Evaluation of the potential of automatic segmentation of the mandibular canal using cone-beam computed tomography

We aimed to investigate the effectiveness of software for automatically tracing the mandibular canal on data from cone-beam computed tomography (CT). After the data had been collected from one dentate and one edentate fresh cadaver head, both a trained Active Shape Model (ASM) and an Active Appearance Model (AAM) were used to automatically segment the canals from the mandibular to the mental foramen. Semiautomatic segmentation was also evaluated by providing the models with manual annotations of the foramina. To find out if the tracings were in accordance with the actual anatomy, we compared the position of the automatic mandibular canal segmentations, as displayed on cross-sectional cone-beam CT views, with histological sections of exactly the same region. The significance of differences between results were analysed with the help of Fisher's exact test and Pearson's correlation coefficient. When tracings based on AAM and ASM were used, differences between cone-beam CT and histological measurements varied up to 3.45 mm and 4.44 mm, respectively. Manual marking of the mandibular and mental foramina did not improve the results, and there were no significant differences (p = 0.097) among the methods. The accuracy of automatic segmentation of the mandibular canal by the AAM and ASM methods is inadequate for use in clinical practice

3-Dimensional CBCT analysis of mandibular asymmetry in unilateral condylar hyperplasia

Three-dimensional quantification of asymmetry in UCH has not been reported yet, but would be useful for diagnosing and evaluating the degree of deformity in this disease. It enables profound decision-making and timing of surgery. Unilateral condylar hyperplasia (UCH) can subjectively be classified in hemimandibular elongation (HE), hemimandibular hyperplasia (HH) and a combination of these two (hybrid form). The main purpose of this study was to quantify mandibular asymmetry in UCH patients with a reliable and reproducible method. Secondly, it was evaluated whether the existing classification can be confirmed. 37 UCH-patients with progressive mandibular asymmetry, supported by a positive bone scan and/or such clinical progression that condylectomy was performed, were included in this retrospective study. A group of healthy subjects, matched for age and gender, was used as the control group. Cone-beam computed tomography (CBCT) scans were imported in Maxilim(®) software. Each mandibular half was divided into three skeletal segments (condyle, ramus, and body). Linear and volumetric measurements were calculated for these skeletal units on the affected and unaffected side, for both patients and controls. Significant differences between affected and unaffected sides in the patient group were found in condylar, ramus, and body segments for linear (p < 0.01) as well as for volumetric quantitative measurements (p < 0.0040). A mean linear difference between affected and unaffected sides in the condylar region of the UCH patient group was found of 3.6 mm (sd 2.9) versus 0.2 mm (sd 1.5) in controls. For volumetric measurements there was a mean difference between the left and right condyle of 718 mm(3) (sd 638) in the patient group versus 8 mm(3) (sd 225) difference in the control group. The condyle was the most affected segment. Differences between sides were significantly larger in the patient group than in the control group (p < 0.001). It was not possible to objectify differences between HE and HH. CBCT is a useful and accurate modality for quantification and evaluation of mandibular asymmetry in UCH. It enables objective monitoring. The existing classification in HE and HH could not be confirme