METHODS: This study included 344 patients from the Korean Obstructive Lung Disease (KOLD) cohort. External validation was performed on a cohort of 112 patients. In total, 525 chest CT-based radiomics features were semi-automatically extracted. The five most useful features for survival prediction were selected by least absolute shrinkage and selection operation (LASSO) Cox regression analysis and used to generate a RS. The ability of the RS for classifying COPD patients into high or low mortality risk groups was evaluated with the Kaplan-Meier survival analysis and Cox proportional hazards regression analysis.

RESULTS: The five features remaining after the LASSO analysis were %LAA-950, AWT_Pi10_6th, AWT_Pi10_heterogeneity, %WA_heterogeneity, and VA18mm. The RS demonstrated a C-index of 0.774 in the discovery group and 0.805 in the validation group. Patients with a RS greater than 1.053 were classified into the high-risk group and demonstrated worse overall survival than those in the low-risk group in both the discovery (log-rank test, < 0.001; hazard ratio [HR], 5.265) and validation groups (log-rank test, < 0.001; HR, 5.223). For both groups, RS was significantly associated with overall survival after adjustments for patient age and body mass index.

CONCLUSIONS: A radiomics approach for survival prediction and risk stratification in COPD patients is feasible, and the constructed radiomics model demonstrated acceptable performance. The RS derived from chest CT data of COPD patients was able to effectively identify those at increased risk of mortality.

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.

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).

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.

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.