Novel application and validation of in vivo micro‐CT to study bone modelling in 3D

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/149362/1/ocr12265.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/149362/2/ocr12265_am.pd

3D superimposition of craniofacial imaging—The utility of multicentre collaborations

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/149360/1/ocr12281.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/149360/2/ocr12281_am.pd

Dental long axes using digital dental models compared to cone-beam computed tomography

Objective: Standard methods of evaluating tooth long axes are not comparable (digital dental models [DDMs], panoramic and cephalometric radiographs) or expose patients to more radiation (cone-beam computed tomography [CBCT]). This study aimed to compare angular changes in tooth long axes using DDMs vs using CBCTs. Settings and sample population: Secondary data analysis of DDMs and CBCTs, taken before and after orthodontic treatment with piezocision of 24 patients. Methods: Angular changes in tooth long axes were evaluated using landmarks on first molars (centre of the occlusal surface and centre of the furcation), canines and incisors (cusp tip and centre of the root at the cementoenamel junction). Wilcoxon test, intraclass correlation coefficient (ICC) and Bland-Altman plots were used to test intra- and inter-rater agreement and compare DDM and CBCT measurements. Results: The mesiodistal angulation and buccolingual inclination DDM measurements were reproducible. Overall mean differences between DDM and CBCT measurements of mesiodistal angulation, 1.9°±1.5°, and buccolingual inclination, 2.2 ± 2.2°, were not significant for all teeth. ICC between DDM and CBCT measurements ranged from good (0.85 molars) to excellent (0.94 canines; 0.96 incisors). The percentages of measurements outside the range of ±5 were 17.4% for molars, 13.8% for canines and 4.5% for incisors. Conclusions: DDM assessment of changes in tooth long axes has good reproducibility and yields comparable measurements to those obtained from CBCT within a 5° range. These findings lay the groundwork for machine learning approaches that synthesize crown and root canal information towards planning tooth movement without the need for ionizing radiation scans