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- Verhelst, PJ, et al.
(author)
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Automatic 3D dense phenotyping provides reliable and accurate shape quantification of the human mandible
- 2021
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In: Scientific reports. - : Springer Science and Business Media LLC. - 2045-2322. ; 11:1, s. 8532-
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Journal article (peer-reviewed)abstract
- Automatic craniomaxillofacial (CMF) three dimensional (3D) dense phenotyping promises quantification of the complete CMF shape compared to the limiting use of sparse landmarks in classical phenotyping. This study assesses the accuracy and reliability of this new approach on the human mandible. Classic and automatic phenotyping techniques were applied on 30 unaltered and 20 operated human mandibles. Seven observers indicated 26 anatomical landmarks on each mandible three times. All mandibles were subjected to three rounds of automatic phenotyping using Meshmonk. The toolbox performed non-rigid surface registration of a template mandibular mesh consisting of 17,415 quasi landmarks on each target mandible and the quasi landmarks corresponding to the 26 anatomical locations of interest were identified. Repeated-measures reliability was assessed using root mean square (RMS) distances of repeated landmark indications to their centroid. Automatic phenotyping showed very low RMS distances confirming excellent repeated-measures reliability. The average Euclidean distance between manual and corresponding automatic landmarks was 1.40 mm for the unaltered and 1.76 mm for the operated sample. Centroid sizes from the automatic and manual shape configurations were highly similar with intraclass correlation coefficients (ICC) of > 0.99. Reproducibility coefficients for centroid size were < 2 mm, accounting for < 1% of the total variability of the centroid size of the mandibles in this sample. ICC’s for the multivariate set of 325 interlandmark distances were all > 0.90 indicating again high similarity between shapes quantified by classic or automatic phenotyping. Combined, these findings established high accuracy and repeated-measures reliability of the automatic approach. 3D dense CMF phenotyping of the human mandible using the Meshmonk toolbox introduces a novel improvement in quantifying CMF shape.
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- Verhelst, PJ, et al.
(author)
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Validation of a 3D CBCT-based protocol for the follow-up of mandibular condyle remodeling
- 2020
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In: Dento maxillo facial radiology. - : British Institute of Radiology. - 0250-832X. ; 49:3, s. 20190364-
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Journal article (peer-reviewed)abstract
- Three-dimensional models of mandibular condyles provide a way for condylar remodeling follow-up. The overall aim was to develop and validate a user-friendly workflow for cone beam CT (CBCT)-based semi-automatic condylar registration and segmentation. Methods: A rigid voxel-based registration (VBR) technique for registration of two post-operative CBCT-scans was tested. Two modified mandibular rami, with or without gonial angle, were investigated as the volume of interest for registration. Inter- and intraoperator reproducibility of this technique was tested on 10 mandibular rami of orthognathic patients by means of intraclass correlation coefficients (ICC’s) and descriptive statistics of the transformation values from the VBR. The difference in reproducibility between the two modified rami was evaluated using a paired t-test (p < 0.05). For the segmentation, eight fresh frozen cadaver heads were scanned with CBCT and micro-CT. These data were used to test the inter- and intraoperator reproducibility (ICC’s) and accuracy (Bland–Altman plot) of a newly designed workflow based on semi-automated contour enhancement. Results: Excellent ICC’s (0.94–0.99) were obtained for the voxel-based registration technique using both modified rami. If the gonial angle was not included in the volume of interest, there was a trend of increased operator error suggested by significant higher interoperator differences in translation values (p = 0,0036). The segmentation workflow proved to be highly reproducible with excellent ICC’s (0.99), low absolute mean volume differences between operators (23.19 mm3), within operators (28.93 mm3) and low surface distances between models of different operators (<0.20 mm). Regarding the accuracy, CBCT-models slightly overestimate the condylar volume compared to micro-CT. Conclusions: This study provides a validated user-friendly and reproducible method of creating three-dimensional-surface models of mandibular condyles out of longitudinal CBCT-scans.
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