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CT- and MRI-Based 3D Reconstruction of Knee Joint to Assess Cartilage and Bone
For the observation of human joint cartilage, X-ray, computed tomography (CT) or magnetic resonance imaging (MRI) are the main diagnostic tools to evaluate pathologies or traumas. The current work introduces a set of novel measurements and 3D features based on MRI and CT data of the knee joint, used...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8870751/ https://www.ncbi.nlm.nih.gov/pubmed/35204370 http://dx.doi.org/10.3390/diagnostics12020279 |
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author | Ciliberti, Federica Kiyomi Guerrini, Lorena Gunnarsson, Arnar Evgeni Recenti, Marco Jacob, Deborah Cangiano, Vincenzo Tesfahunegn, Yonatan Afework Islind, Anna Sigríður Tortorella, Francesco Tsirilaki, Mariella Jónsson, Halldór Gargiulo, Paolo Aubonnet, Romain |
author_facet | Ciliberti, Federica Kiyomi Guerrini, Lorena Gunnarsson, Arnar Evgeni Recenti, Marco Jacob, Deborah Cangiano, Vincenzo Tesfahunegn, Yonatan Afework Islind, Anna Sigríður Tortorella, Francesco Tsirilaki, Mariella Jónsson, Halldór Gargiulo, Paolo Aubonnet, Romain |
author_sort | Ciliberti, Federica Kiyomi |
collection | PubMed |
description | For the observation of human joint cartilage, X-ray, computed tomography (CT) or magnetic resonance imaging (MRI) are the main diagnostic tools to evaluate pathologies or traumas. The current work introduces a set of novel measurements and 3D features based on MRI and CT data of the knee joint, used to reconstruct bone and cartilages and to assess cartilage condition from a new perspective. Forty-seven subjects presenting a degenerative disease, a traumatic injury or no symptoms or trauma were recruited in this study and scanned using CT and MRI. Using medical imaging software, the bone and cartilage of the knee joint were segmented and 3D reconstructed. Several features such as cartilage density, volume and surface were extracted. Moreover, an investigation was carried out on the distribution of cartilage thickness and curvature analysis to identify new markers of cartilage condition. All the extracted features were used with advanced statistics tools and machine learning to test the ability of our model to predict cartilage conditions. This work is a first step towards the development of a new gold standard of cartilage assessment based on 3D measurements. |
format | Online Article Text |
id | pubmed-8870751 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-88707512022-02-25 CT- and MRI-Based 3D Reconstruction of Knee Joint to Assess Cartilage and Bone Ciliberti, Federica Kiyomi Guerrini, Lorena Gunnarsson, Arnar Evgeni Recenti, Marco Jacob, Deborah Cangiano, Vincenzo Tesfahunegn, Yonatan Afework Islind, Anna Sigríður Tortorella, Francesco Tsirilaki, Mariella Jónsson, Halldór Gargiulo, Paolo Aubonnet, Romain Diagnostics (Basel) Article For the observation of human joint cartilage, X-ray, computed tomography (CT) or magnetic resonance imaging (MRI) are the main diagnostic tools to evaluate pathologies or traumas. The current work introduces a set of novel measurements and 3D features based on MRI and CT data of the knee joint, used to reconstruct bone and cartilages and to assess cartilage condition from a new perspective. Forty-seven subjects presenting a degenerative disease, a traumatic injury or no symptoms or trauma were recruited in this study and scanned using CT and MRI. Using medical imaging software, the bone and cartilage of the knee joint were segmented and 3D reconstructed. Several features such as cartilage density, volume and surface were extracted. Moreover, an investigation was carried out on the distribution of cartilage thickness and curvature analysis to identify new markers of cartilage condition. All the extracted features were used with advanced statistics tools and machine learning to test the ability of our model to predict cartilage conditions. This work is a first step towards the development of a new gold standard of cartilage assessment based on 3D measurements. MDPI 2022-01-22 /pmc/articles/PMC8870751/ /pubmed/35204370 http://dx.doi.org/10.3390/diagnostics12020279 Text en © 2022 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 Ciliberti, Federica Kiyomi Guerrini, Lorena Gunnarsson, Arnar Evgeni Recenti, Marco Jacob, Deborah Cangiano, Vincenzo Tesfahunegn, Yonatan Afework Islind, Anna Sigríður Tortorella, Francesco Tsirilaki, Mariella Jónsson, Halldór Gargiulo, Paolo Aubonnet, Romain CT- and MRI-Based 3D Reconstruction of Knee Joint to Assess Cartilage and Bone |
title | CT- and MRI-Based 3D Reconstruction of Knee Joint to Assess Cartilage and Bone |
title_full | CT- and MRI-Based 3D Reconstruction of Knee Joint to Assess Cartilage and Bone |
title_fullStr | CT- and MRI-Based 3D Reconstruction of Knee Joint to Assess Cartilage and Bone |
title_full_unstemmed | CT- and MRI-Based 3D Reconstruction of Knee Joint to Assess Cartilage and Bone |
title_short | CT- and MRI-Based 3D Reconstruction of Knee Joint to Assess Cartilage and Bone |
title_sort | ct- and mri-based 3d reconstruction of knee joint to assess cartilage and bone |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8870751/ https://www.ncbi.nlm.nih.gov/pubmed/35204370 http://dx.doi.org/10.3390/diagnostics12020279 |
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