PURPOSE: To study the surgical morphometry of C1 and C2 vertebrae in Chinese, Indian, and Malay patients.
OVERVIEW OF LITERATURE: C1 lateral mass and C2 pedicle screw fixation is gaining popularity. However, there is a lack of C1-C2 morphometric data for the Asian population.
METHODS: Computed tomography analysis of 180 subjects (60 subjects each belonging to Chinese, Indian, and Malay populations) using simulation software was performed. Length and angulations of C1 lateral mass (C1LM) and C2 pedicle (C2P) screws were assessed.
RESULTS: The predicted C1LM screw length was between 23.2 and 30.2 mm. The safe zone of trajectories was within 11.0°±7.7° laterally to 29.1°±6.2° medially in the axial plane and 37.0°±10.2° caudally to 20.9°±7.8° cephalically in the sagittal plane. The shortest and longest predicted C2P screw lengths were 22.1±2.8 mm and 28.5±3.2 mm, respectively. The safe trajectories were from 25.1° to 39.3° medially in the axial plane and 32.3° to 45.9° cephalically in the sagittal plane.
CONCLUSIONS: C1LM screw length was 23-30 mm with the axial safe zone from 11° laterally to 29° medially and sagittal safe zone at 21° cephalically. C2P screw length was 22-28 mm with axial safe zone from 26° to 40° medially and sagittal safe zone from 32° to 46° cephalically. These data serve as an important reference for Chinese, Indian, and Malay populations during C1-C2 instrumentation.
METHODS: Two 3D printed models were designed and fabricated using actual patient imaging data with reference marker points embedded artificially within these models that were then registered to a surgical navigation system using 3 different methods. The first method uses a conventional manual registration, using the actual patient's imaging data. The second method is done by directly scanning the created model using intraoperative computed tomography followed by registering the model to a new imaging dataset manually. The third is similar to the second method of scanning the model but eventually uses an automatic registration technique. The errors for each experiment were then calculated based on the distance of the surgical navigation probe from the respective positions of the embedded marker points.
RESULTS: Errors were found in the preparation and printing techniques, largely depending on the orientation of the printed segment and postprocessing, but these were relatively small. Larger errors were noted based on a couple of variables: if the models were registered using the original patient imaging data as opposed to using the imaging data from directly scanning the model (1.28 mm vs. 1.082 mm), and the accuracy was best using the automated registration techniques (0.74 mm).
CONCLUSION: Spatial accuracy errors occur consistently in every 3D fabricated model. These errors are derived from the fabrication process, the image registration process, and the surgical process of registration.
METHODS: Six hemi-mandible samples were scanned using the i-CAT CBCT system. The scanned data was transferred to the OsiriX software for measurement protocol and subsequently into Mimics software to fabricate customized cutting jigs and 3D biomodels based on rapid prototyping technology. The hemi-mandibles were segmented into 5 dentoalveolar blocks using the customized jigs. Digital calliper was used to measure six distances surrounding the mandibular canal on each section. The same distances were measured on the corresponding cross-sectional OsiriX images and the 3D biomodels of each dentoalveolar block.
RESULTS: Statistically no significant difference was found when measurements from OsiriX images and 3D biomodels were compared to the "gold standard" -direct digital calliper measurement of the cadaveric dentoalveolar blocks. Moreover, the mean value difference of the various measurements between the different study components was also minimal.
CONCLUSION: Various distances surrounding the mandibular canal from 3D biomodels produced from the CBCT scanned data was similar to that of direct digital calliper measurements of the cadaveric specimens.
METHODS: CT scans of 50 lower limbs were analyzed. Key anatomical landmarks such as the medial epicondyle (ME), lateral epicondyle, and transepicondylar width (TEW) were determined on 3D models constructed from the CT images. Best-fit planes placed on the most distal and posterior loci of points on the femoral condyles were used to define the distal and posterior joint lines, respectively. Statistical analysis was performed to determine the relationships between the anatomical landmarks and the distal and posterior joint lines.
RESULTS: There was a strong correlation between the distance from the ME to the distal joint line of the medial condyle (MEDC) and the distance from the ME to the posterior joint line of the medial condyle (MEPC) (p
METHODS: Computational Fluid Dynamics (CFD) approach is used to simulate the airflow in a neonate, an infant and an adult in sedentary breathing conditions. The healthy CT scans are segmented using MIMICS 21.0 (Materialise, Ann arbor, MI). The patient-specific 3D airway models are analyzed for low Reynolds number flow using ANSYS FLUENT 2020 R2. The applicability of the Grid Convergence Index (GCI) for polyhedral mesh adopted in this work is also verified.
RESULTS: This study shows that the inferior meatus of neonates accounted for only 15% of the total airflow. This was in contrast to the infants and adults who experienced 49 and 31% of airflow at the inferior meatus region. Superior meatus experienced 25% of total flow which is more than normal for the neonate. The highest velocity of 1.8, 2.6 and 3.7 m/s was observed at the nasal valve region for neonates, infants and adults, respectively. The anterior portion of the nasal cavity experienced maximum wall shear stress with average values of 0.48, 0.25 and 0.58 Pa for the neonates, infants and adults.
CONCLUSIONS: The neonates have an underdeveloped nasal cavity which significantly affects their airway distribution. The absence of inferior meatus in the neonates has limited the flow through the inferior regions and resulted in uneven flow distribution.