ABSTRACT
The aim of this study was to investigate the potential of using multidetector computed tomography (MDCT) to measure the bone mineral density (BMD) in the medial meta-epiphyseal region of clavicle (MERC) for adult age estimation. A total of 1064 chest MDCT scans from individuals aged 21 to 102 years were utilized to determine the MERC BMD. The Mimics software was used for the BMD measurements, and the average BMD of both MERC was also calculated. Regression analysis was conducted with chronological age as a dependent variable and MERC BMD as an independent variable to establish a mathematical model for age estimation. The mean absolute error (MAE) was calculated to evaluate the accuracy of the regression model using an independent validation sample. Among all the models, the cubic regression model showed the highest correlation between MERC BMD and chronological age and also provided the most accurate age prediction for both males and females (MAE = 9.41 for males, MAE = 10.38 for females). Our study suggests that BMD measured by MERC can be utilized for age estimation in adults when more reliable indicators are not available.
ABSTRACT
This study aimed to explore and develop data mining models for adult age estimation based on CT reconstruction images from the sternum. Maximum intensity projection (MIP) images of chest CT were retrospectively collected from a modern Chinese population, and data from 2700 patients (1349 males and 1351 females) aged 20 to 70 years were obtained. A staging technique within four indicators was applied. Several data mining models were established, and mean absolute error (MAE) was the primary comparison parameter. The intraobserver and interobserver agreement levels were good. Within internal validation, the optimal data mining model obtained the lowest MAE of 9.08 in males and 10.41 in females. For the external validation (N = 200), MAEs were 7.09 in males and 7.15 in females. In conclusion, the accuracy of our model for adult age estimation was among similar studies. MIP images of the sternum could be a potential age indicator. However, it should be combined with other indicators since the accuracy level is still unsatisfactory.
Subject(s)
Sternum , Tomography, X-Ray Computed , Adult , Male , Female , Humans , Retrospective Studies , Tomography, X-Ray Computed/methods , Sternum/diagnostic imaging , Data Mining , ChinaABSTRACT
OBJECTIVE: Adult age estimation (AAE) is a challenging task. Deep learning (DL) could be a supportive tool. This study aimed to develop DL models for AAE based on CT images and compare their performance to the manual visual scoring method. METHODS: Chest CT were reconstructed using volume rendering (VR) and maximum intensity projection (MIP) separately. Retrospective data of 2500 patients aged 20.00-69.99 years were obtained. The cohort was split into training (80%) and validation (20%) sets. Additional independent data from 200 patients were used as the test set and external validation set. Different modality DL models were developed accordingly. Comparisons were hierarchically performed by VR versus MIP, single-modality versus multi-modality, and DL versus manual method. Mean absolute error (MAE) was the primary parameter of comparison. RESULTS: A total of 2700 patients (mean age = 45.24 years ± 14.03 [SD]) were evaluated. Of single-modality models, MAEs yielded by VR were lower than MIP. Multi-modality models generally yielded lower MAEs than the optimal single-modality model. The best-performing multi-modality model obtained the lowest MAEs of 3.78 in males and 3.40 in females. On the test set, DL achieved MAEs of 3.78 in males and 3.92 in females, which were far better than the MAEs of 8.90 and 6.42 respectively, for the manual method. For the external validation, MAEs were 6.05 in males and 6.68 in females for DL, and 6.93 and 8.28 for the manual method. CONCLUSIONS: DL demonstrated better performance than the manual method in AAE based on CT reconstruction of the costal cartilage. CLINICAL RELEVANCE STATEMENT: Aging leads to diseases, functional performance deterioration, and both physical and physiological damage over time. Accurate AAE may aid in diagnosing the personalization of aging processes. KEY POINTS: ⢠VR-based DL models outperformed MIP-based models with lower MAEs and higher R2 values. ⢠All multi-modality DL models showed better performance than single-modality models in adult age estimation. ⢠DL models achieved a better performance than expert assessments.
Subject(s)
Costal Cartilage , Deep Learning , Male , Female , Humans , Adult , Middle Aged , Retrospective Studies , Tomography, X-Ray Computed/methods , ThoraxABSTRACT
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.
ABSTRACT
OBJECTIVES: To assess the performance of knee MRI for forensic age prediction and classification for 12-, 14-, 16-, and 18-year thresholds. METHODS: The ossification stages of distal femoral epiphyses and proximal tibial epiphyses were assessed using an integrated staging system by Schmeling et al. and Kellinghaus et al. for knee 3.0T MRI with T1-weighted turbo spin-echo (T1-TSE) in sagittal orientation among 852 Chinese Han individuals (483 males and 369 females) aged 7-30 years. Regression models for age prediction were constructed and their performances were evaluated based on mean absolute deviation (MAD) values. In addition, the performances of age classification were assessed using receiver operating characteristic (ROC) analyses. RESULTS: The intra- and inter-observer agreement levels were very good (κ > 0.80). The complete fusion of those two types of epiphyses took place before 18.0 years in our study participants. The minimum MAD values were 2.51 years (distal femur) and 2.69 years (proximal tibia) in males, and 2.75 years (distal femur) and 2.87 years (proximal tibia) in females. The specificity values of constructed prediction models were all above 90% for the 12-, 14-, and 16-year thresholds, compared to the 74.8-84.6% for the 18-year threshold. Better performances of age prediction and classification were observed in males by distal femoral epiphyses. CONCLUSIONS: Ossification stages via 3.0T MRI of the knee with T1-TSE sequence using an integrated staging system could be a reliable noninvasive method for age prediction or for age classification for 12-, 14-, and 16-year thresholds, especially in males by distal femoral epiphyses. However, assessments based on the full bony fusion of the distal femoral epiphysis and proximal tibial epiphysis seemed not reliable for age classification for the 18-year threshold in the Chinese Han population.
Subject(s)
Age Determination by Skeleton , Epiphyses , Age Determination by Skeleton/methods , China , Epiphyses/diagnostic imaging , Female , Femur/diagnostic imaging , Humans , Magnetic Resonance Imaging/methods , Male , Osteogenesis , Tibia/diagnostic imagingABSTRACT
OBJECTIVES: To expand the database on magnetic resonance imaging (MRI) analysis of distal tibial and calcaneal epiphyses as proposed by Saint-Martin et al. and investigate a more elaborate staging technique to establish regression models for age estimation in a modern Chinese Han population. MATERIALS AND METHODS: T1-weighted ankle MRIs were retrospectively collected from April 2008 to July 2019, and data from 590 individuals (372 males and 218 females; aged from 8 to 25 years old) were obtained. One-sided sagittal images were assessed because data from both sides were considered coincidental, as no significant differences were found (P > 0.05). Three-stage and six-stage staging techniques were applied separately and subsequently compared. A subset was re-assessed a second time and by a different observer. Regression models were established accordingly. RESULTS: Our results showed very good repeatability and consistency of two staging techniques (all Cohen's kappa values were more than 0.8). By comparison, the values of the coefficient of determination (R2) of the six-stage technique were generally higher than those of the three-stage technique. Compared with the distal tibia and two ankle bones combined, the calcaneus decreased the mean absolute deviation (MAD) with the six-stage technique. In males, incorporating only the calcaneus resulted in a MAD of 2.15 years, with correct classification rates of 87.5% adults and 50.0% among minors. In females, the corresponding results were 1.67 years, 100.0%, and 44.4%, respectively. CONCLUSIONS: The six-stage technique may outperform the three-stage technique in MRI analysis of ankle bones for age estimation, while age estimation based on the calcaneus may perform better than that based on the distal tibia or both ankle bones in a modern Chinese Han population.
Subject(s)
Age Determination by Skeleton/methods , Ankle Joint/diagnostic imaging , Calcaneus/diagnostic imaging , Epiphyses/diagnostic imaging , Adolescent , Ankle Joint/growth & development , Asian People/ethnology , Calcaneus/growth & development , Child , Epiphyses/growth & development , Female , Humans , Magnetic Resonance Imaging , Male , Regression Analysis , Reproducibility of Results , Young AdultSubject(s)
Coronavirus Infections , Disease Outbreaks , Pandemics , Pneumonia, Viral , Autopsy , Betacoronavirus , COVID-19 , Humans , Italy/epidemiology , SARS-CoV-2ABSTRACT
Age estimation is an important topic of human identification in forensic practice, especially coming to biological samples in crime scene, such as blood, saliva, semen. As rate-limiting enzyme in Nucleotide excision repair (NER) that was associated with aging, Excision repair cross-complementation group 5 (ERCC5) was considered to be a candidate biomarker for individual age estimation. The ERCC5 mRNA and protein expression levels association with age have been demonstrated in our previous study. However, very little is known about relationship DNA-based quantification of ERCC5 with age. In this study, we detected ERCC5 level in peripheral blood from a Chinese Han population by SYBR qPCR assay to gain better insight into the quantitative relationship with age. The results showed ERCC5 level declined with individual age with a negative correlation(r = -0.8, R2 = 0.63, P < 0.001). The data model for age estimation based on ERCC5 level was Y = -31.352X + 14.436 ± 10.28 (Y: age, year; X: CqTBP-CqERCC5; standard error: year). The accuracy about the data model for age estimation was about 73.33%. The mean absolute difference (MAD) values were 8.22, 8.09 and 8.38 in total, male and female, respectively. Furthermore, ERCC5 quantification for age estimation was also applicable for stored blood samples under low temperature up to 6 months. It was suggested that the ERCC5 quantification was expected to be a valuable additional method for individual age estimation, especially in cases where traditional morphologic method is absent or inefficient in forensic practice.
Subject(s)
Aging , DNA Repair , China , DNA , Female , Humans , Male , RNA, MessengerABSTRACT
To develop population - specific stature prediction equations from measurements of the lower limb bone in a contemporary Chinese. 303 individuals of Han group in Western China, including 201 females and 102 males were collected. The study sample was randomly divided into two subgroups. A calibration sample, which consisted of 171 females and 87 males, was used to develop the regression formula. A validation sample comprising the remaining 30 female and 15 male individuals was then used to test the predictive accuracy of the established formula. The regression equations were developed from intact bones and fragments of the femur, tibia and fibula, the maximum lengths of femur, tibia, and fibula were highly correlated with the stature. The maximum length of femur provide the most accurate result with the prediction accuracy of 3.84â¯cm for unknown sex, 4.00â¯cm in the male group, 3.45â¯cm in the female group, 3.61â¯cm in the group with age no more than 45, 3.45â¯cm in the group with age above 45. Moreover, the multiple regression equations were developed, and they portray a more accurate stature in instances in which the femur, tibia and fibula are available. This paper provides indications that the femur, tibia and fibula are important bones for stature estimation and they could be effectively used in forensic cases.
Subject(s)
Asian People , Body Height , Bones of Lower Extremity/anatomy & histology , Bones of Lower Extremity/diagnostic imaging , Adolescent , Adult , Aged , Anatomic Landmarks , Child , China , Female , Forensic Anthropology , Humans , Male , Middle Aged , Radiography , Regression Analysis , Young AdultABSTRACT
Sex estimation is an important part of creating a biological profile, and ultimately assisting in creating a presumptive identification of unidentified skeletal remains. However, manual methods of anthropometric are time-consuming and prone to observer variability. The present study is an attempt to estimation of sex from automatic measurement of patella by multidetector computed tomography (MDCT) in a contemporary Chinese population. Four measurements for every patella, including maximum height (MAXH), maximum breadth (MAXB), maximum thickness (MAXT) and patellar volume (PV), were automatically provided by the software from CT image of 300 Chinese. The sample is composed of 156 males and 144 females with an average age of 41.44 and 45.68 years, respectively. The statistical analyses showed that all variables were sexually dimorphic. Receiver operating characteristic (ROC) analysis was performed to estimate sex from patella. The univariate analysis of each patellar parameter yielded a sex classification accuracy rate of 73.1% to 85.7%. The classification accuracy rates of sex estimation using the combination of the patellar parameters are 81.9% to 91.6%. This paper provides indications that the patella is important bone for sex estimation and it may be used as an alternative in forensic cases when the skull and pelvis are unavailable.
Subject(s)
Forensic Anthropology/methods , Multidetector Computed Tomography , Patella/anatomy & histology , Patella/diagnostic imaging , Sex Determination by Skeleton/methods , Adolescent , Adult , Aged , Aged, 80 and over , Asian People , Female , Humans , Imaging, Three-Dimensional , Male , Middle Aged , ROC Curve , Sensitivity and Specificity , Young AdultABSTRACT
The present study is an attempt to estimation of stature and sex from skull measurements by multidetector computed tomography (MDCT) in contemporary Chinese. In the present study, fifteen measurements for every skull were taken from CT image of 382 Chinese. The sample was composed of 200 males and 182 females with an average age of 47 and 46â¯years, respectively. Discriminant function was used in sex determination and regression analysis was used in stature estimation from skull measurements. The stepwise analysis of all measurements yielded a sex classification accuracy rate of 89.3%. The classification accuracy rates of the univariate discriminant function analyses were from 50.5% to 84.8%. For stature estimation, the standard error of estimate (SEE) ranged from 5.072 to 6.355â¯cm for male, from 5.090 to 5.829â¯cm for female, respectively. This study is the first to provide a metric and statistical characterization of the skull in contemporary Chinese, and indicates that it is feasible to sex estimation by skull measurement. Furthermore, the equations presented for stature estimation in this study may be used as alternatives in forensic cases, particularly in cases where better predictors such as the long bones are not available.
Subject(s)
Body Height , Multidetector Computed Tomography , Sex Determination by Skeleton/methods , Skull/diagnostic imaging , Anatomic Landmarks , Asian People , Cephalometry , China , Discriminant Analysis , Female , Humans , Imaging, Three-Dimensional , Male , Middle AgedABSTRACT
The objective of the present study was to generate multiple regression models for stature estimation on the basis the combination of the clavicle, scapula and sternum derived from 3D-VRT images in Chinese population. The study sample comprised 363 individuals from China, including 159 females and 204 males, with documented ages between 19 and 82 years. Separate multiple linear regression equations for estimating stature on the basis of the measurements from the clavicle, scapula and sternum were then devised for males and females. For assessing the correlation between the stature and measurements of the clavicle, scapula and sternum, the Pearson's correlation coefficient was calculated and its significance was tested by Students t test. Finally, the multiple regression equations calculated from the measurements of the clavicle, scapula and sternum in relation to stature for each sex were established in the present study. The accuracy of stature prediction ranged from 4.777 to 5.313 cm for male and from 4.388 to 4.658 cm for female. In conclusion, the present results provide indications that the combination of the clavicle, scapula and sternum should be used as alternatives for stature estimation, and the multiple equations presented for stature estimation seem to be a more accurate than the equations from single bone.
Subject(s)
Body Height , Clavicle , Forensic Anthropology , Adult , Aged , Aged, 80 and over , China , Female , Humans , Male , Middle Aged , Regression Analysis , Scapula , Sternum , Young AdultABSTRACT
The present study is an attempt to estimation of stature and sex from sacrum and coccyx measurements by multidetector computed tomography (MDCT) in a contemporary Chinese population. Nine measurements for every sacrum and coccyx were taken from CT image of 350 Chinese. The sample is composed of 190 males and 160 females with an average age of 55 and 50â¯years, respectively. Discriminant function was used in sex estimation and regression analysis was used in stature estimation from these two bones. The stepwise analysis of all measurements yielded a sex classification accuracy rate of 84.9%. The classification accuracy rates of the univariate discriminant function analyses are 58.3%-76.9%. For stature estimation, the accuracy of stature prediction ranged from 4.891 to 6.107â¯cm for male, from 4.474 to 5.606â¯cm for female, respectively. This paper provides indications that the sacrum and coccyx are important bones for sex estimation and they could be effectively used as alternatives in forensic cases when the skull and pelvis are unavailable. Furthermore, the regression equations presented in this study may be useful for forensic estimation of the stature of Chinese individuals, particularly in cases where better predictors such as the long bones are not available.