Accuracy and Reproducibility of Voxel Based Superimposition of Cone Beam Computed Tomography Models on the Anterior Cranial Base and the Zygomatic Arches

Nada, Rania M.; Maal, T.J.J.; Breuning, K. Hero; Bergé, Stefaan; Mostafa, Yehya A.; Kuijpers-Jagtman, Anne Marie

doi:10.1371/journal.pone.0016520

Cited by 137 publications

(135 citation statements)

References 12 publications

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“…Pre-and posttreatment images were registered on the anterior cranial base surface on all studies, 3,7,12,16,21,25 and one was also superimposed on the left zygomatic arch. 12 …”

Section: Results Of Individual Studiesmentioning

confidence: 99%

“…A second study 12 assessed the voxel-based method on pairs of CBCT scans of 16 adult patients. The mean absolute distances between the two 3D images were calculated in four different regions (cranial base, forehead, and right and left zygomatic arches).…”

Section: Voxel-based Methodsmentioning

confidence: 99%

“…The application of this method has been widely 25 Cevidanes et al 16 Nada et al 12 DeCesare et al 7 Gkantidis et al 21 Weissheimer et al…”

Section: Summary Of Evidencementioning

confidence: 99%

“…The results showed that the interobserver errors had a range of 0.26 mm. Similarly, Nada et al 12 used the voxel-based image registration method to test the reliability and measurement error of CBCT superimposition on the anterior cranial base in adult patients who underwent combined surgical orthodontic treatment. The authors reported small differences within 0.5 mm, which were considered to be clinically insignificant.…”

Section: E G F P E G F P E G F P E G F P E G F P E G F Pmentioning

confidence: 99%

“…9,11 Recently, similar to 2D cephalometric tracings, CBCT images can be superimposed, allowing a 3D evaluation of growth changes, treatment effects, and stability over a certain time interval through registration points, angles, shapes, and volumes. [12][13][14] One of the main challenges of 3D superimposition of serial images is to understand that linear/angular measurements in 2D and 3D images are not directly comparable because of differences in size, shape, and relative spatial location of the skeletal, dental, and soft tissue between the two imaging systems. 4,15 The following three general methods of 3D cephalometric superimposition have been published and used for clinical diagnosis and assessment of orthodontic treatment outcomes: (1) voxel based, 3,4,[16][17][18][19] (2) landmark based, 7,20 and (3) surface based.…”

Section: Introductionmentioning

confidence: 99%

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Reliability of three-dimensional anterior cranial base superimposition methods for assessment of overall hard tissue changes: A systematic review

Ponce-Garcia

Lagravère-Vich

Cevidanes

et al. 2017

The Angle Orthodontist

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Objective: The purpose of this systematic review was to synthesize the available literature concerning the reliability of three-dimensional superimposition methods when assessing changes in craniofacial hard tissues. Materials and Methods: Four electronic databases were searched. Two authors independently reviewed potentially relevant articles for eligibility. Clinical trials, cohort, case-control, and crosssectional studies that evaluated the reliability of three-dimensional superimposition methods on the anterior cranial base were included. Results: Six studies fulfilled the inclusion criteria. Four studies used the voxel-based registration method, one used the landmark-based method and one used the surface-based method. Regarding reliability, the voxel-based studies showed on average a difference of 0.5 mm or less between images. The optimized analysis using a six-point correction algorithm in the landmarkbased method showed 1.24 mm magnitude of error between images. Conclusions: Although reliability appears to be adequate, the small sample size and high risk of bias among studies make available evidence still insufficient to draw strong conclusions. (Angle Orthod. 2018;88:233-245.)

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“…Pre-and posttreatment images were registered on the anterior cranial base surface on all studies, 3,7,12,16,21,25 and one was also superimposed on the left zygomatic arch. 12 …”

Section: Results Of Individual Studiesmentioning

confidence: 99%

Section: Voxel-based Methodsmentioning

confidence: 99%

“…The application of this method has been widely 25 Cevidanes et al 16 Nada et al 12 DeCesare et al 7 Gkantidis et al 21 Weissheimer et al…”

Section: Summary Of Evidencementioning

confidence: 99%

Section: E G F P E G F P E G F P E G F P E G F P E G F Pmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Reliability of three-dimensional anterior cranial base superimposition methods for assessment of overall hard tissue changes: A systematic review

Ponce-Garcia

Lagravère-Vich

Cevidanes

et al. 2017

The Angle Orthodontist

View full text Add to dashboard Cite

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3D Assessment of Orthognathic Surgical Outcomes

Kim

Park

Paula

et al. 2014

Cone Beam Computed Tomography in Orthodontics: Indications, Insights, and Innovations

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Adaptable cascaded registration for personalized maxilla completion and cleft defect volume estimation

Zhang,

Pei,

Guo

et al. 2024

Medical Physics

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BackgroundCone‐beam computed tomography (CBCT) images provide high‐resolution insights into the underlying craniofacial anomaly in patients with cleft lip and palate (CLP), requiring non‐negligible annotation costs to measure the cleft defect for the guidance of the clinical secondary alveolar bone graft procedures. Considering the cumbersome volumetric image acquisition, there is a lack of paired CLP CBCTs and normal CBCTs for learning‐based anatomical structure restoration models. Nowadays, the registration‐based method relieves the annotation burden, though one‐shot registration and the regular mask are limited to handling fine‐grained shape variations and harmony between restored bony tissues and the defected maxilla.PurposeThis study aimed to design and evaluate a novel method for deformable partial registration of the CLP CBCTs and normal CBCTs, enabling personalized maxilla completion and cleft defect volume prediction from CLP CBCTs.MethodsWe proposed an adaptable deep registration framework for personalized maxilla completion and cleft defect volume prediction from CLP CBCTs. The key ingredient was a cascaded partial registration to exploit the maxillary morphology prior and attribute transfer. Cascaded registration with coarse‐to‐fine registration fields handled morphological variations of cleft defects and fine‐grained maxillary restoration. We designed an adaptable cleft defect mask and volumetric Boolean operators for reliable voxel filling of the defected maxilla. A total of 36 clinically obtained CLP CBCTs were used to train and validate the proposed model, among which 22 CLP CBCTs were used to generate a training dataset with 440 synthetic CBCTs by B‐spline deformation‐based data augmentation and the remaining for testing. The proposed model was evaluated on maxilla completion and cleft defect volume prediction from clinically obtained unilateral and bilateral CLP CBCTs.ResultsExtensive experiments demonstrated the effectiveness of the adaptable cleft defect mask and the cascaded partial registration on maxilla completion and cleft defect volume prediction. The proposed method achieved state‐of‐the‐art performances with the Dice similarity coefficient of 0.90 0.02 on the restored maxilla and 0.84 0.04 on the estimated cleft defect, respectively. The average Hausdorff distance between the estimated cleft defect and the manually annotated ground truth was 0.30 0.08 mm. The relative volume error of the cleft defect was 0.08. The proposed model allowed for the prediction of cleft defect maps that were in line with the ground truth in the challenging unilateral and bilateral CLP CBCTs.ConclusionsThe results suggest that the proposed adaptable deep registration model enables patient‐specific maxilla completion and automatic annotation of cleft defects, relieving tedious voxel‐wise annotation and image acquisition burdens.

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Accuracy and Reproducibility of Voxel Based Superimposition of Cone Beam Computed Tomography Models on the Anterior Cranial Base and the Zygomatic Arches

Cited by 137 publications

References 12 publications

Reliability of three-dimensional anterior cranial base superimposition methods for assessment of overall hard tissue changes: A systematic review

Reliability of three-dimensional anterior cranial base superimposition methods for assessment of overall hard tissue changes: A systematic review

3D Assessment of Orthognathic Surgical Outcomes

Adaptable cascaded registration for personalized maxilla completion and cleft defect volume estimation

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