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Automatic 3D dense phenotyping provides reliable and accurate shape quantification of the human mandible
- Source :
- Scientific Reports, Scientific Reports, Vol 11, Iss 1, Pp 1-10 (2021)
- Publication Year :
- 2021
- Publisher :
- Nature Publishing Group UK, 2021.
-
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 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. 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 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. ispartof: Scientific Reports vol:11 issue:1 ispartof: location:England status: published
- Subjects :
- 0301 basic medicine
Oral anatomy
Similarity (geometry)
Intraclass correlation
Computer science
Cephalometry
Science
Mandible
Article
Root mean square
03 medical and health sciences
0302 clinical medicine
Imaging, Three-Dimensional
Image processing
Genetics research
Humans
Oral manifestations
Reliability (statistics)
Reproducibility
Electronic Data Processing
Multidisciplinary
Landmark
Musculoskeletal system
business.industry
Centroid
Reproducibility of Results
Pattern recognition
030206 dentistry
Cone-Beam Computed Tomography
Computational biology and bioinformatics
Euclidean distance
030104 developmental biology
Phenotype
Medicine
Artificial intelligence
Anatomic Landmarks
business
Software
Subjects
Details
- Language :
- English
- ISSN :
- 20452322
- Volume :
- 11
- Database :
- OpenAIRE
- Journal :
- Scientific Reports
- Accession number :
- edsair.doi.dedup.....dd579f6d6c1c5d6e69b8446ec669e0ca