The accuracy and reliability of WebCeph for cephalometric analysis

Abstract Objective The rapid development of artificial intelligence technologies for medical imaging has recently enabled automatic identification of anatomical landmarks on radiographs. The purpose of this study was to compare the results of an automatic cephalometric analysis using convolutional neural network with those obtained by a conventional cephalometric approach. Material and methods Cephalometric measurements of lateral cephalograms from 35 patients were obtained using an automatic program and a conventional program. Fifteen skeletal cephalometric measurements, nine dental cephalometric measurements, and two soft tissue cephalometric measurements obtained by the two methods were compared using paired t test and Bland-Altman plots. Results A comparison between the measurements from the automatic and conventional cephalometric analyses in terms of the paired t test confirmed that the saddle angle, linear measurements of maxillary incisor to NA line, and mandibular incisor to NB line showed statistically significant differences. All measurements were within the limits of agreement based on the Bland-Altman plots. The widths of limits of agreement were wider in dental measurements than those in the skeletal measurements. Conclusions Automatic cephalometric analyses based on convolutional neural network may offer clinically acceptable diagnostic performance. Careful consideration and additional manual adjustment are needed for dental measurements regarding tooth structures for higher accuracy and better performance.

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Machine learning for image-based detection of patients with obstructive sleep apnea: an exploratory study

Sleep And Breathing ◽

10.1007/s11325-021-02301-7 ◽

2021 ◽

Author(s):

Satoru Tsuiki ◽

Takuya Nagaoka ◽

Tatsuya Fukuda ◽

Yuki Sakamoto ◽

Fernanda R. Almeida ◽

...

Keyword(s):

Neural Network ◽

Machine Learning ◽

Obstructive Sleep Apnea ◽

Sleep Apnea ◽

Convolutional Neural Network ◽

Deep Convolutional Neural Network ◽

Apnea Hypopnea Index ◽

Cephalometric Analysis ◽

Obstructive Sleep ◽

Main Region

Abstract Purpose In 2-dimensional lateral cephalometric radiographs, patients with severe obstructive sleep apnea (OSA) exhibit a more crowded oropharynx in comparison with non-OSA. We tested the hypothesis that machine learning, an application of artificial intelligence (AI), could be used to detect patients with severe OSA based on 2-dimensional images. Methods A deep convolutional neural network was developed (n = 1258; 90%) and tested (n = 131; 10%) using data from 1389 (100%) lateral cephalometric radiographs obtained from individuals diagnosed with severe OSA (n = 867; apnea hypopnea index > 30 events/h sleep) or non-OSA (n = 522; apnea hypopnea index < 5 events/h sleep) at a single center for sleep disorders. Three kinds of data sets were prepared by changing the area of interest using a single image: the original image without any modification (full image), an image containing a facial profile, upper airway, and craniofacial soft/hard tissues (main region), and an image containing part of the occipital region (head only). A radiologist also performed a conventional manual cephalometric analysis of the full image for comparison. Results The sensitivity/specificity was 0.87/0.82 for full image, 0.88/0.75 for main region, 0.71/0.63 for head only, and 0.54/0.80 for the manual analysis. The area under the receiver-operating characteristic curve was the highest for main region 0.92, for full image 0.89, for head only 0.70, and for manual cephalometric analysis 0.75. Conclusions A deep convolutional neural network identified individuals with severe OSA with high accuracy. Future research on this concept using AI and images can be further encouraged when discussing triage of OSA.

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Modern 3D cephalometry in pediatric orthodontics—downsizing the FOV and development of a new 3D cephalometric analysis within a minimized large FOV for dose reduction

Clinical Oral Investigations ◽

10.1007/s00784-021-03779-x ◽

2021 ◽

Author(s):

Pamela Kissel ◽

James K. Mah ◽

Axel Bumann

Keyword(s):

Dose Reduction ◽

Cephalometric Analysis ◽

3D Cephalometry ◽

3D Cephalometric Analysis

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An orthodontic perspective on Larsen syndrome

BMC Oral Health ◽

10.1186/s12903-021-01454-x ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Madoka Yasunaga ◽

Hiroyuki Ishikawa ◽

Kenichi Yanagita ◽

Sachio Tamaoki

Keyword(s):

Foot Deformities ◽

Dental Arch ◽

Cephalometric Analysis ◽

Craniofacial Anomalies ◽

Nasal Bridge ◽

Skeletal Morphology ◽

Larsen Syndrome ◽

Craniofacial Dysmorphism ◽

Joint Dislocations ◽

Large Joint

Abstract Background Larsen syndrome (LS) is a rare disorder of osteochondrodysplasia. In addition to large-joint dislocations, craniofacial anomalies are typical characteristics. In this report, we performed orthodontic analyses, including skeletal and occlusal evaluations, to examine whether the craniofacial skeletal morphology leads to the craniofacial anomalies in LS. Case presentation A 5 year old Japanese girl who was clinically diagnosed with LS was referred to the orthodontic clinic in the Fukuoka Dental College Medical and Dental Hospital because of a malocclusion. Clinical findings at birth were knee-joint dislocations, equinovarus foot deformities, and cleft soft palate. The patient showed craniofacial anomalies with hypertelorism, prominent forehead, depressed nasal bridge, and flattened midface. To evaluate the craniofacial skeletal morphology, cephalometric analysis was performed. In the frontal cephalometric analysis, the larger widths between bilateral points of the orbitale were related to hypertelorism. The lateral cephalometric analysis revealed the midface hypoplasia and the retrognathic mandible. These findings were responsible for the flattened appearance of the patient’s face, even if the anteroposterior position of the nasion was normal. Her forehead looked prominent in relation to the face probably because of the retrognathic maxilla and mandible. Both the study model and the frontal cephalometric analysis indicated constriction of the upper and lower dental arches. The posterior crossbite facilitated by the premature contacts had developed in association with the constriction of the upper dental arch. Conclusions This patient had some craniofacial anomalies with characteristic appearances in LS. It was evident that the underlying skeletal morphology led to the craniofacial dysmorphism.

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Cephalometric analysis in patients with obstructive sleep apnoea syndrome.

The Journal of Laryngology & Otology ◽

10.1017/s0022215100108746 ◽

1989 ◽

Vol 103 (3) ◽

pp. 293-297 ◽

Cited By ~ 87

Author(s):

T. Lyberg ◽

O. Krogstad ◽

G. Djupesland

Keyword(s):

Obstructive Sleep Apnoea ◽

Sleep Apnoea ◽

Obstructive Sleep Apnoea Syndrome ◽

Cephalometric Analysis ◽

Sleep Apnoea Syndrome ◽

Obstructive Sleep

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Cephalometric Analysis of Modifications of the Mandible Due to Reduction Mandibuloplasty in Patients With Prominent Mandibular Angle

Journal of Craniofacial Surgery ◽

10.1097/scs.0000000000003446 ◽

2017 ◽

Vol 28 (3) ◽

pp. 654-658 ◽

Cited By ~ 5

Author(s):

Guoping Wu ◽

Minkai Xie ◽

Chunbing Hu ◽

Bin Zhou ◽

Hao Dai ◽

...

Keyword(s):

Cephalometric Analysis ◽

Mandibular Angle ◽

Prominent Mandibular Angle

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Craniofacial Morphology in Children with Complete Bilateral Cleft Lip and Palate: Does Infantile Size of the Premaxilla Predetermine Outcome?

The Cleft Palate-Craniofacial Journal ◽

10.1597/03-021.1 ◽

2004 ◽

Vol 41 (4) ◽

pp. 410-415 ◽

Cited By ~ 6

Author(s):

Yu-Fang Liao ◽

Chiung-Shing Huang ◽

Ya-Yu Tsai ◽

M. Samuel Noordhoff

Keyword(s):

Retrospective Study ◽

Outcome Measures ◽

Cleft Lip ◽

Cleft Lip And Palate ◽

Craniofacial Morphology ◽

University Hospital ◽

Cephalometric Analysis ◽

Bilateral Cleft Lip ◽

Dental Cast ◽

Craniofacial Characteristics

Objective To evaluate the possible association between the size of the premaxilla in infants and craniofacial morphology in children with complete bilateral cleft lip and palate (CBCLP) and identify the characteristics of craniofacial morphology in children with CBCLP with median facial dysplasia (MFD). Design Retrospective study. Setting A university hospital craniofacial center. Subjects Thirty-four patients with nonsyndromic CBCLP, 24 boys and 10 girls, had large premaxilla (LP group). Thirty-six patients with nonsyndromic CBCLP, 16 boys and 20 girls, had small premaxilla (SP group). Thirteen CBCLP patients with MFD, five boys and eight girls (MFD group). Main Outcome Measures Infant maxillary dental cast at the age of 1 year was used to measure the size of the premaxilla. Cephalometric analysis was used to determine craniofacial morphology in children at the age of 5 years. Results The size of the premaxilla in infants with CBCLP varied greatly. The LP group tended to have a longer maxilla and a more protruded maxilla, producing a better interjaw relation. The opposite phenomena were observed in the MFD group; the SP group yielded results between those of the LP and the MFD groups. Conclusion The size of the premaxilla in infants with CBCLP can be used to predetermine subsequent craniofacial morphology at the age of 5 years. Children with nonsyndromic CBCLP had craniofacial characteristics that differed significantly from those of children with CBCLP with median facial dysplasia.

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