Improving the Age Estimation Efficiency by Calculation of the Area Ratio Index Using Semi-Automatic Segmentation of Knee MRI Images

Abstract

The knee is an anatomical structure that can provide a great deal of data for research on age estimation. The aim of this study was to evaluate and apply a method for semi-automatic measurements of the area under the growth plate closure of the femur distal epiphysis and the growth plate closure itself on the 2D coronary slices using T2 weighted images (T2WI) generated on magnetic resonance (MRI) devices of different technical and technological characteristics. After the semi-automatic segmentation of the femur distal epiphysis under the growth plate closure and the growth plate closure itself, the areas of the measured closures were calculated using MATLAB version: 9.12. (R2022a), MathWorks Inc., Natick, MA, USA, for each individual coronal slice. The area ratio index (ARI) was calculated as the ratio between the area under the growth plate closure of the femur distal epiphysis and the growth plate closure itself. The study sample consisted of 27 female and 23 male Caucasian participants aged 10 to 26 years. A total of 339 T2WI images were used for ARI calculations. There was a positive correlation between chronological age and the average ARI measured by three independent observers (r = 0.8280, p < 0.001). Multiple regression analysis did not show any significant impact of the technical and technological characteristics of the MRI devices on ARI. The results of this study showed that ARI could serve as a useful tool for age estimation using knee MRI as well as for the further development of artificial intelligence (AI) applications.

Bone Age Determination of Epiphyseal Fusion at Knee Joint and Its Correlation with Chronological Age

“…Another factor which limits the generalizability of results is the small sample size, which led to biases, and this was attributed to the limited archived resources at the age range. It is highly recommended that future studies with a prospective design and with large sample size are carried out to minimize inherited biases and allow more precise tracing of the progression of epiphyseal fusion in individuals [26]. Furthermore, radiographic findings of this study would provide a basis for the use of other techniques such as MRI and ultrasound images, and allow the comparison and exploration of more subjects.…”

“…A recent review highlighted the impact of heterogeneity in studies using knee MRI images as a predictive method for determining bone age. It found there was potential for false predictions, especially among young people [14]; however, this could be improved by introducing computed aided measurements and AI [26].…”

Demystifying the Radiography of Age Estimation in Criminal Jurisprudence: A Pictorial Review

“…Being an objective parameter, ARI can be an effective and efficient tool for strengthening bone age estimation by artificial intelligence (AI). 66 …”