METHODS: CT scans of the neck of two hundred patients were analysed by two groups of raters. For thyrohyoid approach, mean distance from the superior border of the thyroid cartilage to the laryngeal cavity (THd) and mean angle from the superior border of the thyroid cartilage to mid-true cords (THa) were measured. For transthyroid approach, mean distance from mid-thyroid cartilage to mid-true cords (TTd) and Hounsfield unit (HU) at mid-thyroid cartilage (TTc) were measured. For cricothyroid approach, mean distance from the inferior border of the thyroid cartilage to the laryngeal cavity (CTd) and mean angle from the inferior border of the thyroid cartilage to mid-true cords (CTa) were measured.

RESULTS: There were statistically significant differences between males and females for all measurements except for CTa (p three approaches (p > 0.05). There was a significant fair positive correlation between age and TTc (p = 0.0002). For all measurements obtained, there were moderate to excellent inter-group consistency and intra-rater reliability.

METHODS: The study included 590 hips of 295 OI patients, who were older than 5 years, and did not have a pelvic fracture. The incidence of a deformed acetabulum (center-edge angle >40 degrees) and its correlation with disease severity were investigated. In 40 hips for which 3D-CT was available, 3-dimensional morphology of the acetabular deformity was analyzed to delineate PPAD. On plain radiographs, PPAD-related signs were determined, focusing on the contour of ilioischial line, iliopectineal line, acetabular line, and their relationship. These radiographic signs were also evaluated in the remaining hips with deformed acetabula that did not have 3D-CT.

RESULTS: One hundred twenty-three hips of 590 hips (21%) showed deformed acetabula. The incidence of deformed acetabula was significantly associated with disease severity (P<0.001). Three-dimensional analysis showed that 10 hips had protrusio acetabuli, whereas 17 had PPAD, which showed that the hemipelvis was crumpled, the acetabular roof was rotated upwardly and medially, and the hip center migrated superiorly, uncovering the anterior femoral head. Among the PPAD-related signs, superomedial bulging of the iliopectineal line was the most predictive radiographic sign (73% sensitivity and 100% specificity). This sign was also observed in almost one third of deformed acetabula of those investigated only with plain radiographs.

CONCLUSIONS: This study showed that acetabular deformity is common in OI patients and is associated with disease severity. A substantial number of hips showed PPAD, which may not cause femoroacetabular impingement but result in anterior uncovering of the hip joint. Superomedial bulging of the iliopectineal line suggests this pattern of acetabular deformity.

METHODS: Sixteen computed tomography scan of SC patients (8 months-6 years old) were imported to Materialise Interactive Medical Image Control System (MIMICS) and Materialise 3-matics software. Three-dimensional (3D) OC models were fabricated, and linear measurements were obtained. Mathematical formulas were used for calculation of OC volume and surface area from the 3D model. The same measurements were obtained from the software and used as ground truth. Data normality was investigated before statistical analyses were performed. Wilcoxon test was used to validate differences of OC volume and surface area between 3D model and software.

RESULTS: The mean values for OC surface area for 3D model and MIMICS software were 103.19 mm2 and 31.27 mm2, respectively, whereas the mean for OC volume for 3D model and MIMICS software were 184.37 mm2 and 147.07 mm2, respectively. Significant difference was found between OC volume (P = 0.0681) and surface area (P = 0.0002) between 3D model and software.

METHODS: In this study, we propose a multi-view secondary input residual (MV-SIR) convolutional neural network model for 3D lung nodule segmentation using the Lung Image Database Consortium and Image Database Resource Initiative (LIDC-IDRI) dataset of chest computed tomography (CT) images. Lung nodule cubes are prepared from the sample CT images. Further, from the axial, coronal, and sagittal perspectives, multi-view patches are generated with randomly selected voxels in the lung nodule cubes as centers. Our model consists of six submodels, which enable learning of 3D lung nodules sliced into three views of features; each submodel extracts voxel heterogeneity and shape heterogeneity features. We convert the segmentation of 3D lung nodules into voxel classification by inputting the multi-view patches into the model and determine whether the voxel points belong to the nodule. The structure of the secondary input residual submodel comprises a residual block followed by a secondary input module. We integrate the six submodels to classify whether voxel points belong to nodules, and then reconstruct the segmentation image.

RESULTS: The results of tests conducted using our model and comparison with other existing CNN models indicate that the MV-SIR model achieves excellent results in the 3D segmentation of pulmonary nodules, with a Dice coefficient of 0.926 and an average surface distance of 0.072.

MATERIALS AND METHODS: Nineteen linear facial measurements were derived from 16 standardized surface landmarks obtained from 37 cleft patients (20 males, 17 females; mean age 23.84 years, standard deviation ± 6.02). They were taken manually with calipers and were compared with the digitally calculated distance on the 3D images captured using the VECTRA-M5 360° Imaging System with pre-marked landmarks. Another pair of 19 linear measurements were computed on the 3D images 2 weeks apart for intra- and inter-observer agreements. Statistical analyses used were paired t test, the Bland-Altman analysis, and the intra-class correlation coefficient (ICC) index.

RESULTS: Most of the linear measurements showed no statistically significant differences between the proposed method and direct anthropometry linear measurements. Nevertheless, bias of the 3D imaging system is present in the linear measurements of the nose width and the upper vermillion height. The measurements' mean biases were within 2 mm, but the 95% limit of agreement was more than 2 mm. Intra- and inter-observer measurements generally showed good reproducibility. Four inter-observer measurements, the upper and lower face heights, nose width, and pronasale to left alar base were clinically significant.

CONCLUSIONS: Measurements obtained from this 3D imaging system are valid and reproducible for evaluating CLP patients.

Method: A sample of 80 individuals with three-dimensional facial images at rest and during speech were recorded. Subjects were asked to pronounce four bilabial words in a relaxed manner and scanned using the 3dMDFace™ Dynamic System at 48 frames per second. Six lip landmarks were identified at rest and the landmark displacement vectors for the frame of maximal lip movement for all six visemes were recorded. Principal component analysis was applied to isolate relationship between lip traits and their registered coordinates. Eight specific resting morphological lip traits were identified for each individual. The principal component (PC) scores for each viseme were labelled by lip morphological trait and were graphically visualized as ellipses to discriminate any differences in lip movement.

Results: The first five PCs accounted for up to 95% of the total variance in lip shape during movement, with PC1 accounting for at least 38%. There was no clear discrimination between PC1, PC2 and PC3 for any of the resting morphological lip traits.