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

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 its...

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Autores principales: Matijaš, Tatjana, Pinjuh, Ana, Dolić, Krešimir, Radović, Darijo, Galić, Tea, Božić Štulić, Dunja, Mihanović, Frane
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10377215/
https://www.ncbi.nlm.nih.gov/pubmed/37509685
http://dx.doi.org/10.3390/biomedicines11072046
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author Matijaš, Tatjana
Pinjuh, Ana
Dolić, Krešimir
Radović, Darijo
Galić, Tea
Božić Štulić, Dunja
Mihanović, Frane
author_facet Matijaš, Tatjana
Pinjuh, Ana
Dolić, Krešimir
Radović, Darijo
Galić, Tea
Božić Štulić, Dunja
Mihanović, Frane
author_sort Matijaš, Tatjana
collection PubMed
description 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.
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spelling pubmed-103772152023-07-29 Improving the Age Estimation Efficiency by Calculation of the Area Ratio Index Using Semi-Automatic Segmentation of Knee MRI Images Matijaš, Tatjana Pinjuh, Ana Dolić, Krešimir Radović, Darijo Galić, Tea Božić Štulić, Dunja Mihanović, Frane Biomedicines Article 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. MDPI 2023-07-20 /pmc/articles/PMC10377215/ /pubmed/37509685 http://dx.doi.org/10.3390/biomedicines11072046 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Matijaš, Tatjana
Pinjuh, Ana
Dolić, Krešimir
Radović, Darijo
Galić, Tea
Božić Štulić, Dunja
Mihanović, Frane
Improving the Age Estimation Efficiency by Calculation of the Area Ratio Index Using Semi-Automatic Segmentation of Knee MRI Images
title Improving the Age Estimation Efficiency by Calculation of the Area Ratio Index Using Semi-Automatic Segmentation of Knee MRI Images
title_full Improving the Age Estimation Efficiency by Calculation of the Area Ratio Index Using Semi-Automatic Segmentation of Knee MRI Images
title_fullStr Improving the Age Estimation Efficiency by Calculation of the Area Ratio Index Using Semi-Automatic Segmentation of Knee MRI Images
title_full_unstemmed Improving the Age Estimation Efficiency by Calculation of the Area Ratio Index Using Semi-Automatic Segmentation of Knee MRI Images
title_short Improving the Age Estimation Efficiency by Calculation of the Area Ratio Index Using Semi-Automatic Segmentation of Knee MRI Images
title_sort improving the age estimation efficiency by calculation of the area ratio index using semi-automatic segmentation of knee mri images
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10377215/
https://www.ncbi.nlm.nih.gov/pubmed/37509685
http://dx.doi.org/10.3390/biomedicines11072046
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