Bone development shows certain regularity with age. The regularity can be used to infer age and serve many fields such as justice, medicine, archaeology, etc. As a non-invasive evaluation method of the epiphyseal development stage, MRI is widely used in living age estimation. In recent years, the rapid development of machine learning has significantly improved the effectiveness and reliability of living age estimation, which is one of the main development directions of current research. This paper summarizes the analysis methods of age estimation by knee joint MRI, introduces the current research trends, and future application trend.
Epiphyses/diagnostic imaging* ; Age Determination by Skeleton/methods* ; Reproducibility of Results ; Magnetic Resonance Imaging/methods* ; Knee Joint/diagnostic imaging*

OBJECTIVES: To find the appropriate method for age estimation for different ages and sexes. METHODS: The costal cartilage, sternum and pubic symphysis of 91 unknowns from 2000 to 2020 from the Forensic Department of the Criminal Investigation Team of Shanghai Public Security Bureau were collected. Costal cartilage, sternal and pubic symphysis inferences were used to estimate the age, and the consistency between the estimated results and the actual physiological age of the unknowns was tested. The accuracy of age estimation of different samples was compared, and the relationship between accuracy and age and sex was analyzed. RESULTS: Using the costal cartilage method, the inference errors of males, females and the whole population under 40 years old were (0.608±2.298) years, (0.429±1.867) years and (0.493±2.040) years, while those over 40 years old were (-1.707±3.770) years, (-3.286±4.078) years and (-2.625±4.029) years. The differences between different age groups in these three populations were statistically significant (P<0.05). Using the sternum method, the inference errors of males and females under the age of 40 were (0.921±3.019) years and (0.452±1.451) years, while those over the age of 40 were (-5.903±5.088) years and (-1.429±2.227) years. The differences between different age groups in males and females were statistically significant (P<0.05). Using the pubic symphysis method, the inference errors of males and females under 40 years old were (-0.204±1.876) years and (0.238±2.477) years, while those over 40 years old were (1.500±2.156) years and (-2.643±4.270) years. The differences between different age groups in males and females were statistically significant (P<0.05). Using the sternum method and pubic symphysis method for age estimation of over 40 years old, the difference between different sexes was statistically significant (P<0.05). CONCLUSIONS All three methods of age estimation are stable and effective and more accurate for people under 40 years old. For age estimation of unknowns over 40 years old, the pubic symphysis method is preferred in males and the sternum method is preferred in females.
Adult ; Age Determination by Skeleton/methods* ; Child, Preschool ; China ; Female ; Forensic Anthropology/methods* ; Forensic Medicine ; Humans ; Infant ; Male ; Pubic Symphysis/anatomy & histology*

Objective To establish a regression algorithm model that applies to bone age estimation of Xinjiang Uygur adolescents with machine learning methods such as histogram of oriented gradient （HOG）, local binary patterns （LBP）, support vector machine （SVM）, principal component analysis （PCA）. Methods DR images of knee-joints from 275 male and 225 female subjects aged 12.0-<19.0 years old were collected, PCA method was used to reduce the dimensionality of the HOG and LBP features, and support vector regression （SVR） was used to establish a knee-joint bone age estimation algorithm model. Stratified random sampling method was used to select 215 male samples, 180 female samples for the model training set. K-fold cross validation method was used to optimize parameters of the model. The remaining samples as the independent test set was used to compare the sample's true age and model estimated age, and had an accuracy rate in the statistical error range of ±0.8 and ±1.0 years, respectively. Then the mean absolute error （MAE） and root mean square error （RMSE） were calculated. Results The accuracy rate of male in the statistical error range of ±0.8 and ±1.0 year was 80.67%, 89.33%, respectively. The MAE and RMSE were 0.486 and 0.606 years, respectively. The accuracy rate of female in the statistical error range of ±0.8 and ±1.0 years was 80.19%, 90.45%, respectively. The MAE and RMSE were 0.485 and 0.590 years, respectively. Conclusion Establishment of prediction model for bone age estimation by feature dimension reduction of HOG and LBP in DR images of knee-joint based on PCA and SVM has relatively high accuracy.
Adolescent ; Adult ; Age Determination by Skeleton/methods* ; Algorithms ; Asian People/ethnology* ; China ; Female ; Humans ; Image Processing, Computer-Assisted ; Knee Joint/diagnostic imaging* ; Machine Learning ; Male ; Principal Component Analysis ; Support Vector Machine ; Young Adult

Individual identification by measuring the human skeleton is an important research in the field of forensic anthropology. Computed tomography （CT） technology can provide high-resolution image of skeleton. Skeleton image can be reformed by software in the post-processing workstation. Different skeleton measurement indexes of anthropology, such as diameter, angle, area and volume, can be measured on section and reformative images. Measurement process is barely affected by human factors. This paper reviews the literatures at home and abroad about the application of measuring skeleton by CT in forensic anthropology research for individual identification in four aspects, including sex determination, height infer, facial soft tissue thickness measurement and age estimation. The major technology and the application of CT in forensic anthropology research are compared and discussed, respectively.
Age Determination by Skeleton ; Bone and Bones/diagnostic imaging* ; Forensic Anthropology/trends* ; Humans ; Sex Determination Analysis ; Software ; Tomography, X-Ray Computed/methods*

OBJECTIVE: To compare the reliability of the Greulich-Pyle (GP) method, Tanner-Whitehouse 3 (TW3) method and Korean standard bone age chart (KS) in the evaluation of bone age of prepubertal healthy Korean children. MATERIALS AND METHODS: Left hand-wrist radiographs of 212 prepubertal healthy Korean children aged 7 to 12 years, obtained for the evaluation of the traumatic injury in emergency department, were analyzed by two observers. Bone age was estimated using the GP method, TW3 method and KS, and was calculated in months. The correlation between bone age measured by each method and chronological age of each child was analyzed using Pearson correlation coefficient, scatterplot. The three methods were compared using one-way analysis of variance. RESULTS: Significant correlations were found between chronological age and bone age estimated by all three methods in whole group and in each gender (R2 ranged from 0.87 to 0.9, p < 0.01). Although bone age estimated by KS was slightly closer to chronological age than those estimated by the GP and TW3 methods, the difference between three methods was not statistically significant (p > 0.01). CONCLUSION: The KS, GP, and TW3 methods show good reliability in the evaluation of bone age of prepubertal healthy Korean children without significant difference between them. Any are useful for evaluation of bone age in prepubertal healthy Korean children.
Age Determination by Skeleton/*methods ; Asian Continental Ancestry Group ; Child ; Emergency Service, Hospital ; Female ; Hand/*radiography ; Humans ; Male ; Republic of Korea ; Wounds and Injuries

OBJECTIVETo investigate the maturation of individual bones on the hand and wrist in children with central precocious puberty (CPP) and idiopathic short stature (ISS).

METHODSHand and wrist films of 25 children with CPP, 29 children with ISS and 21 normal controls were evaluated by conventional Greulich-Pyle (GP) atlas method and individual bone assessment method, in which all twenty bones of the hand and wrist were evaluated based on GP atlas, including 2 radius and ulna, 7 carpal bones, 11 metacarpal and phalangeal bones, the average bone age (BA) was calculated. The differences in groups were analyzed by independent samples t test. The differences between the two methods were analyzed by paired sample t test. The differences between BA and chronological age (CA) were analyzed by ROC with SPSS 17.0.

RESULTSCompared with the normal control group, the advance of BA in the CPP group was 0.70-2.26 y (1.48 ±0.78) by the GP atlas method, while that was 0.28-2.00 y(1.14 ±0.86) by the individual bone evaluation method. In all twenty bones, the advance of metacarpal and phalangeal BA was the greatest [0.34-2.06 y(1.2±0.86)]. In the ISS group,the delay of BA was 0.47-2.91 y(-1.69±1.22) by the GP atlas method, while that was 0.48-2.50 y (-1.49±1.01) by individual bone evaluation method.The delay of carpal BA was the greatest [0.59-2.73 y(-1.66±1.07)] in all twenty bones. In the ISS group and the normal control group, there were no statistic differences between the two methods. In the CPP group, statistic difference was found between two methods. There were no statistic differences for the areas under ROC curves between two methods.

CONCLUSIONThe advance of metacarpal and phalangeal BA is the greatest in CPP group and the delay of carpal BA is the greatest in ISS group.Both methods provide diagnostic information for bone age in CPP and ISS children.

Age Determination by Skeleton ; methods ; Carpal Bones ; diagnostic imaging ; Case-Control Studies ; Child ; Dwarfism ; diagnostic imaging ; Female ; Hand ; diagnostic imaging ; Humans ; Male ; Puberty, Precocious ; diagnostic imaging

OBJECTIVE: To estimate the chronological age of Han teenagers in Sichuan by the epiphyses development characteristics of iliac crest and ischial tuberosity in X-ray digital images. METHODS: According to TW2 classification principle, combining with the age range of our subjects and epiphyses development regularity, the degree of epiphyses development of iliac crest and ischial tuberosity had been divided into 8 grades (0-7) and 7 grades (0-6), respectively. Based on the degrees, the pelvic X-rays digital images of 691 samples of 16-20 aged teenagers were read and statistically analyzed by SPSS 19.0 software. The multiple linear regression equation was established by skeletal age (Y), development degree of iliac crest epiphyses (X1) and ischial tuberosity epiphyses (X2). RESULTS: There were no statistical differences between two sides of epiphyses development of iliac crest and ischial tuberosity (P>0.05). There were no statistical difference between genders (P>0.05). The re-substitution method of the samples showed that the accuracy of equation as Y=15.269+0.444X1+0.236 X2 was high. The result of the re-substitution method showed a high accuracy of the equation. CONCLUSION The multiple linear regression equation could be used to identify the skeletal age for providing the scientific basis to identify the 18-year-old Han population in Sichuan.
Adolescent ; Age Determination by Skeleton/methods* ; Age Factors ; Asian People/ethnology* ; Bone Development/physiology* ; China/ethnology* ; Epiphyses/diagnostic imaging* ; Female ; Forensic Anthropology/methods* ; Humans ; Ilium/diagnostic imaging* ; Ischium/diagnostic imaging* ; Linear Models ; Male ; Pelvis/diagnostic imaging* ; Tomography, X-Ray Computed ; Young Adult

It is practical value for determination the teenagers whether the age is full of the legal responsibility age of 18 years old or not by estimating skeletal age of sternal end of clavicle. The traditional methods mainly based on X-ray radiography. However, sternal end of clavicle and adjacent lung, bronchus, sternum, rib, transverse process of thoracic vertebra are overlapped each other. As a result of overlapping, there will be obtained false negative or positive film reading results when according to X-ray observation of epiphyseal growth of sternal end of clavicle, which directly affect the scientificalness and accuracy of estimating of skeletal age. In recent years, the scholars at home and abroad have started to use thin layer CT scan technology to estimate skeletal age of the sternal end of clavicle. With the 2D and 3D CT recombination technology, the accuracy of the film reading distinctly improves by making the shape, size and position of epiphysis displayed clearly. This article reviews the application and research progress of thin layer CT scanning technology in estimating skeletal age of sternal end of clavicle at home and abroad, analyzes the superiority and value of thin layer CT scan technology, which applied to skeletal age of sternal end of clavicle.
Adolescent ; Age Determination by Skeleton/methods* ; Clavicle/growth & development* ; Epiphyses/growth & development* ; Female ; Forensic Anthropology/methods* ; Humans ; Image Processing, Computer-Assisted ; Male ; Osteogenesis ; Retrospective Studies ; Sternum/growth & development* ; Tomography, X-Ray Computed/methods* ; Young Adult

OBJECTIVE: To establish a CT staging method of sternal end of clavicle epiphyseal growth for teenagers by thin layer CT scan, multiplanar reconstruction (MPR) and volume reconstruction (VR) technologies. METHODS: The CT imaging characteristics, which collected from 460 teenagers (aged from 15 to 25) in East and South China, were studied through both sternal ends of clavicles' imagings by thin layer coronal CT scan and axial CT scan, MPR and VR technologies. The parameters of sternal end of clavicle including the longest diameter of epiphysis, the longest diameter of metaphysis, their length ratio, area of epiphysis, area of metaphysis, and their area ratio were measured and calculated in order to establish new classification. RESULTS: Based on the staging method of Schmeling, integrating the CT imaging reconstruction information of sternal end of clavicle, the new classification of sternal end of clavicle epiphyseal growth were divided into 1 to 5 stages, and stage 2 and stage 3, respectively, contained a, b and c sub-classification. CONCLUSION This new classification has merits of large sample size, wide age range and easy operability. By using CT imaging reconstruction techniques and analyzing the data which closely related to sternal end of clavicle epiphyseal growth of teenagers, the feasibility of the staging method could be increased.
Adolescent ; Adult ; Age Determination by Skeleton/methods* ; China ; Clavicle/growth & development* ; Epiphyses/growth & development* ; Feasibility Studies ; Female ; Forensic Anthropology ; Humans ; Image Processing, Computer-Assisted ; Male ; Osteogenesis ; Sex Characteristics ; Sternum/growth & development* ; Tomography, X-Ray Computed ; Young Adult

OBJECTIVE: To discuss bone development trend in the knee joint of Tibetan teenagers in Sichuan province and to effectively update the database for estimating the living age of Tibetan teenagers in terms of bone age of the knee joint. METHODS: Radiographs including epiphysis of distal femur, proximal tibia and proximal fibula were taken from 483 Tibetan male and female teenagers aged from 14 to 19 years old in Aba prefecture of Sichuan province in order to observe epiphyseal growth situation. The descriptive data of the epiphyseal closure ages of these teenagers' knee joints were statistically analyzed by SPSS 16.0 software. RESULTS: The distal femur epiphyseal closure occurred earliest, while the proximal fibula epiphyseal closure occurred latest. The epiphyseal growth of knee joints of females occurred about one year earlier than that of males. CONCLUSION The forensic information and data related to Tibetan teenagers' bone age identification should be updated regularly. These results provide potential value for the practice of forensic medicine, anthropology and clinical medicine.
Adolescent ; Age Determination by Skeleton/methods* ; Bone Development/physiology* ; China/ethnology* ; Epiphyses/growth & development* ; Female ; Femur/growth & development* ; Humans ; Knee Joint/growth & development* ; Male ; Sex Characteristics ; Tibia/growth & development* ; X-Ray Film ; Young Adult