The persistence of epiphyseal scars in the distal radius in adult individuals

Medico-legal indicators and cut-offs in different age classes through quantitative analysis of epiphyseal fusion segments on knee CT scans

Scientists are interested in determining age in subadults for several forensic purposes. High- resolution instrumental techniques are being increasingly used for age estimation, driven by the need to minimize errors; in this context, several studies have focused on the knee joint, recognized as a potential site for age examination in late adolescence. We analyzed 200 CT scans performed on Russian subjects (106 males and 94 females) between 13 and 20 years, without growth diseases, endocrine disorders, or osteodystrophy. Each subject underwent two scans, one for each leg. Two indicators were measured for each bone (femur, tibia and fibula): the entire length of the epiphyseal scar and the length of the part/s that is/are fused with metaphysis. Intra class Correlation Coefficient (ICC) was performed to evaluate the intra-operator reproducibility. The ratio between the two lengths was calculated for each bone (FemurR, TibiaR and FibulaR). The first aim was to evaluate a correlation between the ratios of the three bones and the three bones treated as a single parameter (given by the sum of the ratios) versus age. The results showed good correlations in both cases (τ a = 0.74, 0.64, 0.57 and 0.67). The second aim was to estimate the cut-offs derived from the sum of the three ratios respect to four age classes (14-15 years: cut-off ≤ 0.63, 15-16 years: cut-off ≤ 1.19, 16-17 years: cut-off ≥ 0.68 and 17-18 years: cut-off ≥ 1.49. The results from this research encourage further studies of the knee joint as an indicator of legal adult age.

Age Estimation in Sportspersons From the Epiphyseal Fusion Around Wrist, Elbow, and Pelvic Joints

Background Age estimation of an individual is an integral part of medicolegal work. Out of many scenarios for which age estimation is performed, competitive sports is the one emerging field where experts are consulted for providing accurate age of the athlete. Owing to the chances of deliberately increasing (padding) or decreasing (shaving) the age of the athlete for his own advantage, accurate age estimation is crucial. The Sports Authority of India (SAI) mandates age verification from experts prior to participation in sports events in various age group categories. One of the widely used methods of age estimation in athletes is the radiological examination of the ossification centers of bones. Methodology The study was performed on 134 athletes (72 males and 62 females) with an age range of 12-18 years old with due permission from the Sports Authority of India (SAI) for this study. These participants compete at state, national, and international levels in squash, handball, swimming, cricket, and judo in under-14, under-16, and under-19 age categories. X-rays of the wrists, elbows, and pelvis were analyzed using the Schmeling five-stage method for the fusion of ossification centers. Results A greater degree of correlation between the fusion stages of all regions of interest and chronological age was observed in males than in females. The highest correlation in both sexes is observed between the fusion score of the head of the radius and the age (R = 0.814 for males and R = 0.647 for females). The lowest correlation for both males and females is seen between the fusion score of the lateral epicondyle of the humerus and age (R = 0.754 for males and R = 0.441 for females). Multiple linear regression models showed a standard error of estimate (SEE) of 1.093 years for the elbow joint, 1.147 years for the wrist joint, 1.039 years for the pelvis joint, and 1.030 years for all three joints. Conclusion Regression models generated for estimating the age of sportspersons from the ossification centers of the elbow, wrist, and pelvis in the present study can be applied for the age estimation of individuals aged between 12 and 18 years. Future population-specific studies on the age estimation of sportspersons with greater sample sizes are necessary to validate the findings of the present study.

Comparison of reliability of magnetic resonance imaging using cartilage and T1-weighted sequences in the assessment of the closure of the growth plates at the knee

Background

Growth development is traditionally evaluated with plain radiographs of the hand and wrist to visualize bone structures using ionizing radiation. Meanwhile, MRI visualizes bone and cartilaginous tissue without radiation exposure.

Purpose

To determine the state of growth plate closure of the knee in healthy adolescents and young adults and compare the reliability of staging using cartilage sequences and T1-weighted (T1W) sequence between pediatric and general radiologists.

Material and Methods

A prospective, cross-sectional study of MRI of the knee with both cartilage and T1W sequences was performed in 395 male and female healthy subjects aged between 14.0 and 21.5 years old. The growth plate of the femur and the tibia were graded using a modified staging scale by two pediatric and two general radiologists. Femur and tibia were graded separately with both sequences.

Results

The intraclass correlation was overall excellent. The inter- and intra-observer agreement for pediatric radiologists on T1W was 82% (κ = 0.73) and 77% (κ = 0.65) for the femur and 90% (κ = 0.82) and 87% (κ = 0.75) for the tibia. The inter-observer agreement for general radiologists on T1W was 69% (κ = 0.56) for the femur and 56% (κ = 0.34) for the tibia. Cohen’s kappa coefficient showed a higher inter- and intra-observer agreement for cartilage sequences than for T1W: 93% (κ = 0.86) and 89% (κ = 0.79) for the femur and 95% (κ = 0.90) and 91% (κ = 0.81) for the tibia.

Conclusion

Cartilage sequences are more reliable than T1W sequence in the assessment of the growth plate in adolescents and young adults. Pediatric radiology experience is preferable.

Staging Clavicular Development on MRI: Pitfalls and Suggestions for Age Estimation

BACKGROUND

MRI of the clavicle's sternal end has been studied for age estimation. Several pitfalls have been noted, but how they affect age estimation performance remains unclear.

PURPOSE/HYPOTHESIS

To further study these pitfalls and to make suggestions for a proper use of clavicle MRI for forensic age estimation. Our hypotheses were that age estimation would benefit from 1) discarding stages 1 and 4/5; 2) including advanced substages 3aa, 3ab, and 3ac; 3) taking both clavicles into account; and 4) excluding morphological variants.

STUDY TYPE

Prospective cross-sectional.

POPULATION

Healthy Caucasian volunteers between 11 and 30 years old (524; 277 females, 247 males).

FIELD STRENGTH/SEQUENCE

3T, T₁ -weighted gradient echo volumetric interpolated breath-hold examination (VIBE) MR-sequence.

ASSESSMENT

Four observers applied the most elaborate staging technique for long bone development that has been described in the current literature (including stages, substages, and advanced substages). One of the observers repeated a random selection of the assessments in 110 participants after a 2-week interval. Furthermore, all observers documented morphological variants.

STATISTICAL TESTS

Weighted kappa quantified reproducibility of staging. Bayes' rule was applied for age estimation with a continuation ratio model for the distribution of the stages. According to the hypotheses, different models were tested. Mean absolute error (MAE) differences between models were compared, as were MAEs between cases with and without morphological variants.

RESULTS

Weighted kappa equaled 0.82 for intraobserver and ranged between 0.60 and 0.64 for interobserver agreement. Stages 1 and 4/5 were allocated interchangeably in 4.3% (54/1258). Age increased steadily in advanced substages of stage 3, but improvement in age estimation was not significant (right P = 0.596; left P = 0.313). The model that included both clavicles and discarded stages 1 and 4/5 yielded an MAE of 1.97 years, a root mean squared error of 2.60 years, and 69% correctly classified minors. Morphological variants rendered significantly higher MAEs (right 3.84 years, P = 0.015; left 2.93 years, P = 0.022).

DATA CONCLUSION

Our results confirmed hypotheses 3) and 4), while hypotheses 1) and 2) remain to be investigated in larger studies.

LEVEL OF EVIDENCE

1 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2020;51:377-388.

Bone age assessment with various machine learning techniques: A systematic literature review and meta-analysis

BACKGROUND

The assessment of bone age and skeletal maturity and its comparison to chronological age is an important task in the medical environment for the diagnosis of pediatric endocrinology, orthodontics and orthopedic disorders, and legal environment in what concerns if an individual is a minor or not when there is a lack of documents. Being a time-consuming activity that can be prone to inter- and intra-rater variability, the use of methods which can automate it, like Machine Learning techniques, is of value.

OBJECTIVE

The goal of this paper is to present the state of the art evidence, trends and gaps in the research related to bone age assessment studies that make use of Machine Learning techniques.

METHOD

A systematic literature review was carried out, starting with the writing of the protocol, followed by searches on three databases: Pubmed, Scopus and Web of Science to identify the relevant evidence related to bone age assessment using Machine Learning techniques. One round of backward snowballing was performed to find additional studies. A quality assessment was performed on the selected studies to check for bias and low quality studies, which were removed. Data was extracted from the included studies to build summary tables. Lastly, a meta-analysis was performed on the performances of the selected studies.

RESULTS

26 studies constituted the final set of included studies. Most of them proposed automatic systems for bone age assessment and investigated methods for bone age assessment based on hand and wrist radiographs. The samples used in the studies were mostly comprehensive or bordered the age of 18, and the data origin was in most of cases from United States and West Europe. Few studies explored ethnic differences.

CONCLUSIONS

There is a clear focus of the research on bone age assessment methods based on radiographs whilst other types of medical imaging without radiation exposure (e.g. magnetic resonance imaging) are not much explored in the literature. Also, socioeconomic and other aspects that could influence in bone age were not addressed in the literature. Finally, studies that make use of more than one region of interest for bone age assessment are scarce.