% for ages under 40 and over 70 years old. We identified three models with two validated models with an adjusted R² of 85.6% and 84.8%, respectively; a standard error of 0.688 and 0.706, respectively; and a good correlation of all variables and no inter-correlation. The first validated model included the three morphological criteria scores, and the second model was based on the total score.

CONCLUSION

GIR applied to CT provides photorealistic images that can be useful for forensic imaging intended for age estimation based on morphological methods.

Cone-beam computed tomography cinematic rendering: clinical, teaching and research applications

Cone-beam computed tomography (CBCT) is an essential imaging method that increases the accuracy of diagnoses, planning and follow-up of endodontic complex cases. Image postprocessing and subsequent visualization relies on software for three-dimensional navigation, and application of indexation tools to provide clinically useful information according to a set of volumetric data. Image postprocessing has a crucial impact on diagnostic quality and various techniques have been employed on computed tomography (CT) and magnetic resonance imaging (MRI) data sets. These include: multiplanar reformations (MPR), maximum intensity projection (MIP) and volume rendering (VR). A recent advance in 3D data visualization is the new cinematic rendering reconstruction method, a technique that generates photorealistic 3D images from conventional CT and MRI data. This review discusses the importance of CBCT cinematic rendering for clinical decision-making, teaching, and research in Endodontics, and a presents series of cases that illustrate the diagnostic value of 3D cinematic rendering in clinical care.