Age estimation based on computed tomography exploration: a combined method

Bascou, Agathe; Dubourg, Olivier; Telmon, Norbert; Saint‐Martin, Pauline; Savall, F.

doi:10.1007/s00414-021-02666-0

Cited by 17 publications

(5 citation statements)

References 31 publications

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“…[27][28][29]33,50,55,64 A major share of investigations with the Suchey-Brooks method utilized descriptives reported within the original study to establish the accuracy and precision associated with the method. 9,[22][23][24][25][26]28,29,[31][32][33]35,[40][41][42][43]45,[47][48][49][50][51][52][53][54][55][56][57][59][60][61] However, the application of such fixed descriptive parameters to demographically variant population groups can often induce bias, namely, age mimicry and population bias amongst others. A characteristic result of this age mimicry bias is the over-ageing observed with younger individuals and under-ageing observed with older individuals.…”

Section: Discussionmentioning

confidence: 99%

“…30,38,39 The standard error for consecutive phase transitions was also observed to increase with progressing transitions in both sexes, corroborating the higher error rates associated with ageing older individuals. 9,[23][24][25][26]28,29,[31][32][33]35,41,48,[50][51][52][54][55][56][57]61 Mean transition age values obtained with males of an Indian population are lower than those reported by Kimmerle et al 38 for a Balkan population. However, the mean transition age obtained herein for phases V and VI in males is higher than those reported by Lottering et al 39 for an Australian population and Hisham et al 33 for a Malaysian population.…”

Section: Discussionmentioning

confidence: 99%

“…21 However, in the years that followed, investigations undertaken with the Suchey–Brooks method using different population groups demonstrated varying applicability. 9,22–72 Moreover, despite being one of the most commonly utilized age estimation methods, investigations evaluating the forensic suitability of the Suchey–Brooks method for ageing an Indian population are currently limited. 73…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2023

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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.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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

et al. 2023

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“…As such, the decrease in trabecular bone begins prematurely -during early adulthood -in both sexes when compared with cortical bone loss [18]. Imaging studies of skeletal age modifications in adults have portrayed metamorphosis of bone structure, bone loss, as well as changes in gross morphology during different stages of life, e.g., [16,[19][20][21][22][23][24][25][26][27][28][29][30][31]. Age-related changes in trabecular structure and bone loss are well described [32,33], and macroscopically observable features of trabecular bone in different skeletal locations have been used to develop and evaluate aging standards in adult individuals, e.g., [19,[34][35][36][37][38][39].…”

Section: Introductionmentioning

confidence: 99%

Eigenfemora – Age at Death Estimation in the Proximal Femur through an Image Processing Approach

Navega,

Ferreira,

Curate

2023

Preprint

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Estimating age at death is essential to establish a biological profile from human skeletal remains in both forensic and archeological settings. Imaging studies of skeletal age changes in adults have described metamorphosis of trabecular bone structure and bone loss in the proximal femur , as well as changes in morphology during different stages of life. This study aims to assess the utility of a digital representation of conventional X-ray films of the proximal femur for the estimation of age at death in a sample of 91 adult individuals (47 females and 44 males) of the Coimbra Identified Skeletal Collection. The proposed approach showed a root mean squared error (RMSE) of 17.32 years (and mean absolute error of 13.47 years) for females and an RMSE of 14.06 years (mean absolute error of 11.08 years) for males. The main advantage of this approach is the consistency in the feature detection and extraction, as X-ray images projected on the femora space will always produce the same set features to be analyzed for age estimation while more traditional methods rely heavily on operator experience which can lead to inconsistent age estimates among experts.

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“…As such, the decrease in the trabecular bone begins prematurely-during early adulthood-in both sexes when compared with cortical bone loss [18]. Imaging studies of skeletal age modifications in adults have portrayed the metamorphosis of bone structure and bone loss as well as changes in the gross morphology during different stages of life; e.g., [16,[19][20][21][22][23][24][25][26][27][28][29][30][31]. Age-related changes in trabecular structure and bone loss are well described [32,33], and macroscopically observable features of trabecular bones in different skeletal locations have been used to develop and evaluate aging standards in adult individuals; e.g., [19,[34][35][36][37][38][39].…”

Section: Introductionmentioning

confidence: 99%

Eigenfemora—Age-at-Death Estimation in the Proximal Femur through an Image Processing Approach

Navega,

Ferreira,

Curate

2023

Forensic Sciences

View full text Add to dashboard Cite

Estimating age at death is essential to establish biological profiles from human skeletal remains in both forensic and archeological settings. Imaging studies of skeletal age changes in adults have described the metamorphosis of trabecular bone structure and bone loss in the proximal femur as well as changes in morphology during different stages of life. This study aims to assess the utility of a digital representation of conventional X-ray films of the proximal femur for the estimation of age at death in a sample of 91 adult individuals (47 females and 44 males) of the Coimbra Identified Skeletal Collection. The proposed approach showed a root mean squared error (RMSE) of 17.32 years (and mean absolute error of 13.47 years) for females and an RMSE of 14.06 years (mean absolute error of 11.08 years) for males. The main advantage of this approach is consistency in feature detection and extraction, as X-ray images projected on the femora space will always produce the same set features to be analyzed for age estimation, while more traditional methods rely heavily on operator experience that can lead to inconsistent age estimates among experts.

show abstract

Age estimation based on computed tomography exploration: a combined method

Cited by 17 publications

References 31 publications

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

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

Eigenfemora – Age at Death Estimation in the Proximal Femur through an Image Processing Approach

Eigenfemora—Age-at-Death Estimation in the Proximal Femur through an Image Processing Approach

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