Intérêt de la méthode de maturation des vertèbres cervicales (CVM) en orthopédie dento-faciale : mise au point

Elhaddaoui, Rajae; Benyahia, Hicham; Azaroual, Faouzi; Zaoui, Fatima

doi:10.1016/j.revsto.2014.09.003

Cited by 6 publications

(6 citation statements)

References 22 publications

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“…He used measurements of mandibular length on several annual lateral cephalograms to describe individual mandibular growth curve, and correlated it with morphological description of vertebrae morphology at each stage. This method was modified several times first by Hassel and Farman (1995) [ 15 ], then twice by Baccetti et al (2002 and 2005) for a more accurate assessment of cervical maturation, by six stages identified by morphological changes in the C2,C3,C4 vertebral bodies on a single lateral cephalogram, independently of patient gender [ 16 ].…”

Section: The Classical Radiographic Manual Methodsmentioning

confidence: 99%

“…Many researchers found this method as valid and reliable as hand and wrist Xray [ 14 ]. The cervical vertebrae maturation stages have been demonstrated as a clinically useful maturation indicators for evaluation of pubertal growth height and mandibular velocities [ 18 , 19 , 20 ], by correlation between chronological age and cervical vertebrae maturation, between hand–wrist and cervical-vertebrae maturation [ 16 , 21 , 22 , 23 ].…”

Section: The Classical Radiographic Manual Methodsmentioning

confidence: 99%

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Deep Learning and Artificial Intelligence for the Determination of the Cervical Vertebra Maturation Degree from Lateral Radiography

Makaremi

Lacaule

Mohammad-Djafari³

2019

Entropy

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Deep Learning (DL) and Artificial Intelligence (AI) tools have shown great success in different areas of medical diagnostics. In this paper, we show another success in orthodontics. In orthodontics, the right treatment timing of many actions and operations is crucial because many environmental and genetic conditions may modify jaw growth. The stage of growth is related to the Cervical Vertebra Maturation (CVM) degree. Thus, determining the CVM to determine the suitable timing of the treatment is important. In orthodontics, lateral X-ray radiography is used to determine it. Many classical methods need knowledge and time to look and identify some features. Nowadays, ML and AI tools are used for many medical and biological diagnostic imaging. This paper reports on the development of a Deep Learning (DL) Convolutional Neural Network (CNN) method to determine (directly from images) the degree of maturation of CVM classified in six degrees. The results show the performances of the proposed method in different contexts with different number of images for training, evaluation and testing and different pre-processing of these images. The proposed model and method are validated by cross validation. The implemented software is almost ready for use by orthodontists.

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Section: The Classical Radiographic Manual Methodsmentioning

confidence: 99%

Section: The Classical Radiographic Manual Methodsmentioning

confidence: 99%

Deep Learning and Artificial Intelligence for the Determination of the Cervical Vertebra Maturation Degree from Lateral Radiography

Makaremi

Lacaule

Mohammad-Djafari³

2019

Entropy

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show abstract

“…He has used measurements of mandibular length on several annual lateral cephalograms to describe individual mandibular growth curve, and correlated it with morphological description of vertebrae morphology at each stage. This method were modified several times first by Hassel and Farman (1995) [15], then twice by Baccetti et al (2002 and2005) for a more accurate assessment of cervical maturation, by 6 stages identified by morphological changes in the C2,C3,C4 vertebral bodies on a single lateral cephalogram, independently of patient gender [16].…”

Section: Vertebrae Maturation Cvmmentioning

confidence: 99%

“…Many researchers found this method as valid and reliable as hand and wrist Xray [14]. The cervical vertebrae maturation stages have been demonstrated as a clinically useful maturation indicators for evaluation of pubertal growth height and mandibular velocities [18][19][20], by correlation between chronological age and cervical vertebrae maturation, between hand-wrist and cervical-vertebrae maturation [16,[21][22][23].…”

Section: Cephalometric Appraisalsmentioning

confidence: 99%

Determination of the Cervical Vertebra Maturation Degree from Lateral Radiography

Makaremi

Lacaule

Mohammad-Djafari³

2020

The 39th International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering

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Many environmental and genetic conditions may modify jaws growth. In orthodontics, the right treatment timing is crucial. This timing is a function of the Cervical Vertebra Maturation (CVM) degree. Thus, determining the CVM is important. In orthodontics, the lateral X-ray radiography is used to determine it. Many classical methods need knowledge and time to look and identify some features to do it. Nowadays, Machine Learning (ML) and Artificial Intelligent (AI) tools are used for many medical and biological image processing, clustering and classification. This paper reports on the development of a Deep Learning (DL) method to determine directly from the images the degree of maturation of CVM classified in six degrees. Using 300 such images for training and 200 for evaluating and 100 for testing, we could obtain a 90% accuracy. The proposed model and method are validated by cross validation. The implemented software is ready for use by orthodontists.

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“…Cervical spine radiographs are already being used when making diagnoses in DFO. Moreover, there is a good correlation between carpal bone age, mandibular growth, and the pubertal growth peak 6,7,11 . There are six stages of maturation.…”

Section: Bone Maturationmentioning

confidence: 95%

Skeletal growth and maturation in children afflicted with major endocrine disorders

Duhamel

Kerdanet

2017

J Dentofacial Anom Orthod

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Orthodontic and dentofacial orthopedic strategies depend on both skeletal growth and maturation stages. In children, various parameters such as growth curves shown in the child's health record, pubertal changes, or skeletal maturation (using the vertebral maturation method) need to be evaluated. These elements allow the practitioner to choose the optimal moment to start treatment or to discontinue it. Endocrine disorders such as growth hormone variations, thyroid disorders, and pubertal issues could modify skeletal growth and maturation. Diagnoses and treatment of these pathologies affect maxillofacial growth and development. Thus, these pathologies should be taken into consideration during orthodontic and dentofacial orthopedic treatment in children.

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Intérêt de la méthode de maturation des vertèbres cervicales (CVM) en orthopédie dento-faciale : mise au point

Cited by 6 publications

References 22 publications

Deep Learning and Artificial Intelligence for the Determination of the Cervical Vertebra Maturation Degree from Lateral Radiography

Deep Learning and Artificial Intelligence for the Determination of the Cervical Vertebra Maturation Degree from Lateral Radiography

Determination of the Cervical Vertebra Maturation Degree from Lateral Radiography

Skeletal growth and maturation in children afflicted with major endocrine disorders

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