The Reliability of Two- and Three-Dimensional Cephalometric Measurements: A CBCT Study

Li, Chenshuang; Teixeira, Hellen S.; Tanna, Nipul; Zheng, Zhong; Chen, Stephanie Hsiang Yi; Zhang, Min; Chung, Chun-Hsi

doi:10.3390/diagnostics11122292

Cited by 19 publications

(23 citation statements)

References 42 publications

(50 reference statements)

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“…However, there is no 3D conventional or validated list of anatomical landmarks, also because 3D data made it possible to identify hidden structures to 2D analysis. Despite that, the main advantage represented by 3D analysis is to avoid the superimposition of bilateral structures and the distortion caused by the representation of a 3D object into a 2D image, resulting in a greater accuracy [ 6 ]; furthermore, CBCT technology in orthodontics allows the reduction of the X-rays exposition due to reduction of field of view and through the use of new reference landmarks and planes [ 7 ].…”

Section: Introductionmentioning

confidence: 99%

Accuracy of automated 3D cephalometric landmarks by deep learning algorithms: systematic review and meta-analysis

et al. 2023

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Objectives The aim of the present systematic review and meta-analysis is to assess the accuracy of automated landmarking using deep learning in comparison with manual tracing for cephalometric analysis of 3D medical images. Methods PubMed/Medline, IEEE Xplore, Scopus and ArXiv electronic databases were searched. Selection criteria were: ex vivo and in vivo volumetric data images suitable for 3D landmarking (Problem), a minimum of five automated landmarking performed by deep learning method (Intervention), manual landmarking (Comparison), and mean accuracy, in mm, between manual and automated landmarking (Outcome). QUADAS-2 was adapted for quality analysis. Meta-analysis was performed on studies that reported as outcome mean values and standard deviation of the difference (error) between manual and automated landmarking. Linear regression plots were used to analyze correlations between mean accuracy and year of publication. Results The initial electronic screening yielded 252 papers published between 2020 and 2022. A total of 15 studies were included for the qualitative synthesis, whereas 11 studies were used for the meta-analysis. Overall random effect model revealed a mean value of 2.44 mm, with a high heterogeneity (I2 = 98.13%, τ2 = 1.018, p-value < 0.001); risk of bias was high due to the presence of issues for several domains per study. Meta-regression indicated a significant relation between mean error and year of publication (p value = 0.012). Conclusion Deep learning algorithms showed an excellent accuracy for automated 3D cephalometric landmarking. In the last two years promising algorithms have been developed and improvements in landmarks annotation accuracy have been done.

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Section: Introductionmentioning

confidence: 99%

Accuracy of automated 3D cephalometric landmarks by deep learning algorithms: systematic review and meta-analysis

et al. 2023

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“…Traditionally, the field of orthodontics has heavily relied on two‐dimensional (2D) forms of radiography. Common limitations that arise with 2D radiographs include magnification, geometric distortion, projective displacements, rotational errors, and overlap of anatomical structures 1–4 . With all things being considered, an accurate methodology to aid in the understanding of the complex anatomical relationships and surrounding structures of the maxillofacial skeleton is critical for appropriate diagnosis and treatment.…”

Section: Introductionmentioning

confidence: 99%

“…Common limitations that arise with 2D radiographs include magnification, geometric distortion, projective displacements, rotational errors, and overlap of anatomical structures. [1][2][3][4] With all things being considered, an accurate methodology to aid in the understanding of the complex anatomical relationships and surrounding structures of the maxillofacial skeleton is critical for appropriate diagnosis and treatment. Cone-beam computed tomography (CBCT) has emerged over the past two decades as a rapid acquisition technology that has transformed 2D images into a 3D anatomically volumetric dataset.…”

Section: Introductionmentioning

confidence: 99%

Cone‐beam computed tomography use in postgraduate orthodontic programs in North America and Europe

Guberman

Chung

2023

Journal of Dental Education

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Objectives Cone‐beam computed tomography (CBCT) has emerged over recent decades as a rapid acquisition technology that allows practitioners to view the craniofacial complex in high spatial detail. This study aimed to assess the latest trend of CBCT use in postgraduate orthodontic programs in North America and Europe/Australia. Methods An electronic multiple‐choice survey was sent via email requesting anonymous participation of postgraduate orthodontic program directors: 73 in North America (as listed on the American Association of Orthodontists website) and 189 in Europe/Australia (as listed on the European Orthodontic Society website). Survey collection was over a 2‐month period with two follow‐up emails sent 2 weeks and 1 month after the initial email to each program director who had not responded. Responses were collected directly on Qualtrics for analysis. Results The response rate was 46.6% (34 responses) for North America and 11.1% (21 responses) for Europe/Australia. Results revealed that 100% of respondents from North America had access to a CBCT scanner, while 90.48% of respondents (19 responses) from Europe/Australia had access. Most North American postgraduate orthodontic programs have CBCT scanners within their clinic, while most European/Australian programs do not, and they refer patients to the radiology department. Although there is a higher percentage of programs in North America compared to Europe/Australia that use CBCT as part of routine orthodontic records for all patients, most programs in both regions use CBCT imaging for specific diagnostic purposes and not for routine records. Conclusion Overall, North American programs have more access to CBCT scanners in postgraduate clinics and use CBCT imaging more routinely than European/Australian programs.

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“…Cephalometric analysis, first introduced by Hofrath H [1] and Broadbent BH [2], has been a standard diagnostic tool in orthodontics and craniofacial surgery for the last few decades [3][4][5][6]. As is well known in orthodontic and orthognathic surgery fields, the accurate quantification of deformities and precise surgical planning requires the digitization Diagnostics 2023, 13, 2360 2 of 23 (detection and localization) of cranio-maxillofacial (CMF) landmarks.…”

Section: Introductionmentioning

confidence: 99%

The Reliability of Three-Dimensional Landmark-Based Craniomaxillofacial and Airway Cephalometric Analysis

et al. 2023

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Cephalometric analysis is a standard diagnostic tool in orthodontics and craniofacial surgery. Today, as conventional 2D cephalometry is limited and susceptible to analysis bias, a more reliable and user-friendly three-dimensional system that includes hard tissue, soft tissue, and airways is demanded in clinical practice. We launched our study to develop such a system based on CT data and landmarks. This study aims to determine whether the data labeled through our process is highly qualified and whether the soft tissue and airway data derived from CT scans are reliable. We enrolled 15 patients (seven males, eight females, 26.47 ± 3.44 years old) diagnosed with either non-syndromic dento–maxillofacial deformities or OSDB in this study to evaluate the intra- and inter-examiner reliability of our system. A total of 126 landmarks were adopted and divided into five sets by region: 28 cranial points, 25 mandibular points, 20 teeth points, 48 soft tissue points, and 6 airway points. All the landmarks were labeled by two experienced clinical practitioners, either of whom had labeled all the data twice at least one month apart. Furthermore, 78 parameters of three sets were calculated in this study: 42 skeletal parameters (23 angular and 19 linear), 27 soft tissue parameters (9 angular and 18 linear), and 9 upper airway parameters (2 linear, 4 areal, and 3 voluminal). Intraclass correlation coefficient (ICC) was used to evaluate the inter-examiner and intra-examiner reliability of landmark coordinate values and measurement parameters. The overwhelming majority of the landmarks showed excellent intra- and inter-examiner reliability. For skeletal parameters, angular parameters indicated better reliability, while linear parameters performed better for soft tissue parameters. The intra- and inter-examiner ICCs of airway parameters referred to excellent reliability. In summary, the data labeled through our process are qualified, and the soft tissue and airway data derived from CT scans are reliable. Landmarks that are not commonly used in clinical practice may require additional attention while labeling as they are prone to poor reliability. Measurement parameters with values close to 0 tend to have low reliability. We believe this three-dimensional cephalometric system would reach clinical application.

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The Reliability of Two- and Three-Dimensional Cephalometric Measurements: A CBCT Study

Cited by 19 publications

References 42 publications

Accuracy of automated 3D cephalometric landmarks by deep learning algorithms: systematic review and meta-analysis

Accuracy of automated 3D cephalometric landmarks by deep learning algorithms: systematic review and meta-analysis

Cone‐beam computed tomography use in postgraduate orthodontic programs in North America and Europe

The Reliability of Three-Dimensional Landmark-Based Craniomaxillofacial and Airway Cephalometric Analysis

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